Factors Associated With Mortality Among the COVID-19 Patients Treated at Gulu Regional Referral Hospital: A Retrospective Study

Prevalence and correlates of facemask usage during the second wave of COVID-19 pandemic in Uganda

The World Health Organization (WHO) and the United States Centers for Disease Control and Prevention (US CDC) documented wearing facemasks in public as one of the most important prevention measures to limit COVID-19 spread. Considering this, WHO and the US CDC developed guidelines for wearing facemasks in public. This study aimed to determine the prevalence and correlates of facemask wearing during the COVID-19 pandemic in northern Uganda. We conducted a cross-sectional study on 587 adults across nine districts in northern Uganda, across 24 high-volume health facilities offering free COVID-9 vaccines. Respondents were selected from the health facilities using a single-stage systematic sampling method. Data was collected in a face-to-face questionnaire interview with an internal validity of Cronbach's α = 0.72 and entered into Excel. A local Institutional Research Board (IRB) approved the study, and Stata 18 was used for data analysis using Modified Poisson Regression to generate prevalence ratios (PR) and adjusted prevalence ratios (aPR), with a p-value set at < 0.05. The reported prevalence of facemask wearing in public among respondents was high [88.7%,95%CI:86%,-91%]. A multivariate analysis found that obese respondents and those who were receptive (agreed) to the lockdown measures were respectively,1.12 times more likely to wear facemasks [aPR = 1.12,95%CI:1.04-1.19;p < 0.01], and1.23 times more likely to wear facemasks [aPR = 1.23, 95%CI:1.07-1.41;p < 0.01]. The most significant finding from this study was the high prevalence of self-reported facemask wearing among adult community members in northern Uganda. The correlates of wearing facemasks were, being obese and agreeing with the presidential directives on the lockdown measures. Although this prevalence is within acceptable rates, the strict enforcement of the practice by security forces has raised concerns among many community members and human rights advocates. We recommend more studies on communities' perspectives on the challenges and benefits of facemask-wearing after the COVID-19 pandemic.

Evaluation of hematological changes and immune response biomarkers as a prognostic factor in critical patients with COVID-19

COVID-19 disease has been a challenge for health systems worldwide due to its high transmissibility, morbidity, and mortality. Severe COVID-19 is associated with an imbalance in the immune response, resulting in a cytokine storm and a hyperinflammation state. While hematological parameters correlate with prognosis in COVID patients, their predictive value has not been evaluated specifically among those severely ill. Therefore, we aim to evaluate the role of hematological and immune response biomarkers as a prognostic factor in critically ill patients with COVID-19 admitted to the intensive care unit. From May 2020 to July 2021, a retrospective cohort study was conducted in a reference hospital in Manaus, which belongs to the Brazilian public health system. This study was carried out as single-center research. Clinical and laboratory parameters were analyzed to evaluate the association with mortality. We also evaluated the role of neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and C-reactive protein-to-lymphocyte ratio (CLR). We gathered information from medical records, as well as from prescriptions and forms authorizing the use of antimicrobial medications. During the study period, 177 patients were included, with a mean age of 62.58 ± 14.39 years. The overall mortality rate was 61.6%. Age, mechanical ventilation (MV) requirement, leukocytosis, neutrophilia, high c-reactive protein level, NLR, and CLR showed a statistically significant association with mortality in the univariate analysis. In the multivariate logistic regression analysis, only MV (OR 35.687, 95% CI: 11.084-114.898, p< 0.001) and NLR (OR 1.026, 95% CI: 1.003-1.050, p = 0.028) remained statistically associated with the outcome of death (AUC = 0.8096). While the need for mechanical ventilation is a parameter observed throughout the hospital stay, the initial NLR can be a primary risk stratification tool to establish priorities and timely clinical intervention in patients with severe COVID-19 admitted to the ICU.

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.

Respiratory Support Techniques for COVID-19-Related ARDS in a Sub-Saharan African Country: A Multicenter Observational Study

BACKGROUND

Limited data from low-income countries report on respiratory support techniques in COVID-19-associated ARDS.

RESEARCH QUESTION

Which respiratory support techniques are used in patients with COVID-19-associated ARDS in Uganda?

