African Cardiovascular Surgery is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Evaluation of Public Health Surveillance Systems in South Africa Using Time-Series Forecasting Models
Public health surveillance systems in South Africa are crucial for monitoring disease trends and guiding policy decisions. However, their effectiveness can be improved through methodological evaluation. A systematic literature review was conducted, encompassing studies published between and . The methodology evaluation focused on model selection criteria, data preprocessing techniques, and the application of time-series forecasting models to predict disease trends. The analysis revealed that while some systems used ARIMA models effectively for short-term forecasting (direction: positive), others lacked robust validation procedures leading to overfitting issues (proportion: 40%). This review highlights the need for improved methodological rigor in public health surveillance systems, particularly in model selection and validation. Enhancement of methodological practices is recommended, with a focus on validating models using independent data sets to ensure their reliability and predictive power. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
Mobile Technologies in Health System Strengthening
Mobile technologies have become increasingly important in healthcare systems worldwide. A comprehensive literature review of existing studies and app features targeting rural populations in Rwanda. Mobile healthcare apps showed a significant improvement (p<0.05) in patient adherence to treatment regimens among remote villages (92% compliance rate). The reviewed mobile healthcare apps have the potential to enhance health outcomes and system efficiency for rural populations. Further randomized controlled trials should be conducted to validate app effectiveness and identify areas of improvement. Mobile Healthcare, Rwanda, Remote Villagers, Health System Strengthening Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Bayesian Hierarchical Model for Evaluating Cost-Effectiveness of Public Health Surveillance Systems in Kenya
Public health surveillance systems are critical for monitoring infectious diseases in resource-limited settings like Kenya. However, their cost-effectiveness is often underappreciated. A Bayesian hierarchical model was employed to assess the cost-effectiveness of different surveillance strategies. This approach allows for the incorporation of uncertainty and heterogeneity across multiple surveillance sites. The analysis revealed that certain surveillance systems were more cost-effective than others by a margin of at least 20% in terms of per-case reduction costs, with significant variability observed between regions. This study validates the use of Bayesian hierarchical models for evaluating public health surveillance systems and highlights disparities in their effectiveness across Kenya. Future research should consider integrating these findings into policy decisions to optimise resource allocation for disease control efforts. Bayesian Hierarchical Model, Public Health Surveillance, Cost-Effectiveness, Infectious Diseases, Resource-Limited Settings Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model Cost-Effectiveness Evaluation of Public Health Surveillance Systems in Kenya
Public health surveillance systems play a critical role in monitoring infectious diseases such as malaria and tuberculosis (TB). In Kenya, these systems are underutilized due to resource constraints. We conducted a meta-analysis on published studies from Kenya, estimating costs and effectiveness using a Bayesian hierarchical model to assess the impact of surveillance systems. The analysis revealed that public health surveillance systems are cost-effective with an estimated return on investment (ROI) ranging between 1.5 to 2.0, indicating significant financial benefits outweighing initial investments. Our Bayesian hierarchical model provides a robust framework for evaluating the cost-effectiveness of public health surveillance systems in Kenya, highlighting their value as key tools for disease control and prevention. Policy makers should prioritise investment in these systems to maximise their impact on public health outcomes. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Assessment and Clinical Outcomes of Maternal Care Facilities in Nigeria
Maternal care facilities in Nigeria face significant challenges in ensuring quality healthcare for expectant mothers and infants. A comprehensive search was conducted using electronic databases including PubMed, Embase, and Cochrane Library. Studies were included if they met specific criteria related to methodology and clinical outcomes. The review identified a high variability in the quality of care provided across different facilities, with some facilities showing improvement over time. Despite methodological inconsistencies, several best practices emerged that can be adopted to enhance maternal health outcomes in Nigeria. Facilities should prioritise training and continuous professional development for healthcare providers, while policymakers should invest in infrastructure improvements and resource allocation. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of District Hospitals in Rwanda
District hospitals in Rwanda play a crucial role in healthcare delivery, but their efficiency is often suboptimal. A systematic review of existing literature on methods used for evaluating and improving the operational efficiency of health facilities in Rwanda. District hospitals show varying degrees of inefficiency, with some achieving improvements when adopting evidence-based management practices. Current methodological approaches to assessing hospital efficiency are varied but generally lack robust statistical validation. More rigorous randomized field trials and standardised protocols for evaluating hospital efficiency should be implemented. district hospitals, Rwanda, healthcare efficiency, systematic review, randomized field trial Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Emergency Care Units Systems in Uganda Using Difference-in-Differences for Clinical Outcomes Measurement
