Evidence map›Paper›PMID 38130889›Full record

ArticleStroke research and treatment2023

Modeling Survival Time to Death among Stroke Patients at Jimma University Medical Center, Southwest Ethiopia: A Retrospective Cohort Study.

Bikiltu Wakuma Negasa, Teramaj Wongel Wotale, Mesfin Esayas Lelisho, Legesse Kassa Debusho, Kibrealem Sisay, Wubishet Gezimu

Abstract read
In one paragraph

Article in Stroke research and treatment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

6 authors.

Bikiltu Wakuma NegasaDepartment of Statistics, College of Natural and Computational Sciences, Mattu University, Mattu, Ethiopia.
Teramaj Wongel WotaleDepartment of Statistics, College of Natural and Computational Sciences, Mattu University, Mattu, Ethiopia.ORCID https://orcid.org/0000-0002-4937-333X
Mesfin Esayas LelishoDepartment of Statistics, College of Natural and Computational Sciences, Mizan-Tepi University, Tepi, Ethiopia.ORCID https://orcid.org/0000-0002-3207-1829
Legesse Kassa DebushoDepartment of Statistics, University of South Africa, Pretoria, South Africa.ORCID https://orcid.org/0000-0002-0128-3116
Kibrealem SisayDepartment of Statistics, College of Natural and Computational Sciences, Jimma University, Jimma, Ethiopia.
Wubishet GezimuDepartment of Nursing, College of Health Sciences, Mattu University, Mattu, Ethiopia.ORCID https://orcid.org/0000-0002-5503-1360

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Stroke is a life-threatening condition that occurs due to impaired blood flow to brain tissues. Every year, about 15 million people worldwide suffer from a stroke, with five million of them suffering from some form of permanent physical disability. Globally, stroke is the second-leading cause of death following ischemic heart disease. It is a public health burden for both developed and developing nations, including Ethiopia. Objectives: This study is aimed at estimating the time to death among stroke patients at Jimma University Medical Center, Southwest Ethiopia. Methods: A facility-based retrospective cohort study was conducted among 432 patients. The data were collected from stroke patients under follow-up at Jimma University Medical Center from January 1, 2016, to January 30, 2019. A log-rank test was used to compare the survival experiences of different categories of patients. The Cox proportional hazard model and the accelerated failure time model were used to analyze the survival analysis of stroke patients using R software. An Akaike's information criterion was used to compare the fitted models. Results: Of the 432 stroke patients followed, 223 (51.6%) experienced the event of death. The median time to death among the patients was 15 days. According to the results of the Weibull accelerated failure time model, the age of patients, atrial fibrillation, alcohol consumption, types of stroke diagnosed, hypertension, and diabetes mellitus were found to be the significant prognostic factors that contribute to shorter survival times among stroke patients. Conclusion: The Weibull accelerated failure time model better described the time to death of the stroke patients' data set than other distributions used in this study. Patients' age, atrial fibrillation, alcohol consumption, being diagnosed with hemorrhagic types of stroke, having hypertension, and having diabetes mellitus were found to be factors shortening survival time to death for stroke patients. Hence, healthcare professionals need to thoroughly follow the patients who pass risk factors. Moreover, patients need to be educated about lifestyle modifications.

Identifiers

PMID38130889
PMCPMC10733594

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.