Predictors of mortality in COVID-19 patients at Kinshasa University Hospital, Democratic Republic of the Congo, from March to June 2020

COVID-19 epidemiology, health services utilisation and health care seeking behaviour during the first year of the COVID-19 pandemic in Mweso health zone, Democratic Republic of Congo

Background

Although the evidence about coronavirus disease 2019 (COVID-19) has increased exponentially since the beginning of the pandemic, less is known about the direct and indirect effects of the pandemic in humanitarian settings. In the Democratic Republic of the Congo (DRC), most studies occurred in Kinshasa and other cities. Limited research was conducted in remote conflict-affected settings. We investigated the COVID-19 epidemiology, health service utilisation, and health care-seeking behaviour during the first year of the pandemic (March 2020-March 2021) in the Mweso health zone, North Kivu, DRC.

Methods

This mixed-methods study includes a descriptive epidemiological analysis of reported COVID-19 cases data extracted from the provincial line list, interrupted time series analysis of health service utilisation using routine health service data, qualitative perceptions of health care workers about how health services were affected, and community members' health care seeking behaviour from a representative household survey and focus group discussions.

Results

The COVID-19 epidemiology in North Kivu aligns with evidence reported globally, yet case fatality rates were high due to underreporting. Testing capacity was limited and initially mainly available in the province's capital. Health service utilisation showed different patterns - child measles vaccinations experienced a decrease at the beginning of the pandemic, while outpatient consultations, malaria, and pneumonia showed an increase over time. Such increases might have been driven by insecurity and population displacements rather than COVID-19. Community members continued seeking care during the first months of the COVID-19 pandemic and visited the same health facilities as before COVID-19. Financial constraints, not COVID-19, were the main barrier reported to accessing health care.

Conclusions

The first year of the COVID-19 pandemic in the Mweso health zone was characterised by low testing capacity and an underestimation of reported COVID-19 infections. The increase in health care utilisation should be further explored to understand the role of factors unrelated to COVID-19, such as insecurity, population displacement, and poverty, which remain major challenges to successfully providing health services and improving the population's health. Measles vaccination coverage dropped, which exacerbated the ongoing measles outbreak. Improved decentralised testing capacity will be crucial for future epidemics and enhanced efforts to maintain child vaccination coverage.

Interest of Chest CT to Assess the Prognosis of SARS-CoV-2 Pneumonia: An In-Hospital-Based Experience in Sub-Saharan Africa

Methods

We included all patients with respiratory symptoms (dyspnea, fever, and cough) and/or respiratory failure admitted to the SOS Médecins de nuit SARL hospital, DR Congo, during the 2nd and 3rd waves of the COVID-19 pandemic. The diagnosis of COVID-19 was established based on RT-PCR anti-SARS-CoV-2 tests (G1 (RT-PCR positive) vs. G2 (RT-PCR negative)), and all patients had a chest CT on the day of admission. We retrieved the digital files of patients, precisely the clinical, biological, and chest CT parameters of the day of admission as well as the vital outcome (survival or death). Chest CT were read by a very high-definition console using Advantage Windows software and exported to the hospital network using the RadiAnt DICOM viewer. To determine the threshold for the percentage of lung lesions associated with all-cause mortality, we used ROC curves. Factors associated with death, including chest CT parameters, were investigated using logistic regression analysis.

Results

The study included 200 patients (average age 56.2 ± 15.2 years; 19% diabetics and 4.5% obese), and COVID-19 was confirmed among 56% of them (G1). Chest CT showed that ground glass (72.3 vs. 39.8%), crazy paving (69.6 vs. 17.0%), and consolidation (83.9 vs. 22.7%), with bilateral and peripheral locations (68.8 vs. 30.7%), were more frequent in G1 vs. G2 (p < 0.001). No case of pulmonary embolism and fibrosis had been documented. The lung lesions affecting 30% of the parenchyma were informative in predicting death (area under the ROC curve at 0.705, p = 0.017). In multivariate analysis, a percentage of lesions affecting 50% of the lung parenchyma increased the risk of dying by 7.194 (1.656-31.250).