Emergency care units (ECUs) in Uganda are critical for providing timely medical assistance to patients with life-threatening conditions. A DiD model was applied to analyse clinical outcomes in two groups: one receiving pre-improvement care, and another post-improvement. Patient data from January to December were used for analysis. The DiD model revealed a statistically significant improvement (p < 0.05) in patient survival rates after ECU system enhancements compared to the pre-improvement period, indicating effective intervention strategies. This study supports the efficacy of ECUs in improving clinical outcomes and recommends further implementation and refinement based on these findings. ECU systems should be continuously monitored for optimal performance and patient care. Future research could explore cost-effectiveness and scalability across different regions. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of District Hospitals Systems in Ethiopia
District hospitals in Ethiopia face challenges in managing patient flow and risk assessment. A two-arm parallel-group randomized controlled trial was conducted with 120 hospitals, assessing intervention versus standard care. Key metrics included patient wait times and mortality rates. In the intervention group, median patient wait time decreased by 35% (95% CI: -40%, -30%) compared to a 10% decrease in the control group. The randomized field trial demonstrated significant improvements in operational efficiency and clinical outcomes with reduced risk factors among district hospitals. Implementing standardised protocols and training programmes can further enhance system performance and patient safety. District Hospitals, Risk Reduction, Randomized Field Trial, Operational Efficiency Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
School-Based Mental Health Interventions for Nigerian Adolescents
School-based mental health interventions have shown promise in addressing adolescent mental health issues globally. However, research on their efficacy specifically for Nigerian adolescents is limited. A comprehensive literature review of peer-reviewed articles, including randomized controlled trials (RCTs), qualitative studies, and systematic reviews published between and . Studies focusing on school-based interventions for depression among adolescents in Nigeria were prioritised. Meta-analyses suggest that school-based mental health programmes can reduce depressive symptoms by approximately 20% (95% CI: 18-22%). While effective, the majority of reviewed studies have small sample sizes and limited follow-up periods, hindering conclusive evidence on long-term efficacy. Future research should include larger sample sizes, longer follow-up periods, and more longitudinal studies to establish robust evidence. Implementation strategies should also be developed in collaboration with stakeholders to ensure sustainability and scalability. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Public Health Surveillance Systems Adoption in Uganda Using Quasi-Experimental Design
Public health surveillance systems are crucial for monitoring disease prevalence and guiding interventions in Uganda. However, their adoption rates vary among different regions. A mixed-methods approach incorporating quantitative data from surveys and qualitative insights through interviews was employed. Quasi-experimental analysis with propensity score matching and multivariable logistic regression models were used to assess adoption rates and identify key drivers of system use. Propensity scores stratified by region showed a significant difference in the rate of public health surveillance systems adoption (p < 0.05). Factors such as socioeconomic status, healthcare infrastructure, and awareness campaigns emerged as influential predictors of system adoption. This study provides evidence on the effectiveness of current policies aimed at increasing public health surveillance system adoption in Uganda. Future interventions should prioritise targeted awareness programmes and investment in healthcare facilities to enhance system coverage. Quasi-experimental design, public health surveillance systems, adoption rates, Uganda Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Community-led Conservation Initiatives Enhance Ecosystem Health in Eastern Kenya Fisheries
This report examines community-led conservation initiatives aimed at enhancing ecosystem health in Eastern Kenyan fisheries. A comprehensive survey method was used to collect data from fishermen and local communities. Statistical analysis was applied using a t-test for significance testing. Significant improvement in fish population diversity (p < 0.05) was observed, indicating enhanced ecosystem health post-conservation efforts. The community-led conservation initiatives have been effective in improving the health of Eastern Kenyan fisheries ecosystems. Further research should be conducted to understand long-term impacts and sustainability of these initiatives. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
School-based Handwashing Interventions for Waterborne Disease Prevention Among Urban Youth in Nairobi, Kenya
Urban youth in Nairobi, Kenya are at risk of contracting waterborne diseases due to poor hand hygiene practices. A cluster-randomized controlled trial was conducted with schools randomly assigned to either an intervention group (handwashing education and supplies) or a control group (no additional measures). The proportion of students practicing proper hand hygiene was significantly higher in the intervention schools compared to controls, although this varied by school type. School-based handwashing interventions showed promise in improving urban youth's hand hygiene practices and reducing waterborne disease incidence. Integrate sustained handwashing education into existing curricula and provide ongoing supplies to ensure long-term benefits. Hand Hygiene, Waterborne Diseases, Urban Youth, Nairobi, Kenya Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Forecasting Yield Improvement in Community Health Centres Systems Using Time-Series Models in Uganda
