Biological profile and risk factors of mortality in COVID-19 patients at Adlucem hospital in Banka-Bafang, Cameroon: a cross-sectional study
- Open Access
- 01.12.2025
- Research
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Abstract
Introduction
The SARS-CoV-2 virus, responsible for COVID-19, continues to circulate throughout the world. The World Health Organisation (WHO) estimates that more than 776 million cases have been recorded and that almost 7.1 million people have died; more than 4,000 deaths have been reported in the last 28 days, despite the existence of a vaccine and measures to control the spread [1]. COVID-19 presents clinically with a wide spectrum of symptoms, ranging from no symptom, isolated pneumopathy to multi-system involvement with potentially fatal complications, thus sometimes misleading characteristics [2]. The acute inflammatory effects of COVID-19 range from mild to severe clinical, biological and radiological manifestations reaching multiple organ systems besides the lungs. Although the case was reported in Egypt in February 2020, the first two waves progressed rather slowly in Africa than other continents [3]. Within three months with spread across most African, mostly imported from Europe and America and not from China where the virus originated [4]. Data on associated complications are important to inform management strategies but remain scarce in Africa due to limited reporting. In Cameroon, the first cases of the COVID-19 were reported on March 06, 2020. By March 30, 2020, three weeks later, (the country had recorded 142 confirmed cases of COVID-19 and 2 related deaths [5]. This exponential growth in reported infections prompted the Cameroon government, through its Ministry of Public Health, to set out a series of public health measures to limit the spread of the virus in accordance with WHO recommendations [6]. These measures included regular handwashing, social distancing, and banning gatherings of more than fifty people nationwide, and instituted screening at points of entry into Cameroon active case finding and isolation of suspected cases.
A lower number of confirmed cases and associated deaths were reported in African countries, compared to European countries [7]. The differences in observed mortality across Africa compared to other continents (Asia, the Americas and Europe) are potentially associated with the younger population structure in Africa, the lower epidemiology of comorbidities known to increase risk of COVID-19 severity and symptoms presentation does not exclude limited capacity for diagnosis [8]. To date, several studies have reported an overview of the evolution of the disease in Cameroon, vulnerability to the severity of COVID-19 and access to healthcare, and its potential socio-economic consequences [9‐13]. However, no study has presented the specific biological profile of COVID-19 in Cameroonian patients. Knowledge of the biological factors associated with the development of severe disease will inform accurate patient stratification and resource allocations for management of COVID-19 cases in Cameroon. The aim of this study was therefore to describe the biological profiles of COVID19 patients diagnosed at the Adlucem hospital in Banka-Bafang, West Region in Cameroon and identify risk factors for death in patients to optimize management and improve public health.
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Materials and methods
Study design and framework
This study was a part of a research project entitled “COVID-19 and cardio metabolic syndrome in Cameroon which started in December 2021 and ended in March 2023. The project used cross-sectional (at the admission for biological parameters) and prospective (follow-up of 15 months for survivors). Data presented in this publication are biological parameters of each patient at the admission and some parameters of the hospitalization. This study was conducted at the Adlucem hospital in Banka-Bafang, Haut-Nkam Division, West Cameroon region, located between latitude 5° 9’ 5” north and longitude 10° 10’ 60” east. This hospital was one of the Special Care Centers for the diagnosis of COVID-19 and management of COVID patients approved by the health authorities and was under the technical and clinical supervision of the Bafoussam Regional hospital, West Region of Cameroun. It is also one of the most frequently visited hospitals in the Bafang health district (60% of the consultations), will focus on patients managed for severe COVID-19 in a dedicated departmental management Centre set up during the pandemic.
Study population and inclusion of participants
The study population included all individuals, irrespective of age or sex, who received a consultation at Adlucem hospital in Banka-Bafang for signs or symptoms suggestive of SARS-CoV-2 infection during the study period. Two nasopharyngeal samples were taken from each patient using swabs. One swab was used for rapid diagnosis using the Accu-Tell ® COVID-19 antigen cassette, which is a rapid chromatographic immunoassay for the qualitative detection of SARS-CoV-2 antigen. The second swabs was used to confirm the diagnosis at the regional hospital of Bafoussam by RT-PCR (reverse transcription polymerase chain reaction) using the AmpliQuick® SARS-CoV-2 PCR Kit, which enables detection of 2 SARS-CoV-2 viral genes (the RdRp gene and the E gene) and a human control gene (the RNaseP gene). The lowest cycle threshold (Ct) value was determined for each gene after RT-PCR analysis and was used for statistical analysis. The RT-PCR result was positive when a specific SARS-CoV-2 gene was amplified with less than 33 cycles. The RT-PCR result was negative in the absence of SARS-CoV-2 gene amplification.
