Evidence map›Paper›PMID 37868680›Full record

ArticleJournal of community hospital internal medicine perspectives2023

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

Gaurav Mohan, Poorva Bhide, Amer Abu-Shanab, Medha Ghose, Adhithya Rajamohan, Tayyeb Muhammad, Anosh A Khan, Mahrukh Khan, Farhan Khalid, Rana P Padappayil and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of community hospital internal medicine perspectives, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Observational
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 2 countries.

Gaurav MohanDepartment of Internal Medicine, Rutgers-Monmouth Medical Center, Long Branch, NJ, USA.
Poorva BhideDepartment of Internal Medicine, Rutgers-Monmouth Medical Center, Long Branch, NJ, USA.
Amer Abu-ShanabOffice of Scientific Affairs and Research, King Hussein Cancer Center, Amman, Jordan.
Medha GhoseDepartment of Internal Medicine, Rutgers-Monmouth Medical Center, Long Branch, NJ, USA.
Adhithya RajamohanDepartment of Internal Medicine, Rutgers-Monmouth Medical Center, Long Branch, NJ, USA.
Tayyeb MuhammadDepartment of Internal Medicine, Rutgers-Monmouth Medical Center, Long Branch, NJ, USA.
Anosh A KhanDepartment of Internal Medicine, Rutgers-Monmouth Medical Center, Long Branch, NJ, USA.
Mahrukh KhanDepartment of Internal Medicine, Rutgers-Monmouth Medical Center, Long Branch, NJ, USA.
Farhan KhalidDepartment of Internal Medicine, Rutgers-Monmouth Medical Center, Long Branch, NJ, USA.
Rana P PadappayilDepartment of Internal Medicine, Rutgers-Monmouth Medical Center, Long Branch, NJ, USA.
Doantrang DuDepartment of Internal Medicine, Rutgers-Monmouth Medical Center, Long Branch, NJ, USA.
Monmouth Medical Center · USRutgers, The State University of New Jersey · USKing Hussein Cancer Center · JO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Alcohol abuseAlcohol dependenceAlcohol withdrawalBenzodiazepine useCIWA-Ar protocol

Identifiers

PMID37868680
PMCPMC10589036
OpenAlexW4386399904

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.