ObjectiveIn this systematic review, we estimate the prevalence of six types of arthritis in Africa; namely rheumatoid arthritis, osteoarthritis, juvenile arthritis, psoriatic arthritis, gout, and ankylosing spondylitis.MethodsWe comprehensively searched literature on 31 August 2014 in MEDLINE, EMBASE, Web of Science and the Cochrane Library to identify eligible studies from 1975 up to 31 July 2014. Two review authors independently selected studies, extracted data, and appraised studies. We carried out random effects meta-analysis of prevalence of arthritis and assessed heterogeneity through subgroup analyses. We performed separate analyses for population- and hospital-based studies, as well as rural and urban settings.Main FindingsWe included 27 cross-sectional studies (20 population-based and 7 hospital-based) from Africa reporting on the prevalence of arthritis. The majority of the studies were from South Africa (44.4%, 12/27). Rheumatoid arthritis in urban settings ranged from 0.1% in Algeria, 0.6% in the DRC, to a meta-analysis overall prevalence of 2.5% in South Africa, and in rural settings ranged from a meta-analysis overall prevalence of 0.07% in South Africa, 0.3% in Egypt, to 0.4% in Lesotho. Osteoarthritis was the most prevalent form of arthritis and in urban settings it was 55.1% in South Africa and in rural settings, all in South Africa, ranged from 29.5%, 29.7%, up to 82.7% among adults aged over 65 years. Other results include highest prevalence of 33.1% for knee osteoarthritis in rural South Africa, 0.1% for ankylosing spondylitis in rural South Africa, 4.4% for psoriatic arthritis in urban South Africa, 0.7% for gout in urban South Africa, and 0.3% for juvenile idiopathic arthritis in urban Egypt. A third of the included studies had a low risk of bias (33.3%, 9/27), 40.8% (11/27) moderate risk, and 25.9% (7/27) had a high risk of bias.ConclusionsIn this systematic review, we have identified the paucity of latest prevalence data on arthritis in Africa. More studies are needed to address the prevalence and the true burden of this disease in Africa.
Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. Clinical trial registration: NCT03044899.
Summary Background Risk of mortality following surgery in patients across Africa is twice as high as the global average. Most of these deaths occur on hospital wards after the surgery itself. We aimed to assess whether enhanced postoperative surveillance of adult surgical patients at high risk of postoperative morbidity or mortality in Africa could reduce 30-day in-hospital mortality. Methods We did a two-arm, open-label, cluster-randomised trial of hospitals (clusters) across Africa. Hospitals were eligible if they provided surgery with an overnight postoperative admission. Hospitals were randomly assigned through minimisation in recruitment blocks (1:1) to provide patients with either a package of enhanced postoperative surveillance interventions (admitting the patient to higher care ward, increasing the frequency of postoperative nursing observations, assigning the patient to a bed in view of the nursing station, allowing family members to stay in the ward, and placing a postoperative surveillance guide at the bedside) for those at high risk (ie, with African Surgical Outcomes Study Surgical Risk Calculator scores ≥10) and usual care for those at low risk (intervention group), or for all patients to receive usual postoperative care (control group). Health-care providers and participants were not masked, but data assessors were. The primary outcome was 30-day in-hospital mortality of patients at low and high risk, measured at the participant level. All analyses were done as allocated (by cluster) in all patients with available data. This trial is registered with ClinicalTrials.gov , NCT03853824 . Findings Between May 3, 2019, and July 27, 2020, 594 eligible hospitals indicated a desire to participate across 33 African countries; 332 (56%) were able to recruit participants and were included in analyses. We allocated 160 hospitals (13 275 patients) to provide enhanced postoperative surveillance and 172 hospitals (15 617 patients) to provide standard care. The mean age of participants was 37·1 years (SD 15·5) and 20 039 (69·4%) of 28 892 patients were women. 30-day in-hospital mortality occurred in 169 (1·3%) of 12 970 patients with mortality data in the intervention group and in 193 (1·3%) of 15 242 patients with mortality data in the control group (relative risk 0·96, 95% CI 0·69–1·33; p=0·79). 45 (0·2%) of 22 031 patients at low risk and 309 (5·6%) of 5500 patients at high risk died. No harms associated with either intervention were reported. Interpretation This intervention package did not decrease 30-day in-hospital mortality among surgical patients in Africa at high risk of postoperative morbidity or mortality. Further research is needed to develop interventions that prevent death from surgical complications in resource-limited hospitals across Africa. Funding Bill & Melinda Gates Foundation and the World Federati...
Background: Patients with confirmed COVID-19 admitted to intensive care units have a high mortality rate, which appears to be associated with increasing age, male sex, smoking history, hypertension and diabetes mellitus. Methods: A systematic review to determine risk factors and interventions associated with mortality/survival in adult patients admitted to an intensive care unit (ICU) with confirmed COVID-19/SARS-CoV-2 infection. The protocol was registered with PROSPERO (CRD42020181185). Results: The search identified 483 abstracts between 1 January and 7 April 2020, of which nine studies were included in the final review. Only one study was of low bias. Advanced age (odds ratio [OR] 11.99, 95% confidence interval [CI] 5.35–18.62) and a history of hypertension were associated with mortality (OR 4.17, 95% CI 2.90–5.99). Sex was not associated with mortality. There was insufficient data to assess the association between other comorbidities, laboratory results or critical care risk indices and mortality. The critical care interventions of mechanical ventilation (OR 6.25, 95% CI 0.75–51.93), prone positioning during ventilation (OR 2.06, 95% CI 0.20–21.72), and extracorporeal membrane oxygenation (ECMO) (OR 8.00, 95% CI 0.69, 92.33) were not associated with mortality. The sample size was insufficient to conclusively determine the association between these interventions and ICU mortality. The need for inotropes or vasopressors was associated with mortality (OR 6.36, 95% CI 1.89–21.36). Conclusion: The studies provided little granular data to inform risk stratification or prognostication of patients requiring intensive care admission. Larger collaborative research is needed to address this limitation.
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