A convenient sampling approach was used whereby all patients with a confirmed laboratory positive test for SARS-Cov-2 infection diagnosed by a qualitative reverse transcriptase polymerase chain reaction (RT-PCR) test performed on nasopharyngeal swab samples was included in the study. After sampling, 300 participants were selected for the study. Subjects confirmed positive for SARS-Cov-2 infection and attending Bafang district hospital with missing clinical records and relevant laboratory tests were excluded from the study as illustrated in the Fig. 1 below.
Fig. 1
Flow chart of sample selection
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Data collection and study variables
Medical records were reviewed to collect demographic and clinical characteristics (age, sex, history of chronic illness and lifestyle, clinical signs on admission). Biological data including haemogram, biochemical markers (C-reactive protein (CRP), blood glucose and ionograms in particular) of COVID-19 patients managed at the Adlucem hospital, Banka-Bafang.
Collection of biological data and applied definitions
Biological parameters of interest included hemoglobin, red blood cells, white blood cells, platelets, CRP, total cholesterol, triglycerides, HDL-cholesterol (HDL-c), LDL-cholesterol (LDL-c), glucose, glycated hemoglobin, aspartate amino transferase (ASAT), alanine amino transferase (ALAT), urea, creatinine, sodium, potassium and chlorine. Fasting blood glucose was assessed by the Glucose Oxidase-Peroxidase (GOP-POD) method. Total cholesterol, plasma triglycerides, HDL-c, LDL-c, AST, ALT, urea, serum creatinine were assessed enzymatically and colorimetrically using ChronoLab kits (Traverssia Prat de la Riba 34 B 08849 Sant Climent de Llobregat Barcelona, Spain). The full blood count was performed using a Sysmex poch-100i (USA) automatic analyzer and red blood cell count (RBC), white blood cell count (WBC), platelets (PLQ) counts and total hemoglobin (Hb) were determined.
Diagnostic criteria were defined as follows: anemia was defined as a hemoglobin level below 12 g/dL [14], hyperleukocytosis as a leukocyte count above 11 × 103 /mm, polycythemia as a red blood cell count above 4.5 × 103 /mm³ and thrombocytosis as a platelet count above 450 × 103 /mm³ [15]. A C-reactive protein (CRP) level above 12 mg/L was considered high [16]. Potassium levels below 3.3 mmol/L and above 5.1 mmol/L defined hypokalemia and hyperkalemia respectively [17]. Similarly, sodium levels below 135 mmol/L and above 145 mmol/L corresponded to hyponatremia and hypernatremia respectively [18]. Chlorides below 95 mmol/L and above 105 mmol/L corresponded to hypochloremia and hyperchloremia respectively [19]. Finally, hepatic function was assessed by ALAT levels above 50 IU/L and ASAT above 40 IU/L [20]. Elevated blood uremia was considered for urea levels above 0.43 g/L [21] and hypercreatinemia was diagnosed by blood creatinine levels above 14 mg/L and 11 mg/dL for men and women respectively [22].
Statistical analysis
Statistical analyses were performed using SPSS version 25.0 for Windows (SPSS, Inc., IBM Corporation, Chicago, USA). Quantitative data were expressed as mean ± standard error, while qualitative data were expressed as frequencies (%). The Student’s t test was used to compare means, while the chi-square test or Fisher’s exact test was used to compare proportions. Logistic regression was used to identify risk factors associated with the death. The effect of potential confounding factors was adjusted for in the logistic regression model in multivariate analysis. Statistical significance was retained for a p-value < 0.05.
Results
Sociodemographic and clinical characteristics of COVID-19 patients
During the study period, 259 patients were confirmed positive for Covid-19 with more men [62.2% (161/259)] than women [37.8% (98/259)]. The hospitalization rate for men (64.4%) was higher than for those who succumbed to the disease (55.9%). Among women, the number of deaths was higher than the number of living (hospitalized) patients (44.1% vs. 35.6%). More than half of patients aged 70 years and over died compared 28.8% still hospitalized for COVID (p = 0.002) as of the time of data collection. Vomiting, abdominal pain, dyspnea, fever were the most significantly reported symptoms among the COVID patients who demised compared to all hospitalized patients (p < 0.05) (Table 1).
