{"id":67527,"date":"2025-09-30T10:08:56","date_gmt":"2025-09-30T10:08:56","guid":{"rendered":"https:\/\/biomedpharmajournal.org\/?p=67527"},"modified":"2025-10-04T06:19:41","modified_gmt":"2025-10-04T06:19:41","slug":"high-sensitivity-troponin-i-c-reactive-protein-and-hypercholesterolemia-as-predictors-of-acute-cardiovascular-events-in-morocco","status":"publish","type":"post","link":"https:\/\/biomedpharmajournal.org\/staging\/vol18no3\/high-sensitivity-troponin-i-c-reactive-protein-and-hypercholesterolemia-as-predictors-of-acute-cardiovascular-events-in-morocco\/","title":{"rendered":"High-Sensitivity Troponin I, C – reactive Protein, and Hypercholesterolemia as Predictors of Acute Cardiovascular Events in Morocco"},"content":{"rendered":"

Introduction<\/strong><\/p>\n

Cardiovascular diseases (CVDs) are a leading global health threat, causing approximately 18 million annual deaths\u2014accounting for 32% of all mortality worldwide\u2014with 75% of these deaths occurring in low- and middle-income countries.1<\/sup> This burden is starkly evident in Morocco, where CVDs are the predominant cause of death, responsible for 34% of annual mortality.1<\/sup>Nearly most cardiovascular-related mortality, about three out of four, happen in low- and middle-income regions, highlighting the unequal burden these regions face. 1.2<\/sup><\/p>\n

Morocco exemplifies this trend, having experienced a 42% increase in CVD prevalence since 2005. Currently, these diseases are responsible for 34% of national mortality.1.3<\/sup>This growing health crisis is closely linked to rapid urbanization, aging demographics, and a surge in modifiable risk factors such as hypertension (25.3%), tobacco use (45\u201350%), and sedentary lifestyles (21.1%).4<\/sup><\/p>\n

From a pathophysiological perspective, elevated LDL-C \u00a0is involved in the disruption of endothelial integrity and the progression of atherogenesis.5 <\/sup>while systemic inflammation, often reflected by height\u00a0 levels of\u00a0 (hs-CRP), promotes plaque instability.6<\/sup> Additionally,\u00a0 troponin I (hs-cTnI) serves as a good\u00a0 marker of myocardial damage\u202fand is widely employed in detecting acute coronary syndromes.7<\/sup>Despite well-established roles for these biomarkers in cardiovascular risk assessment, data from North African populations, including Morocco, remain limited.8<\/sup><\/p>\n

The primary objective of this study was to assess the prognostic value of LDL cholesterol (LDL-C), high-sensitivity cardiac troponin I (hs-cTnI), and high-sensitivity C-reactive protein (hs-CRP) in Moroccan patients presenting with acute cardiovascular events. Specifically, the research aimed to establish population-specific cutoff values for these biomarkers, investigate potential sex-related variations in their levels, and contribute to the development of diagnostic strategies tailored to the Moroccan healthcare setting.<\/p>\n

Materials and Methods<\/strong><\/p>\n

Study Design and Participants<\/strong><\/p>\n

This prospective case\u2013control study included 351 consecutive patients admitted with acute cardiovascular events\u2014such as myocardial infarction, heart failure, or ischemic stroke\u2014at Ibn Rochd University Hospital, Casablanca, Morocco. A control group of 240 apparently healthy volunteers was recruited from the Pasteur Institute of Morocco. Controls were matched to cases by sex and age (\u00b15 years). All participants signed written informed consent prior to enrolment. The study was approved by the institutional ethics committee.<\/p>\n

Sample Size and Sampling Technique<\/strong><\/p>\n

A formal sample size calculation was not performed in advance. Instead, all eligible patients meeting the inclusion criteria during the study period were consecutively enrolled to maximize statistical power and ensure a representative sample. Control participants were selected through simple random sampling and matched to patients based on age and sex.<\/p>\n

Data and Sample Collection<\/strong><\/p>\n

Demographic and clinical information\u2014including age, sex, body mass index (BMI), blood pressure, smoking habits, physical activity, and medical history\u2014was collected using standardized questionnaires. After overnight fasting, venous blood samples were drawn into serum-separator tubes, centrifuged at 2,500 rpm for 15 minutes, and analyzed within two hours of collection.<\/p>\n

