Evidence map›Paper›PMID 36579212›Full record

ArticleCureus2022

Prevalence of Cerebrovascular Accidents Among the US Population With Substance Use Disorders: A Nationwide Study.

Nikhila Chelikam, Zeeshan Mohammad, Krishna Tavrawala, Anjali N Krishnakumar, Anitta Varghese, Tanvi Yogesh Shrivastav, Baris Tarimci, Sushil Kumar, Stephan Z Francis, Vikramaditya Samala Venkata and 2 more

Abstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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, 1 synthesis or guideline pooled it.

  1. Pooled it
  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

12 authors.

Nikhila ChelikamInternal Medicine, Icahn School of Medicine at Mount Sinai, New York, USA.
Zeeshan MohammadInternal Medicine, BLK-Max Super Speciality Hospital, New Delhi, IND.
Krishna TavrawalaInternal Medicine, Smt. B. K. Shah Medical Institute & Research Centre, Vadodara, IND.
Anjali N KrishnakumarInternal Medicine, Ahalia Diabetes Hospital, Palakkad, IND.
Anitta VargheseEmergency Medicine, Iqraa International Hospital and Research Centre, Kozhikode, IND.
Tanvi Yogesh ShrivastavGeneral Medicine, Davao Medical School Foundation, Davao City, PHL.
Baris TarimciInternal Medicine, Ege University Faculty of Medicine, Izmir, TUR.
Sushil KumarInternal Medicine, Mallige Hospital, Banglore, IND.
Stephan Z FrancisInternal Medicine, Saba University School of Medicine, The Bottom, BES.
Vikramaditya Samala VenkataInternal Medicine, Cheshire Medical Center, Dartmouth-Hitchcock, Keene, USA.
Urvish K PatelPublic Health and Neurology, Icahn School of Medicine at Mount Sinai, New York, USA.
Lokesh ManjaniInternal Medicine, Medsrar Washington Hospital Center, Washington, DC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Globally, stroke is one of the top ten causes of death. The incidence of stroke in patients aged 44 years and younger was noted to have risen over the past three decades. This rise in stroke diagnosis among young adults could be attributed to multiple reasons, including the rising prevalence of comorbidities like diabetes, hypertension, substance use disorders (SUDs), etc. Aim & objectives This study's primary aim was to evaluate the prevalence of stroke in the US population and the prevalence of SUDs amongst patients with a prior history of stroke. The secondary aim was to evaluate the association between Stroke and SUDs. Methods Our population was obtained from the National Health and Nutrition Examination Survey (NHANES) between the years 2013 to 2018. We identified respondents diagnosed with stroke using the questionnaire and the history of various SUDs amongst this population. The data were analyzed using SAS software (Version 9.4). We performed univariate analysis using the chi-square and Mann-Whitney test, and a p-value of <0.05 was considered statistically significant. Results Two hundred sixty-four thousand seven hundred forty (264,740) respondents were included in this study, and 10435 (3.94%) respondents were noted to have a history of stroke. The population subset with a stroke diagnosis was older (68 years vs. 51 years). Higher prevalence was noted among the female sex (52.14% females vs. 47.86% males), Non-Hispanic white ethnicity, followed by Non-Hispanic black & then other Hispanics (47.56% vs.25.47% vs. 7.82%), and those belonging to a lower annual household income of $0-$25,000 and $25,000-$65,000 ( 46.61% vs. 35.93% ). (p<0.0001). After adjusting for socio-demographics and coexisting comorbidities, e-cigarette [OR: 2.03; 95% CI: 2.03-2.03], cocaine [OR: 1.54; 95%CI:1.54-1.54], heroin [OR: 1.83; 95%CI: 1.83-1.83], marijuana or hashish [OR: 1.01; 95% CI: 1.01-1.01], were observed to have an association with higher odds of stroke than the population without a history of using these illicit drugs.  Conclusion Among respondents with a history of stroke, the use of cocaine was most prevalent, followed by marijuana/hashish, heroin, e-cigarettes, and injecting illegal drugs. The odds of having a stroke were two times higher in the population using an e-cigarette and higher among those using heroin, cocaine, and marijuana/ hashish. The Government should plan policy changes to treat SUDs in the USA, which could help reduce the stroke burden. Recall that bias and geographic variations in response rate by participants of the study were the limitations of our survey-based study.

Indexed as

cross-sectional studyepidemiology and public healthnhanesprevalencestrokesubstance use

Identifiers

PMID36579212
PMCPMC9786611

What OpenQuestion holds

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LicenceCC BY
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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.