<?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">AID</journal-id><journal-title-group><journal-title>Advances in Infectious Diseases</journal-title></journal-title-group><issn pub-type="epub">2164-2648</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/aid.2021.113024</article-id><article-id pub-id-type="publisher-id">AID-111413</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>
 
 
  The Impact of Coronavirus Disease 2019 (COVID-19) among Immune Compromised Patients in Augusta Victoria Hospital AVH-2021
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Maen</surname><given-names>Hajmohammasd</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>Rami</surname><given-names>Zighari</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>Hammam</surname><given-names>Rjoup</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>Tahreer</surname><given-names>Taha</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>Sari</surname><given-names>Abu Hania</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>Faeda</surname><given-names>Eqtait</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>Bilal</surname><given-names>Shawamreh</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>Yousef</surname><given-names>Hamamra</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>Haitham</surname><given-names>Al-Amleh</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>Murad</surname><given-names>Krajah</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>Noor</surname><given-names>Ismael</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>Ali</surname><given-names>Sabateen</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Arab American University, Jenin, Palestine</addr-line></aff><aff id="aff1"><addr-line>Augusta Victoria Hospital, Jerusalem, Palestine</addr-line></aff><pub-date pub-type="epub"><day>23</day><month>08</month><year>2021</year></pub-date><volume>11</volume><issue>03</issue><fpage>269</fpage><lpage>277</lpage><history><date date-type="received"><day>20,</day>	<month>July</month>	<year>2021</year></date><date date-type="rev-recd"><day>20,</day>	<month>August</month>	<year>2021</year>	</date><date date-type="accepted"><day>23,</day>	<month>August</month>	<year>2021</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>
 
 
  Background: Coronavirus disease 2019 which is officially known as COVID-19 belongs to family viruses. COVID-19 manifestations vary among affected people. These symptoms may become more serious among patients suffering from chronic disease and those who are on treatment which may af-fect their defense mechanism or immune-compromised patients who become more vulnerable to complications of COVID-19, and at high risk for morbidity and mortality with any bacterial or viral illness. 
  Method: A retrospective, non-experimental research design was applied with a quantitative approach among patients with COVID-19 who were admitted to COVID-19 department at AVH with a total of 72 patients. Data were extracted from a patients’ elec-tronic medical record. 
  Results: During COVID-19 outbreak 72 patients were admitted to COVID department at AVH, 54.2% were female and 33% of study participants were from Gaza governorate followed by Jerusalem 27%. Most participants 34.7% had first clinic visit after two days from the onset of COVID-19 symptoms. 45.8% were discharged to home while 13.9% died. All inflammatory markers that include ferritin, C-RP, IL-6 and D-dimer are in-creasing in all patients that were admitted to hospital; IL-6 and D-dimer were significant inflammatory markers in relation to the mortality rate. The study found the risk of mortality with IL-6 mean (218.5), and D-dimer mean (12). Furthermore there was a relation between increased risk of mortality and im-mune comprised. 
  Conclusion: Mortality rate increased among COVID-19 pa-tients when IL-6 was higher than 218.5 and D-dimer higher than 12, and there was a relationship between increased risk of mortality and immune comprised.
