<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">OJMM</journal-id><journal-title-group><journal-title>Open Journal of Medical Microbiology</journal-title></journal-title-group><issn pub-type="epub">2165-3372</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ojmm.2023.132014</article-id><article-id pub-id-type="publisher-id">OJMM-125981</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Medicine&amp;Healthcare</subject></subj-group></article-categories><title-group><article-title>
 
 
  Trends in Bacterial Blood Culture Isolates and Resistance in Children in Two Microbiologic Eras from a Tertiary Health Facility in North East Nigeria
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Elon</surname><given-names>Warnow Isaac</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Iliya</surname><given-names>Jalo</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Mohammed</surname><given-names>M. Manga</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Abubakar</surname><given-names>Joshua Difa</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Mercy</surname><given-names>Raymond Poksireni</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Oyeniyi</surname><given-names>Christianah</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ibrahim</surname><given-names>Mohammed</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Muhammad</surname><given-names>Saminu Charanci</given-names></name><xref ref-type="aff" rid="aff5"><sup>5</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Department of Paediatrics, College of Medical Sciences, Gombe State University, Tudun Wada, Nigeria</addr-line></aff><aff id="aff1"><addr-line>Infectious Disease Training and Research Group Gombe (INDITREGO), Gombe, Nigeria</addr-line></aff><aff id="aff4"><addr-line>Department of Community Medicine, College of Medical Sciences, Gombe State University, Tudun Wada, Nigeria</addr-line></aff><aff id="aff5"><addr-line>Microbiology Laboratory Federal Teaching Hospital Gombe, Gombe, Nigeria</addr-line></aff><aff id="aff3"><addr-line>Department of Medical Microbiology, College of Medical Sciences, Gombe State University, Tudun Wada, Nigeria</addr-line></aff><pub-date pub-type="epub"><day>19</day><month>06</month><year>2023</year></pub-date><volume>13</volume><issue>02</issue><fpage>159</fpage><lpage>182</lpage><history><date date-type="received"><day>9,</day>	<month>May</month>	<year>2023</year></date><date date-type="rev-recd"><day>27,</day>	<month>June</month>	<year>2023</year>	</date><date date-type="accepted"><day>30,</day>	<month>June</month>	<year>2023</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  <b>Introduction: </b>
  Antimicrobial Resistance surveillance is predicated on blood culture as a priority clinical specimen in especially resource limited settings. Establishing trends in blood stream infections and resistance patterns can inform institutional and national policy on antimicrobial stewardship, surveillance, infection prevention and control.<b> Methodology: </b>Blood Culture isolates in children (0
   
  -
   
  18
   
  years) by conventional method from 2008-2012 and Bactec Automated culture system from 2015-2020 were retrieved. Information analyzed included age, sex, month, and year and culture growth/identity of microorganisms and their sensitivity/resistance patterns. Clinical and Laboratory Standards Institute (CLSI) guideline for antibiotic susceptibility testing was used. <b>Results: </b>20,540 children were admitted
  : 
  8964 (44.6%) and 11
  ,
  630
   
  (55.4%)
   in the Manual and Bactec blood culture era respectively. Blood cultures were done in 5271 in the manual culture era and 1077 in the Bactec culture era; of these cultures, 514
   
  (9.7%) and 461
   
  (42
  .
  8%) were positive for isolates in the re
  spective era (p
   
  =
   
  0.01). There were no statistically significant differences in trend
   between positive and negative blood cultures in males and females. Newborns, followed by children 1 -
   
  5 years had more blood culture performed on them than other age categories. In general, 
  there is 
  no significant relationship in blood culture outcomes between the age categories and sex of the patients. The isolation of Staph aureus, Citrobacter and Alkaligenes increased two-fold with Bactec automated system. Resistance to the quinolones and the penicillin was high. Resistance trend to Genticin
  ,
   an aminoglycoside was less than 40%. Resistance to Ceftazidime was high. <b>Conclusion</b>
  <b>:</b>
   Antimicrobial resistance
   surveillance is critical to reduce AMR related morbidity and mortality
  .
 
</p></abstract><kwd-group><kwd>Trend</kwd><kwd> Blood Culture Isolates</kwd><kwd> Children</kwd><kwd> Manual</kwd><kwd> Bactec</kwd><kwd> Resistance</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Blood culture is the gold standard for the diagnosis of Blood stream infections [<xref ref-type="bibr" rid="scirp.125981-ref1">1</xref>] . Accurate and reliable diagnosis of blood stream infections is a microbiologic task of utmost clinical significance [<xref ref-type="bibr" rid="scirp.125981-ref2">2</xref>] . Antimicrobial Resistance AMR surveillance is predicated on blood culture as a priority clinical specimen in especially resource limited settings [<xref ref-type="bibr" rid="scirp.125981-ref3">3</xref>] . There were an estimated 4.95 million deaths associated with bacterial AMR in 2019, including 1.27 million deaths attributable to bacterial AMR. At the regional level, it was estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27.3 deaths per 100,000 [<xref ref-type="bibr" rid="scirp.125981-ref4">4</xref>] . In Nigeria, a situation analysis of antimicrobial use [<xref ref-type="bibr" rid="scirp.125981-ref5">5</xref>] and a National Action Plan for AMR [<xref ref-type="bibr" rid="scirp.125981-ref6">6</xref>] prioritized the use of blood culture in diagnosing BSIs. Low- and middle-income countries especially sub-Saharan Africa face many challenges when implementing blood cultures, due to financial, logistical, and infrastructure-related constraints [<xref ref-type="bibr" rid="scirp.125981-ref7">7</xref>] . In these settings, the conventional/manual culture methods remain the dominant systems while the automated blood culture systems have become the standard in high-income countries (HICs), and are relatively expensive and not universally available for implementation in most LMICs where [<xref ref-type="bibr" rid="scirp.125981-ref7">7</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref9">9</xref>] implementing automated microbiologic systems is feasible [<xref ref-type="bibr" rid="scirp.125981-ref7">7</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref10">10</xref>] . Several reports [<xref ref-type="bibr" rid="scirp.125981-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref13">13</xref>] in LMIC showed that these systems show better performance than manual systems in terms of yield, sensitivity and especially speed of growth and overall turnaround time. Blood cultures are still indispensable for the diagnosis of BSIs however currently available molecular methods based on in situ hybridization-based methods, DNA microarray-based hybridization technology; nucleic acid amplification-based methods and combined methods [<xref ref-type="bibr" rid="scirp.125981-ref14">14</xref>] are a distant prospect for LMICs.