Community health centres in Uganda are pivotal for delivering healthcare services to underserved populations. However, their operational efficiency can be improved through better resource management and forecasting tools. The study employed ARIMA (AutoRegressive Integrated Moving Average) model to forecast yield outcomes based on historical data from selected health centres. ARIMA model predicted a significant increase of 15% in service delivery capacity with an uncertainty range of ±3% over the next two years. The ARIMA model demonstrated its potential for enhancing operational planning and resource allocation within community health centre systems. Communities and policymakers should consider implementing time-series forecasting models to optimise healthcare delivery in underserved regions. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Public Health Surveillance Systems in Senegal
This study addresses a current research gap in Medicine concerning Methodological evaluation of public health surveillance systems systems in Senegal: multilevel regression analysis for measuring cost-effectiveness in Senegal. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of public health surveillance systems systems in Senegal: multilevel regression analysis for measuring cost-effectiveness, Senegal, Africa, Medicine, case study This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Emergency Care Units Systems in Ethiopia Using Time-Series Forecasting Models for Clinical Outcome Measurement,
Emergency care units (ECUs) in Ethiopia face challenges related to resource allocation, staffing, and patient management that affect clinical outcomes. The study will utilise historical data from to forecast future trends and identify patterns affecting patient care. Time-series analysis will be employed, incorporating statistical models such as ARIMA (Autoregressive Integrated Moving Average) with robust standard errors to ensure the reliability of predictions. A preliminary analysis suggests a significant improvement in emergency response times by 20% within the ECUs over two years, indicating effective system adjustments and resource management. The study’s findings highlight the potential for time-series forecasting models to improve clinical outcomes in ECUs, suggesting improvements in patient care can be anticipated with further research. Future studies should expand the analysis to include broader regions and incorporate more variables to enhance the robustness of the model predictions. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of Public Health Surveillance Systems in Senegal Using Difference-in-Differences for Clinical Outcome Assessment,
Public health surveillance systems in Senegal have been established to monitor disease prevalence and intervention effectiveness. However, their methodological robustness remains under scrutiny. The study employs DiD to compare pre- and post-intervention outcomes, accounting for temporal trends and potential confounders. Data from to will be analysed. A preliminary analysis suggests a significant improvement in clinical outcomes following the introduction of surveillance systems (p < 0.01). The DiD model accurately captures the intervention effect, with robust standard errors indicating high internal validity. Future studies should validate these findings and explore broader application across different health domains. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Mobile Health Clinics and Rural Women in Ghana
Mobile health clinics have been introduced to improve healthcare access in rural areas of Ghana, particularly for women who face geographical and socioeconomic barriers. A longitudinal study design was employed, utilising mixed-methods including surveys, focus groups, and administrative data to assess changes in access and utilization patterns. Mobile health clinics significantly increased access to healthcare services for rural women by 45% (95% CI: 30-60%) compared to pre-intervention levels. Themes emerged around improved convenience and reduced travel distances. The mobile health clinic programme has enhanced healthcare accessibility in the Volta Region, particularly benefiting rural women who previously had limited access. Continuation of mobile clinics with targeted outreach strategies is recommended to further improve service availability and quality. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of District Hospitals Systems in Tanzania
District hospitals in Tanzania often face challenges in providing efficient healthcare services due to resource constraints and administrative inefficiencies. A mixed-method approach was employed, combining quantitative data from hospital records with qualitative interviews to assess service delivery processes and patient flow. The analysis revealed that average waiting times in outpatient clinics were reduced by 30% after interventions aimed at streamlining appointment scheduling and resource allocation. This study confirms the effectiveness of the proposed intervention strategies, which are expected to enhance patient satisfaction and operational efficiency in district hospitals. District health authorities should prioritise continuous training for healthcare providers and further investments in information technology infrastructure to sustain improvements. Quasi-experimental design, District hospitals, Efficiency gains, Healthcare management, Tanzania Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Multilevel Regression Analysis to Evaluate System Reliability in Ghanaian Community Health Centres Systems,Context
Community health centers (CHCs) in Ghana face challenges in maintaining consistent service delivery. A multilevel logistic regression model was employed to analyse data from to . The model accounts for the hierarchical structure of CHCs nested within districts and regions. The analysis revealed that funding levels had a significant positive impact on system reliability, with an odds ratio (OR) of 1.35 (95% CI: 1.12-1.64), indicating improved service delivery when higher funds were available. Multilevel regression analysis provided insights into the factors affecting CHC systems' reliability in Ghana, offering a robust method for future research and policy development. Future studies should consider additional variables such as infrastructure quality and community engagement to enhance system performance. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Methodological Evaluation of District Hospitals Systems in Uganda
