Adherence to Artemisinin Combination Therapy for the treatment of uncomplicated malaria in the Democratic Republic of the Congo
Bibliographic record
Abstract
Between 2011 and 2013 the number of recorded malaria cases had more than doubled, and between 2009 and 2013 had increased almost 4-fold in MSF-OCA (Médecins sans Frontières – Operational Centre Amsterdam) programmes in the Democratic Republic of the Congo (DRC). The reasons for this rise are unclear. Incorrect intake of Artemisinin Combination Therapy (ACT) could result in failure to treat the infection and potential recurrence. An adherence study was carried out to assess whether patients were completing the full course of ACT. One hundred and eight malaria patients in Shamwana, Katanga province, DRC were visited in their households the day after ACT was supposed to be completed. They were asked a series of questions about ACT administration and the blister pack was observed (if available). Sixty seven (62.0%) patients were considered probably adherent. This did not take into account the patients that vomited or spat their pills or took them at the incorrect time of day, in which case adherence dropped to 46 (42.6%). The most common reason that patients gave for incomplete/incorrect intake was that they were vomiting or felt unwell (10 patients (24.4%), although the reasons were not recorded for 22 (53.7%) patients). This indicates that there may be poor understanding of the importance of completing the treatment or that the side effects of ACT were significant enough to over-ride the pharmacy instructions. Adherence to ACT was poor in this setting. Health education messages emphasising the need to complete ACT even if patients vomit doses, feel unwell or their health conditions improve should be promoted.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".