Identifying Life-Threatening Admissions for Drug Dependence or Abuse (ILIADDA): Derivation and Validation of a Model.

Tri Long Nguyen; Thierry Boudemaghe; Géraldine Leguelinel-Blache; Céline Eiden; Jean Marie Kinowski; Yannick Le Manach; Hélène Peyrière; Paul Landais

doi:10.1038/srep44428

Identifying Life-Threatening Admissions for Drug Dependence or Abuse (ILIADDA): Derivation and Validation of a Model.

Tri Long Nguyen^*, Thierry Boudemaghe, Géraldine Leguelinel-Blache, Céline Eiden, Jean Marie Kinowski, Yannick Le Manach, Hélène Peyrière, Paul Landais

^*Corresponding author for this work

5 Citations (Scopus)

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Abstract

Given that drug abuse and dependence are common reasons for hospitalization, we aimed to derive and validate a model allowing early identification of life-Threatening hospital admissions for drug dependence or abuse. Using the French National Hospital Discharge Data Base, we extracted 66,101 acute inpatient stays for substance abuse, dependence, mental disorders or poisoning associated with medicines or illicit drugs intake, recorded between January 1 st, 2009 and December 31 st, 2014. We split our study cohort at the center level to create a derivation cohort and a validation cohort. We developed a multivariate logistic model including patient's age, sex, entrance mode and diagnosis as predictors of a composite primary outcome of in-hospital death or ICU admission. A total of 2,747 (4.2%) patients died or were admitted to ICU. The risk of death or ICU admission was mainly associated with the consumption of opioids, followed by cocaine and other narcotics. Particularly, methadone poisoning was associated with a substantial risk (OR: 35.70, 95% CI [26.94-47.32], P < 0.001). In the validation cohort, our model achieved good predictive properties in terms of calibration and discrimination (c-statistic: 0.847). This allows an accurate identification of life-Threatening admissions in drug users to support an early and appropriate management.

Original language	English
Article number	44428
Journal	Scientific Reports
Volume	7
ISSN	2045-2322
DOIs	https://doi.org/10.1038/srep44428
Publication status	Published - 2017
Externally published	Yes

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Identifying Life-Threatening Admissions for Drug Dependence or Abuse (ILIADDA)Final published version, 591 KBLicence: CC BY

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title = "Identifying Life-Threatening Admissions for Drug Dependence or Abuse (ILIADDA): Derivation and Validation of a Model.",

abstract = "Given that drug abuse and dependence are common reasons for hospitalization, we aimed to derive and validate a model allowing early identification of life-Threatening hospital admissions for drug dependence or abuse. Using the French National Hospital Discharge Data Base, we extracted 66,101 acute inpatient stays for substance abuse, dependence, mental disorders or poisoning associated with medicines or illicit drugs intake, recorded between January 1 st, 2009 and December 31 st, 2014. We split our study cohort at the center level to create a derivation cohort and a validation cohort. We developed a multivariate logistic model including patient's age, sex, entrance mode and diagnosis as predictors of a composite primary outcome of in-hospital death or ICU admission. A total of 2,747 (4.2%) patients died or were admitted to ICU. The risk of death or ICU admission was mainly associated with the consumption of opioids, followed by cocaine and other narcotics. Particularly, methadone poisoning was associated with a substantial risk (OR: 35.70, 95% CI [26.94-47.32], P < 0.001). In the validation cohort, our model achieved good predictive properties in terms of calibration and discrimination (c-statistic: 0.847). This allows an accurate identification of life-Threatening admissions in drug users to support an early and appropriate management.",

author = "Nguyen, {Tri Long} and Thierry Boudemaghe and G{\'e}raldine Leguelinel-Blache and C{\'e}line Eiden and Kinowski, {Jean Marie} and {Le Manach}, Yannick and H{\'e}l{\`e}ne Peyri{\`e}re and Paul Landais",

year = "2017",

doi = "10.1038/srep44428",

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T1 - Identifying Life-Threatening Admissions for Drug Dependence or Abuse (ILIADDA)

T2 - Derivation and Validation of a Model.

AU - Nguyen, Tri Long

AU - Boudemaghe, Thierry

AU - Leguelinel-Blache, Géraldine

AU - Eiden, Céline

AU - Kinowski, Jean Marie

AU - Le Manach, Yannick

AU - Peyrière, Hélène

AU - Landais, Paul

PY - 2017

Y1 - 2017

N2 - Given that drug abuse and dependence are common reasons for hospitalization, we aimed to derive and validate a model allowing early identification of life-Threatening hospital admissions for drug dependence or abuse. Using the French National Hospital Discharge Data Base, we extracted 66,101 acute inpatient stays for substance abuse, dependence, mental disorders or poisoning associated with medicines or illicit drugs intake, recorded between January 1 st, 2009 and December 31 st, 2014. We split our study cohort at the center level to create a derivation cohort and a validation cohort. We developed a multivariate logistic model including patient's age, sex, entrance mode and diagnosis as predictors of a composite primary outcome of in-hospital death or ICU admission. A total of 2,747 (4.2%) patients died or were admitted to ICU. The risk of death or ICU admission was mainly associated with the consumption of opioids, followed by cocaine and other narcotics. Particularly, methadone poisoning was associated with a substantial risk (OR: 35.70, 95% CI [26.94-47.32], P < 0.001). In the validation cohort, our model achieved good predictive properties in terms of calibration and discrimination (c-statistic: 0.847). This allows an accurate identification of life-Threatening admissions in drug users to support an early and appropriate management.

AB - Given that drug abuse and dependence are common reasons for hospitalization, we aimed to derive and validate a model allowing early identification of life-Threatening hospital admissions for drug dependence or abuse. Using the French National Hospital Discharge Data Base, we extracted 66,101 acute inpatient stays for substance abuse, dependence, mental disorders or poisoning associated with medicines or illicit drugs intake, recorded between January 1 st, 2009 and December 31 st, 2014. We split our study cohort at the center level to create a derivation cohort and a validation cohort. We developed a multivariate logistic model including patient's age, sex, entrance mode and diagnosis as predictors of a composite primary outcome of in-hospital death or ICU admission. A total of 2,747 (4.2%) patients died or were admitted to ICU. The risk of death or ICU admission was mainly associated with the consumption of opioids, followed by cocaine and other narcotics. Particularly, methadone poisoning was associated with a substantial risk (OR: 35.70, 95% CI [26.94-47.32], P < 0.001). In the validation cohort, our model achieved good predictive properties in terms of calibration and discrimination (c-statistic: 0.847). This allows an accurate identification of life-Threatening admissions in drug users to support an early and appropriate management.

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DO - 10.1038/srep44428

M3 - Journal article

C2 - 28290530

AN - SCOPUS:85015301111

SN - 2045-2322

VL - 7

JO - Scientific Reports

JF - Scientific Reports

M1 - 44428

ER -

Identifying Life-Threatening Admissions for Drug Dependence or Abuse (ILIADDA): Derivation and Validation of a Model.

Abstract

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