The primary endpoint was the presence of dyslipidemia with an indication for lipid-lowering therapy based on LDL-C according to the 2021 European Society of Cardiology (ESC) guidelines, which set LDL-cholesterol targets according to cardiovascular risk level. Any patient whose lipid profile did not allow the LDL-cholesterol value to be obtained was excluded from the study.

Data were collected using a data collection form based on information available in patient medical records and consultation registers. The variables studied were sociodemographic (age, sex, place of residence, socio-professional activity, and level of education), lifestyle-related, history, comorbidities (alcohol, tobacco, sedentary lifestyle, hypertension, HIV, stroke, cardiovascular risk), anthropometric (weight, height, BMI), paraclinical (glycated hemoglobin, total cholesterol, HDL cholesterol, LDL cholesterol, and triglycerides), and therapeutic (therapeutic attitudes of treating physicians, type of lipid-lowering medication).

Regarding TI, for each patient included, cardiovascular risk was assessed in primary prevention according to the WHO HEARTS technical guide in order to define the LDL-C target. Patients in secondary prevention were considered from the outset to be at very high cardiovascular risk. Then, for each patient and for each consultation with a lipid profile available, we checked whether initiation or optimization of lipid-lowering treatment was necessary in accordance with the 2021 ESC recommendations based on the level of cardiovascular risk. This step made it possible to determine the presence or absence of TI, its modality, and to calculate the inertia score for each physician and the overall therapeutic inertia score.

The data were analyzed using STATA software. Proportions and means were compared using the Chi-square test or Fisher's exact test for qualitative data, and Student's t-test for quantitative data, with a significance level of p < 5%.

The study protocol was approved by the Director General of CHU-YO. Data collection and analysis were carried out in strict compliance with confidentiality requirements, using anonymous and coded questionnaires.

A total of 220 files of patients with type 2 diabetes (T2D) were included and analyzed. The average age of the patients was 60.6 ± 7.9 years. The study population was predominantly female (69.5%; sex ratio of 0.43), civil servants (40.9%), and married (84.1%). Nearly a quarter had a higher education level.

The sociodemographic characteristics of the population are summarized in Table 1.

Table 1. Sociodemographic characteristics of the study population.

The average duration of diabetes was 10.9 ± 6.7 years with regular follow-up in 91.8% of patients. Cardiovascular risk was high in 55% of our patients. The clinical characteristics of the study population are summarized in Table 2.

Table 2.Clinical characteristics of the study population.

Our patients had well-controlled diabetes (HbA1c ≤ 7%) in 59.54% of cases, but the LDL-C target was only achieved in 13.18% of patients. The mean LDL-C and glycated hemoglobin values according to the cardiovascular risk level of our patients for consultations involving lipid testing are summarized in Table 3.

Table 3. Mean LDL-C and glycated hemoglobin levels according to patients’ cardiovascular risk level.

LDL-C: Low-Density Lipoprotein Cholesterol. HbA1c: Hemoglobin A1c.

Therapeutic characteristics

Patient follow-up was carried out by a team of seven internists and one endocrinologist. Rosuvastatin was the statin used in more than half (71%) of cases. The majority of our patients (85%) were treated with oral antidiabetic drugs (Table 4).

Table 4. Distribution of patients according to therapeutic characteristics.

Among the 220 patients in the study, individual and non-cumulative analysis of TI during each consultation revealed that 187 patients (85%) experienced therapeutic inertia at least once. Similarly, the main non-cumulative forms of TI observed in the 187 patients affected by TI were non-initiation in 130 patients (69.52%) and non-intensification of therapy in 57 patients (30.48%).

However, out of a total of 313 cumulative consultations, therapeutic intervention was indicated in 296 consultations but was not carried out in 226 cases, corresponding to an overall therapeutic inertia score of 72.2%.

The characteristics of therapeutic inertia according to consultations are detailed in Table 5(a)-(c).

Table 5.(a) Proportion of patients who experienced therapeutic inertia during different consultations. (b) Therapeutic inertia score during different consultations. (c) Distribution of therapeutic inertia modalities during different consultations.

3.5.1. Bivariate Analysis

In bivariate analysis, the variables with a p-value less than 0.2 were: marital status (p = 0.013), educational level (p = 0.165), duration of disease (p = 0.154), and presence of diabetes complications (p = 0.121) (Table 6).

Table 6. Association between different variables and therapeutic inertia.

(Additional clinical, biological, and therapeutic data tables continue with similar formatting).

3.5.2. Multivariate Analysis

In multivariate analysis, a statistically significant association was found between treatment inertia and two factors: marital status, with a higher risk among married individuals (OR = 2.83; p = 0.038), and higher education (OR adjusted = 0.22; p = 0.047).

Thus, married individuals were more than twice as likely to experience therapeutic inertia, while patients with a higher level of education were 78% less likely to do so (Table 7).

Table 7. Factors associated with therapeutic inertia in multivariate analysis in diabetic and dyslipidemic patients.

The average age was 60.57 years. These results were similar to those of Sow in Senegal [10]. However, our results differed from those of Garcia-Ulloa et al. in Mexico, who found an average age of 54 years [11]. This difference could be explained by a longer duration of diabetes in our series. The predominance of women (69.55%) is also reported in several reports from Burkina Faso [12][13].

