Cargando…

Predictors of Escalation to Intensive Care Unit Level of Care Among Admissions for Alcohol Withdrawal

According to the 2019 National Survey on Drug Use and Health, 14.5 million people ages 12 and older had alcohol abuse disorder. Alcohol withdrawal syndrome (AWS) can be defined as a collection of physical symptoms experienced due to abrupt cessation of alcohol after long-term dependence. In instance...

Descripción completa

Detalles Bibliográficos
Autores principales: Mohan, Gaurav, Bhide, Poorva, Abu-Shanab, Amer, Ghose, Medha, Rajamohan, Adhithya, Muhammad, Tayyeb, Khan, Anosh A., Khan, Mahrukh, Khalid, Farhan, Padappayil, Rana P., Du, Doantrang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Greater Baltimore Medical Center 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589036/
https://www.ncbi.nlm.nih.gov/pubmed/37868680
http://dx.doi.org/10.55729/2000-9666.1241
_version_ 1785123707159576576
author Mohan, Gaurav
Bhide, Poorva
Abu-Shanab, Amer
Ghose, Medha
Rajamohan, Adhithya
Muhammad, Tayyeb
Khan, Anosh A.
Khan, Mahrukh
Khalid, Farhan
Padappayil, Rana P.
Du, Doantrang
author_facet Mohan, Gaurav
Bhide, Poorva
Abu-Shanab, Amer
Ghose, Medha
Rajamohan, Adhithya
Muhammad, Tayyeb
Khan, Anosh A.
Khan, Mahrukh
Khalid, Farhan
Padappayil, Rana P.
Du, Doantrang
author_sort Mohan, Gaurav
collection PubMed
description According to the 2019 National Survey on Drug Use and Health, 14.5 million people ages 12 and older had alcohol abuse disorder. Alcohol withdrawal syndrome (AWS) can be defined as a collection of physical symptoms experienced due to abrupt cessation of alcohol after long-term dependence. In instances where regular inpatient management fails to control AWS symptoms, patients are shifted to intensive care units (ICUs) for closer monitoring and prevention of life-threatening complications like withdrawal seizures and delirium tremens (DTs), labeled as severe alcohol withdrawal syndrome (SAWS). Although this represents a significant healthcare burden, minimal studies have been conducted to determine objective predictors. In this study, we aim to determine the effect of patient demographics, socio-economic status, biochemical parameters, and clinical factors on the need for escalation to ICU level of care among admissions for AWS. Our study showed that factors such as a history of DTs or alcohol-related seizures, the initial protocol of management, degree of reported alcohol usage, activation of rapid response teams, mean corpuscular value, alcohol level on admission, highest Clinical Institute Withdrawal Assessment Alcohol Revised (CIWA-Ar) scored during the hospital stay, and the total amount of sedatives used were significantly associated with escalation to ICU level of care. Clinicians must use these objective parameters to identify high-risk patients and intervene early. We encourage further studies to establish a scoring algorithm incorporating biochemical parameters to tailor management algorithms that might better suit high-risk patients.
format Online
Article
Text
id pubmed-10589036
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Greater Baltimore Medical Center
record_format MEDLINE/PubMed
spelling pubmed-105890362023-10-21 Predictors of Escalation to Intensive Care Unit Level of Care Among Admissions for Alcohol Withdrawal Mohan, Gaurav Bhide, Poorva Abu-Shanab, Amer Ghose, Medha Rajamohan, Adhithya Muhammad, Tayyeb Khan, Anosh A. Khan, Mahrukh Khalid, Farhan Padappayil, Rana P. Du, Doantrang J Community Hosp Intern Med Perspect Research Article According to the 2019 National Survey on Drug Use and Health, 14.5 million people ages 12 and older had alcohol abuse disorder. Alcohol withdrawal syndrome (AWS) can be defined as a collection of physical symptoms experienced due to abrupt cessation of alcohol after long-term dependence. In instances where regular inpatient management