Trends in severe acute malnutrition admissions, characteristics, and treatment outcomes in Malawi from 2011 through 2019
Bibliographic record
Abstract
Background: Community-based Management of Acute Malnutrition (CMAM) has been successfully implemented across Malawi, yet trends in admissions, characteristics, and treatment outcomes in children with severe acute malnutrition (SAM) have not been examined. The objective was therefore to investigate trends in admissions, characteristics including percentage of children with SAM with HIV and oedema, and treatment outcomes across the decade following implementation of CMAM. Methods: This research involved a retrospective analysis of existing data routinely collected across Malawi by the Ministry of Health between 2011 and 2019. Results: These data showed an increase in outpatient therapeutic feeding (OTP) admissions from 30323 children in 2011 to 37655 in 2019 (p=0.045). However, a significant decrease in nutritional rehabilitation unit (NRU) admissions was observed, from 11389 annual admissions in 2011 to 6271 in 2019 (p=0.006). In children identified with SAM, the percentage with oedema decreased in OTPs with an average annual rate of reduction (AARR) of 5.6% (p=0.001) and by 26.2% in NRUs in this timeframe with an AARR of 8.5% (p<0.001). The percentage of children with SAM who had HIV decreased over time in OTPs with an AARR of 16.1% (p=0.001). HIV rates also decreased in NRUs with an AARR of 7.2% (p=0.4), but this difference was not significant. Death rates decreased in OTPs with an AARR of 6.0% (p=0.01). Mortality rates did not change in NRUs over time with an AARR of 0.9% (p=0.5) with the NRU mortality rate in 2019 being 11.0%. Conclusions: These trends indicate that there has been an increase in OTP admissions and a corresponding decrease in NRU admissions. There have been decreases in the percentage of children with oedematous SAM in OTPs and in NRUs and with HIV in OTPs. Children remain at high risk of mortality in NRUs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".