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Validation of the naloxone cardiac arrest decision instrument for identifying opioid-associated cardiac arrests

2025· article· en· W4414873071 on OpenAlexaffabout
David Dillon, Katherine S. Allan, Juan Carlos C. Montoy, Mika’il Visanji, Robert M. Rodriguez, Steve Lin, Ralph C. Wang

Bibliographic record

VenueResuscitation · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsMcMaster UniversityToronto Rehabilitation Institute
FundersNational Heart, Lung, and Blood Institute
Keywords(+)-NaloxoneOccultIdentification (biology)Psychological interventionResuscitation

Abstract

fetched live from OpenAlex

BACKGROUND: Up to fifteen percent of out-of-hospital cardiac arrests (OHCAs) are precipitated by occult drug overdose - cases without history or evidence of drug use that are often attributed to a non-overdose cause. The NAloxone Cardiac ARrest Decision Instrument (NACARDI) was derived to help emergency medical service (EMS) providers rapidly identify patients at higher risk of occult opioid-associated (OA)-OHCAs during resuscitation. In this analysis we externally validate NACARDI in an independent cohort of OHCA patients. METHODS: We conducted a retrospective validation using data from EMS-attended OHCA patients and coroner records in Ontario, Canada between 2020-2021. Inclusion criteria were age ≥18 years and OHCA death with a coroner record. Exclusion criteria were EMS-suspected drug overdose or known cause of the OHCA. NACARDI consists of two criteria: patient age and unwitnessed cardiac arrest. Two cut-offs for patient age were assessed for this validation: <50 years (NACARDI-50) and <60 years (NACARDI-60). The primary outcome was coroner adjudicated cause of death. We calculated screening characteristics and receiver operating characteristic (ROC) curves using standard formulae. RESULTS: Of 2904 OHCA cases without an obvious cause, 791 had coroner evaluations and 121 (15.3 %) were adjudicated as occult OA-OHCA. NACARDI-60 had: sensitivity 82.6 % (95 %CI 74.9-88.4 %), specificity 77.1 % (95 %CI 73.8-80.1 %), negative predictive value 96.1 % (95 %CI 94.1-97.4 %), and positive predictive value 39.4 % (95 %CI 33.6-45.5 %). NACARDI-50 had: sensitivity 63.6 % (95 %CI 54.4-72.2 %), specificity 89.3 % (95 %CI 86.7-91.5 %), negative predictive value 93.2 % (95 %CI 90.9-95.0 %), and positive predictive value 51.7 % (95 %CI 43.4-59.9 %). ROC curves for both NACARDI-50 and NACARDI-60 demonstrated excellent discrimination for occult OA-OHCA. CONCLUSION: In this external validation cohort, NACARDI had a sensitivity and specificity sufficiently high to aid in the real-time identification of occult OA-OHCA in the field. NACARDI has the potential to guide targeted interventions for OA-OHCA.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.104
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.313
Teacher spread0.292 · 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 source (direct Gemma or distilled Codex), 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".

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Citations5
Published2025
Admission routes2
Has abstractyes

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