Table 1
Clinical symptoms characteristics of COVID-19 patients
Variables | Death | ||
|---|---|---|---|
No | Yes | p value | |
Sex | |||
Women | 35.6 (68) | 44.1 (30) | 0.214 |
Men | 64.4 (123) | 55.9 (38) | |
Age (years) | |||
18–29 years | 13.1 (25) | 7.4 (5) | 0.002 |
30–49 years | 19.9 (38) | 20.6 (14) | |
50–69 years | 38.2 (73) | 19.1 (13) | |
≥ 70 years | 28.8 (55) | 52.9 (36) | |
Vomiting | |||
Yes | 3.7 (7) | 14.7 (10) | 0.002 |
No | 96.3 (184) | 85.3 (58) | |
Abdominal pain | |||
Yes | 2.1 (4) | 19.1 (13) | < 0.0001 |
No | 97.9 (187) | 80.9 (55) | |
Cough | |||
Yes | 85.9 (164) | 77.9 (53) | 0.128 |
No | 14.1 (27) | 22.1 (15) | |
Fever | |||
Yes | 74.3 (142) | 39.7 (27) | < 0.0001 |
No | 25.7 (49) | 60.3 (41) | |
Headache | |||
Yes | 32.1 (61) | 25.4 (17) | 0.303 |
No | 67.9 (129) | 74.6 (50) | |
Dyspnea | |||
Yes | 48.9 (93) | 64.2 (43) | 0.032 |
No | 51.1 (97) | 35.8 (24) | |
Asthenia | |||
Yes | 60.2 (115) | 57.4 (39) | 0.680 |
No | 39.8 (76) | 42.6 (29) | |
Anorexia | |||
Yes | 22.5 (43) | 20.6 (14) | 0.742 |
No | 77.5 (148) | 79.4 (54) | |
Nasal discharge | |||
Yes | 2.6 (5) | 4.4 (3) | 0.463 |
No | 97.4 (186) | 95.6 (65) | |
Diarrhea | |||
Yes | 8.4 (16) | 8.8 (6) | 0.910 |
No | 91.6 (175) | 91.2 (62) | |
Anthropometric, hematological and ionic characteristics of COVID-19 patients
The results of anthropometric, hematological and ionic characteristics of COVID-19 patients are reported in Table 2 below. Mean weight (76.10 ± 9.66 kg vs. 73.28 ± 10.19 kg, p = 0.049) and body mass index (26.40 ± 2.93 kg/m2 vs. 25.22 ± 3.55 kg/m2, P = 0.014) were significantly higher in deceased patients than in those still hospitalized. The mean serum creatinine concentrations were significantly higher in deceased patients than in patients still in hospitalized at the time of the study (16.77 ± 1.14 g/L vs. 12.88 ± 0.41 g/L) (p < 0.05). Analysis of electrolyte homeostasis found the mean serum potassium concentrations to be significantly lower for patients who died compared to those who survived still in hospitalize (3.55 ± 0.11 mmol/L vs. 3.85 ± 0.06 mmol/L) (p < 0.05). The mean white blood cell count was also significantly higher in deceased patients compared to the survived (12.32 ± 1.19 g/L vs. 10.01 ± 0.45 g/L) (p < 0.05).
