Mortality and its Predictors among children on Antiretroviral treatment in Ethiopia: A systematic review and Meta –analysis
Bibliographic record
Abstract
Abstract Background: It is well known that antiretroviral therapy (ART) decrease the progress of acquired immune deficiency syndrome (AIDS) related morbidity and mortality and helps the progress towards achieving the United Nations Program on HIV/ AIDS(UNAIDS) treatment goals. Despite this, mortality in Ethiopia becomes public health concern, and variance is observed across studies. With this gap, there is no pooled estimate. Thus, the goal of this study was to assess the pooled mortality and its predictors among antiretroviral treated HIV/AIDS patients.Methods: PubMed, Scopus and Google Scholar databases were used to search articles. The quality of studies was assessed using the Newcastle Ottawa quality assessment scale. The funnel plot and Egger's test were performed to confirm the presence of publication bias. Heterogeneity across studies was evaluated using the I2 statistic. The pooled incidence rate and its predictors were estimated using a weighted inverse variance random-effects model. Subgroup analysis and sensitivity analysis were also performed. Results: In this review, 12 studies with the cohort size of 4,935 were included. The overall incidence of mortality rate was 6.02 (95% CI: 3.7, 8.2) per 100 person-years. A higher incidence of mortality was observed (12.51% (95%CI: 0.32, 24.7)) in south nation nationality and Peoples (SNNP) on subgroup analysis. Being advanced world health organization(WHO) clinical stage (AHR:5.34( 95% CI: 3.1,9.2.6)), lower CD4 cell count (AHR :2.46 (95 %CI: 1.8, 3.2)), anemia (AHR :2.76 (95% CI: 1.9,3.9)), and nutritional status (AHR :1.9 (95%CI: 1.3, 2.6)) were major predictors of mortality. In contrast, cotrimoxazole preventive therapy (CPT) (AHR: 0.34, (95% CI 0.05, 0.63)) reduced mortality.Conclusions: In Ethiopia, the incidence of mortality was high. Lower CD4 cell count, anemia, WHO clinical staging (III/IV), and undernutrition were the contributing factors. But cotrimoxazole preventive therapy had a high effect on mortality reduction. Therefore, an earlier management would be started before advancing signs of acquired immune deficiency syndrome (AIDS) regardless of WHO staging, CD4 cell level, and nutritional status.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.025 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".