Evidence map›Paper›PMID 38310430›Full record

ArticleArchives of Iranian medicine2023

A Spatial Variation Analysis of In-Hospital Stroke Mortality Based on Integrated Pre-Hospital and Hospital Data in Mashhad, Iran.

Eisa Nazar, Habibollah Esmaily, Razieh Yousefi, Jamshid Jamali, Kavian Ghandehari, Soheil Hashtarkhani, Zahra Jafari, Mohammad Taghi Shakeri

Open access · hybridAbstract read
In one paragraph

Article in Archives of Iranian medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

8 authors at 3 institutions in 2 countries.

Eisa NazarPsychiatry and Behavioral Sciences Research Center, Addiction Institute, Mazandaran University of Medical Sciences, Mazandaran, Iran.ORCID 0000-0002-2860-6034
Habibollah EsmailyDepartment of Biostatistics, School of Public Health, Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Razieh YousefiStudent Research Committee, Mashhad University of Medical Sciences, Mashhad, Iran.
Jamshid JamaliDepartment of Biostatistics, School of Public Health, Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Kavian GhandehariNeurocognitive Research Center, Department of Neurology, Mashhad University of Medical Sciences, Mashhad, Iran.
Soheil HashtarkhaniCenter for Biomedical Informatics, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, USA.
Zahra JafariClinical Research Development Unit, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran.
Mohammad Taghi ShakeriDepartment of Biostatistics, School of Public Health, Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID 0000-0002-8287-9594
Mashhad University of Medical Sciences · IRMazandaran University of Medical Sciences · IRUniversity of Tennessee Health Science Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite significant advances in the quality and delivery of specialized stroke care, there still persist remarkable spatial variations in emergency medical services (EMS) transport delays, stroke incidence, and its outcomes. Therefore, it is very important to investigate the possible geographical variations of in-hospital stroke mortality and to identify its associated factors.

methodsThis historical cohort study included suspected stroke cases transferred to Ghaem Hospital of Mashhad by the EMS from March 2018 to March 2019. Using emergency mission IDs, the pre-hospital emergency data were integrated with the patient medical records in the hospital. We used the Bayesian approach for estimating the model parameters.

resultsOut of 301 patients (142 (47.2%) females vs. 159 (52.8%) males) with a final diagnosis of stroke, 61 (20.3%) cases had in-hospital mortality. Results from Bayesian spatial log-logistic proportional odds (PO) model showed that age (PO=1.07), access rate to EMS (PO=0.78), arrival time (evening shift vs. day shift, PO=0.09), and sequelae variables (PO=9.20) had a significant association with the odds of in-hospital stroke mortality (

conclusionMarked regional variations were found in the odds of in-hospital stroke mortality in Mashhad. There was a direct association between age and odds of in-hospital stroke mortality. Hence, the prognosis of in-hospital stroke mortality could be improved by better control of hypertension, prevention of the occurrence of sequelae, increasing the access rate to EMS, and optimizing shift work schedule.

Indexed as

StrokeBayes TheoremCohort StudiesFemaleHospital MortalityHospitalsHumansIranMaleBayesianIn-hospital MortalityIranSequelaeSpatial survival modelStroke

Identifiers

PMID38310430
PMCPMC10685828
OpenAlexW4387425079

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.