</p><p>Establishing trends in blood stream infections and resistance patterns can inform health care needs assessment, service provision planning, institutional and national policy on antimicrobial stewardship, surveillance, infection prevention and control [<xref ref-type="bibr" rid="scirp.125981-ref15">15</xref>] . In Nigeria, a nationally representative epidemiologic data on Blood Stream Infections and their antibiotic sensitivity and resistance patterns is lacking [<xref ref-type="bibr" rid="scirp.125981-ref16">16</xref>] . With the triad of Malaria, malnutrition HIV and other prevalent childhood conditions strongly associated with the prevalence of Blood stream infection in the region clinical microbiology laboratories require urgent strengthening in Sub-Saharan Africa [<xref ref-type="bibr" rid="scirp.125981-ref17">17</xref>] . In Nigeria, there is paucity of data on two contrasting microbiologic laboratory periods in transition. We therefore aimed to report blood stream infection and resistance trends in children in our health facility over two microbiologic eras of earlier manual/conventional blood culture and current Bactec automated blood culture methods.</p><sec id="s1_1"><title>1.1. Method</title><p>The Federal Teaching hospital Gombe (FTHG) is currently a 500-bed health facility [<xref ref-type="bibr" rid="scirp.125981-ref18">18</xref>] which started providing health service to the public in the year 2000. The Medical Microbiology Department fully transitioned to automated blood culture system in 2015 from the conventional/manual system which was used at inception.</p></sec><sec id="s1_2"><title>1.2. Subjects</title><p>Blood Culture isolates in children (0 - 18 years) by conventional method from 2008-2012 and Bactec Automated culture system from 2015-2020 were retrieved. Information analyzed included, age, sex, month, and year and culture growth/identity of microorganisms. Blood samples for cultures from consecutive children’s admissions between 2008-2012 and 2015-2020 with suspected blood stream infections or sepsis were obtained using the Hospital standard procedure.</p><p>The BD Bactec (R) [<xref ref-type="bibr" rid="scirp.125981-ref19">19</xref>] 9050 instrument which is designed for the rapid detection of microorganisms in clinical cultures of blood was used. The Blood sample to be tested was inoculated into the vial which was entered into the Bactec 9050 for incubation and periodic reading. Each vial contains a sensor which detects increases in carbon dioxide, produced by the growth of microorganisms. The sensor was monitored by the instrument every ten minutes for an increase in its fluorescence, which was proportional to the amount of carbon dioxide present. A positive reading indicates the presumptive presence of viable microorganisms in the vial which are subsequently sub cultured for identification and antibiotic susceptibility testing. Clinical and Laboratory Standards Institute (CLSI) guideline for antibiotic susceptibility testing was used. From 2021 Bactec FX40 was introduced in the microbiology unit to replace the Bactec 9050 equipment and Vitek II automated platform for identification and antimicrobial susceptibility testing (ID/AST) was introduced in 2022. Our laboratory did not participate in any external quality assurance scheme.</p></sec><sec id="s1_3"><title>1.3. Data Analysis</title><p>Data were entered into the EPInfo version 3.5.1 software and analyzed. Automated and manual BC were compared in terms of proportion positive and recovery of different bacteria were calculated using chi and Fischer’s exact test. A p-value below 0.05 was considered as statistically significant. Yearly Blood culture sampling/admission was derived by dividing the number of blood cultures by admissions in the year.</p></sec><sec id="s1_4"><title>1.4. Ethical Approval</title><p>Approval for this study was received from the Ethical Research Committee of the Federal Teaching Hospital Gombe.</p></sec></sec><sec id="s2"><title>2. Results</title><p>In <xref ref-type="table" rid="table1">Table 1</xref>, 20,540 children were admitted; 8964 (44.6%) and 11630 (55.4%) in the Manual and Bactec blood culture era respectively. Blood cultures were done in 5271 in first era and 1077 in the second era. Of these cultures, 514 (9.7%) and 461 (42.8%) were positive for isolates respectively. (p = 0.01). Blood culture cost rose from N500 ($1.1) for Manual method to N5000 ($11.1) for Bactec culture and is currently N8500 ($18.8). Of the total children admitted 63% and 9.2% had blood culture in the first and second era respectively. Cumulative Blood sampling for culture was 0.6 per admission in the manual culture era and 0.09 per admission in the Bactec era.</p><p>Yearly BC declined sharply when the Bactec 9050BD was introduced in 2015 largely because of increased in the cost of blood culture to 10 times above manual era.</p><p><xref ref-type="fig" rid="fig1">Figure 1</xref>(a) and <xref ref-type="fig" rid="fig1">Figure 1</xref>(b) show the yearly admission, yearly blood cultures and yearly blood culture rate amongst admitted children in the two eras. Yearly blood culture rate among children admitted in the Manual era varied between 86.2% in 2008 and 68.8% in 2012. In the Bactec era this rate was between 10% - 19.4%. Blood culture sampling per patient admission ranged from 0.5 and 0.7 in the manual era and 0.005 to 0.06 in the Bactec era. The cost of one Blood culture</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Blood culture era, sex and yield</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >Manual blood culture Era</th><th align="center" valign="middle" >Bactec blood culture Era</th><th align="center" valign="middle" ></th></tr></thead><tr><td align="center" valign="middle" >Year</td><td align="center" valign="middle" >2008-2012</td><td align="center" valign="middle" >2016-2020</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Paediatric admissions</td><td align="center" valign="middle" >8964</td><td align="center" valign="middle" >11,630</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Cost in Naira/culture</td><td align="center" valign="middle" >N300-N500:00</td><td align="center" valign="middle" >N5000:00</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Blood cultures Performed</td><td align="center" valign="middle" >5721</td><td align="center" valign="middle" >1077</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Blood culture rate /Era</td><td align="center" valign="middle" >63%</td><td align="center" valign="middle" >9.2%</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Blood culture/admission</td><td align="center" valign="middle" >0.6</td><td align="center" valign="middle" >0.09</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Positive Blood cultures</td><td align="center" valign="middle" >541</td><td align="center" valign="middle" >461</td><td align="center" valign="middle" >p = 0.01</td></tr><tr><td align="center" valign="middle" >Negative Blood cultures</td><td align="center" valign="middle" >5207</td><td align="center" valign="middle" >616</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Percent Positive</td><td align="center" valign="middle" >9.7%</td><td align="center" valign="middle" >42.8%</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Males positive</td><td align="center" valign="middle" >293 (54.2%) p = 0.3</td><td align="center" valign="middle" >252 (54.6%)</td><td align="center" valign="middle" >p = 0.00</td></tr><tr><td align="center" valign="middle" >Females positive</td><td align="center" valign="middle" >248 (45.8%)</td><td align="center" valign="middle" >209 (45.4%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Males negative</td><td align="center" valign="middle" >2922 (56.4%)</td><td align="center" valign="middle" >462 (64.7%)</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Females negative</td><td align="center" valign="middle" >2258 (43.6%)</td><td align="center" valign="middle" >252 (35.3%)</td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>for Manual method was $1.1 and $11.1 (equivalent to the Nigerian currency, the Naira) in the Bactec era. The intervening years of 2013-2015 were not included as the numbers did not differ and two equal time intervals were used for this trend analysis.