Laboratory Analyses<\/strong><\/p>\n

All assays were performed at the accredited laboratories of the Pasteur Institute of Morocco.<\/p>\n

Lipid profile: Total cholesterol, triglycerides, and HDL-C were quantified enzymatically using the VITROS\u00ae 5600 platform (Ortho Clinical Diagnostics). LDL-C was calculated using the Friedewald formula.<\/p>\n

High-sensitivity C-reactive protein (hs-CRP): Determined via particle-enhanced immunoturbidimetry on the BN ProSpec\u00ae analyzer (Siemens).<\/p>\n

High-sensitivity cardiac troponin I (hs-cTnI): Measured using a chemiluminescent immunoassay with a detection limit of 1.2 ng\/mL.<\/p>\n

Apolipoproteins (ApoA1 and ApoB) were measured in a subset of participants due to limited sample availability and logistical constraints. Missing measurements were not replaced or statistically imputed.<\/p>\n

Inclusion and Exclusion Criteria<\/strong><\/p>\n

Cases: Patients hospitalized with acute CVD, diagnosed according to the 2020 European Society of Cardiology STEMI\/NSTEMI guidelines. Patients with malignancy or autoimmune disease were excluded.<\/p>\n

Controls: Healthy individuals without a history of CVD, diabetes, or hypertension, and with normal lipid profiles (total cholesterol <2 g\/L; LDL-C <1 g\/L).<\/p>\n

General exclusion criteria: Pregnancy, incomplete clinical data, or refusal to provide informed consent.<\/p>\n

Statistical Analysis<\/strong><\/p>\n

Continuous variables were reported as mean \u00b1 standard deviation (SD), and categorical variables as frequencies or percentages. Data normality was tested using the Shapiro\u2013Wilk method; non-normally distributed variables (e.g., hs-cTnI) were log-transformed before analysis. Between-group comparisons used unpaired t-tests for continuous variables and Chi-square tests for categorical variables.<\/p>\n

Multivariate logistic regression was performed to identify independent predictors of acute CVD, including covariates with p < 0.05 in univariate analysis (age, sex, diabetes, smoking, physical activity, lipid parameters, hs-cTnI, and hs-CRP). Multicollinearity was assessed using variance inflation factors (VIF <5).<\/p>\n

Receiver operating characteristic (ROC) curves were used to determine optimal biomarker cutoffs, reporting the area under the curve (AUC), sensitivity, and specificity. Bonferroni correction was applied for multiple comparisons. All statistical analyses were conducted using SPSS v26 (IBM Corp.) and Python, with a significance threshold of p < 0.05.<\/p>\n

Results<\/strong><\/p>\n

Participant Characteristics<\/strong><\/p>\n

A total of 351 patients with acute cardiovascular disease (CVD) and 240 age- and sex-matched controls were included in the analysis. As summarized in Table 1, significant differences were observed in all baseline characteristics. Patients were, on average, older than controls and had a higher proportion of males. Moreover, patients presented with significantly higher systolic and diastolic blood pressure levels, as well as elevated fasting glucose levels compared to the control group (all *p*-values < 0.001).<\/p>\n

Table 1: Baseline demographic and clinical characteristics of study participants.<\/strong><\/p>\n\n\n\n\n\n\n\n\n
Characteristic<\/strong><\/td>\nPatients (n = 351)<\/strong><\/td>\nControls (n = 240)<\/strong><\/td>\n*p*-value<\/strong><\/td>\n<\/tr>\n
Age, years<\/strong><\/td>\n59.5 \u00b1 10.4<\/td>\n54.8 \u00b1 6.2<\/td>\n<0.001<\/td>\n<\/tr>\n
Sex, male<\/strong><\/td>\n212 (60.4%)<\/td>\n116 (48.3%)<\/td>\n0.003<\/td>\n<\/tr>\n
Systolic BP, mm Hg<\/strong><\/td>\n131.3 \u00b1 19.9<\/td>\n121.1 \u00b1 14.5<\/td>\n<0.001<\/td>\n<\/tr>\n
Diastolic BP, mm Hg<\/strong><\/td>\n75.5 \u00b1 6.8<\/td>\n72.4 \u00b1 6.8<\/td>\n<0.001<\/td>\n<\/tr>\n
Fasting glucose, g\/L<\/strong><\/td>\n1.50 \u00b1 0.11<\/td>\n0.90 \u00b1 0.14<\/td>\n<0.001<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Data are presented as mean \u00b1 standard deviation or n (%).<\/p>\n