Table 2
Anthropometric, hematological and ionic characteristics of COVID-19 patients
Variables | Death | ||
|---|---|---|---|
No | Yes | p value | |
Clinical characteristics | |||
SBP (mmHg) | 135.03 ± 28.86 | 140.86 ± 29.85 | 0.095 |
DBP (mmHg) | 74.73 ± 11.41 | 76.73 ± 14.78 | 0.254 |
Anthropometric characteristics | |||
Weight (Kg) | 73.28 ± 10.19 | 76.10 ± 9.66 | 0.049 |
BMI (Kg/m2) | 25.22 ± 3.55 | 26.40 ± 2.93 | 0.014 |
Blood count | |||
White blood cells (g/L) | 10.01 ± 0.45 | 12.32 ± 1.19 | 0.027 |
Red blood cells (g/L) | 4.14 ± 0.21 | 4.13 ± 0.15 | 0.073 |
platelets (g/L) | 228.91 ± 6.19 | 254.10 ± 17.21 | 0.085 |
Hemoglobin (g/dL) | 11.42 ± 0.13 | 11.59 ± 0.16 | 0.465 |
Biochemicals characteristics | |||
CRP (mg/L) | 57.93 ± 3.15 | 58.58 ± 6.04 | 0.919 |
Total Cholesterol (g/L) | 1.88 ± 0.05 | 1.92 ± 0.07 | 0.672 |
Triglycerides (g/L) | 1.22 ± 0.05 | 1.26 ± 0.09 | 0.738 |
HDL-cholesterol (g/L) | 0.45 ± 0.01 | 0.50 ± 0.03 | 0.154 |
LDL-cholesterol (g/L) | 1.25 ± 0.04 | 1.20 ± 0.04 | 0.418 |
H1ABc | 6.99 ± 0.16 | 7.47 ± 0.18 | 0.065 |
Glucose (g/L) | 1.42 ± 0.07 | 1.57 ± 1.19 | 0.379 |
AST (UI/L) | 48.27 ± 5.40 | 61.76 ± 22.71 | 0.386 |
ALT (UI/L) | 46.28 ± 3.42 | 47.00 ± 6.04 | 0.926 |
Urea (g/L) | 0.38 ± 0.02 | 0.44 ± 0.03 | 0.220 |
Creatinine (g/L) | 12.88 ± 0.41 | 16.77 ± 1.14 | 0.004 |
Ionics characteristics | |||
Potassium (mmol/L) | 3.85 ± 0.06 | 3.55 ± 0.11 | 0.010 |
Sodium (mmol/L) | 136.71 ± 1.48 | 131.44 ± 3.25 | 0.092 |
Chlorine (mmol/L) | 91.16 ± 2.45 | 85.19 ± 2.01 | 0.121 |
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Main biological abnormalities observed in COVID-19 patients
An analysis of biological abnormalities in patients with covid-19 is presented in Table 3 below. This study found more overweight in the group that survived still admitted in hospital than those who died (41.1% vs. 27.9%; p = 0.05), but more obese people in the group that demised. There was Electrolyte imbalance with in the patients who demised having higher hypochloremia (86.2% vs. 70.0%) than the survived group, followed by hyponatremia (35.4% vs. 19.3%) and hypokalemia (26.2% vs. 12.9%), than in hospitalized patients (p < 0.05). Over 57.4% of the demised patients had leukocytosis, compared with 39.8% of those who survived hospitalized (p < 0.05). In addition, thrombocytosis was observed in 8.8% of patients who died compared to only 2.1% of survivor’s still hospitalized (p < 0.05).
Table 3
Main biological abnormalities observed in COVID-19 patients
Abnormality | Death | |||
|---|---|---|---|---|
No | Yes | p value | ||
% (n) | % (n) | |||
Anthropometric abnormality | ||||
Overweight | 41.1 (79) | 27.9 (19) | 0.05 | |
Obesity | 6.8 (13) | 8.8 (6) | 0.146 | |
Biochemical abnormality | ||||
Total hypercholesterolemia | 77.0 (67) | 70.0 (35) | 0.365 | |
Hypertriglyceridemia | 36.8 (32) | 34.0 (17) | 0.744 | |
Hypocholesterolemia HDL | 36.8 (32) | 30.0 (15) | 0.421 | |
Hypercholesterolemia LDL | 26.4 (23) | 28.0 (14) | 0.843 | |
High CRP | 91.6 (175) | 88.2 (60) | 0.408 | |
Hyper creatinemia | 28.9 (55) | 26.5 (18) | 0.697 | |
High urea | 22.1 (42) | 30.9 (21) | 0.148 | |
Hypokalemia | 12.9 (18) | 26.2 (17) | 0.019 | |
Hyponatremia | 19.3 (27) | 35.4 (23) | 0.044 | |
hypochloremia | 70.0 (98) | 86.2 (56) | 0.042 | |
Blood count | ||||
High white blood cells | 39.8 (76) | 57.4 (39) | 0.028 | |
High red blood cells | 4.2 (8) | 2.9 (2) | 0.076 | |
High platelets | 2.1 (4) | 8.8 (6) | 0.013 | |
Low hemoglobin | 62.3 (119) | 52.9 (36) | 0.175 | |
Biological predictors of death in COVID-19 patients in the study population
Bivariate analyses identified several risk factors associated with death in COVID patients. Leukocytosis (OR = 2.035; 95%CI: 1.161–3.567; p = 0.013), thrombocytosis (OR = 4.286; 95%CI: 1.152–15.950; p = 0.030), hypokalemia (OR = 2.400; 95%CI: 1.143–5.042; p = 0.021), hyponatremia (OR = 2.292; 95%CI: 1.185–4.431; p = 0.014) and hypochloremia (OR = 2.644; 95%CI: 1.188–5.882; p = 0.017) were determined to be independent predictors of death in COVID-19. Furthermore, after adjustment for sex and age, overweight (AOR = 1.877; 95%CI: 1.017–3.477; p = 0.044) also emerged as a significant risk factor for dying of COVID-19 (Table 4).