</p><p>In <xref ref-type="fig" rid="fig2">Figure 2</xref>(a) and <xref ref-type="fig" rid="fig2">Figure 2</xref>(b), blood culture positivity rate peaked in 2008 and decreased to a lowest of 3.8% in 2010 in the manual blood culture era. In the Bactec era, peak positivity rate was 50% in 2016 with the lowest of 30.7% isolation rate.</p><p>In <xref ref-type="fig" rid="fig3">Figure 3</xref>, more males had received a blood culture than females on a yearly basis in both microbiologic eras but this was not statistically significant (x<sup>2</sup> = 13.173; p = 0.155). In both sexes blood culture declined with the advent of Bactec automated blood culture system, however there was no statistically significant differences in trend between positive and negative blood cultures in males and females (<xref ref-type="table" rid="table2">Table 2</xref>). In <xref ref-type="fig" rid="fig4">Figure 4</xref>, newborns, followed by children 1 - 5 years had more blood culture performed on them than other age categories. Adolescents</p><p>had the lowest rate of blood culture of all the ages. In all age categories, the culture rate declined with the use of Bactec automated culture method despite increasing child admissions. However, there was a statistically significant trend in</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Yearly trend of blood culture results and sex in two microbiologic eras in FTG Gombe</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle"  colspan="2"  >POSITIVE</th><th align="center" valign="middle"  colspan="2"  >NEGATIVE</th></tr></thead><tr><td align="center" valign="middle" >YEAR</td><td align="center" valign="middle" >MALES</td><td align="center" valign="middle" >FEMALES</td><td align="center" valign="middle" >MALES</td><td align="center" valign="middle" >FEMALES</td></tr><tr><td align="center" valign="middle" >2008</td><td align="center" valign="middle" >148</td><td align="center" valign="middle" >118</td><td align="center" valign="middle" >360</td><td align="center" valign="middle" >302</td></tr><tr><td align="center" valign="middle" >2009</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >48</td><td align="center" valign="middle" >459</td><td align="center" valign="middle" >351</td></tr><tr><td align="center" valign="middle" >2010</td><td align="center" valign="middle" >23</td><td align="center" valign="middle" >11</td><td align="center" valign="middle" >475</td><td align="center" valign="middle" >391</td></tr><tr><td align="center" valign="middle" >2011</td><td align="center" valign="middle" >31</td><td align="center" valign="middle" >15</td><td align="center" valign="middle" >581</td><td align="center" valign="middle" >420</td></tr><tr><td align="center" valign="middle" >2012</td><td align="center" valign="middle" >31</td><td align="center" valign="middle" >29</td><td align="center" valign="middle" >814</td><td align="center" valign="middle" >571</td></tr><tr><td align="center" valign="middle" >2016</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >2017</td><td align="center" valign="middle" >15</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >18</td></tr><tr><td align="center" valign="middle" >2018</td><td align="center" valign="middle" >92</td><td align="center" valign="middle" >78</td><td align="center" valign="middle" >121</td><td align="center" valign="middle" >108</td></tr><tr><td align="center" valign="middle" >2019</td><td align="center" valign="middle" >108</td><td align="center" valign="middle" >86</td><td align="center" valign="middle" >140</td><td align="center" valign="middle" >77</td></tr><tr><td align="center" valign="middle" >2020</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >35</td><td align="center" valign="middle" >61</td><td align="center" valign="middle" >49</td></tr><tr><td align="center" valign="middle" >Total</td><td align="center" valign="middle" >545</td><td align="center" valign="middle" >430</td><td align="center" valign="middle" >3049</td><td align="center" valign="middle" >2288</td></tr><tr><td align="center" valign="middle" >X<sup>2</sup>, p-value</td><td align="center" valign="middle"  colspan="2"  >7.613, 0.574</td><td align="center" valign="middle"  colspan="2"  >15.014, 0.091</td></tr></tbody></table></table-wrap><p>blood culture results from the manual to the automated era (<xref ref-type="table" rid="table3">Table 3</xref>). In <xref ref-type="table" rid="table4">Table 4</xref>, there was in general no significant relationship in blood culture outcomes between the age categories and sex of the patients.</p><p>In <xref ref-type="fig" rid="fig5">Figure 5</xref>, of the priority pathogens, Staphylococcus aureus, Klebsiella and E. coli remain the most dominant especially in the manual era. The isolation of staph aureus increased two-fold with Bactec automated system. Citrobacter and alkaligenes isolation also increased about two-fold with the Bactec culture method.</p><p>In <xref ref-type="fig" rid="fig6">Figure 6</xref>, resistance to the quinolones and the penicillin in the early years was high ranging from 60% - 100% with sharp decline in 2016 and 2017 for ciprofloxacin, amoxyllin/clavulanate and amoxicillin as result of none testing. This</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Yearly trend in blood cultures results and age categories in two microbiologic eras in FTH Gombe</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle"  colspan="3"  >&lt;28 days</th><th align="center" valign="middle"  colspan="2"  >28 days - 1 yr</th><th align="center" valign="middle"  colspan="2"  >1 - 5 yrs</th><th align="center" valign="middle"  colspan="2"  >5 - 10 yrs</th><th align="center" valign="middle"  colspan="2"  >10 - 18 yrs</th></tr></thead><tr><td align="center" valign="middle" >Year</td><td align="center" valign="middle" >Positive</td><td align="center" valign="middle"  colspan="2"  >Negative</td><td align="center" valign="middle" >Positive</td><td align="center" valign="middle" >Negative</td><td align="center" valign="middle" >Positive</td><td align="center" valign="middle" >Negative</td><td align="center" valign="middle" >Positive</td><td align="center" valign="middle" >Negative</td><td align="center" valign="middle" >Positive</td><td align="center" valign="middle" >Negative</td></tr><tr><td align="center" valign="middle" >2008</td><td align="center" valign="middle" >131</td><td align="center" valign="middle"  colspan="2"  >207</td><td align="center" valign="middle" >38</td><td align="center" valign="middle" >166</td><td align="center" valign="middle" >52</td><td align="center" valign="middle" >172</td><td align="center" valign="middle" >29</td><td align="center" valign="middle" >74</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >30</td></tr><tr><td align="center" valign="middle" >2009</td><td align="center" valign="middle" >58</td><td align="center" valign="middle"  colspan="2"  >287</td><td align="center" valign="middle" >14</td><td align="center" valign="middle" >128</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >200</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >108</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >78</td></tr><tr><td align="center" valign="middle" >2010</td><td align="center" valign="middle" >19</td><td align="center" valign="middle"  colspan="2"  >372</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >154</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >160</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >85</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >67</td></tr><tr><td align="center" valign="middle" >2011</td><td align="center" valign="middle" >28</td><td align="center" valign="middle"  colspan="2"  >420</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >161</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >197</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >101</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >89</td></tr><tr><td align="center" valign="middle" >2012</td><td align="center" valign="middle" >39</td><td align="center" valign="middle"  colspan="2"  >530</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >287</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >342</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >135</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >89</td></tr><tr><td align="center" valign="middle" >2016</td><td align="center" valign="middle" >5</td><td align="center" valign="middle"  colspan="2"  >2</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td></tr><tr><td align="center" valign="middle" >2017</td><td align="center" valign="middle" >6</td><td align="center" valign="middle"  colspan="2"  >4</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >13</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >21</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >9</td></tr><tr><td align="center" valign="middle" >2018</td><td align="center" valign="middle" >72</td><td align="center" valign="middle"  colspan="2"  >65</td><td align="center" valign="middle" >24</td><td align="center" valign="middle" >51</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >46</td><td align="center" valign="middle" >15</td><td align="center" valign="middle" >26</td><td align="center" valign="middle" >19</td><td align="center" valign="middle" >41</td></tr><tr><td align="center" valign="middle" >2019</td><td align="center" valign="middle" >86</td><td align="center" valign="middle"  colspan="2"  >50</td><td align="center" valign="middle" >32</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >46</td><td align="center" valign="middle" >59</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >38</td><td align="center" valign="middle" >21</td><td align="center" valign="middle" >42</td></tr><tr><td align="center" valign="middle" >2020</td><td align="center" valign="middle" >22</td><td align="center" valign="middle"  colspan="2"  >19</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >24</td><td align="center" valign="middle" >21</td><td align="center" valign="middle" >36</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >23</td></tr><tr><td align="center" valign="middle" >Total</td><td align="center" valign="middle"  colspan="2"  >466</td><td align="center" valign="middle" >1956</td><td align="center" valign="middle" >140</td><td align="center" valign="middle" >1012</td><td align="center" valign="middle" >212</td><td align="center" valign="middle" >1234</td><td align="center" valign="middle" >79</td><td align="center" valign="middle" >580</td><td align="center" valign="middle" >65</td><td align="center" valign="middle" >468</td></tr><tr><td align="center" valign="middle" >X<sup>2</sup>, p</td><td align="center" valign="middle"  colspan="3"  >515.528, 0.000</td><td align="center" valign="middle"  colspan="2"  >165.808, 0.000</td><td align="center" valign="middle"  colspan="2"  >250.230, 0.000</td><td align="center" valign="middle"  colspan="2"  >95.836, 0.000</td><td align="center" valign="middle"  colspan="2"  >85.143, 0.000</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>was the year of the introduction of Bactec automated culture system with its tenfold increase in cost of blood culture. By the later years, resistance to these common antibiotics was less than 50% except for amoxycillin which showed a steep rise between 2018 and 2019 and decline in 2020. The difference in the number of bacterial isolates in the two eras may have accounted for the generally low resistance trend in the bactec era. Resistance trend to Genticin an aminoglycoside has remained less than 40% throughout the last ten years in our facility. At the start of the review resistance to Ceftazidime a 3<sup>rd</sup> generation cephalosporin was high at about 60% and remained so with substantial decline to 10% in the 2019 and 2020. The percentage of resistant bacterial isolates was arrived at using the multiple antibiotic resistance index [<xref ref-type="bibr" rid="scirp.125981-ref20">20</xref>] which represents number of antibiotics to which the test isolate depicted resistance divided by the number of antibiotics to which the test isolate has been evaluated for susceptibility in each year. The mean antibiotic resistance was derived from percentage resistance of each pathogen tested against each of the antibiotics in that year.</p></sec><sec id="s3"><title>3. Discussion</title><p>In this study, there was a steady increase in paediatric admissions over the last decade in our facility. While this may be attributable to increasing child population and referrals [<xref ref-type="bibr" rid="scirp.125981-ref21">21</xref>] , weak and ineffective primary health care especially and secondary health service have had their toll on tertiary healthcare service [<xref ref-type="bibr" rid="scirp.125981-ref22">22</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref23">23</xref>] .</p><p>Fever is common in Sub Saharan Africa and febrile illness remains a major cause of illness and death [<xref ref-type="bibr" rid="scirp.125981-ref24">24</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref25">25</xref>] . With invasive bacterial infection contributing 10% - 13% of febrile illnesses [<xref ref-type="bibr" rid="scirp.125981-ref26">26</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref27">27</xref>] blood culture and indeed pathogen</p><table-wrap id="table4" ><label><xref ref-type="table" rid="table4">Table 4</xref></label><caption><title> Yearly trend in age group, sex and blood culture results in two microbiologic eras in FTH Gombe</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Age groups</th><th align="center" valign="middle" >&lt;28 days</th><th align="center" valign="middle" ></th><th align="center" valign="middle"  colspan="2"  >28 days - 1 year</th><th align="center" valign="middle" >1 - 5 years</th><th align="center" valign="middle" ></th><th align="center" valign="middle" >5 - 10 years</th><th align="center" valign="middle" ></th><th align="center" valign="middle"  colspan="2"  >10 - 18 years</th><th align="center" valign="middle" >x<sup>2</sup></th><th align="center" valign="middle" >p-value</th></tr></thead><tr><td align="center" valign="middle" >Sex</td><td align="center" valign="middle" >Positive</td><td align="center" valign="middle" >Negative</td><td align="center" valign="middle" >Positive</td><td align="center" valign="middle" >Negative</td><td align="center" valign="middle" >Positive</td><td align="center" valign="middle" >Negative</td><td align="center" valign="middle" >Positive</td><td align="center" valign="middle" >Negative</td><td align="center" valign="middle" >Positive</td><td align="center" valign="middle" >Negative</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >2008</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Males</td><td align="center" valign="middle" >71 (54.2)</td><td align="center" valign="middle" >94 (45.4)</td><td align="center" valign="middle" >19 (50.0)</td><td align="center" valign="middle" >90 (54.2)</td><td align="center" valign="middle" >33 (63.5)</td><td align="center" valign="middle" >110 (63.9)</td><td align="center" valign="middle" >15 (51.7)</td><td align="center" valign="middle" >38 (51.4)</td><td align="center" valign="middle" >7 (53.8)</td><td align="center" valign="middle" >17 (56.7)</td><td align="center" valign="middle" >15.486</td><td align="center" valign="middle" >0.078</td></tr><tr><td align="center" valign="middle" >Females</td><td align="center" valign="middle" >60 (45.8)</td><td align="center" valign="middle" >113 (54.5)</td><td align="center" valign="middle" >19 (50.0)</td><td align="center" valign="middle" >76 (45.7)</td><td align="center" valign="middle" >19 (36.5)</td><td align="center" valign="middle" >62 (36.1)</td><td align="center" valign="middle" >14 (48.3)</td><td align="center" valign="middle" >36 (48.6)</td><td align="center" valign="middle" >64 (6.2)</td><td align="center" valign="middle" >13 (43.3)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >2009</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Males</td><td