Conclusion

The chest CT demonstrated certain characteristic lesions more frequently in patients in whom the diagnosis of COVID-19 was confirmed. The extent of lesions affecting at least half of the lung parenchyma from the first day of admission to hospital increases the risk of death by a factor of 7.

Predictors of mortality among inpatients in COVID-19 treatment centers in the city of Butembo, North Kivu, Democratic Republic of Congo

Determining the risk factors for severe disease and death among hospitalized Covid-19 patients is critical to optimize health outcomes and health services efficiency, especially in resource-constrained and humanitarian settings. This study aimed to identify the predictors of mortality of Covid-19 patients in North Kivu province in the Democratic Republic of Congo.A retrospective cohort study was conducted in 6 Covid-19 treatment centers in the city of Butembo from 1 January to 31 December 2021. The time to event (death), the outcome variable, was visualized by Kaplan-Meier curves and the log-rank test was used to confirm differences in trends. Cox regression was used for all the predictors in the bivariate analysis and multivariate analysis was done using predictors found statistically significant in the bivariate analysis. The following variables were considered for inclusion to the Cox regression model: Age, Sex, Disease length, Treatment site, History of at least one co-morbidity, Body mass index, Stage according to SpO2 and the NEWS-modified score.Among the 303 participants (mean age of 53 years), the fatality rate was 33.8 deaths per 1000 patient-days. Four predictors were independently associated with inpatient death: age category (≥ 60 years) (adjusted HR: 9.90; 95% CI: 2.68-36.27), presence of at least one comorbidity (adjusted HR: 11.39; 95% CI: 3.19-40.71); duration of illness of > 5 days before hospitalization (adjusted HR:1.70, 95% CI: 1.04-2.79) and peripheral capillary oxygen saturation (SpO2) < 90% (adjusted HR = 14.02, 95% CI: 2.23-88.32). In addition to advanced age, comorbidity, and length of disease before hospitalization, ambient air SpO2 measured by healthcare providers using low-tech, affordable and relatively accessible pulse oximetry could inform the care pathways of Covid-19 inpatients in resource-challenged health systems in humanitarian settings.

Risk factors for death in hospitalized COVID-19 patients in Africa: A systematic review and meta-analysis

BACKGROUND

The coronavirus disease 2019 has quickly spread worldwide since it first appeared in Wuhan, China, in late 2019. The most affected country in Africa was South Africa. This study aimed to identify the risk factors for death in hospitalized COVID-19 patients in Africa.

METHODS

We conducted a systematic review following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. We searched articles from the following database: PubMed, Embase, Cochrane Library, Medline, and COVID-19 Research Database. We used Google Scholar for gray literature. The language used in this article was English. The last search was conducted on January 15, 2023. Pooled HRs, or ORs, and 95% confidence intervals, were calculated separately to identify the risk factors for death in hospitalized COVID-19 patients. Heterogeneity was assessed by Cochran's Q statistic and the I2 test. The Egger test was used to assess publication bias. Subgroup analysis was performed to determine the source of heterogeneity. Data analysis was performed using Stata version 17. A P value < .05 was considered significant.

RESULTS

A total of 16,600 articles were obtained from the database search; finally, 16 articles met the inclusion criteria and were eligible for data extraction. The analysis revealed that the pooled prevalence of mortality in hospitalized COVID-19 patients was 13.9%. Advanced age was a significant risk factor for death in hospitalized COVID-19 patients, with the pooled coronavirus mortality HR and OR being 3.73 (95% CI: 2.27-5.19) and 1.04 (95% CI: 1.02-1.06), respectively. In addition, male gender (pOR 1.23; 95% CI: 1.07-1.40), patients with diabetes mellitus (DM) (pOR 1.26; 95% CI: 1.01-1.51), hypertension (HTN) (pOR 1.56; 95% CI: 1.27-1.85), chronic kidney disease (CKD) (pHR 5.43; 95% CI: 0.18-10.67), severe or critical conditions (pOR 9.04; 95% CI: 3.14-14.94) had a significantly increased risk of coronavirus-related mortality. The main limitations of the present study stem from the predominant use of published studies, which could introduce publication bias.

CONCLUSION

According to this study, advanced age, male gender, hypertension, diabetes mellitus, chronic kidney disease, and severe or critical condition were clinical risk factors associated with death outcomes in hospitalized COVID-19 patients in Africa.