 
</p></abstract><kwd-group><kwd>Coronavirus</kwd><kwd> Immune Compromised</kwd><kwd> Augusta Victoria Hospital</kwd><kwd> Inflammatory Marker</kwd><kwd> Interleukin 6</kwd><kwd> Mortality</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction and Literature Review</title><p>Coronavirus disease 2019 which is officially known as COVID-19 belongs to family viruses. It was believed that the virus broke out in Wuhan city in China in December 2019, and the virus rapidly spread all over the world [<xref ref-type="bibr" rid="scirp.111413-ref1">1</xref>]. The World Health Organization (WHO) on March 11, 2020, announced the COVID-19 outbreak as a global pandemic [<xref ref-type="bibr" rid="scirp.111413-ref2">2</xref>] and declared a public health emergency problem. This health problem stressed health care systems and increased the need to assign COVID-19 special centers or hospitals worldwide.</p><p>COVID-19 manifestations vary among affected people; some people became asymptomatic, others suffer from mild symptoms like high temperature, dry cough, nasal congestion, general malaise, and sore throat, while others complain of severe symptoms like adult respiratory distress syndrome [<xref ref-type="bibr" rid="scirp.111413-ref3">3</xref>]. These symptoms may become more serious among patients suffering from chronic disease and those who are on treatment which may affect their defense mechanism or immune-compromised patients who become more vulnerable to complications of COVID-19.</p><p>Immune-compromised like hemato-oncology or renal replacement therapy.</p><p>Patients have a defect in immune system reaction due to a primary disease or for another superimposed which makes them at high risk for morbidity and mortality with any bacterial or viral illness and this fully applies to COVID-19 [<xref ref-type="bibr" rid="scirp.111413-ref4">4</xref>]. During the peak of the COVID-19 pandemic, and due to the continuous increase in the number of affected people, there was an urgent need to increase the number of hospital beds. As the immune-compromised patients are at risk for a more severe outcome, the need for hospitalization increases for these people [<xref ref-type="bibr" rid="scirp.111413-ref5">5</xref>]. The immune-compromised patients with COVID-19 are presumed to have severe clinical features and bad outcomes as they have a low inflammatory response [<xref ref-type="bibr" rid="scirp.111413-ref4">4</xref>]. However, the relationship between the immune response to coronaviruses and the severity of clinical features is still inquired, as the adaptive immune system is not an indicator to prevent a severe viral illness [<xref ref-type="bibr" rid="scirp.111413-ref6">6</xref>]. It is thought that these patients who are on life-sustaining treatment, will be more physiologically vulnerable to COVID-19.</p><p>Up to our knowledge, till now, there is no clear evidence that immune-compromised patients are at more risk for mortality or morbidity from COVID-19. Thus our research will focus more on these patients to explore evidence about the impact of (COVID-19) among immune-compromised patients who seek care at Augusta Victoria Hospital. Augusta Victoria Hospital (AVH) is a program of the Lutheran World Federated, a church-hospital complex and the second largest hospital located in East Jerusalem. Augusta Victoria Hospital provides special care for Palestinian people from Jerusalem, West Bank, and Gaza Strip. It provides hemato-oncology care including bone marrow transplant, artificial kidney units, and skilled nursing care [<xref ref-type="bibr" rid="scirp.111413-ref7">7</xref>].</p></sec><sec id="s2"><title>2. Methodology</title><p>A retrospective, non-experimental research design was applied with a quantitative approach, to assess the impact of Coronavirus disease 2019 (COVID-19) among immune compromised patients. Study enrolled adult inpatients (≥18 years old) from AVH (East Jerusalem, West Bank). This study enrolled in patients who were hospitalized for COVID-19 department between April/ 2020-January, 2021 and with outcome either dead or discharged.</p><p>The investigator specifies the subjects according to the inclusion criteria. Patients with other respiratory problems were excluded. This study includes 72 patients. Data for this study were obtained retrospectively from electronic medical records of COVID-19 in AVH during course of illness. The socio-demographic, laboratory tests, signs and symptoms and outcome data were extracted from a patients’ electronic medical record in AVH. All required data were entered by two researchers into electronic form which was created by researchers for this purpose. Data were revised by third researcher for completeness and correctness.