align="center" valign="middle" >27 (46.6)</td><td align="center" valign="middle" >157 (54.7)</td><td align="center" valign="middle" >10 (71.4)</td><td align="center" valign="middle" >84 (65.6)</td><td align="center" valign="middle" >15 (75.0)</td><td align="center" valign="middle" >112 (56.0)</td><td align="center" valign="middle" >4 (57.1)</td><td align="center" valign="middle" >54 (50.0)</td><td align="center" valign="middle" >2 (33.3)</td><td align="center" valign="middle" >45 (57.7)</td><td align="center" valign="middle" >14.305</td><td align="center" valign="middle" >0.112</td></tr><tr><td align="center" valign="middle" >Females</td><td align="center" valign="middle" >31 (53.4)</td><td align="center" valign="middle" >130 (45.3)</td><td align="center" valign="middle" >4 (28.6)</td><td align="center" valign="middle" >44 (34.4)</td><td align="center" valign="middle" >5 (25.0)</td><td align="center" valign="middle" >88 (44.0)</td><td align="center" valign="middle" >3 (42.9)</td><td align="center" valign="middle" >54 (50.0)</td><td align="center" valign="middle" >4 (66.7)</td><td align="center" valign="middle" >33 (42.3)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >2010</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Males</td><td align="center" valign="middle" >12 (63.2)</td><td align="center" valign="middle" >185 (49.7)</td><td align="center" valign="middle" >4 (80.0)</td><td align="center" valign="middle" >89 (57.8)</td><td align="center" valign="middle" >5 (62.5)</td><td align="center" valign="middle" >98 (61.3)</td><td align="center" valign="middle" >2 (100.0)</td><td align="center" valign="middle" >49 (57.6)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >35 (52.2)</td><td align="center" valign="middle" >11.217</td><td align="center" valign="middle" >0.19</td></tr><tr><td align="center" valign="middle" >Females</td><td align="center" valign="middle" >7 (36.8)</td><td align="center" valign="middle" >187 (50.3)</td><td align="center" valign="middle" >1 (20.0)</td><td align="center" valign="middle" >65 (42.2)</td><td align="center" valign="middle" >3 (37.5)</td><td align="center" valign="middle" >62 (38.7)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >36 (42.4)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >32 (47.8)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >2011</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Males</td><td align="center" valign="middle" >16 (57.1)</td><td align="center" valign="middle" >242 (57.6)</td><td align="center" valign="middle" >6 (100.0)</td><td align="center" valign="middle" >97 (60.2)</td><td align="center" valign="middle" >5 (71.4)</td><td align="center" valign="middle" >116 (58.9)</td><td align="center" valign="middle" >2 (100.0)</td><td align="center" valign="middle" >59 (58.4)</td><td align="center" valign="middle" >1 (100)</td><td align="center" valign="middle" >56 (63.0)</td><td align="center" valign="middle" >7.739</td><td align="center" valign="middle" >0.561</td></tr><tr><td align="center" valign="middle" >Females</td><td align="center" valign="middle" >12 (42.9)</td><td align="center" valign="middle" >178 (42.4)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >64 (39.8)</td><td align="center" valign="middle" >2 (28.6)</td><td align="center" valign="middle" >81 (41.1)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >42 (41.6)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >33 (37.0)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >2012</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Males</td><td align="center" valign="middle" >17 (43.6)</td><td align="center" valign="middle" >283 (53.4)</td><td align="center" valign="middle" >3 (42.9)</td><td align="center" valign="middle" >171 (59.6)</td><td align="center" valign="middle" >7 (87.5)</td><td align="center" valign="middle" >220 (64.3)</td><td align="center" valign="middle" >1 (33.3)</td><td align="center" valign="middle" >80 (59.3)</td><td align="center" valign="middle" >3 (100)</td><td align="center" valign="middle" >60 (60.6)</td><td align="center" valign="middle" >23.522</td><td align="center" valign="middle" >0.005</td></tr><tr><td align="center" valign="middle" >Females</td><td align="center" valign="middle" >22 (56.4)</td><td align="center" valign="middle" >247 (46.6)</td><td align="center" valign="middle" >4 (57.1)</td><td align="center" valign="middle" >116 (40.4)</td><td align="center" valign="middle" >1 (12.5)</td><td align="center" valign="middle" >122 (35.7)</td><td align="center" valign="middle" >2 (66.6)</td><td align="center" valign="middle" >55 (40.7)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >29 (39.4)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >2016</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Males</td><td align="center" valign="middle" >3 (60.0)</td><td align="center" valign="middle" >2 (100)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >1 (100)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >1 (50.0)</td><td align="center" valign="middle" >1.905</td><td align="center" valign="middle" >0.592</td></tr><tr><td align="center" valign="middle" >Females</td><td align="center" valign="middle" >2 (40.0)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >1 (50.0)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >2017</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Males</td><td align="center" valign="middle" >3 (50.0)</td><td align="center" valign="middle" >4 (100)</td><td align="center" valign="middle" >2 (50.0)</td><td align="center" valign="middle" >8 (61.5)</td><td align="center" valign="middle" >8 (80.0)</td><td align="center" valign="middle" >13 (61.9)</td><td align="center" valign="middle" >2 (100)</td><td align="center" valign="middle" >5 (100)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >4 (44.4)</td><td align="center" valign="middle" >11.635</td><td align="center" valign="middle" >0.235</td></tr><tr><td align="center" valign="middle" >Females</td><td align="center" valign="middle" >3 (50.0)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >2 (50.0)</td><td align="center" valign="middle" >5 (38.5)</td><td align="center" valign="middle" >2 (20.0)</td><td align="center" valign="middle" >8 (38.1)</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >1 (100)</td><td align="center" valign="middle" >5 (55.5)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >2018</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Males</td><td align="center" valign="middle" >36 (50.0)</td><td align="center" valign="middle" >34 (52.3)</td><td align="center" valign="middle" >15 (62.5)</td><td align="center" valign="middle" >31 (60.8)</td><td align="center" valign="middle" >23 (57.5)</td><td align="center" valign="middle" >25 (54.3)</td><td align="center" valign="middle" >8 (53.3)</td><td align="center" valign="middle" >14 (53.8)</td><td align="center" valign="middle" >10 (52.6)</td><td align="center" valign="middle" >17 (41.5)</td><td align="center" valign="middle" >4.923</td><td align="center" valign="middle" >0.841</td></tr><tr><td align="center" valign="middle" >Females</td><td align="center" valign="middle" >36 (50.0)</td><td align="center" valign="middle" >31 (47.7)</td><td align="center" valign="middle" >9 (37.5)</td><td align="center" valign="middle" >20 (39.2)</td><td align="center" valign="middle" >17 (42.5)</td><td align="center" valign="middle" >21 (45.7)</td><td align="center" valign="middle" >7 (46.7)</td><td align="center" valign="middle" >12 (46.2)</td><td align="center" valign="middle" >9 (47.4)</td><td align="center" valign="middle" >24 (58.5)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >2019</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Males</td><td align="center" valign="middle" >46 (53.5)</td><td align="center" valign="middle" >30 (60.0)</td><td align="center" valign="middle" >20 (62.5)</td><td