Task-sharing spinal anaesthesia care in three rural Indian hospitals: a non-inferiority randomised controlled clinical trial
Bibliographic record
Abstract
BACKGROUND: Task-sharing of spinal anaesthesia care by non-specialist graduate physicians, termed medical officers (MOs), is commonly practised in rural Indian healthcare facilities to mitigate workforce constraints. We sought to assess whether spinal anaesthesia failure rates of MOs were non-inferior to those of consultant anaesthesiologists (CA) following a standardised educational curriculum. METHODS: We performed a randomised, non-inferiority trial in three rural hospitals in Tamil Nadu and Chhattisgarh, India. Patients aged over 18 years with low perioperative risk (ASA I & II) were randomised to receive MO or CA care. Prior to the trial, MOs underwent task-based anaesthesia training, inclusive of remotely accessed lectures, simulation-based training and directly observed anaesthetic procedures and intraoperative care. The primary outcome measure was spinal anaesthesia failure with a non-inferiority margin of 5%. Secondary outcome measures consisted of incidence of perioperative and postoperative complications. FINDINGS: Between 12 July 2019 and 8 June 2020, a total of 422 patients undergoing surgical procedures amenable to spinal anaesthesia care were randomised to receive either MO (231, 54.7%) or CA care (191, 45.2%). Spinal anaesthesia failure rate for MOs (7, 3.0%) was non-inferior to those of CA (5, 2.6%); difference in success rate of 0.4% (95% CI=0.36-0.43%; p=0.80). Additionally, there were no statistically significant differences observed between the two groups for intraoperative or postoperative complications, or patients' experience of pain during the procedure. INTERPRETATION: This study demonstrates that failure rates of spinal anaesthesia care provided by trained MOs are non-inferior to care provided by CAs in low-risk surgical patients. This may support policy measures that use task-sharing as a means of expanding anaesthesia care capacity in rural Indian hospitals. TRIAL REGISTRATION NUMBER: NCT04438811.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".