Severe malaria-related disability in African children: a scoping review
Bibliographic record
Abstract
PURPOSE: Disability is a consequence of severe malaria for a significant proportion of African children. This scoping review aims to describe the impact of severe malaria on African children according to current literature using an international biopsychical classification and framework of disability and functioning. MATERIALS AND METHODS: MEDLINE, EMBASE, Global Health, and CINHAL databases were searched for original research conducted on African children aged 0-18 using terms related to severe malaria and components of disability. Independent and dependent variables were extracted and classified using the World Health Organization's International Classification of Functioning, Disability, and Health-Children and Youth version (ICF-CY) using standardized coding methods. RESULTS: Seventy-two percent of the measured variables in the 34 included studies were coded as "body functions," (i.e., impairments), such as mental, neuromusculoskeletal, movement, and sensory functions, and 23.3% of variables were coded as "activities and participation" (i.e., activity limitations/participation restrictions), such as difficulties with general tasks and demands, communication, mobility, interpersonal interactions, and relationships. "Environment" variables such as family support, health access, education, or societal attitudes were not found in the included studies. CONCLUSIONS: Existing peer-reviewed quantitative research of severe malaria-related disability is focused on neurological sequelae, with less research about activity limitations and participation restrictions.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".