Evidence map›Paper›PMID 31266385›Full record

ArticleJournal of the American Heart Association2019

Sensitivity of Administrative Coding in Identifying Inpatient Acute Strokes Complicating Procedures or Other Diseases in UK Hospitals.

Linxin Li, Lucy E Binney, Samantha Carter, Sergei A Gutnikov, Sally Beebe, Karen Bowsher-Brown, Louise E Silver, Peter M Rothwell, Oxford Vascular Study

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Infection, Inflammation, and Poststroke Cognitive Impairment.Journal of the American Heart Association · 2024
    Article
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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

9 authors.

Linxin Li1 Centre for Prevention of Stroke and Dementia Nuffield Department of Clinical Neuroscience University of Oxford United Kingdom.
Lucy E Binney1 Centre for Prevention of Stroke and Dementia Nuffield Department of Clinical Neuroscience University of Oxford United Kingdom.
Samantha Carter1 Centre for Prevention of Stroke and Dementia Nuffield Department of Clinical Neuroscience University of Oxford United Kingdom.
Sergei A Gutnikov1 Centre for Prevention of Stroke and Dementia Nuffield Department of Clinical Neuroscience University of Oxford United Kingdom.
Sally Beebe1 Centre for Prevention of Stroke and Dementia Nuffield Department of Clinical Neuroscience University of Oxford United Kingdom.
Karen Bowsher-Brown1 Centre for Prevention of Stroke and Dementia Nuffield Department of Clinical Neuroscience University of Oxford United Kingdom.
Louise E Silver1 Centre for Prevention of Stroke and Dementia Nuffield Department of Clinical Neuroscience University of Oxford United Kingdom.
Peter M Rothwell1 Centre for Prevention of Stroke and Dementia Nuffield Department of Clinical Neuroscience University of Oxford United Kingdom.
Oxford Vascular Study

Funding

Wellcome Trust
6 · The paper itself

Abstract

Background Administrative hospital diagnostic coding data are increasingly used in "big data" research and to assess complication rates after surgery or acute medical conditions. Acute stroke is a common complication of several procedures/conditions, such as carotid interventions, but data are lacking on the sensitivity of administrative coding in identifying acute stroke during inpatient stay. Methods and Results Using all acute strokes ascertained in a population-based cohort (2002-2017) as the reference, we determined the sensitivity of hospital administrative diagnostic codes ( International Classification of Diseases, Tenth Revision; ICD-10) for identifying acute strokes that occurred during hospital admission for other reasons, stratified by coding strategies, study periods, and stroke severity (National Institutes of Health Stroke Score</≥5). Of 3011 acute strokes, 198 (6.6%) occurred during hospital admissions for procedures/other diseases, including 122 (61.6%) major strokes. Using stroke-specific codes ( ICD-10=I60-I61 and I63-I64) in the primary diagnostic position, 66 of the 198 cases were correctly identified (sensitivity for any stroke, 33.3%; 95% CI, 27.1-40.2; minor stroke, 30.3%; 95% CI, 21.0-41.5; major stroke, 35.2%; 95% CI, 27.2-44.2), with no improvement of sensitivity over time ( P

Indexed as

HospitalizationInternational Classification of DiseasesAgedAged, 80 and overBig DataData CollectionFemaleHumansMalePostoperative ComplicationsSeverity of Illness IndexStrokeUnited Kingdomcerebrovascular disease/strokediagnostic codingperioperative strokeprospective cohort studystroke

Identifiers

PMID31266385
PMCPMC6662118

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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.