STUDY DESIGN AND METHODS

A multicenter, prospective, observational study was conducted at 13 Ugandan hospitals during the pandemic and included adults with COVID-19-associated ARDS. Patient characteristics, clinical and laboratory data, initial and most advanced respiratory support techniques, and 28-day mortality were recorded. Standard tests, log-rank tests, and logistic regression analyses were used for statistical analyses.

RESULTS

Four hundred ninety-nine patients with COVID-19-associated ARDS (mild, n = 137; moderate, n = 247; and severe, n = 115) were included (ICU admission, 38.9%). Standard oxygen therapy (SOX), high-flow nasal oxygen (HFNO), CPAP, noninvasive ventilation (NIV), and invasive mechanical ventilation (IMV) was used as the first-line (most advanced) respiratory support technique in 37.3% (35.3%), 10% (9.4%), 11.6% (4.8%), 23.4% (14.4%), and 17.6% (36.6%) of patients, respectively. The first-line respiratory support technique was escalated in 19.8% of patients. Twenty-eight-day mortality was 51.9% (mild ARDS, 13.1%; moderate ARDS, 62.3%; severe ARDS, 75.7%; P < .001) and was associated with respiratory support techniques as follows: SOX, 19.9%; HFNO, 31.9%; CPAP, 58.3%; NIV 61.1%; and IMV, 83.9% (P < .001). Proning was used in 79 patients (15.8%; 59 of 79 awake) and was associated with lower mortality (40.5% vs 54%; P = .03). The oxygen saturation to Fio2 ratio (OR, 0.99; 95% CI, 0.98-0.99; P < .001) and respiratory rate (OR, 1.07; 95% CI, 1.03-1.12; P = .002) at admission and NIV (OR, 6.31; 95% CI, 2.29-17.37; P < .001) or IMV (OR, 8.08; 95% CI, 3.52-18.57; P < .001) use were independent risk factors for death.

INTERPRETATION

SOX, HFNO, CPAP, NIV, and IMV were used as respiratory support techniques in patients with COVID-19-associated ARDS in Uganda. Although these data are observational, they suggest that the use of SOX and HFNO therapy as well as awake proning are associated with a lower mortality resulting from COVID-19-associated ARDS in a resource-limited setting.

Prediction of in-hospital mortality rate in COVID-19 patients with diabetes mellitus using machine learning methods

Background

Since its emergence in December 2019, until June 2022, coronavirus 2019 (COVID-19) has impacted populations all around the globe with it having been contracted by ~ 535 M people and leaving ~ 6.31 M dead. This makes identifying and predicating COVID-19 an important healthcare priority.

Method and Material

The dataset used in this study was obtained from Shahid Beheshti University of Medical Sciences in Tehran, and includes the information of 29,817 COVID-19 patients who were hospitalized between October 8, 2019 and March 8, 2021. As diabetes has been shown to be a significant factor for poor outcome, we have focused on COVID-19 patients with diabetes, leaving us with 2824 records.

Results

The data has been analyzed using a decision tree algorithm and several association rules were mined. Said decision tree was also used in order to predict the release status of patients. We have used accuracy (87.07%), sensitivity (88%), and specificity (80%) as assessment metrics for our model.

Conclusion

Initially, this study provided information about the percentages of admitted Covid-19 patients with various underlying disease. It was observed that diabetic patients were the largest population at risk. As such, based on the rules derived from our dataset, we found that age category (51-80), CPR and ICU residency play a pivotal role in the discharge status of diabetic inpatients.

Thirty-Day Outcomes of Young and Middle-Aged Adults Admitted with Severe COVID-19 in Uganda: A Retrospective Cohort Study

Background

There is scarcity of data regarding young and middle-aged adults hospitalized with severe Corona Virus Disease 2019 (COVID-19) in Africa. In this study, we describe the clinical characteristics and 30-day survival among adults aged 18 to 49 years admitted with severe COVID-19 in Uganda.

Methods

We reviewed treatment records of patients admitted with severe COVID-19 across five COVID-19 treatment units (CTU) in Uganda. We included individuals aged 18 to 49 years, who had a positive test or met the clinical criteria for COVID-19. We defined severe COVID-19 as having an oxygen saturation <94%, lung infiltrates >50% on imaging and presence of a co-morbidity that required admission in the CTU. Our main outcome was the 30-day survival from the time of admission. We used a Cox proportional hazards model to determine the factors associated with 30-day survival at a 5% level of significance.