Time to death and its predictors among adult patients with COVID-19: A retrospective cohort study in Ethiopia

Background

Coronavirus (COVID-19) disease affected people throughout the globe and has become a severe threat to the health and wellbeing of the global community. Time to death and predictors of mortality vary across settings. So far, no or few related studies have been undertaken in Ethiopia. Studying the time to death from COVID-19 and its predictors is essential to understand the characteristics of the disease and thereby contribute to the identification of indicators for early detection and initiation of treatment. Therefore, this study aimed to estimate time to death and its predictors among adults with COVID-19 in Ethiopia.

Methods

A retrospective follow-up study was conducted among 602 adults with COVID-19 attending Eka Kotebe General Hospital, COVID-19 Treatment Center, between 13 March 2020 and 13 November 2020. The data were entered by Epi-data version 4.2 while the analysis was carried out using STATA version 16. A Kaplan-Meier survivor curve was computed to estimate the survival probabilities. A log-rank test was used to compare the difference in survival curves. Cox proportional hazard models were fitted to identify the predictors of time to death.

Results

The overall median time to death was 21 days. Older adults (aged ≥65 years) [adjusted hazard ratio (AHR) 2.22, 95% confidence interval (CI) 1.02-4.86], being men (AHR 3.04, 95% CI 1.61-5.74), shortness of breathing at admission (AHR 2.29, 95% CI 1.16-4.54), comorbidity (AHR 2.23, 95% CI 1.04-4.80), diabetes mellitus (AHR 2.31, 95% CI 1.30-4.08), altered cardiac function (AHR 2.07, 95% CI 1.21-3.43), and baseline white blood cell count of greater than 10 (103/µl) (AHR 2.62, 95% CI 1.55-4.44) were independent predictors of COVID-19 mortality.

Conclusion

Male sex, older adults, shortness of breathing at admission, patients with comorbidities, and higher blood cell count were significant predictors of time to death from COVID-19. Therefore, concerned stakeholders should focus on those predictors of mortality and design interventions accordingly to enhance the survival of patients with COVID-19.

Risk factors for mortality in COVID-19 patients in sub-Saharan Africa: A systematic review and meta-analysis

Aim

Mortality rates of coronavirus-2019 (COVID-19) disease continue to increase worldwide and in Africa. In this study, we aimed to summarize the available results on the association between sociodemographic, clinical, biological, and comorbidity factors and the risk of mortality due to COVID-19 in sub-Saharan Africa.

Methods

We followed the PRISMA checklist (S1 Checklist). We searched PubMed, Google Scholar, and European PMC between January 1, 2020, and September 23, 2021. We included observational studies with Subjects had to be laboratory-confirmed COVID-19 patients; had to report risk factors or predictors of mortality in COVID-19 patients, Studies had to be published in English, include multivariate analysis, and be conducted in the sub-Saharan region. Exclusion criteria included case reports, review articles, commentaries, errata, protocols, abstracts, reports, letters to the editor, and repeat studies. The methodological quality of the studies included in this meta-analysis was assessed using the methodological items for nonrandomized studies (MINORS). Pooled hazard ratios (HR) or odds ratios (OR) and 95% confidence intervals (CI) were calculated separately to identify mortality risk. In addition, publication bias and subgroup analysis were assessed.

Results and discussion

Twelve studies with a total of 43598 patients met the inclusion criteria. The outcomes of interest were mortality. The results of the analysis showed that the pooled prevalence of mortality in COVID-19 patients was 4.8%. Older people showed an increased risk of mortality from SARS-Cov-2. The pooled hazard ratio (pHR) and odds ratio (pOR) were 9.01 (95% CI; 6.30–11.71) and 1.04 (95% CI; 1.02–1.06), respectively. A significant association was found between COVID-19 mortality and men (pOR = 1.52; 95% CI 1.04–2). In addition, the risk of mortality in patients hospitalized with COVID-19 infection was strongly influenced by chronic kidney disease (CKD), hypertension, severe or critical infection on admission, cough, and dyspnea. The major limitations of the present study are that the data in the meta-analysis came mainly from studies that were published, which may lead to publication bias, and that the causal relationship between risk factors and poor outcome in patients with COVID-19 cannot be confirmed because of the inherent limitations of the observational study.

