Background: Children comprise a large proportion of the population in sub-Saharan Africa. The burden of paediatric surgical disease exceeds available resources in Africa, potentially increasing morbidity and mortality. There are few prospective paediatric perioperative outcomes studies, especially in low-and middle-income countries (LMICs). Methods: We conducted a 14-day multicentre, prospective, observational cohort study of paediatric patients (aged <16 yrs) undergoing surgery in 43 government-funded hospitals in South Africa. The primary outcome was the incidence of in-hospital postoperative complications. Results: We recruited 2024 patients at 43 hospitals. The overall incidence of postoperative complications was 9.7% [95% confidence interval (CI): 8.4e11.0]. The most common postoperative complications were infective (7.3%; 95% CI: 6.2e8.4%). In-hospital mortality rate was 1.1% (95% CI: 0.6e1.5), of which nine of the deaths (41%) were in ASA physical status 1 and 2 patients. The preoperative risk factors independently associated with postoperative complications were ASA physcial status, urgency of surgery, severity of surgery, and an infective indication for surgery. Conclusions: The risk factors, frequency, and type of complications after paediatric surgery differ between LMICs and high-income countries. The in-hospital mortality is 10 times greater than in high-income countries. These findings
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...
There is sufficient RCT evidence to suggest that SSCs decrease hospital mortality and surgical outcomes in tertiary and community hospitals. However, randomised evidence of the efficacy of the SSC at rural hospital level is absent.
Background No African countries were included in the development of the Simplified Acute Physiology Score 3 (SAPS 3). This study aimed to assess the performance of the SAPS 3 as a predictor of hospital mortality in patients admitted to a multidisciplinary tertiary intensive care unit (ICU) in South Africa. Methods A prospective cohort study was undertaken in a tertiary single-centre closed multidisciplinary ICU with 16 beds over 12 months in 2017. First time admissions 12 years and over were included. Exclusions were patients who died within six hours of admission, incomplete data sets and unknown outcome after ICU discharge. Demographic data, clinical admission data and co-morbidities were recorded. The SAPS 3 score was calculated within the first hour of ICU admission. The highest Sequential Organ Failure Assessment score, vasopressor use, mechanical ventilation requirements and details of acute kidney injury, if present, were recorded. Discrimination of the model was evaluated using an area under the receiver operating characteristic curve (AUROC) and calibration by the Hosmer-Lemeshow (HL) Goodness of Fit Test (Ĉ and Ĥ statistic). The observed versus the SAPS 3 model predicted mortality ratios were compared and the standardized mortality ratio (SMR) was calculated. Results A total of 829 admissions with a mean SAPS 3 (SD) of 48.1 (16) were included. Of patients with a known human immunodeficiency virus (HIV) status, 32,4% were positive. The ICU and hospital mortality rates were 13.3% and 21.4% respectively. The SAPS 3 model had a AUROC of 0.796 and HLĈ and Ĥ statistics were 12.1 and 11.8 (p-values 0.15 and 0.16).
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