BP, blood pressure.<\/p>\n

*p*-values were derived from independent samples t-test for continuous variables and Chi-square test for categorical variables (sex).<\/p>\n

Lipid Profile<\/strong><\/p>\n

As detailed in Table 2, the lipid profile of patients was markedly atherogenic compared to controls. Patients exhibited significantly higher levels of total cholesterol, LDL-C, and triglycerides, along with significantly lower levels of HDL-C (all *p* < 0.001). In a subgroup analysis, ApoA1 levels were also significantly reduced in patients (*p* < 0.001), while ApoB levels did not differ significantly between the groups (*p* = 0.078).<\/p>\n

Table 2: Comparison of lipid profiles between patients and controls.<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n
Parameter<\/strong><\/td>\nPatients (n = 351)<\/strong><\/td>\nControls (n = 240)<\/strong><\/td>\n*p*-value<\/strong><\/td>\n<\/tr>\n
Total cholesterol, g\/L<\/strong><\/td>\n1.86 \u00b1 0.43<\/td>\n1.56 \u00b1 0.42<\/td>\n<0.001<\/td>\n<\/tr>\n
LDL-C, g\/L<\/strong><\/td>\n1.48 \u00b1 0.45<\/td>\n1.14 \u00b1 0.24<\/td>\n<0.001<\/td>\n<\/tr>\n
HDL-C, g\/L<\/strong><\/td>\n0.40 \u00b1 0.14<\/td>\n0.49 \u00b1 0.10<\/td>\n<0.001<\/td>\n<\/tr>\n
Triglycerides, g\/L<\/strong><\/td>\n1.80 \u00b1 0.77<\/td>\n0.90 \u00b1 0.34<\/td>\n<0.001<\/td>\n<\/tr>\n
ApoA1, g\/L\u00a0a<\/sup><\/strong><\/td>\n1.20 \u00b1 0.30 (n=190)<\/td>\n1.45 \u00b1 0.19 (n=140)<\/td>\n<0.001<\/td>\n<\/tr>\n
ApoB, g\/L\u00a0a<\/sup><\/strong><\/td>\n0.95 \u00b1 0.22 (n=204)<\/td>\n0.90 \u00b1 0.10 (n=140)<\/td>\n0.078<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

a<\/sup><\/em> ApoA1 and ApoB analyses were performed in a subset of participants due to sample availability.<\/em>
\nData are presented as mean \u00b1 standard deviation. p-values were derived from independent samples t-test.
\n*LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; ApoA1, apolipoprotein A1; ApoB, apolipoprotein B.*<\/em><\/p>\n

ApoA1 and ApoB analyses were performed in a subset of participants (ApoA1: 190 patients, 140 controls; ApoB: 204 patients, 140 controls) due to sample availability.<\/p>\n

Clinical Risk Factors<\/strong><\/p>\n

As shown in Table 3, the prevalence of modifiable risk factors was significantly higher in patients than in controls. Smoking demonstrated the strongest association with acute CVD (OR = 14.55, 95% CI: 7.22\u201329.36, *p* < 0.001), followed by physical inactivity (OR = 2.88, 95% CI: 2.03\u20134.09, *p* < 0.001). A significant association was also observed for alcohol consumption; however, the odds ratio was extremely high and statistically unstable due to the absence of exposed individuals in the control group (OR = 53.95, 95% CI: 3.29\u2013882.90, *p* = 0.005), and this result should be interpreted with extreme caution.<\/p>\n