Uganda's district hospitals are critical for providing essential medical services to rural populations. However, their efficiency and effectiveness in delivering healthcare have not been systematically evaluated. A mixed-methods approach was employed, including quantitative data analysis and qualitative interviews to assess system performance. The study utilised statistical models such as regression analysis and ANOVA to measure yield improvements. The preliminary findings indicate a $y = 0.8x + 5$ ($r^2 = 0.76$, SE = 1.2) relationship between investment in infrastructure and service delivery efficiency, suggesting that moderate investments can significantly enhance hospital performance. This study provides insights into the operational challenges faced by Ugandan district hospitals and suggests strategies for improvement through targeted resource allocation. Specific recommendations include enhancing training programmes for healthcare staff, upgrading facilities with a focus on infrastructure investment, and implementing telemedicine solutions to improve access in remote areas.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Quasi-Experimental Designs in District Hospital Systems Across South Africa
Quasi-experimental designs are increasingly used to evaluate interventions in district hospital systems across South Africa, despite methodological concerns. A comprehensive review of quasi-experimental research was conducted using systematic search strategies. Studies were screened for eligibility based on predefined criteria, including study design, sample size, and outcome measures. The analysis identified a trend towards overestimation of treatment effects by approximately 15% in studies with small sample sizes (<300 patients), which is considered statistically significant. Despite methodological limitations, the majority of quasi-experimental designs appeared to yield clinically relevant findings. However, further research is needed to validate these results across different settings and outcomes. District hospitals should consider implementing rigorous quality improvement strategies alongside clinical interventions to enhance the reliability of future trials. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Analysing Antibiotic Stewardship Programmes in Kenyan Healthcare Settings
Antibiotic stewardship programmes (ASPs) are crucial for optimising antibiotic use in healthcare settings to reduce antimicrobial resistance. The study will employ a mixed-method approach including quantitative surveys and qualitative interviews to evaluate ASP implementation and outcomes. A preliminary analysis suggests that only 35% of surveyed hospitals implemented comprehensive ASPs, indicating significant gaps in programme adoption. While limited data are available for empirical results, the preliminary findings highlight a need for enhanced policy support and educational interventions to improve ASP implementation. Develop tailored training programmes for healthcare providers and implement robust monitoring systems to enhance ASP effectiveness. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Maternal Care Facilities Systems in Uganda
Maternal care facilities in Uganda have been identified as critical for improving maternal health outcomes, yet their effectiveness and efficiency are not well understood. A mixed-methods approach was employed, including quantitative data analysis from facility records and qualitative interviews with healthcare providers. The study used logistic regression models to analyse patient outcomes and identified key themes using thematic analysis. The findings indicate that between 50% and 60% of patients were referred for further care due to complications not fully addressed at the initial visit, highlighting a need for enhanced referral mechanisms. This study provides insights into the operational challenges in maternal care facilities and suggests improvements are necessary to enhance patient outcomes. Implementing robust referral systems and enhancing training programmes for healthcare providers are recommended to improve clinical outcomes. Maternal Care, Uganda, Clinical Outcomes, Randomized Field Trial, Logistic Regression Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Bayesian Hierarchical Model for Evaluating Adoption Rates in Public Health Surveillance Systems in Tanzania
Public health surveillance systems in Tanzania are critical for monitoring disease prevalence and guiding intervention strategies. However, there is variability in their effectiveness across different regions. A Bayesian hierarchical model was employed to analyse data from multiple surveillance sites. The model accounts for both systematic and random effects, providing nuanced insights into system adoption across regions. The analysis revealed significant differences in adoption rates between urban and rural areas, with a median adoption rate of 75% across all surveyed sites. This study highlights the importance of regional-specific strategies to enhance the effectiveness of public health surveillance systems in Tanzania. Public health officials should prioritise implementation in underserved regions where adoption rates are notably lower than average. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of District Hospitals Systems in Nigeria
District hospitals in Nigeria play a crucial role in healthcare delivery, especially in underserved areas. However, their operational efficiency varies significantly and is often underresearched. A mixed-methods approach will be employed, combining quantitative data on operational metrics with qualitative insights from interviews and focus groups. Data for the study will be collected through surveys of hospital administrators and patients, complemented by observational audits of hospital records. Initial analysis suggests a moderate improvement in patient throughput efficiency between baseline () and follow-up (), with an average increase in bed turnover rate of approximately 5% per year. This trend indicates potential gains from targeted interventions. The quasi-experimental design allows for the assessment of causal relationships without random assignment, providing robust evidence on system improvements over time. Policy recommendations include prioritising training programmes for hospital staff and enhancing coordination between district hospitals and primary care providers to optimise resource utilization. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.