fails to control AWS symptoms, patients are shifted to intensive care units (ICUs) for closer monitoring and prevention of life-threatening complications like withdrawal seizures and delirium tremens (DTs), labeled as severe alcohol withdrawal syndrome (SAWS). Although this represents a significant healthcare burden, minimal studies have been conducted to determine objective predictors. In this study, we aim to determine the effect of patient demographics, socio-economic status, biochemical parameters, and clinical factors on the need for escalation to ICU level of care among admissions for AWS. Our study showed that factors such as a history of DTs or alcohol-related seizures, the initial protocol of management, degree of reported alcohol usage, activation of rapid response teams, mean corpuscular value, alcohol level on admission, highest Clinical Institute Withdrawal Assessment Alcohol Revised (CIWA-Ar) scored during the hospital stay, and the total amount of sedatives used were significantly associated with escalation to ICU level of care. Clinicians must use these objective parameters to identify high-risk patients and intervene early. We encourage further studies to establish a scoring algorithm incorporating biochemical parameters to tailor management algorithms that might better suit high-risk patients. Greater Baltimore Medical Center 2023-09-02 /pmc/articles/PMC10589036/ /pubmed/37868680 http://dx.doi.org/10.55729/2000-9666.1241 Text en © 2023 Greater Baltimore Medical Center https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ).
spellingShingle Research Article
Mohan, Gaurav
Bhide, Poorva
Abu-Shanab, Amer
Ghose, Medha
Rajamohan, Adhithya
Muhammad, Tayyeb
Khan, Anosh A.
Khan, Mahrukh
Khalid, Farhan
Padappayil, Rana P.
Du, Doantrang
Predictors of Escalation to Intensive Care Unit Level of Care Among Admissions for Alcohol Withdrawal
title Predictors of Escalation to Intensive Care Unit Level of Care Among Admissions for Alcohol Withdrawal
title_full Predictors of Escalation to Intensive Care Unit Level of Care Among Admissions for Alcohol Withdrawal
title_fullStr Predictors of Escalation to Intensive Care Unit Level of Care Among Admissions for Alcohol Withdrawal
title_full_unstemmed Predictors of Escalation to Intensive Care Unit Level of Care Among Admissions for Alcohol Withdrawal
title_short Predictors of Escalation to Intensive Care Unit Level of Care Among Admissions for Alcohol Withdrawal
title_sort predictors of escalation to intensive care unit level of care among admissions for alcohol withdrawal
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589036/
https://www.ncbi.nlm.nih.gov/pubmed/37868680
http://dx.doi.org/10.55729/2000-9666.1241
work_keys_str_mv AT mohangaurav predictorsofescalationtointensivecareunitlevelofcareamongadmissionsforalcoholwithdrawal
AT bhidepoorva predictorsofescalationtointensivecareunitlevelofcareamongadmissionsforalcoholwithdrawal
AT abushanabamer predictorsofescalationtointensivecareunitlevelofcareamongadmissionsforalcoholwithdrawal
AT ghosemedha predictorsofescalationtointensivecareunitlevelofcareamongadmissionsforalcoholwithdrawal
AT rajamohanadhithya predictorsofescalationtointensivecareunitlevelofcareamongadmissionsforalcoholwithdrawal
AT muhammadtayyeb predictorsofescalationtointensivecareunitlevelofcareamongadmissionsforalcoholwithdrawal
AT khananosha predictorsofescalationtointensivecareunitlevelofcareamongadmissionsforalcoholwithdrawal
AT khanmahrukh predictorsofescalationtointensivecareunitlevelofcareamongadmissionsforalcoholwithdrawal
AT khalidfarhan predictorsofescalationtointensivecareunitlevelofcareamongadmissionsforalcoholwithdrawal
AT padappayilranap predictorsofescalationtointensivecareunitlevelofcareamongadmissionsforalcoholwithdrawal
AT dudoantrang predictorsofescalationtointensivecareunitlevelofcareamongadmissionsforalcoholwithdrawal