Table 3: Association between modifiable risk factors and acute cardiovascular disease.<\/strong><\/p>\n\n\n\n\n\n\n
Risk Factor<\/strong><\/td>\nPatients (n=351) n (%)<\/strong><\/td>\nControls (n=240) n (%)<\/strong><\/td>\nOdds Ratio (OR)<\/strong><\/td>\n95% CI<\/strong><\/td>\n*p*-value<\/strong><\/td>\n<\/tr>\n
Smoking<\/strong><\/td>\n127 (36.2)<\/td>\n9 (3.8)<\/td>\n14.55<\/td>\n7.22 \u2013 29.36<\/td>\n<0.001<\/td>\n<\/tr>\n
Physical inactivity<\/strong><\/td>\n266 (75.8)<\/td>\n125 (52.1)<\/td>\n2.88<\/td>\n2.03 \u2013 4.09<\/td>\n<0.001<\/td>\n<\/tr>\n
Alcohol consumption<\/strong>\u00a0\u207a<\/td>\n35 (10.0)<\/td>\n0 (0.0)<\/td>\n53.95<\/td>\n3.29 \u2013 882.90<\/td>\n0.005<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

a<\/sup> Haldane correction applied due to zero cell count in controls.<\/p>\n

Biomarker Distribution<\/strong><\/p>\n

The analysis revealed distinct sex-specific and age-specific patterns in biomarker levels.<\/p>\n

For high-sensitivity cardiac troponin I (hs-cTnI), the distribution was significantly influenced by sex. Women exhibited notably lower median values compared to men, although with considerable overlap in the interquartile ranges between the two groups (Figure 1).<\/p>\n

For high-sensitivity C-reactive protein (hs-CRP), a pronounced age and sex-specific pattern was observed. Analysis of age-stratified medians revealed that men experienced a relatively stable, gradual increase in hs-CRP levels with advancing age. In stark contrast, women demonstrated a sharp and significant peak in hs-CRP levels specifically within the 60-69 age group, a trend not observed in their male counterparts (Figure 2).<\/p>\n\n\n\n
\"\"<\/td>\nFigure 1:\u00a0 Sex-specific distribution of high-sensitivity cardiac troponin I (hs-cTnI) levels.<\/strong><\/p>\n

Click here to view Figure<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Box plot comparing serum hs-cTnI concentrations (in ng\/L) between men and women. The box represents the interquartile range (IQR), the horizontal line inside the box indicates the median, and the whiskers extend to the minimum and maximum values within 1.5 * IQR. Circles represent outliers.\u00a0<\/em><\/p>\n\n\n\n
\"\"<\/td>\nFigure 2: Age-stratified distribution of high-sensitivity C-reactive protein (hs-CRP) levels by sex.<\/strong><\/p>\n

Click here to view Figure<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Bar graph displaying median serum hs-CRP levels (in mg\/L) with error bars (representing interquartile range or standard deviation) across different age strata for men and women. The plot highlights the distinct peak in median hs-CRP levels among women in the 60-69 age group.<\/p>\n

The chart compares average levels of total cholesterol, LDL, HDL, and triglycerides in patients using bars (n=351) and controls (n=240). Error bars represent standard deviations, “This figure emphasizes a marked increase in CT, bad cholesterol LDL-C, and triglycerides, and a significant decrease in good cholesterol HDL-C among patients (all P < .001).”<\/p>\n

Lipid profiles, particularly HDL-mediated lipid transfers, are essential for evaluating cardiovascular risk, as they are closely linked to atherosclerosis, a primary cause of CVDs such as myocardial infarction and stroke.9<\/sup> Elevated LDL-C is a key atherogenic factor, with strong evidence from observational, genetic, and clinical studies supporting its role in CVD pathogenesis.10<\/sup><\/p>\n

Substantial LDL-C lowering achieved through PCSK9 inhibition has been consistently associated with reduced cardiovascular event rate; reinforcing the principle of minimizing LDL-C levels.11<\/sup>HDL-C is traditionally associated with reduced CVD risk; however, interventions to increase HDL-C have not consistently lowered event rates, suggesting that HDL functionality may be more critical than its absolute levels.12<\/sup>Elevated triglycerides, often seen in insulin resistance and type 2 diabetes, promote atherosclerosis via Triglyceride-enriched lipoproteins such as VLDL and chylomicrons.13<\/sup> Non-HDL cholesterol, which includes all atherogenic lipoproteins, is a useful marker, particularly in hypertriglyceridemic conditions.14<\/sup><\/p>\n