Table 4
Biological predictors of death in COVID-19 patients in the study population
Variables | OR (95% CI) | p value | AOR (95% CI) | p value |
|---|---|---|---|---|
Overweight | 1.819 (0.995–3.324) | 0.052 | 1.877 (1.017–3.477) | 0.044 |
Total hypercholesterolemia | 0.697 (0.318–1.526) | 0.366 | 0.669 (0.300-1.489) | 0.324 |
Hypertriglyceridemia | 0.885 (0.427–1.837) | 0.744 | 0.879 (0.416–1.857) | 0.735 |
Hypocholesterolemia HDL | 0.737 (0.350–1.552) | 0.422 | 0.770 (0.360–1.648) | 0.501 |
Hypercholesterolemia LDL | 1.082 (0.496–2.360) | 0843 | 1.167 (0.526–2.590) | 0.705 |
High CRP | 0.686 (0.279–1.683) | 0.410 | 0.678 (0.271–1.695) | 0.405 |
Hyper creatinemia | 0.884 (0.474–1.648) | 0.697 | 0.800 (0.421–1.522) | 0.497 |
High urea | 1.574 (0.849–2.921) | 0.150 | 1.390 (0.734–2.632) | 0.313 |
High white blood cells | 2.035 (1.161–3.567) | 0.013 | 1.940 (1.093–3.442) | 0.023 |
High red blood cells | 0.686 (0.142–3.312) | 0.639 | 0.762 (0.152–3.823) | 0.741 |
High platelets | 4.524 (1.236–16.557 | 0.023 | 4.286 (1.152–15.950) | 0.030 |
Hypokalemia | 2.400 (1.143–5.042) | 0.021 | 2.600 (1.213–5.576) | 0.014 |
Hyponatremia | 2.292 (1.185–4.431) | 0.014 | 2.144 (1.092–4.207) | 0.027 |
Hypochloremia | 2.667 (1.209–5.883) | 0.015 | 2.644 (1.188–5.882) | 0.017 |
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Discussion
This study aimed to describe the biological profile of COVID-19 patients in hospital that was central to the diagnosis and management of COVID-19 at a health district in Bafang in the West region of Cameroon and to identify risk factors for dying of COVID-19. COVID-19 severity and mortality was higher in older patients than those who survived (72% vs. 67%), with the over 70 years old patients (52.1%) seeing a significantly higher mortality than any other age group. These results are similar to those of other African studies, notably in Kinshasa in the Democratic Republic of Congo, highlighting the impact of advanced age on COVID-19-related mortality [23] and an association of higher age with disease severity [2] explained by the aging immune system, which renders the elderly more vulnerable to severe complications of the disease. Indeed, Nlandu et al. [24] and Pan et al. [25] also suggested that immunosenescence is characterized by reduced production of native T and B cells and dysfunction of innate immune cells, which could explain the greater vulnerability of the elderly to COVID-19. This altered immune response particularly favors viral persistence and a deregulated inflammatory response, leading to a cytokine storm.
The symptoms most observed in patients who demised were vomiting, abdominal pain, dyspnea and fever. However, the frequency of these signs were low compared with those observed by Mandina et al. [26] in Kinshasa, Democratic Republic of Congo, and Chen et al. [27] in China. Whether this is associated with the consumption of traditional medicinal products informally reported in the Cameroonian population is not known.
Analysis of the biological abnormalities observed in deceased COVID-19 patients and those still in hospital showed that electrolyte disorders (hypokalemia (26.2), hyponatremia (35.4%) and hypochloremia (86.2%)); leukocytosis (57.4%) and thrombocytosis (8.8%) were significantly more prevalent in deceased patients (p < 0.05).
