Reported recreational drug and new psychoactive substance use versus laboratory detection of substances by high-resolution mass spectrometry in patients presenting to an emergency department in London with acute drug toxicity
Notice bibliographique
Résumé
INTRODUCTION: Clinicians managing patients with acute recreational drug or new psychoactive substance toxicity typically depend on self-reported drug(s) used. This study compares patient self-report (and/or from other sources) to the substance(s) that were subsequently identified in serum. METHODS: A prospective sample of 1,000 adults presenting to a tertiary care, urban emergency department in London, United Kingdom, with acute recreational drug/new psychoactive substance toxicity was collected from 1 February 2019 to 2 February 2020. A total of 939 appropriate samples underwent qualitative analysis by high-resolution mass spectrometry with comparison to a database of drugs/metabolites. Data on the stated drug(s) used were extracted from the routine medical chart/records; results were batched by drug class, when appropriate, and analysis was performed using R software. RESULTS: Seven hundred and ninety-nine (85.1%) patients were male with a median (IQR) age of 34 years (27 to 42 years). Six hundred and thirty-five (67.6%) patients reported using two or more drugs. The median (IQR) positive predictive value of a self-report substance having been taken was 0.68 (IQR: 0.44-0.86); conversely, the median negative predictive value of a substance having not been taken was 0.90 (IQR: 0.53-0.95). There was variability in the accuracy of reporting. For example, self-reported opioid use had a 90.5% likelihood that opioids were detected on analysis, whereas hallucinogens were only detected in 18.8% of samples when use was reported. Individuals were also mostly accurate in not underreporting substances. For example, those not explicitly reporting gamma-hydroxybutyrate use were 97.5% truly negative. DISCUSSION: Overall, most users were relatively accurate in their self-report of what class of drugs they had used, although there was variability in this accuracy. However, other drugs were present even when not reported, for example, opioids with disproportionate detection of prescription and over-the-counter (non-prescription) opioids that were unreported. CONCLUSIONS: Self-report (and/or collateral reports) had overall relatively high concordance with the likelihood that a substance was, or was not, recently used. Therefore, clinicians can make initial treatment decisions based on the self-reported drug(s) used in most cases.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».