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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

2016· article· en· W2554174556 on OpenAlexaff
Madavan Nambiar, Nisanth Menon Nedungalaparambil, O. P. Aslesh

Bibliographic record

VenueWorld Journal of Emergency Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsAlberta Health Services
FundersAmerican Heart Association
KeywordsMedicineBasic life supportAdvanced cardiac life supportHealth professionalsCardiopulmonary resuscitationHealth careResuscitationFamily medicineEmergency medicine

Abstract

fetched live from OpenAlex

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: =0.003) had significantly 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 fibrillation 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.406
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations56
Published2016
Admission routes1
Has abstractyes

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