Evidence map›Paper›PMID 33541273›Full record

ArticleBMC medical research methodology2021

National surveillance of stroke quality of care and outcomes by applying post-stratification survey weights on the Get With The Guidelines-Stroke patient registry.

Boback Ziaeian, Haolin Xu, Roland A Matsouaka, Ying Xian, Yosef Khan, Lee S Schwamm, Eric E Smith, Gregg C Fonarow

Abstract read
In one paragraph

Article in BMC medical research methodology, 2021. 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
–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. 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

8 authors.

Boback ZiaeianDivision of Cardiology, David Geffen School of Medicine at University of California, 10833 LeConte Avenue, Room A2-237 CHS, Los Angeles, CA, 90095-1679, USA. bziaeian@mednet.ucla.edu.ORCID 0000-0001-9787-3649
Haolin XuDuke Clinical Research Institute, Durham, North Carolina, UK.
Roland A MatsouakaDuke Clinical Research Institute, Durham, North Carolina, UK.
Ying XianDuke Clinical Research Institute, Durham, North Carolina, UK.
Yosef KhanHealthcare Quality Research and Bioinformatics, American Heart Association, Dallas, TX, USA.
Lee S SchwammDepartment of Neurology, Comprehensive Stroke Center Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Eric E SmithDepartment of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
Gregg C FonarowDivision of Cardiology, David Geffen School of Medicine at University of California, 10833 LeConte Avenue, Room A2-237 CHS, Los Angeles, CA, 90095-1679, USA.

Funding

The Effect of Nanoparticle Encapsulated Resveratrol on Treatment of PeriodontitisKL2TR001882 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Elizabeta Nemeth · 2016 to 2026
$13.1M
American Heart Association 17SDG33630113American Heart Association-American Stroke Association 17SDG33630113NCATS NIH HHS KL2 TR001882
6 · The paper itself

Abstract

backgroundThe U.S. lacks a stroke surveillance system. This study develops a method to transform an existing registry into a nationally representative database to evaluate acute ischemic stroke care quality.

methodsTwo statistical approaches are used to develop post-stratification weights for the Get With The Guidelines-Stroke registry by anchoring population estimates to the National Inpatient Sample. Post-stratification survey weights are estimated using a raking procedure and Bayesian interpolation methods. Weighting methods are adjusted to limit the dispersion of weights and make reasonable epidemiologic estimates of patient characteristics, quality of hospital care, and clinical outcomes. Standardized differences in national estimates are reported between the two post-stratification methods for anchored and non-anchored patient characteristics to evaluate estimation quality. Primary measures evaluated are patient and hospital characteristics, stroke severity, vital and laboratory measures, disposition, and clinical outcomes at discharge.

resultsA total of 1,388,296 acute ischemic strokes occurred between 2012 and 2014. Raking and Bayesian estimates of clinical data not available in administrative data are estimated within 5 to 10% of margin for expected values. Median weight for the raking method is 1.386 and the weights at the 99th percentile is 6.881 with a maximum weight of 30.775. Median Bayesian weight is 1.329 and the 99th percentile weights is 11.201 with a maximum weight of 515.689.

conclusionsLeveraging existing databases with patient registries to develop post-stratification weights is a reliable approach to estimate acute ischemic stroke epidemiology and monitoring for stroke quality of care nationally. These methods may be applied to other diseases or settings to better monitor population health.

Indexed as

Brain IschemiaStrokeBayes TheoremHumansQuality of Health CareRegistriesBayesian analysisEpidemiologyHealth servicesIschemic strokePopulation surveillanceQuality and outcomes

Identifiers

PMID33541273
PMCPMC7863276

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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.