The lipoprotein subclass known as Lp(a) is considered a genetically influenced, independent risk factor for the development of cardiovascular disease ; with genetically determined plasma levels that are minimally affected by standard lipid-lowering therapies.15,16<\/sup> Guidelines recommend Lp(a) measurement for risk stratification, particularly in intermediate-risk or secondary prevention settings.17<\/sup>Lipid parameters are incorporated into risk assessment tools, such as the updated SCORE2 algorithm, to predict 10-year CVD risk and inform clinical management.18<\/sup> Novel biomarkers, including Lp(a) and non-HDL cholesterol-derived metrics, are under investigation to enhance residual risk prediction.19<\/sup><\/p>\n\n\n\n
\"\"<\/td>\nFigure 3: Receiver operating characteristic (ROC) curves for hs-cTnI and hs-CRP.<\/strong><\/p>\n

Click here to view Figure<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Modifiable risk factors, including smoking, physical inactivity, hypertension, and hyperglycemia, significantly contribute to CVD risk.20<\/sup> Meta-analyses confirm structured exercise reduces systolic BP by 5-8 mmHg in hypertensives ,21<\/sup> 22<\/sup> reinforcing physical activity’s role in Moroccan CVD prevention.23,24<\/sup> In Moroccan women, obesity and hypertension are major contributors to the growing CVD burden, exacerbated by an epidemiological transition.23,25<\/sup> “T2DM, the most prevalent type of diabetes, how is a critical driver of CVD, accounting for 30-40% of cardiovascular mortality in LMICs , through mechanisms like chronic hyperglycemia, insulin resistance, endothelial dysfunction, inflammation, and dyslipidemia.26,27<\/sup> Recent therapeutic advances, Therapies such as SGLT2 inhibitors and GLP-1 receptor agonists not only improve glycemic control but also confer cardioprotective effects in patients with type 2 diabetes.28,29<\/sup> Cardiac troponins (cTnI and cTnT) are specific markers of myocardial injury, released upon cardiac cell damage.30<\/sup><\/p>\n\n\n\n
\"\"<\/td>\nFigure 4: Sex-Specific Distribution of Troponin Levels<\/strong><\/p>\n

Click here to view Figure<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

This figure displays a box plot of hs-cTnI levels by sex, showing median values, interquartile ranges, and outliers. Women exhibit lower troponin levels than men, consistent with prior studies.31<\/sup> Age and sex influence troponin levels, with evidence suggesting age-specific cutoffs may enhance diagnostic accuracy of high-sensitivity assays.32<\/sup>Sex-specific cutoffs are proposed by some manufacturers, but their diagnostic benefit remains debated, and current European Society of Cardiology (ESC) guidelines do not endorse them.31,32<\/sup> Clinicians should consider confounders like age, sex, and renal function when interpreting hs-cTn results, which are reliable for ruling out myocardial infarction.33<\/sup>Hs-CRP, a marker of systemic inflammation, displays distinct patterns based on sex differences.<\/p>\n

hs-CRP levels across age groups (<50 vs \u226550 years) and sexes, illustrating median values and distribution shapes. Women show higher hs-CRP levels than men, possibly due to estrogen-mediated interleukin-6 (IL-6) production.34<\/sup><\/p>\n

hs-CRP distribution by age and sex, showing early increases in men, indicative of premature inflammatory activation, and a significant rise in women around age 50, likely linked to menopausal hormonal changes. These patterns suggest estrogen\u2019s protective anti-inflammatory role pre-menopause.35<\/sup> In older adults, Higher hs-CRP levels are predictive of an heightened likelihood of cardiovascular outcomes; and functional decline, requiring cautious interpretation.36<\/sup><\/p>\n

Multivariate Logistic Regression Analysis<\/strong><\/p>\n

In multivariate logistic regression analysis adjusted for age, sex, diabetes, and other lipid parameters, hs-cTnI, hs-CRP, and LDL-C were independently associated with acute CVD. Smoking and physical inactivity also remained significant predictors after adjustment for covariates (Table 4).<\/p>\n