</p></sec><sec id="s3"><title>3. Ethical Consideration</title><p>This study was approved by the Augusta Victoria Hospital AVH. Approval from COVID-19 patients was obtained. Several strategies were utilized to protect the subjects rights who agreed to participate in this study. Oral verbal consent of the COVID-19 patients was obtained prior to utilize data. COVID-19 patients were informed of the purpose of the study, and that they had the right to refuse to participate. Also the voluntary nature of participation was stressed as well as confidentiality.</p></sec><sec id="s4"><title>4. Data Analysis</title><p>The quantitative data was analyzed using the SPSS (Statistical Package for Social Sciences version 23.0), and the level of significance (α) set at 0.05.</p><p>- Descriptive statistics: descriptive statistical analysis includes frequencies, percentages.</p><p>- Inferential statistic: Difference in course of illness scores analyzed by using T-test; to determine if there is a significant difference between the means of two groups.</p><p>- Chi-square: Examine the differences between categorical variables in the same population.</p></sec><sec id="s5"><title>5. Results</title><p>The majority of sample was female (54.2%), and (62%) of them were married, (95.8%) of study participants are lived in city, and (66.7%) never smoked (<xref ref-type="table" rid="table1">Table 1</xref>).</p><p>Results show that the majority of participants were between 56 - 75 years old, and (6%) below 18 years. Furthermore, most patients were from Gaza governorate (33%), while (27%) were from Jerusalem (<xref ref-type="fig" rid="fig1">Figure 1</xref>).</p><p>In addition study results revealed that there was a difference between patients regarding the time from onset of symptoms to first clinical visit that most patients had the first clinic visit after two days from the onset of symptoms (34.7%), and only (1.4%) patients have the first visit after eight days (<xref ref-type="table" rid="table2">Table 2</xref>).</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Demographic characteristics of study participants (N = 72)</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >Frequency</th><th align="center" valign="middle" >Percentage</th></tr></thead><tr><td align="center" valign="middle"  colspan="3"  >Gender</td></tr><tr><td align="center" valign="middle" >Male</td><td align="center" valign="middle" >33</td><td align="center" valign="middle" >45.8</td></tr><tr><td align="center" valign="middle" >Female</td><td align="center" valign="middle" >39</td><td align="center" valign="middle" >54.2</td></tr><tr><td align="center" valign="middle"  colspan="3"  >Marital status</td></tr><tr><td align="center" valign="middle" >Married</td><td align="center" valign="middle" >62</td><td align="center" valign="middle" >86.1</td></tr><tr><td align="center" valign="middle" >Single</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >13.9</td></tr><tr><td align="center" valign="middle"  colspan="3"  >Residency</td></tr><tr><td align="center" valign="middle" >City</td><td align="center" valign="middle" >69</td><td align="center" valign="middle" >95.8</td></tr><tr><td align="center" valign="middle" >Village</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >4.2</td></tr><tr><td align="center" valign="middle"  colspan="3"  >History of smoking</td></tr><tr><td align="center" valign="middle" >Smoker</td><td align="center" valign="middle" >19</td><td align="center" valign="middle" >26.4</td></tr><tr><td align="center" valign="middle" >Ex-smoker</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >6.9</td></tr><tr><td align="center" valign="middle" >Never smoking</td><td align="center" valign="middle" >48</td><td align="center" valign="middle" >66.7</td></tr></tbody></table></table-wrap><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Time from onset of symptoms to first clinical visit</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Days</th><th align="center" valign="middle" >Frequency</th><th align="center" valign="middle" >Percent</th></tr></thead><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >21</td><td align="center" valign="middle" >29.2</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >25</td><td align="center" valign="middle" >34.7</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >11</td><td align="center" valign="middle" >15.3</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >13.9</td></tr><tr><td align="center" valign="middle" >5</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >2.8</td></tr><tr><td align="center" valign="middle" >6</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >2.8</td></tr><tr><td align="center" valign="middle" >8</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >1.4</td></tr><tr><td align="center" valign="middle" >Total</td><td align="center" valign="middle" >72</td><td align="center" valign="middle" >100.0</td></tr></tbody></table></table-wrap><p>For the end status of patients who were admitted to ICU, the majority of patients (45.8%) were discharged to home and 27.8% were transferred to more specialized hospital, and 13.9 % of patients were died (<xref ref-type="table" rid="table3">Table 3</xref>).