Previous studies by Ksantini [28] and Daoui [29] showed that 76% and 84.56% of patients presented with severe forms of COVID-19 in Marakech and Agadir. While a Moroccan study found leukocytosis in patients with severe COVID-19, a study at the CHU Hedi Chaker-Sfax in Tunisia found it elevated in only 35.4% of such cases [2]. Similarly, leukocytosis was found to be an independent risk factor for mortality in these COVID-19 patients in Cameroon (OR = 1.940, 95% CI: 1.093–3.442, p = 0.023). Mohebbi et al. [30] and Zhu et al. [31] also showed that patients with higher WBC counts faced a significantly higher risk of dying of COVID-19 patients in Shiraz, Iran and Wu Han province, China respectively. The increase in white blood cells correlates with an increase in neutrophils, which release reactive oxygen species capable of destroying normal or foreign cells, thus reducing the number of lymphocytes needed to fight infectious diseases [32, 33]. Thrombocytosis was found in 8.8% of our patients, slightly higher than the 6.8% found by Chabati et al. [34]; and is associated with an elevated mortality risk in COVID-19 patients (OR = 4.286, 95% CI: 1.152–15.950, p = 0.030). The high risk of mortality in COVID-19 patients with thrombocytosis observed here is not well documented in the literature. COVID-19 patients are more prone to thrombocytopenia [35]. However, it has been established that COVID-19 patients with thrombocytosis had longer hospital stays and poorer outcomes [36]. Previous studies also noted that in severe cases of COVID-19, platelet counts increased significantly due to the cytokine storm. However, the underlying mechanisms remain unclear [37].
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Electrolyte imbalance in the form of hyponatremia, hypokalemia and hypochloremia were more prevalent in patients who died from COVID-19, with the risk of death up to 2 times higher than in patients with normal natremia/hypernatremia. The elevated risk is attributed to the syndrome of inappropriate secretion of antidiuretic hormone secretion (SIADH), frequently seen in hyponatremic patients suffering from acute respiratory distress syndrome [38]. This is similar to earlier study that found of hyponatremia, accompanied by neurological complications (encephalopathy, cerebral edema and convulsions) which can have serious consequences, including death [39]. As for hypokalemia, the high prevalence and high risk of death observed in COVID-19 patients could be explained by the hyperactivation of the renin angiotensin aldosterone system (RAAS) in COVID-19 patients, which promotes potassium excretion in the urine [40]. In addition, the gastrointestinal symptoms (diarrhea, vomiting) observed in patients suffering from COVID-19 could also be evoked. These symptoms may result from the loss of potassium from the gastrointestinal tract [41]. The results observed in this study are in contrast to those of Ramanandafy et al. [42] who showed no significant difference for hypokalemia and hyponatremia in patients with severe forms of COVID-19 compared to patients with mild forms in Madagascar. When it came to hypochloremia, we observed a high frequency in deceased COVID-19 patients and a three times higher mortality risk than in patients with normal/hyperchloremia. These results (hyponatremia, hypokalemia and hypochloremia) are similar to those of Wu et al. [43], who observed a high risk of long-term hospitalization for COVID-19 patients with these electrolyte disorders. Indeed, the longer the duration of hospitalization, the higher the risk of death.
Conclusion
This study highlights critical hematological and biochemical factors associated with mortality in Cameroonian patients with COVID-19, including leukocytosis, thrombocytosis and electrolyte imbalances (hypokalemia, hyponatremia and hypochloremia). These results highlight the unique biological profile of COVID-19 in Cameroon, suggesting the need for tailored therapeutic strategies to address these specificities and improve patient outcomes. At the end of this work, we summarize the factors associated with mortality in covid 19 patients in the form of a diagram (Fig. 2).
Fig. 2
Factors that may contribute to mortality in COVID-19 patients
Acknowledgements
The authors would like to thank the authorities in charge of the Adlucem hospital of Banka-Bafang for allowing this work to be carried out, as well as all the health care staff for their support and the patients.
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Declarations
Ethics approval and consent to participate
This study was approved by the Regional Ethics Committee for Human Health Research of the Western Region of the Ministry of Public Health of Cameroon under number 853/28/08/2024/CE/CRERSH-OU/VP. The collection was authorized by the authorities of the Ad Lucem Hospital in Banka-Bafang. Informed consent was obtained from all participants, who were previously informed of the nature, objectives, potential risks and expected benefits of the research. Participants were fully informed of their right to withdraw from the interview or not participate. Confidentiality measures were put in place, including the allocation of unique codes to each participant. All methods were conducted in accordance with ethical standards, as outlined in the Declaration of Helsinki. To mitigate the risk of COVID-19 transmission, social distancing measures were implemented and participants were provided with necessary protective equipment, such as face masks and hand sanitizer.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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