Hypothermia for encephalopathy in low-income and middle-income countries: feasibility of whole-body cooling using a low-cost servo-controlled device
Bibliographic record
Abstract
Although therapeutic hypothermia (TH) is the standard of care for hypoxic ischaemic encephalopathy in high-income countries, the safety and efficacy of this therapy in low-income and middle-income countries (LMICs) is unknown. We aimed to describe the feasibility of TH using a low-cost servo-controlled cooling device and the short-term outcomes of the cooled babies in LMIC. DESIGN: We recruited babies with moderate or severe hypoxic ischaemic encephalopathy (aged <6 hours) admitted to public sector tertiary neonatal units in India over a 28-month period. We administered whole-body cooling (set core temperature 33.5°C) using a servo-controlled device for 72 hours, followed by passive rewarming. We collected the data on short-term neonatal outcomes prior to hospital discharge. RESULTS: Eighty-two babies were included-61 (74%) had moderate and 21 (26%) had severe encephalopathy. Mean (SD) hypothermia cooling induction time was 1.7 hour (1.5) and the effective cooling time 95% (0.08). The mean (SD) hypothermia induction time was 1.7 hour (1.5 hour), core temperature during cooling was 33.4°C (0.2), rewarming rate was 0.34°C (0.16°C) per hour and the effective cooling time was 95% (8%). Twenty-five (51%) babies had gastric bleeds, 6 (12%) had pulmonary bleeds and 21 (27%) had meconium on delivery. Fifteen (18%) babies died before discharge from hospital. Heart rate more than 120 bpm during cooling (P=0.01) and gastric bleeds (P<0.001) were associated with neonatal mortality. CONCLUSIONS: The low-cost servo-controlled cooling device maintained the core temperature well within the target range. Adequately powered clinical trials are required to establish the safety and efficacy of TH in LMICs. CLINICAL TRIAL REGISTRATION NUMBER: NCT01760629.
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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 | 0.002 |
| 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) | 0.001 | 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".