</p><p>Regarding source of infection from COVID-19, most of patients (73.6%) got the virus from community interaction, while only (8.3%) got infection during hospitalization days (<xref ref-type="table" rid="table4">Table 4</xref>).</p><p>Alongside, to determine if there was a significant relationship between elevated inflammatory marker and mortality rate, t-test was applied to identify if there was a significant difference between the means, so study results indicated that there is significant relationship between elevated increased Interleukin 6 [IL-6] and D-dimer and mortality rate as mortality rate increased with increased Interleukin 6 [IL-6] and D-dimer as P-value less than 0.05 (<xref ref-type="table" rid="table5">Table 5</xref>).</p><p>The results show there was increase in all inflammatory markers CRP, ferritin, IL-6 and D-Dimer above normal range, and the mean risk of mortality was increased with inflammatory markers; IL-6 mean level of (218.5), and D-dimer mean level of (12) (<xref ref-type="table" rid="table6">Table 6</xref>).</p><p>Furthermore, results indicated by t-test that there is significant relation regarding WBC count as P-value less than 0.05, by more focus on WBC differential we found that there is significant relation regarding Lymphocytes count with mortality as P-value less than 0.05, while there is no significant relation regarding Neutrophils count with mortality as P-value more than 0.05 (<xref ref-type="table" rid="table7">Table 7</xref>).</p><p>The results also revealed by using Chi-square test that there is significant relation regarding mortality in immune compromised patients as P-value less than 0.05 (<xref ref-type="table" rid="table8">Table 8</xref>).</p><p>In addition, there was no significant relation by using Chi-square between end stage kidney disease and risk of mortality among patients diagnosed with COVID-19 (<xref ref-type="table" rid="table9">Table 9</xref>).</p><p>The study Chi-square results about mortality rate in oncology patients that there is no significant relation between history of cancer and COVID-19 mortality (<xref ref-type="table" rid="table1">Table 1</xref>0).</p><p>The study results also show by Chi-square that there is no significant relation between history of hematological malignancies and COVID-19 mortality (<xref ref-type="table" rid="table1">Table 1</xref>1).</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> End status of patients who were admitted to ICU</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >Frequency</th><th align="center" valign="middle" >Percent</th></tr></thead><tr><td align="center" valign="middle"  rowspan="5"  >Transferred Discharged home Still admitted at the time of admission died Total</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >27.8</td></tr><tr><td align="center" valign="middle" >33</td><td align="center" valign="middle" >45.8</td></tr><tr><td align="center" valign="middle" >9</td><td align="center" valign="middle" >12.5</td></tr><tr><td align="center" valign="middle" >10</td><td align="center" valign="middle" >13.9</td></tr><tr><td align="center" valign="middle" >72</td><td align="center" valign="middle" >100.0</td></tr></tbody></table></table-wrap><table-wrap id="table4" ><label><xref ref-type="table" rid="table4">Table 4</xref></label><caption><title> Source of infection</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >Frequency</th><th align="center" valign="middle" >Percent</th></tr></thead><tr><td align="center" valign="middle"  rowspan="4"  >family hospital community Total</td><td align="center" valign="middle" >13</td><td align="center" valign="middle" >18.1</td></tr><tr><td align="center" valign="middle" >6</td><td align="center" valign="middle" >8.3</td></tr><tr><td align="center" valign="middle" >53</td><td align="center" valign="middle" >73.6</td></tr><tr><td align="center" valign="middle" >72</td><td align="center" valign="middle" >100.0</td></tr></tbody></table></table-wrap><table-wrap id="table5" ><label><xref ref-type="table" rid="table5">Table 5</xref></label><caption><title> Relationship between inflammatory marker and mortality rate</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="2"   rowspan="2"  ></th><th align="center" valign="middle"  colspan="2"  >Levene’s Test for Equality of Variances</th></tr></thead><tr><td align="center" valign="middle" >F</td><td align="center" valign="middle" >Sig.