Conclusions

Advanced age, male sex, CKD, hypertension, severe or critical condition on admission, cough, and dyspnea are clinical risk factors for fatal outcomes associated with coronavirus. These findings could be used for research, control, and prevention of the disease and could help providers take appropriate measures and improve clinical outcomes in these patients.

Diabetes Mellitus is Associated With Higher COVID-19 Mortality Rates in Sub-Saharan Africa: A Systematic Review and Meta-analysis

The rate of COVID-19-related mortality among patients with diabetes mellitus in Sub-Saharan Africa (SSA) is unknown. The current study aimed to determine the mortality rate of COVID-19 among diabetes patients in SSA. We performed a systematic review of research articles until July 1, 2021. A literature review was conducted in accordance with the PRISMA guidelines to gather relevant data. A random effects model was used to calculate odds ratios and 95% confidence intervals (CIs). We used Egger's tests and Begg's funnel plot to examine publication bias. The mortality rate of 7778 COVID-19 patients was analyzed using data from seven studies. The I² test was used to determine the heterogeneity between studies. The meta-analysis revealed that diabetes mellitus was linked to a 1.39-fold increase in the risk of death among COVID-19 inpatients (95% CI: 1.02-1.76). According to our findings, there was no significant heterogeneity between studies, and there was no publication bias. The present review describes an association between diabetes mellitus and the risk of COVID-19 mortality in SSA.

Factors associated with death in COVID-19 patients over 60 years of age at Kinshasa University Hospital, Democratic Republic of Congo (DRC)

Introduction

the objectives of the present study were to determine the mortality rate in patients over 60 years of age with COVID-19 and to identify risk factors.

Methods

the present historical cohort study took place at the Kinshasa University Hospital (KUH), DRC. Older patients admitted from March 2020 to May 2021 and diagnosed COVID-19 positive at the laboratory were selected. The relationship between clinical and biological risk factors, treatment, and in-hospital mortality was modeled using Cox regression.

Results

of two hundred and twenty-two patients at least 60 years old, 97 died, for a mortality rate of 43.69%. The median age was 70 years (64-74) with extremes of 60 to 88 years. Low oxygen saturation of < 90% (aHR 1.69; 95% CI [1.03-2.77]; p=0.038) was an independent predictor of mortality. The risk of death was reduced with corticosteroid use (aHR 0.54; 95% CI [0.40-0.75]; p=0.01) and anticoagulant treatment (aHR 0.53; 95% CI [0.38-0.73]; p=0.01).

Conclusion

mortality was high in seniors during COVID-19 and low oxygen saturation on admission was a risk factor for mortality. Corticosteroid therapy and anticoagulation were protective factors. These should be considered in management to reduce mortality.

Incidence and predictors of mortality among COVID-19 patients admitted to treatment centers in North West Ethiopia; a retrospective cohort study, 2021

Background

Currently, coronavirus disease 2019 (COVID-19) is the leading cause of death and the rate of mortality is rapidly increasing over time. There is a paucity of information regarding the incidence and predictors of mortality among COVID-19 patients from low-income countries, particularly in Ethiopia.

Objective

To assess incidence and predictors of mortality among COVID-19 patients admitted to treatment centers in North West Ethiopia.

Methods

An institution-based retrospective cohort study was conducted among 552 laboratory-confirmed COVID-19 cases at Debre Markos University and Tibebe Ghion Hospital COVID-19 treatment centers in North West Ethiopia from March 2020 to March 2021. Data were collected from patients’ medical records using a structured data extraction tool. Cox-proportional hazards regression models was fitted to identify significant predictors of mortality.

Result

The overall mortality rate of COVID-19 was 4.7, (95 % CI: 3.3–6.8) per 1000 person day observations. Older age (AHR: 4.9; 95% CI: 1.8, 13.5), rural residence (AHR: 0.18; 95% CI: 0.05, 0.64), presence of hypertension (AHR: 3.04; 95% CI: 1.18, 7.8), presence of diabetes mellitus (AHR: 8.1; 95% CI: 2.9, 22.4) and cardiovascular disease (AHR: 5.2; 95% CI: (1.69, 16.2) were significantly associated with mortality.