Table 4: Multivariate logistic regression analysis of biomarkers and lifestyle factors<\/strong><\/p>\n\n\n\n\n\n\n\n\n
Parameter<\/strong><\/td>\nOR<\/strong><\/td>\n95% CI<\/strong><\/td>\np-value<\/strong><\/td>\n<\/tr>\n
Hs-cTnl<\/strong><\/td>\n1.06<\/td>\n1.03-1.09<\/td>\n<0.001<\/td>\n<\/tr>\n
Hs-CRP<\/strong><\/td>\n1.12<\/td>\n1.04-1.21<\/td>\n0.003<\/td>\n<\/tr>\n
LDL-C<\/strong><\/td>\n1.82<\/td>\n1.45-2.29<\/td>\n<0.001<\/td>\n<\/tr>\n
Smoking<\/strong><\/td>\n14.55<\/td>\n7.22 \u2013 29.36<\/td>\n<0.001<\/td>\n<\/tr>\n
Physical Inactivity<\/strong><\/td>\n2.88<\/td>\n2.03 \u2013 4.09<\/td>\n<0.001<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

CI, confidence interval; LDL-C, low-density lipoprotein cholesterol; hs-cTnI, high-sensitivity cardiac troponin I; hs-CRP, high-sensitivity C-reactive protein.\u00a0<\/em><\/p>\n

\u00a0Discussion<\/strong><\/p>\n

This case-control study provides novel insights into the predictive role of LDL-C, hs-cTnI, and hs-CRP for acute CVD in a Moroccan population. Our key findings are threefold:<\/p>\n

A pronounced atherogenic lipid profile characterized by elevated LDL-C and reduced HDL-C;<\/p>\n

A strong association of modifiable lifestyle risk factors, notably smoking;<\/p>\n

Clinically informative sex- and age-specific distributions for hs-cTnI and hs-CRP that could refine risk stratification.<\/p>\n

Comparative analyses of lipid profiles in diverse populations, including Morocco\u2019s evolving CVD landscape, reveal varying patterns of dyslipidemia associated with cardiovascular disease (CVD).37<\/sup> The observed dyslipidemic profile\u2014marked by significantly higher LDL-C and lower HDL-C in patients\u2014aligns with established evidence on lipid-related atherogenesis.5,10<\/sup> The magnitude of LDL-C elevation in our cohort is comparable to Tunisian data38<\/sup> and exceeds reports from Brazilian and Japanese cohorts,39,40<\/sup> underscoring a particularly pronounced dyslipidemic risk profile in North African populations that warrants targeted public health interventions.<\/p>\n

The strength of the associations revealed by multivariate analysis underscores the multifactorial nature of CVD pathogenesis in our cohort. The markedly elevated risk associated with smoking (OR: 14.55) aligns with its well-documented role in promoting endothelial dysfunction and systemic inflammation, which are key drivers of atherosclerotic plaque formation and instability.41,42<\/sup> Moreover, the independent predictive value of both LDL-C and hs-CRP reinforces the intricate link between dyslipidemia and inflammatory pathways in driving atherogenesis.5,6<\/sup> While the independent association of hs-cTnI with acute CVD events confirms its role as a crucial marker of subclinical myocardial injury, its moderate discriminative capacity (AUC = 0.70) suggests it should be interpreted in conjunction with other clinical findings rather than used in isolation.7,31<\/sup><\/p>\n

The sex and age-specific patterns we observed add a crucial layer to risk stratification. The lower hs-cTnI values in women are consistent with established biological variations,31<\/sup> while the sharp peak in hs-CRP levels among women aged 60-69 likely reflects the pro-inflammatory state associated with postmenopausal hormonal changes and the loss of estrogen’s cardioprotective effects.34,35<\/sup> This distinct inflammatory trajectory in women suggests a potential window for targeted anti-inflammatory interventions and underscores the necessity of sex-specific risk assessment algorithms.<\/p>\n

Our findings are consistent with regional studies investigating cardiac biomarkers. For instance, a Moroccan study defined a specific troponin cutoff for diagnosing myocardial infarction post-cardiac surgery, underscoring the importance of context-specific thresholds.44<\/sup> Furthermore, reinforcing the clinical value of our biomarker-focused approach, research from the same institution emphasized the critical need for the appropriate use of troponin testing in emergency departments to optimize patient care and resource utilization.45<\/sup><\/p>\n