Results

Of the 246 patient files reviewed, 50.8% (n = 125) were male, the mean ± (standard deviation) age was 39 ± 8 years, majority presented with cough, 85.8% (n = 211) and median C-reactive protein (interquartile range) was 48 (47.5, 178.8) mg/L. The 30-day mortality was 23.9% (59/246). At admission, anemia (hazard ratio (HR): 3.00, 95% confidence interval (CI), 1.32-6.82; p = 0.009) and altered mental state (GCS <15) (HR: 6.89, 95% CI: 1.48-32.08, p = 0.014) were significant predictors of 30-day mortality.

Conclusion

There was a high 30-day mortality among young and middle-aged adults with severe COVID-19 in Uganda. Early recognition and targeted management of anemia and altered consciousness are needed to improve clinical outcomes.

Prospective cohort of COVID-19 patients requiring hospital admission in Douala, Cameroon

OBJECTIVES

To report characteristics and outcome of COVID-19 patients who required hospital admission in sub-Saharan Africa clinics with no access to invasive mechanical ventilation.

METHODS

Between April and June 2021, documented COVID-19 patients with SaO₂ <95% who were admitted in two clinics in Douala (Cameroon) were invited to participate. Data were prospectively collected using a standardized questionnaire.

RESULTS

We included 67 patients: 39 males (58%), median age 62 years [50-70]. Comorbidities included hypertension (n=38, 57%), obesity (n=26, 38%), and diabetes (n=16, 24%). No patient reported COVID-19 vaccination. On admission, 35 patients (52%) required O₂ >6L/min. CT scan demonstrated extended lesions (>50%) in 50/61 cases (82%). Most patients received dexamethasone (n=64, 96%), heparin (n=64, 96%), chloroquine/azithromycin (n=59, 88%), and broad-spectrum antibiotics (n=59, 88%). Sixteen patients died (24%), after a median of 11.5 days [7.5-15.5] post-admission.

CONCLUSIONS

Despite the lack of invasive mechanical ventilation, 76% of COVID-19 patients survived.

Clinical and pharmacological factors associated with mortality in patients with COVID-19 in a high complexity hospital in Manaus: A retrospective study

COVID-19 is a contagious infection caused by the SARS-CoV-2 virus, responsible for more than 5 million deaths worldwide, and has been a significant challenge for healthcare systems worldwide. Characterized by multiple manifestations, the most common symptoms are fever, cough, anosmia, ageusia, and myalgia. However, several organs can be affected in more severe cases, causing encephalitis, myocarditis, respiratory distress, hypercoagulable state, pulmonary embolism, and stroke. Despite efforts to identify appropriate clinical protocols for its management, there are still no fully effective therapies to prevent patient death. The objective of this study was to describe the demographic, clinical, and pharmacotherapeutic management characteristics employed in patients hospitalized for diagnosis of COVID-19, in addition to identifying predictive factors for mortality. This is a single-center, retrospective cohort study carried out in a reference hospital belonging to the Brazilian public health system, in Manaus, from March 2020 to July 2021. Data were obtained from analyzing medical records, physical and electronic forms, medical prescriptions, and antimicrobial use authorization forms. During the study period, 530 patients were included, 51.70% male, with a mean age of 58.74 ± 15.91 years. The overall mortality rate was 23.58%. The variables age, number of comorbidities, admission to the ICU, length of stay, oxygen saturation, serum aspartate transaminase, and use of mechanical ventilation showed a positive correlation with the mortality rate. Regarding pharmacological management, 88.49% of patients used corticosteroids, 86.79% used antimicrobials, 94.15% used anticoagulant therapy, and 3.77% used immunotherapy. Interestingly, two specific classes of antibiotics showed a positive correlation with the mortality rate: penicillins and glycopeptides. After multivariate logistic regression analysis, age, number of comorbidities, need for mechanical ventilation, length of hospital stay, and penicillin or glycopeptide antibiotics use were associated with mortality (AUC = 0.958).

