Fever and neutropenia outcomes and areas for intervention: A report from SUCCOUR ‐ Supportive Care for Children with Cancer in Africa
Bibliographic record
Abstract
Abstract Background Death during paediatric cancer treatment is common in sub‐Saharan Africa. Using the infrastructure of Supportive Care for Children with Cancer in Africa (SUCCOUR), our objective was to describe fever and neutropenia (FN) characteristics and outcomes in order to identify potential areas for future intervention. Methods A multicentre prospective, observational cohort study was conducted in sub‐Saharan Africa. Data were collected from September 2019 to March 2020. Children below 16 years with newly diagnosed cancer treated with curative intent were included. Data were abstracted in real time using standardised case report forms by trained personnel. Characteristics and outcomes of FN during the first 3 months of treatment were documented. Results A total of 252 patients were included (median age 6.0, range 0.2–15.0 years, 54% male). The most common cancer was Burkitt lymphoma (63/252, 25%). Among 104 FN episodes, 21 (21%) were associated with prolonged neutropenia (>1 week) and 32 (31%) were associated with profound neutropenia (absolute neutrophil count <0.1 × 10 9 /L). In 10/104 (10%) episodes, empiric antibiotics were started within 1 hour following fever onset and in 16/104 (15%) episodes, a blood culture was obtained before starting antibiotics. Malaria parasitaemia was detected in four of 104 (4%). A total of 11/104 (11%) patients died in the FN episodes. Conclusions Although in most, FN was not associated with prolonged or profound neutropenia, 11% resulted in death. Areas to target include blood cultures prior to antibiotics and earlier initiation of empiric antibiotics. Future efforts should modify FN practices to reduce treatment‐related mortality.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".