</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >CRP result</td><td align="center" valign="middle" >Equal variances assumed</td><td align="center" valign="middle"  rowspan="2"  >0.000</td><td align="center" valign="middle"  rowspan="2"  >0.995</td></tr><tr><td align="center" valign="middle" >Equal variances not assumed</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >IL-6 result</td><td align="center" valign="middle" >Equal variances assumed</td><td align="center" valign="middle"  rowspan="2"  >4.314</td><td align="center" valign="middle"  rowspan="2"  >0.047</td></tr><tr><td align="center" valign="middle" >Equal variances not assumed</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >D-dimer result</td><td align="center" valign="middle" >Equal variances assumed</td><td align="center" valign="middle"  rowspan="2"  >9.738</td><td align="center" valign="middle"  rowspan="2"  >0.004</td></tr><tr><td align="center" valign="middle" >Equal variances not assumed</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Ferritn result</td><td align="center" valign="middle" >Equal variances assumed</td><td align="center" valign="middle"  rowspan="2"  >0.00</td><td align="center" valign="middle"  rowspan="2"  >0.99.</td></tr><tr><td align="center" valign="middle" >Equal variances not assumed</td></tr></tbody></table></table-wrap><table-wrap id="table6" ><label><xref ref-type="table" rid="table6">Table 6</xref></label><caption><title> Distribution of mortality cases according to inflammatory markers</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="2"  >Mortality</th><th align="center" valign="middle" >N</th><th align="center" valign="middle" >Mean</th><th align="center" valign="middle" >Std. Deviation</th><th align="center" valign="middle" >Std. Error Mean</th></tr></thead><tr><td align="center" valign="middle"  rowspan="2"  >CRP result</td><td align="center" valign="middle" >Died</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >152.9000</td><td align="center" valign="middle" >127.69507</td><td align="center" valign="middle" >73.72478</td></tr><tr><td align="center" valign="middle" >Survive</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >99.7282</td><td align="center" valign="middle" >117.25979</td><td align="center" valign="middle" >22.16002</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >IL-6 result</td><td align="center" valign="middle" >Died</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >218.4500</td><td align="center" valign="middle" >228.89047</td><td align="center" valign="middle" >161.85000</td></tr><tr><td align="center" valign="middle" >Survive</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >64.3504</td><td align="center" valign="middle" >91.66694</td><td align="center" valign="middle" >17.32342</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >D-dimer result</td><td align="center" valign="middle" >Died</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >12.0267</td><td align="center" valign="middle" >19.03111</td><td align="center" valign="middle" >10.98761</td></tr><tr><td align="center" valign="middle" >Survive</td><td align="center" valign="middle" >30</td><td align="center" valign="middle" >3.2427</td><td align="center" valign="middle" >6.89275</td><td align="center" valign="middle" >1.25844</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Ferritin result</td><td align="center" valign="middle" >Died</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >1729.0000</td><td align="center" valign="middle" >.</td><td align="center" valign="middle" >.</td></tr><tr><td align="center" valign="middle" >Survive</td><td align="center" valign="middle" >25</td><td align="center" valign="middle" >724.9296</td><td align="center" valign="middle" >1205.23681</td><td align="center" valign="middle" >241.04736</td></tr></tbody></table></table-wrap><table-wrap id="table7" ><label><xref ref-type="table" rid="table7">Table 7</xref></label><caption><title> Relation between complete blood count and mortality rate</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="3"   rowspan="2"  ></th><th align="center" valign="middle"  colspan="2"  >Levene’s Test for Equality of Variances</th></tr></thead><tr><td align="center" valign="middle" >F</td><td align="center" valign="middle" >Sig.</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Platelets count</td><td align="center" valign="middle"  colspan="2"  >Equal variances assumed</td><td align="center" valign="middle"  rowspan="2"  >0.705</td><td align="center" valign="middle"  rowspan="2"  >0.405</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Equal variances not assumed</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >RBC count</td><td align="center" valign="middle"  colspan="2"  >Equal variances assumed</td><td align="center" valign="middle"  rowspan="2"  >0.514</td><td align="center" valign="middle"  rowspan="2"  >0.477</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Equal variances not assumed</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Basophils count</td><td align="center" valign="middle" >Equal variances assumed</td><td align="center" valign="middle"  colspan="2"   rowspan="2"  >0.603</td><td align="center" valign="middle"  rowspan="2"  >0.441</td></tr><tr><td align="center" valign="middle" >Equal variances not