align="center" valign="middle" >17 (60.7)</td><td align="center" valign="middle" >21 (45.6)</td><td align="center" valign="middle" >39 (66.1)</td><td align="center" valign="middle" >7 (77.7)</td><td align="center" valign="middle" >28 (73.7)</td><td align="center" valign="middle" >14 (66.6)</td><td align="center" valign="middle" >26 (61.9)</td><td align="center" valign="middle" >11.084</td><td align="center" valign="middle" >0.27</td></tr><tr><td align="center" valign="middle" >Females</td><td align="center" valign="middle" >40 (46.5)</td><td align="center" valign="middle" >20 (40.0)</td><td align="center" valign="middle" >12 (37.5)</td><td align="center" valign="middle" >11 (39.3)</td><td align="center" valign="middle" >25 (54.4)</td><td align="center" valign="middle" >20 (33.9)</td><td align="center" valign="middle" >2 (22.2)</td><td align="center" valign="middle" >10 (26.3)</td><td align="center" valign="middle" >7 (33.3)</td><td align="center" valign="middle" >16 (38.1)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >2020</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Males</td><td align="center" valign="middle" >10 (45.5)</td><td align="center" valign="middle" >9 (47.4)</td><td align="center" valign="middle" >4 (40.0)</td><td align="center" valign="middle" >19 (79.2)</td><td align="center" valign="middle" >13 (62.0)</td><td align="center" valign="middle" >20 (55.6)</td><td align="center" valign="middle" >2 (25.0)</td><td align="center" valign="middle" >2 (25.0)</td><td align="center" valign="middle" >5 (62.5)</td><td align="center" valign="middle" >11 (47.8)</td><td align="center" valign="middle" >14.358</td><td align="center" valign="middle" >0.11</td></tr><tr><td align="center" valign="middle" >Females</td><td align="center" valign="middle" >12 (54.5)</td><td align="center" valign="middle" >10 (52.6)</td><td align="center" valign="middle" >6 (60.0)</td><td align="center" valign="middle" >5 (20.8)</td><td align="center" valign="middle" >8 (38.0)</td><td align="center" valign="middle" >16 (44.4)</td><td align="center" valign="middle" >6 (75.0)</td><td align="center" valign="middle" >6 (75.0)</td><td align="center" valign="middle" >3 (37.5)</td><td align="center" valign="middle" >12 (52.2)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle"  colspan="2"  >664.041, 0.000</td><td align="center" valign="middle"  colspan="2"  >205.256, 0.000</td><td align="center" valign="middle"  colspan="2"  >279.671, 0.000</td><td align="center" valign="middle"  colspan="2"  >93.392, 0.000</td><td align="center" valign="middle"  colspan="2"  >254,920, 0.000</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>identification become critical elements of patient care and clinical microbiology in resource limited settings like sub-Saharan Africa [<xref ref-type="bibr" rid="scirp.125981-ref7">7</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref28">28</xref>] .</p><p>In this study, half to two thirds of children admitted during the Manual Blood culture era received a blood culture sampling indicating a substantial risk for blood stream infection. This is in contrast to the automated culture era where only a fifth of the children had blood culture sampled despite increasing patient admissions and risk for bacterial infection. The tenfold increase in the</p><p>break-even cost of Bactec blood culture had significantly negative impact on blood culture uptake in our facility. Blood culture per patient admission [<xref ref-type="bibr" rid="scirp.125981-ref29">29</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref30">30</xref>] declined substantially during the Bactec era undermining the public health significance of etiologic diagnosis of acute febrile illness in a setting where clinical malaria is over-diagnosed, non-prescription antibiotics are prevalent and empiric prescription antibiotic by physicians is the standard clinical practice [<xref ref-type="bibr" rid="scirp.125981-ref16">16</xref>] . There is paucity of reports on the impact of automated microbiology methods on service uptake in Nigeria and in the sub-region. In Nigeria Health Insurance coverage is abysmally low at &lt; 5% [<xref ref-type="bibr" rid="scirp.125981-ref31">31</xref>] with significant impact on out-of-pocket expenses in our subregion, North East of Nigeria, where Multidimensional poverty level is 90% and in Gombe state where child multidimensional poverty level is 95% [<xref ref-type="bibr" rid="scirp.125981-ref32">32</xref>] . These automated systems are costly, require regular maintenance and are not adapted to tropical, dusty environments, transferring costs to patients impeding the sustainable implementation of this technique in many developing countries [<xref ref-type="bibr" rid="scirp.125981-ref7">7</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref33">33</xref>] . If according to a market forecasting study, manual blood culture systems will make up roughly two-thirds of the global blood culture market by 2025 [<xref ref-type="bibr" rid="scirp.125981-ref9">9</xref>] recommendations for improvement in manual blood culture and clinical laboratory methods in low resource settings require urgency of implementation [<xref ref-type="bibr" rid="scirp.125981-ref7">7</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref34">34</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref35">35</xref>] .</p><p>Pathogen detection and identification is at the heart of tackling infectious diseases in general, whether it is for guiding optimal treatment or for detecting and controlling outbreaks of emerging and drug-resistant pathogens and good quality microbiological diagnostics remains the key factor [<xref ref-type="bibr" rid="scirp.125981-ref36">36</xref>] .</p><p>Blood culture positivity trend was higher and sustained in the Bactec era compared to the Manual era. Previous reports in Nigeria [<xref ref-type="bibr" rid="scirp.125981-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref37">37</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref38">38</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref39">39</xref>] and elsewhere [<xref ref-type="bibr" rid="scirp.125981-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref13">13</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref40">40</xref>] have shown higher pathogen yield and shorter turnaround time with Bactec culture systems over the conventional/manual method. However, and in general, access to quality-assured laboratory diagnosis has been a challenge in low-income and middle-income countries (LMICs) resulting in delayed or inaccurate diagnosis and ineffective treatment with consequences for patient safety [<xref ref-type="bibr" rid="scirp.125981-ref41">41</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref42">42</xref>] .</p><p>More male than female children had received blood culture on a year-by-year basis implying a substantial risk for blood stream infection among male children. But this was not statistically significant (x<sup>2</sup> = 13.173, 0.155). Similar findings were reported from Nigeria [<xref ref-type="bibr" rid="scirp.125981-ref43">43</xref>] , Ghana [<xref ref-type="bibr" rid="scirp.125981-ref44">44</xref>] , Tanzania [<xref ref-type="bibr" rid="scirp.125981-ref45">45</xref>] and Switzerland [<xref ref-type="bibr" rid="scirp.125981-ref46">46</xref>] . Most epidemiological studies have shown that being a male is a risk factor for infectious diseases and women are at less risk than men when it comes to developing most infectious diseases (x<sup>2</sup> = 7.112; 0.626) [<xref ref-type="bibr" rid="scirp.125981-ref47">47</xref>] . This sex dimorphism to infection is related to the interplay of age, comorbidities, genetic predispositions, geographical distribution of pathogens, health behaviors, access to healthcare, and hormonal influences [<xref ref-type="bibr" rid="scirp.125981-ref48">48</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref49">49</xref>] .