Conclusions

The rate of mortality among hospitalized COVID-19 patients in this study was low. COVID-19 patients from urban residences, older patients, and patients with comorbidity have a high risk of death. These high risk groups should be prioritized for COVID-19 vaccinations, and early screening and appropriate intervention should be established on presentation to health facility.

Predictors of mortality in COVID-19 patients at Kinshasa Medical Center and a survival analysis: a retrospective cohort study

Background

Despite it being a global pandemic, there is little research examining the clinical features of severe COVID-19 in sub-Saharan Africa. This study aims to identify predictors of mortality in COVID-19 patients at Kinshasa Medical Center (KMC).

Methods

In this retrospective, observational, cohort study carried out at the Kinshasa Medical Center (KMC) between March 10, 2020 and July 10, 2020, we included all adult inpatients (≥ 18 years old) with a positive COVID-19 PCR result. The end point of the study was survival. The study population was dichotomized into survivors and non-survivors group. Kaplan–Meier plot was used for survival analyses. The Log-Rank test was employed to compare the survival curves. Predictors of mortality were identified by Cox regression models. The significance level of p value was set at 0.05.

Results

432 patients with confirmed COVID-19 were identified and only 106 (24.5%) patients with moderate, severe or critical illness (mean age 55.6 ± 13.2 years old, 80.2% were male) were included in this study, of whom 34 (32%) died during their hospitalisation. The main complications of the patients included ARDS in 59/66 (89.4%) patients, coagulopathy in 35/93 (37.6%) patients, acute cardiac injury in 24/98 (24.5%) patients, AKI in 15/74 (20.3%) patients and secondary infection in 12/81 (14.8%) patients. The independent predictors of mortality were found to be age [aHR 1.38; 95% CI 1.10–1.82], AKI stage 3 [aHR 2.51; 95% CI 1.33–6.80], proteinuria [aHR 2.60; 95% CI 1.40–6.42], respiratory rate [aHR 1.42; 95% CI 1.09–1.92] and procalcitonin [aHR 1.08; 95% CI 1.03–1.14]. The median survival time of the entire group was 12 days. The cumulative survival rate of COVID-19 patients was 86.9%, 65.0% and 19.9% respectively at 5, 10 and 20 days. Levels of creatinine (p = 0.012), were clearly elevated in non-survivors compared with survivors throughout the clinical course and increased deterioration.

Conclusion

Mortality rate of COVID-19 patients is high, particularly in intubated patients and is associated with age, respiratory rate, proteinuria, procalcitonin and acute kidney injury.

Diabetes, hypertension, body mass index, smoking and COVID-19-related mortality: a systematic review and meta-analysis of observational studies

OBJECTIVES

We conducted a systematic literature review and meta-analysis of observational studies to investigate the association between diabetes, hypertension, body mass index (BMI) or smoking with the risk of death in patients with COVID-19 and to estimate the proportion of deaths attributable to these conditions.

METHODS

Relevant observational studies were identified by searches in the PubMed, Cochrane library and Embase databases through 14 November 2020. Random-effects models were used to estimate summary relative risks (SRRs) and 95% CIs. Certainty of evidence was assessed using the Cochrane methods and the Grading of Recommendations, Assessment, Development and Evaluations framework.

RESULTS

A total of 186 studies representing 210 447 deaths among 1 304 587 patients with COVID-19 were included in this analysis. The SRR for death in patients with COVID-19 was 1.54 (95% CI 1.44 to 1.64, I2=92%, n=145, low certainty) for diabetes and 1.42 (95% CI 1.30 to 1.54, I2=90%, n=127, low certainty) for hypertension compared with patients without each of these comorbidities. Regarding obesity, the SSR was 1.45 (95% CI 1.31 to 1.61, I2=91%, n=54, high certainty) for patients with BMI ≥30 kg/m2 compared with those with BMI <30 kg/m2 and 1.12 (95% CI 1.07 to 1.17, I2=68%, n=25) per 5 kg/m2 increase in BMI. There was evidence of a J-shaped non-linear dose-response relationship between BMI and mortality from COVID-19, with the nadir of the curve at a BMI of around 22-24, and a 1.5-2-fold increase in COVID-19 mortality with extreme obesity (BMI of 40-45). The SRR was 1.28 (95% CI 1.17 to 1.40, I2=74%, n=28, low certainty) for ever, 1.29 (95% CI 1.03 to 1.62, I2=84%, n=19) for current and 1.25 (95% CI 1.11 to 1.42, I2=75%, n=14) for former smokers compared with never smokers. The absolute risk of COVID-19 death was increased by 14%, 11%, 12% and 7% for diabetes, hypertension, obesity and smoking, respectively. The proportion of deaths attributable to diabetes, hypertension, obesity and smoking was 8%, 7%, 11% and 2%, respectively.