assumed</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >Eosinophils count</td><td align="center" valign="middle" >Equal variances assumed</td><td align="center" valign="middle"  colspan="2"   rowspan="2"  >2.398</td><td align="center" valign="middle"  rowspan="2"  >0.128</td></tr><tr><td align="center" valign="middle" >Equal variances not assumed</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Neutrophils count</td><td align="center" valign="middle"  colspan="2"  >2.655</td><td align="center" valign="middle" >0.110</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Lymphocytes count</td><td align="center" valign="middle"  colspan="2"  >5.433</td><td align="center" valign="middle" >0.024</td></tr><tr><td align="center" valign="middle"  colspan="2"  >WBC count</td><td align="center" valign="middle"  colspan="2"  >13.259</td><td align="center" valign="middle" >0.001</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Hb count (g/dl)</td><td align="center" valign="middle"  colspan="2"  >4.010</td><td align="center" valign="middle" >0.051</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></tr></tbody></table></table-wrap><table-wrap id="table8" ><label><xref ref-type="table" rid="table8">Table 8</xref></label><caption><title> Relationship between mortality in immune compromised patients and COIVD-19</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >Value</th><th align="center" valign="middle" >df</th><th align="center" valign="middle" >Asymp. Sig. (2-sided)</th></tr></thead><tr><td align="center" valign="middle" >Pearson Chi-Square</td><td align="center" valign="middle" >3.835<sup>a</sup></td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.049</td></tr><tr><td align="center" valign="middle" >Continuity Correction</td><td align="center" valign="middle" >2.601</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.107</td></tr></tbody></table></table-wrap><table-wrap id="table9" ><label><xref ref-type="table" rid="table9">Table 9</xref></label><caption><title> Mortality in End Stage Kidney Disease ESRD patients</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="6"  >Chi-Square Tests</th></tr></thead><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >Value</td><td align="center" valign="middle" >df</td><td align="center" valign="middle" >Asymp. Sig. (2-sided)</td><td align="center" valign="middle" >Exact Sig. (2-sided)</td><td align="center" valign="middle" >Exact Sig. (1-sided)</td></tr><tr><td align="center" valign="middle" >Pearson Chi-Square</td><td align="center" valign="middle" >0.078<sup>a</sup></td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.780</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Continuity Correction<sup>b</sup></td><td align="center" valign="middle" >0.000</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >1.000</td><td align="center" valign="middle"  rowspan="2"  ></td><td align="center" valign="middle"  rowspan="2"  ></td></tr><tr><td align="center" valign="middle" >Likelihood Ratio</td><td align="center" valign="middle" >0.076</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.783</td></tr><tr><td align="center" valign="middle" >N of Valid Cases</td><td align="center" valign="middle" >72</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" >0.717</td><td align="center" valign="middle" >0.524</td></tr></tbody></table></table-wrap><table-wrap id="table10" ><label><xref ref-type="table" rid="table1">Table 1</xref>0</label><caption><title> Mortality in oncology patients with COVID-19</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="6"  >Chi-Square Tests</th></tr></thead><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >Value</td><td align="center" valign="middle" >df</td><td align="center" valign="middle" >Asymp. Sig. (2-sided)</td><td align="center" valign="middle" >Exact Sig. (2-sided)</td><td align="center" valign="middle" >Exact Sig. (1-sided)</td></tr><tr><td align="center" valign="middle" >Pearson Chi-Square</td><td align="center" valign="middle" >1.196<sup>a</sup></td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.274</td><td align="center" valign="middle"  rowspan="3"  ></td><td align="center" valign="middle"  rowspan="3"  ></td></tr><tr><td align="center" valign="middle" >Continuity Correction<sup>b</sup></td><td align="center" valign="middle" >0.541</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.462</td></tr><tr><td align="center" valign="middle" >Likelihood Ratio</td><td align="center" valign="middle" >1.148</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.284</td></tr><tr><td align="center" valign="middle" >Fisher’s Exact Test</td><td align="center" valign="middle"  rowspan="2"  >1.179</td><td align="center" valign="middle"  rowspan="2"  >1</td><td align="center" valign="middle"  rowspan="2"  >0.278</td><td align="center" valign="middle"  rowspan="2"  >0.301</td><td align="center" valign="middle"  rowspan="2"  >0.228</td></tr><tr><td align="center" valign="middle" >Linear-by-Linear Association</td></tr><tr><td align="center" valign="middle" >N of Valid Cases</td><td align="center" valign="middle" >72</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><table-wrap id="table11" ><label><xref ref-type="table" rid="table1">Table 1</xref>1</label><caption><title> Mortality in patients with hematological malignancies</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="6"  >Chi-Square Tests</th></tr></thead><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" >Value</td><td align="center" valign="middle" >df</td><td align="center" valign="middle" >Asymp. Sig. (2-sided)</td><td align="center" valign="middle" >Exact Sig. (2-sided)</td><td align="center" valign="middle" >Exact Sig. (1-sided)</td></tr><tr><td align="center" valign="middle" >Pearson Chi-Square</td><td align="center" valign="middle" >0.003<sup>a</sup></td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.959</td><td align="center" valign="middle"  rowspan="3"  ></td><td align="center" valign="middle"  rowspan="3"  ></td></tr><tr><td align="center" valign="middle" >Continuity Correction<sup>b</sup></td><td align="center" valign="middle" >0.000</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >1.000</td></tr><tr><td align="center" valign="middle" >Likelihood Ratio</td><td align="center" valign="middle" >0.003</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.959</td></tr><tr><td align="center" valign="middle" >Fisher’s Exact Test</td><td align="center" valign="middle"  rowspan="2"  >0.003</td><td align="center" valign="middle"  rowspan="2"  >1</td><td align="center" valign="middle"  rowspan="2"  >0.960</td><td align="center" valign="middle"  rowspan="2"  >1.000</td><td align="center" valign="middle"  rowspan="2"  >0.673</td></tr><tr><td align="center" valign="middle" >Linear-by-Linear Association</td></tr><tr><td align="center" valign="middle" >N of Valid Cases</td><td align="center" valign="middle" >47</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></sec><sec id="s6"><title>6. Discussion</title><p>In our study we found that all inflammatory markers that include ferritin, C-RP, IL-6 and D-dimer were increased in all patients who were admitted to hospital; the same result was found in the study done in China [<xref ref-type="bibr" rid="scirp.111413-ref8">8</xref>].</p><p>The study revealed that there is significant relationship between elevated inflammatory marker IL-6 and the mortality rate, but in other studies, the higher mortality can be related to increased D-dimer level [<xref ref-type="bibr" rid="scirp.111413-ref9">9</xref>], while the results were consistent with another study which showed that increased IL-6 level was related to increased mortality rate [<xref ref-type="bibr" rid="scirp.111413-ref10">10</xref>].</p><p>In our study there is a relationship between increased risk of mortality and immune comprised, in particular a significant relationship cannot be identified if the patient has a hematological cancer, oncology (solid tumor) or end stage renal diseases. Up to our search there were a few studies that compared each group with risk of mortality in detail. A French study shows that the impact of COVID-19 and mortality in cancer patients depend on patients’ general characteristics like type of chemotherapy [<xref ref-type="bibr" rid="scirp.111413-ref11">11</xref>].</p></sec><sec id="s7"><title>Data Availability</title><p>The datasets used and/or analyzed during the current study are available from the first author on reasonable request.</p></sec><sec id="s8"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s9"><title>Cite this paper</title><p>Hajmohammasd, M., Zighari, R., Rjoup, H., Taha, T., Hania, S.A., Eqtait, F., Shawamreh, B., Hamamra, Y., Al-Amleh, H., Krajah, M., Ismael, N. and Sabateen, A. (2021) The Impact of Coronavirus Disease 2019 (COVID-19) among Immune Compromised Patients in Augusta Victoria Hospital AVH-2021. Advances in Infectious Diseases, 11, 269-277. https://doi.org/10.4236/aid.2021.113024</p></sec></body><back><ref-list><title>References</title><ref id="scirp.111413-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Ali, I. and Alharbi, O.M. (2020) COVID-19: Disease, Management, Treatment, and Social Impact. Science of the Total Environment, 728, 138861. https://doi.org/10.1016/j.scitotenv.2020.138861</mixed-citation></ref><ref id="scirp.111413-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Cucinotta, D. and Vanelli, M. (2020) WHO Declares COVID-19 a Pandemic. Acta bio-Medica: AteneiParmensis, 91, 157-160.</mixed-citation></ref><ref id="scirp.111413-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">Zhao, R., Li, M., Song, H., Chen, J., Ren, W., Feng, Y. and Guo, X. (2020) Early Detection of SARS-CoV-2 Antibodies in COVID-19 Patients as a Serologic Marker of Infection. 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