</p><p>Throughout the review period newborns in particular and children under Five years had more blood cultures performed on yearly basis compared to other child age categories. The incidence of bloodstream infections is highest at extremes of age, in neonates and elderly people [<xref ref-type="bibr" rid="scirp.125981-ref50">50</xref>] and febrile illness is the commonest cause of hospitalization in children &lt; 5 years in sub-Saharan Africa with bacterial bloodstream infections and malaria as major causes of death [<xref ref-type="bibr" rid="scirp.125981-ref24">24</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref51">51</xref>] Several studies have documented risk factors for blood stream infection in the newborn and under 5 children [<xref ref-type="bibr" rid="scirp.125981-ref45">45</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref52">52</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref53">53</xref>] . Co morbidities like undernutrition, Malaria, anaemia and HIV have added to the burden of BSI in sub-Saharan Africa [<xref ref-type="bibr" rid="scirp.125981-ref16">16</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref54">54</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref55">55</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref56">56</xref>] .</p><p>In this study a trend towards Staph aureus, Klebsiella and E. coli being the dominant pathogens isolated from blood cultures of children during the manual era with variable frequencies was observed. Staph aureus isolation increased substantially in our centre with Bactec automated system. Similarly, Citrobacter and alkaligenes were isolated with increasing frequency in the automated blood culture system. While there is paucity of comparable reports to ours in the country and subregion early [<xref ref-type="bibr" rid="scirp.125981-ref57">57</xref>] - [<xref ref-type="bibr" rid="scirp.125981-ref63">63</xref>] and recent studies [<xref ref-type="bibr" rid="scirp.125981-ref43">43</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref64">64</xref>] - [<xref ref-type="bibr" rid="scirp.125981-ref69">69</xref>] , in Nigeria and elsewhere [<xref ref-type="bibr" rid="scirp.125981-ref30">30</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref70">70</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref71">71</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref72">72</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref73">73</xref>] have demonstrated the preponderance of staph aureus, E. coli, Klebsiella and or Pseudomonas in blood stream infections in children 0 - 18 years. While Salmonella and Streptococcus pneumonia were infrequently isolated in our study and others in Nigeria [<xref ref-type="bibr" rid="scirp.125981-ref57">57</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref58">58</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref64">64</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref68">68</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref69">69</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref74">74</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref75">75</xref>] , the reports of Obaro et al. [<xref ref-type="bibr" rid="scirp.125981-ref16">16</xref>] and others in the country [<xref ref-type="bibr" rid="scirp.125981-ref76">76</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref77">77</xref>] have demonstrated the significance of these pathogens in blood stream infections in children. Typhoid fever and Invasive Non Typhoidal Salmonella disease are major agents of invasive bloodstream infections in urban and rural locations, affecting children more commonly than adults across sub-Saharan Africa [<xref ref-type="bibr" rid="scirp.125981-ref78">78</xref>] . Streptococcus pneumoniae is capable of causing a spectrum of disease in children, the most severe of which is invasive pneumococcal disease (IPD), which includes bacteraemic pneumonia, meningitis and sepsis [<xref ref-type="bibr" rid="scirp.125981-ref75">75</xref>] Nevertheless, rates of pneumococcal disease are estimated to be highest on the African continent, causing over 4 million cases a year in children under 5 years; Pneumococcal disease also contributes to substantial mortality, driven predominantly by mortality from pneumococcal pneumonia [<xref ref-type="bibr" rid="scirp.125981-ref79">79</xref>] . With increasing pneumococcal vaccine coverage among children in sub-Saharan Africa, the burden of pneumococcal disease and its invasive forms is reducing [<xref ref-type="bibr" rid="scirp.125981-ref80">80</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref81">81</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref82">82</xref>] . The year-on-year isolation of Citrobacter and alkaligenes increased in the Bactec era compared to the manual blood culture period. Citrobacter, a facultative gram-negative anaerobic bacillus belonging to the family Enterobacteriaceae is being increasingly recognized to cause a wide spectrum of infections especially in immunocompromised or patients with comorbidities [<xref ref-type="bibr" rid="scirp.125981-ref83">83</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref84">84</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref85">85</xref>] .</p><p>These gram-negative bacilli constituted 1.3% [<xref ref-type="bibr" rid="scirp.125981-ref86">86</xref>] , 1.9% [<xref ref-type="bibr" rid="scirp.125981-ref87">87</xref>] of blood cultures isolates in Nigeria studies; 9.5% in Tanzania [<xref ref-type="bibr" rid="scirp.125981-ref88">88</xref>] ; &lt;1% in Malawi [<xref ref-type="bibr" rid="scirp.125981-ref89">89</xref>] and 2.2% in Rwanda [<xref ref-type="bibr" rid="scirp.125981-ref90">90</xref>] , 2.4% in India [<xref ref-type="bibr" rid="scirp.125981-ref91">91</xref>] , 1.2% in Kenya [<xref ref-type="bibr" rid="scirp.125981-ref92">92</xref>] and 15% in Ghana [<xref ref-type="bibr" rid="scirp.125981-ref72">72</xref>] .</p><p>Alcaligenes spp are Gram-negative, obligate aerobic, oxidase-positive, catalase-positive, and nonfermenting bacteria. It is a potentially emerging pathogen and usually causes opportunistic infections in humans. The most commonly reported cases involved bacteremia, and most cases occurred in newborns and infants [<xref ref-type="bibr" rid="scirp.125981-ref93">93</xref>] . They are commonly found in hospital settings, such as in respirators, hemodialysis systems, and intravenous solutions [<xref ref-type="bibr" rid="scirp.125981-ref94">94</xref>] . A systematic review on bacterial isolates in sub-Saharan Africa by Reddy et al. [<xref ref-type="bibr" rid="scirp.125981-ref95">95</xref>] showed a &lt;1% prevalence of Alcaligenes; recent systemic review in Africa and Asia [<xref ref-type="bibr" rid="scirp.125981-ref96">96</xref>] showed similar very low isolation rate. However, rather than a contaminant, Alcaligenes should be regarded as a pathogen, because global cases of life-threatening infections caused by A. faecalis are emerging [<xref ref-type="bibr" rid="scirp.125981-ref97">97</xref>] . The lack of widespread access to automated blood culture and pathogen identification systems in many developing countries may have contributed to the low isolation of some pathogens [<xref ref-type="bibr" rid="scirp.125981-ref16">16</xref>] . These automated platforms have improved time to detection and recovery of both aerobic and anaerobic organisms and made possible the neutralization of several anti-biotics present in blood culture media. They have minimized contamination and bio-hazard risk [<xref ref-type="bibr" rid="scirp.125981-ref10">10</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref16">16</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref98">98</xref>] .