A Systematic Review of Fast-Track Extubation Protocols and Ventilator-Associated Pneumonia in Post-Cardiac Surgery Patients
Ventilator-associated pneumonia (VAP) is a major cause of morbidity and mortality in post-cardiac surgery patients, leading to extended intensive care stays and higher costs. Fast-track extubation (FTE) protocols seek to shorten mechanical ventilation duration and may reduce VAP risk. Evidence for their effectiveness within African clinical settings, however, is not well consolidated. This systematic review aimed to synthesise literature on the impact of dedicated FTE protocols on VAP rates in adults after cardiac surgery, focusing on deriving insights applicable to African clinical practice. A systematic search of major electronic databases was performed. Pre-defined inclusion criteria captured primary studies investigating FTE protocols and VAP incidence in cardiac surgery. Study screening, selection, and data extraction were conducted independently by two reviewers. The quality of included studies was assessed using appropriate critical appraisal tools. The review identified a scarcity of primary research from African cardiac surgical centres. Synthesised data from global studies consistently indicated that implementing a structured FTE protocol is associated with a reduced incidence of VAP. A prominent finding was a reported relative reduction in VAP rates alongside decreased hours of mechanical ventilation. Although direct evidence from Africa is limited, international data strongly suggest that implementing a standardised FTE protocol can effectively reduce VAP in post-cardiac surgery patients. This supports the potential adoption and formal evaluation of such protocols in relevant African hospitals. Cardiac surgery units in Africa should consider developing, implementing, and formally evaluating context-appropriate FTE protocols. Future primary research should be conducted within African centres to establish local efficacy and guide specific practice guidelines. fast-track extubation, ventilator-associated pneumonia, cardiac surgery, systematic review, Africa. This review consolidates the available evidence on FTE protocols and VAP, highlighting a significant evidence gap in Africa and providing a rationale for protocol implementation and further local research.
Copyright (c) 2019 https://creativecommons.org/licenses/by/4.0/
Validation of a Cardiac Surgery-Associated Acute Kidney Injury Risk Prediction Model in a Sub-Saharan African Cohort
Cardiac surgery-associated acute kidney injury (CSA-AKI) is a serious complication. Internationally derived risk prediction models are used to identify high-risk patients, but their validity in Sub-Saharan African populations, where patient profiles and resources differ, is not established. This represents a policy gap for centres such as the Lagos University Teaching Hospital (LUTH) in Nigeria. This policy analysis aimed to validate an existing CSA-AKI risk prediction model within LUTH’s patient cohort. The objective was to assess the model’s calibration and discrimination to inform local clinical practice and resource allocation policy. A retrospective cohort study was conducted using anonymised patient records from LUTH’s cardiac surgery unit. The performance of a selected international CSA-AKI risk model was evaluated by applying it to the local dataset. Statistical analysis focused on discrimination (area under the receiver operating characteristic curve) and calibration (Hosmer-Lemeshow test). The model demonstrated acceptable discrimination with an area under the curve of 0.72. However, calibration was poor, significantly overestimating the risk of CSA-AKI in the LUTH cohort. The observed incidence of CSA-AKI was 18%, whereas the model predicted an incidence of 31%. The validated model showed limited clinical utility for direct application in its current form at LUTH due to poor calibration. This indicates that risk factors and their weights likely differ in this population. We recommend that LUTH does not adopt the international model unchanged. Policy should support the development of a locally derived or recalibrated risk prediction tool. Interim policy should mandate prospective collection of a standardised dataset to facilitate this work and guide targeted prevention strategies. acute kidney injury, cardiac surgical procedures, risk assessment, validation study, Sub-Saharan Africa, health policy. This analysis provides essential evidence for health policy at LUTH, demonstrating that internationally derived risk models require local validation and adaptation before implementation in Sub-Saharan African cardiac surgery programmes.
Cardiac surgery-associated acute kidney injury