The educational level of our population reveals that 75% had not attained a higher education level. Our results are consistent with data from the 2021 STEPS survey, which found that 81.9% of respondents had not attained a higher education level [12].

The average duration of diabetes was 10.86 years. The main comorbidities were overweight (68.64%), hypertension (68.64%), and a sedentary lifestyle (53.18%). This finding is also reported in our context by Guira et al. in Burkina Faso [14] and Adoubi in Sub-Saharan Africa [15], confirming the strong association between diabetes and excess weight. It therefore appears necessary to strengthen prevention strategies focused on nutrition and regular physical activity in the management of type 2 diabetes [16][17].

In our study, nearly two-thirds of patients had at least one high cardiovascular risk factor (65.91%), confirming the important role of dyslipidemia (along with hypertension and obesity) as a major risk factor for atherosclerotic cardiovascular disease in diabetics [18].

The mean LDL cholesterol was 3.63 ± 0.74 mmol/L, which is higher than the values reported in several series: 3.12 ± 0.61 mmol/L in Man et al. (China) [19], and 2.20 mmol/L in Knudsen et al. (Denmark) [20].

The average glycated hemoglobin was 7.33% ± 0.76%. Similar values were reported by Thiam-Tall in Senegal (7.65% ± 3.2%) [10] and by Man et al. in China (7.0% ± 1.2%) [19]. Conversely, other studies show different levels: Herraiz et al. in Spain reported a higher value (8.0% ± 1.5%) [21], while Van Nguyen et al. in Vietnam observed a lower average (6.6%) [22]. In view of the current targets (LDL < 2.6 mmol/L for diabetics with moderate cardiovascular risk), this high average highlights the need to strengthen the management of dyslipidemia in order to improve the achievement of therapeutic goals, which is also crucial [23] because even when blood glucose control is good, cardiovascular risk remains high due to the impact of dyslipidemia, inflammation, and endothelial dysfunction [24].

The frequency of therapeutic inertia in our series was 85%. Herraiz et al. in Spain [21] reported a similar frequency of 80.7%. Sebai et al. in Tunisia [5], Garcia Diaz et al. in Spain [11], and Chew et al. in Malaysia [25] reported frequencies of 42.7%, 43.6%, and 61%, respectively. In general, these frequencies indicate that therapeutic inertia in the treatment of dyslipidemia in diabetics is a major problem both globally and in Africa, thus hindering the achievement of the recommended targets for reducing cardiovascular risk [26].

In our study, 69.72% of patients did not initiate lipid-lowering treatment. Our results are comparable to those reported by Thiam-Tall in Senegal (78.4%) [10]. Non-intensification affected 30.28% of patients. This practice was also reported by Van Nguyen et al. in Vietnam (89.9%) [22]. The inertia observed in our study is consistent with data from the African literature, which describes frequent delays in initiating and intensifying treatment, sometimes lasting several years [27]. These situations can be explained by constraints on access to treatment [28]. In Western countries, inertia manifests itself mainly in delays in initiation or intensification despite eligibility, with approximately 20% - 30% of diabetic patients not reaching the target even in specialized centers [29].

Analysis of Table 3 shows that therapeutic inertia increases with the level of cardiovascular risk. Patients at moderate risk have a favorable prognosis and benefit from overall effective care that is consistent with the objectives. Those at high risk show both lipid and glycemic stagnation linked to a lack of therapeutic adaptation. Finally, patients at very high risk also have poor metabolic health, making them a group that requires immediate therapeutic intensification.

These findings reflect inadequate management of dyslipidemia, despite established recommendations for cardiovascular prevention, and show that TI is a major issue in the optimal management of dyslipidemia in patients with type 2 diabetes. It is therefore necessary to intensify and adapt treatment to reduce cardiovascular morbidity and mortality. But it is also necessary to improve access to treatment, particularly in African contexts [23].

In our study, marital status and level of education are associated with TI. Married patients are more than twice as likely (200%) to experience therapeutic inertia. This association could potentially be explained by financial and socioeconomic burdens on their families, though other factors may also be involved and this relationship merits further investigation. As for high educational level, it contributes to a 78% reduction in TI. Patient-related factors (level of understanding, compliance, financial capacity) and prescriber-related factors (perception of the patient) certainly influence the initiation or intensification of treatment in this group. The relationships between TI and glycemic control, LDL cholesterol threshold, and the presence of diabetes complications, reported in studies by Herraiz et al. (TI less frequent in cases of higher LDL-C levels and lower HbA1c) [21], and Garcia Diaz et al. [11], were not observed in our study.

Our study had two main limitations:

The lack of lipid profiles in nearly a quarter of diabetic patients who consulted in 2024 restricted our sample size and may therefore have led to selection bias.Underreporting in the records of the reasons for not changing treatment made it impossible to determine whether therapeutic inertia was justified or not. Examples of justifiable reasons for not modifying therapy include patient refusal to initiate or intensify treatment, documented side effects or intolerance to statins, prohibitive costs for the patient, or recent treatment adjustments requiring time for assessment. All of these factors may have overestimated the frequency of therapeutic inertia in the study.

Despite these limitations and biases, we obtained results that were compared with data from the literature.