Is current training in basic and advanced cardiac life support (BLS & ACLS) effective? A study of BLS & ACLS knowledge amongst healthcare professionals of North-Kerala
Bibliographic record
Abstract
BACKGROUND: Healthcare professionals are expected to have knowledge of current basic and advanced cardiac life support (BLS/ACLS) guidelines to revive unresponsive patients. METHODS:A cross-sectional study was conducted to evaluate the current practices and knowledge of BLS/ACLS principles among healthcare professionals of North-Kerala using pretested self-administered structured questionnaire.Answers were validated in accordance with American Heart Association's BLS/ ACLS teaching manual and the results were analysed.RESULTS: Among 461 healthcare professionals, 141 (30.6%) were practicing physicians, 268 (58.1%) were nurses and 52 (11.3%) supporting staff.The maximum achievable score was 20 (BLS 15/ ACLS 5).The mean score amongst all healthcare professionals was 8.9±4.7.The mean score among physicians, nurses and support staff were 8.6±3.4,9±3.6 and 9±3.3 respectively.The majority of healthcare professionals scored ≤50% (237, 51.4%); 204 (44.3%) scored 51%-80% and 20 (4.34%) scored >80%.Mean scores decreased with age, male sex and across occupation.Nurses who underwent BLS/ACLS training previously had significantly higher mean scores (10.2±3.4)than untrained (8.2±3.6,P=0.001).Physicians with <5 years experience (P=0.002) and nurses in the private sector (P=0.003) had signifi cantly higher scores.One hundred and sixty three (35.3%)healthcare professionals knew the correct airway opening manoeuvres like head tilt, chin lift and jaw thrust.Only 54 (11.7%) respondents were aware that atropine is not used in ACLS for cardiac arrest resuscitation and 79 (17.1%) correctly opted ventricular fi brillation and pulseless ventricular tachycardia as shockable rhythms.The majority of healthcare professionals (356, 77.2%) suggested that BLS/ACLS be included in academic curriculum. CONCLUSION:Inadequate knowledge of BLS/ACLS principles amongst healthcare professionals, especially physicians, illuminate lacunae in existing training systems and merit urgent redressal.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".