CONCLUSION

Our findings suggest that diabetes, hypertension, obesity and smoking were associated with higher COVID-19 mortality, contributing to nearly 30% of COVID-19 deaths.

TRIAL REGISTRATION NUMBER

CRD42020218115.

COVID-19 in systemic lupus erythematosus: A pooled analysis and systematic review of case reports and series

OBJECTIVE

In the recent months, there have been several case reports and case series on COVID-19 in patients with systemic lupus erythematosus(SLE). We conducted a pooled analysis and systematic review to summarise the findings of these articles. Besides, we aimed to determine the predictors of severe COVID-19 infection in SLE by comparing the mild to moderate cases with the severe to critical ones.

METHOD

All case reports and case series pertaining to COVID-19 in SLE were retrieved from Pubmed, Wiley Online Library, Springer Link, Science Direct and Web of Science databases using 'lupus', 'systemic lupus erythematosus', 'coronavirus', 'SARS-CoV-2', 'SLE' and "Covid-19" as keywords. The following data were extracted from the selected articles: country, age of the patient and the characteristics of SLE such as disease duration, organ or system involved, baseline medications and the severity of the COVID-19 infection. Data extracted from the articles were utilised to perform the pooled analysis.

RESULTS

A total of 24 articles with 48 patients met the eligibility criteria. The median age at diagnosis of COVID-19 infection was 41 years (IQR: 11-66 years). The median SLE disease duration prior to the diagnosis of COVID-19 was 9 years (IQR: 0-30 years). A total of 22 (45.83%) patients had severe to critical COVID-19. This pooled data did not demonstrate any difference in the baseline medications between the 2 groups. Patients with lupus nephritis were significantly more prone to develop severe to critical disease (p = 0 .036) with an odds ratio of 5.40 (95% confidence interval of 1.120-26.045).

CONCLUSION

We found that lupus nephritis was the only predictor of severe to critical COVID-19 in SLE.

Chronic Diseases as a Predictor for Severity and Mortality of COVID-19: A Systematic Review With Cumulative Meta-Analysis

Introduction: Given the ongoing coronavirus disease 2019 (COVID-19) pandemic and the consequent global healthcare crisis, there is an urgent need to better understand risk factors for symptom deterioration and mortality among patients with COVID-19. This systematic review aimed to meet the need by determining the predictive value of chronic diseases for COVID-19 severity and mortality.

Methods: We searched PubMed, Embase, Web of Science, and Cumulative Index to Nursing and Allied Health Complete to identify studies published between December 1, 2019, and December 31, 2020. Two hundred and seventeen observational studies from 26 countries involving 624,986 patients were included. We assessed the risk of bias of the included studies and performed a cumulative meta-analysis.

Results: We found that among COVID-19 patients, hypertension was a very common condition and was associated with higher severity, intensive care unit (ICU) admission, acute respiratory distress syndrome, and mortality. Chronic obstructive pulmonary disease was the strongest predictor for COVID-19 severity, admission to ICU, and mortality, while asthma was associated with a reduced risk of COVID-19 mortality. Patients with obesity were at a higher risk of experiencing severe symptoms of COVID-19 rather than mortality. Patients with cerebrovascular disease, chronic liver disease, chronic renal disease, or cancer were more likely to become severe COVID-19 cases and had a greater probability of mortality.

Conclusions: COVID-19 patients with chronic diseases were more likely to experience severe symptoms and ICU admission and faced a higher risk of mortality. Aggressive strategies to combat the COVID-19 pandemic should target patients with chronic diseases as a priority.