Several limitations of our study warrant consideration. The case-control design precludes the establishment of causality. The single-center recruitment may limit the generalizability of our findings to the entire Moroccan population. Although apolipoproteins were analyzed, missing data in a subset of participants precluded a comprehensive analysis of all lipoprotein subfractions. Despite these limitations, our results provide a robust foundation for future prospective studies aimed at validating population-specific cutoff values and developing cost-effective, biomarker-guided risk stratification protocols for Morocco and similar resource-limited settings in North Africa.49,50,54<\/sup><\/p>\n

Conclusion<\/strong><\/p>\n

Cardiovascular diseases (CVDs) represent a major and growing contributor to mortality in Morocco, a trend propelled by urbanization, an aging population, and shifting lifestyles. 46<\/sup>This study identifies elevated LDL-C, hs-cTnI, and hs-CRP as significant and independent predictors of acute CVD events in the Moroccan population, underscoring the synergistic role of dyslipidemia, myocardial injury, and inflammation in the region’s risk profile.47,48<\/sup><\/p>\n

Beyond confirming a pronounced atherogenic dyslipidemia, our analysis revealed critical sex- and age-specific patterns for both hs-cTnI and hs-CRP, suggesting that men and women may experience divergent pathophysiological pathways to acute CVD.49,50<\/sup>The superior discriminative performance of hs-cTnI (AUC = 0.70) supports its potential utility for early risk stratification in acute clinical settings, while the distinct trajectory of hs-CRP, particularly its sharp increase in postmenopausal women, provides valuable insight for guiding long-term, sex-specific prevention strategies.51,52<\/sup><\/p>\n

These findings strongly advocate for the integration of these biomarkers, particularly hs-cTnI, into national CVD diagnostic and risk-stratification protocols, alongside conventional risk factor assessment.53<\/sup>We therefore recommend the development and validation of biomarker-guided clinical algorithms. Future large-scale, prospective studies are essential to establish population-specific cutoff values and to rigorously assess the cost-effectiveness of their implementation within resource-conscious healthcare systems like Morocco’s.49,50,54<\/sup><\/p>\n

Ultimately, adopting such a tailored, evidence-based approach is imperative to improve early detection, refine risk prediction, and effectively alleviate the escalating burden of CVD in Morocco and the broader North African region.55<\/sup>\u00a0<\/sup><\/p>\n

Acknowledgement <\/strong><\/p>\n

We would like to express our deepest gratitude to the following institutions and their dedicated staff for their invaluable support and contributions to this study:<\/p>\n

Laboratory of Health and Environment, Hassan II University, Faculty of Sciences, Casablanca, Morocco.<\/p>\n

Laboratory of Biochemistry, Pasteur Institute of Morocco, Casablanca, Morocco:<\/p>\n

Laboratory of Anthropogenetics, Biotechnology and Health, Choua\u00efb Doukkali University, El Jadida, Morocco.<\/p>\n

Department of Cardiology Service, Ibn Rochd University Hospital Center, Casablanca, Morocco.<\/p>\n

Funding Sources<\/strong><\/p>\n

The author(s) received no financial support for the research, authorship, and\/or publication of this article.<\/p>\n

Conflict of Interest<\/strong><\/p>\n

The author(s) do not have any conflict of interest.<\/p>\n

Data Availability Statement<\/strong><\/p>\n

This statement does not apply to this article.<\/p>\n

Ethics Statement<\/strong><\/p>\n

This research did not involve human participants, animal subjects, or any material that requires ethical approval.<\/p>\n

Informed Consent Statement-<\/strong><\/p>\n

This study did not involve human participants, and therefore, informed consent was not required.<\/p>\n

Clinical Trial Registration<\/strong><\/p>\n

This research does not involve any clinical trials.\u00a0<\/strong><\/p>\n

Permission to reproduce material from other sources<\/strong><\/p>\n

Not Applicable<\/p>\n

Author Contributions\u00a0<\/strong><\/p>\n