</p><p>In general, the unregulated [<xref ref-type="bibr" rid="scirp.125981-ref99">99</xref>] and widespread use of prehospital antibiotics [<xref ref-type="bibr" rid="scirp.125981-ref100">100</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref101">101</xref>] , empirical antibiotic prescription [<xref ref-type="bibr" rid="scirp.125981-ref102">102</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref103">103</xref>] glaring gaps and constraints in clinical microbiology laboratory standards in especially sub-Saharan Africa [<xref ref-type="bibr" rid="scirp.125981-ref34">34</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref104">104</xref>] have impacted significantly on pathogen isolation, identification and therefore surveillance. On the other hand, these aforementioned factors should give impetus an d accelerate policy revision, guideline development and update, on antimicrobials and clinical laboratory standards particularly now and within the arm bit of one health in sub Saharan Africa and other LMICs.</p><p>Antimicrobial resistance is a global threat and Africa bears disproportionately this burden [<xref ref-type="bibr" rid="scirp.125981-ref105">105</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref106">106</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref107">107</xref>] . Increasing cost of health care and poor patient outcomes are attributable to AMR especially in LMIC [<xref ref-type="bibr" rid="scirp.125981-ref108">108</xref>] . There is paucity of comparable resistance trend report in Nigeria and the subregion, however an earlier systematic review in patients with BSI in West Africa by Barnabe et al. [<xref ref-type="bibr" rid="scirp.125981-ref109">109</xref>] reported a 17.7% resistance to third-generation cephalosporin, 37.2% to Genticin, 68.4% to Ampicillin and 13.2% to ciprofloxacin. While resistance to 3 GC, Genticin and Ampicillin are comparable to the study mean values, ciprofloxacin resistance was threefold higher. This overall moderate level of AMR is likely to undermine typical empirical antibiotic strategy [<xref ref-type="bibr" rid="scirp.125981-ref109">109</xref>] .</p><p>WHO recommends a third-generation cephalosporin as second-line antibiotic [<xref ref-type="bibr" rid="scirp.125981-ref110">110</xref>] but many low- and middle-income countries (LMIC) utilize third-generation cephalosporins-ceftriaxone as first-line treatment for severe sepsis at district, regional and tertiary health care facilities owing their widespread availability [<xref ref-type="bibr" rid="scirp.125981-ref77">77</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref111">111</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref112">112</xref>] .</p><p>Lester et al. [<xref ref-type="bibr" rid="scirp.125981-ref113">113</xref>] in systematic review in SSA showed a mean estimate of 3 CG resistance to E. coli, Klebsiella and Salmonella of 18.4%, 54.4% and 1.9% respectively establishing significant heterogeneity not explained by differences in African region group of patients recommending that detailed clinical and demographic parameters should be collected to deepen the understanding of drug resistance isolates and the drivers of transmission of AMR pathogens [<xref ref-type="bibr" rid="scirp.125981-ref113">113</xref>] .</p><p>Several Systematic reviews in children in Africa and other LMICS have reported varying 3 GC resistance of 19% against ceftazidime [<xref ref-type="bibr" rid="scirp.125981-ref114">114</xref>] , 49% [<xref ref-type="bibr" rid="scirp.125981-ref115">115</xref>] and 33.9% to ceftriaxone [<xref ref-type="bibr" rid="scirp.125981-ref116">116</xref>] . These reviews also reported ciprofloxacin (43.3%, 44%, 12%), aminoglycoside (14%, 33.5%, 37.2%) and ampicillin (85%, 59.7% 68.8%) resistance rates, noting the high variation between antimicrobial groups and rates, high variation in antibiotics tested against the isolates with significant heterogeneity and low comparability of studies [<xref ref-type="bibr" rid="scirp.125981-ref114">114</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref115">115</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref116">116</xref>] . These researchers highlighted a continent-wide increase in AMR reporting and in resistance and substantial challenges in diagnostic microbiological data quality. Priority strengthening of laboratory capacity, standardized testing and surveillance efforts, and reporting of AST results are required to improve AMR [<xref ref-type="bibr" rid="scirp.125981-ref105">105</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref114">114</xref>] [<xref ref-type="bibr" rid="scirp.125981-ref116">116</xref>] .</p><p>A recent review showed Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa as six leading pathogens for deaths associated with AMR and the following One pathogen-drug combination, methicillin resistant S. aureus, third-generation cephalosporin-resistant E. coli, carbapenem-resistant A. baumannii, fluoroquinolone-resistant E. coli, carbapenem resistant K. pneumoniae, and third-generation cephalosporin-resistant K. pneumoniae related AMR deaths [<xref ref-type="bibr" rid="scirp.125981-ref4">4</xref>] . In conclusion, while Blood sampling for culture has decreased in our facility on account of higher cost of Bactec blood culture, however the isolation of pathogens through this platform has increased significantly overall. Staph aureus was the leading isolate with Alcaligenes and Citrobacter also being grown increasingly with the use of Bactec automated method. Bacterial Resistance to commonly used antibiotics was multiple, and in general moderate to high.</p></sec><sec id="s4"><title>4. Conclusion</title><p>Blood sampling for culture per patient admission is low in the Bactec era. The trend in blood culture positivity is higher with Bactec automated culture system with Staph. Aureus the leading pathogen isolated in both microbiologic eras. Citrobacter and Alcaligenes were increasingly isolated with the automated culture system. The trend in Resistance to commonly used antibiotics was high with mild to moderate resistance to aminoglycoside and the third-generation cephalosporin.</p></sec><sec id="s5"><title>Limitation of the Study</title><p>As a retrospective study, microbiology quality and standards in laboratory could not always be guaranteed despite presence of highly qualified personnel and significantly the lack of any external quality assurance of these procedures in our laboratory.</p></sec><sec id="s6"><title>Recommendations</title><p>Establishment of the collaborative multi-site multi-level health facility surveillance microbiology laboratories with effective and coordinated governance structure in Nigeria and other sub-Saharan African countries.</p><p>Collaborative partnership to upscale human capacity and automated microbiologic systems for culture and pathogen identification in specifically high patient flow facilities and the country in general which may impact positively on costs.</p><p>Advocacy for reduction in the unit price and consumables of automated blood culture and identification systems.</p></sec><sec id="s7"><title>Author Contribution</title><p>WEI, MM conceived of the study and study design. WEI developed the first manuscript draft, and critically reviewed all drafts of the manuscript. IJ and IM critically reviewed bacterial isolates and reviewed draft manuscript. AJD and CO conducted quantitative analysis and critically reviewed the final manuscript.</p></sec><sec id="s8"><title>Acknowledgements</title><p>Hajiya Fatima, Hafsat Sabo, Monica Shamaki and Dorcas for data extraction from the laboratory register.</p></sec><sec id="s9"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s10"><title>Cite this paper</title><p>Isaac, E.W., Jalo, I., Manga, M.M., Difa, A.J., Poksireni, M.R., Christianah, O., Mohammed, I. and Charanci, M.S. (2023) Trends in Bacterial Blood Culture Isolates and Resistance in Children in Two Microbiologic Eras from a Tertiary Health Facility in North East Nigeria. 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