Prevalence and Factors Associated With Compliance With COVID-19 Presidential Lockdown Measures: A Cross-Sectional Study

The coronavirus disease 2019 (COVID-19) is one of the most severe global health uncertainties to date. Although significant global effort has been put into implementing COVID-19 pandemic control measures such as lockdowns, travel restrictions, and hygiene precautions, the transmission is expected to resurface once these efforts are discontinued. We aimed to determine the prevalence and factors associated with compliance with presidential 53-day lockdown measures in June-July 2021 in northern Uganda. In this cross-sectional study, 587 adult participants (≥18 years old) from northern Uganda were selected using a systematic sampling method. Data collection involved interviewer-administered questionnaires with an internal validity of Cronbach's α = .72. Socio-demographic characteristics of participants were described, and multivariable modified Poisson regressions were performed to assess prevalence ratios between dependent and selected independent variables, with respective P values at 95% confidence intervals. All analyses were conducted using Stata 17.0. Participants' compliance with the presidential lockdown directives was high at 88%(95% CI: 85%-90%). Compliance with the presidential directives was more likely among participants who agreed to the lockdown measures [adjusted Prevalence Ratio, aPR = 1.28 (95% CI: 1.10-1.49; P = .001)] compared to those who did not, and more likely among those who were afraid of death from COVID-19 [aPR = 1.08 (95% CI: 1.01-1.15; P = .023)] than those who did not. However, compliance was less likely among males [aPR = 0.91 (95% CI: 0.86-0.97; P = .002)] compared to females, those aged 35 to 44 years [aPR = 0.87 (95% CI: 0.79-0.97; P = .013)] compared to those less 25 years; and unmarried [aPR = 0.89 (95% CI: 0.82-0.97; P = .011)] compared to the married. Compliance with the COVID-19 presidential lockdown measures in northern Uganda was high. The factors associated with compliance were the fear of death and agreement with presidential lockdown measures. However, compliance was less likely among males, unmarried persons, and persons aged 35 to 44. The authors recommend more community engagements, participation, sensitization, mobilization, and simultaneous application of multiple public health approaches to improve compliance and control of COVID-19.

Factors Associated with 30-Day in-Hospital Mortality Among Patients Admitted with Severe Covid-19 in Mbarara Regional Referral Hospital

Background

COVID-19 has created a burden on the healthcare system globally. Severe COVID-19 is linked with high hospital mortality. Data regarding 30-day in-hospital mortality and its factors has not been explored in southwestern Uganda.

Methods

We carried out a retrospective, single-center cohort study, and included all in-patients with laboratory-confirmed, radiological, or clinical severe COVID-19 admitted between April 2020 and September 2021 at Mbarara Regional Referral Hospital (MRRH). Demographic, laboratory, treatment, and clinical outcome data were extracted from patients' files. These data were described comparing survivors and non-survivors. We used logistic regression to explore the factors associated with 30-day in-hospital mortality.

Results

Of the 283 patients with severe COVID-19 admitted at MRRH COVID-19 unit, 58.1% were male. The mean age ± standard deviation (SD) was 61±17.4 years; there were no differences in mean age between survivors and non-survivors (59 ± 17.2 versus 64.4 ±17.3, respectively, p=0.24) The median length of hospital stay was 7 (IQR 3-10) days (non-survivors had a shorter median length of stay 5 (IQR 2-9) days compared to the survivors; 8 (IQR 5-11) days, p<0.001. The most frequent comorbidities were hypertension (30.5%) and diabetes mellitus (30%). The overall 30-day in-hospital mortality was 134 of 279 (48%) mortality rate of 47,350×105 with a standard error of 2.99%. The factors associated with 30-day in-hospital mortality were age: 65 years and above (aOR, 3.88; 95% CI, 1.24-11.70; P =0.020) a neutrophil to lymphocyte ratio above 5 (aOR, 4.83; 95% CI, 1.53-15.28; P =0.007) and oxygen requirement ≥15L/min (aOR, 15.80; 95% CI, 5.17-48.25; P <0.001).

Conclusion

We found a high 30-day in-hospital mortality among patients with severe forms of COVID-19. The identified factors could help clinicians to identify patients with poor prognosis at an early stage of admission.