Evidence map›Paper›PMID 34344914›Full record

ArticleScientific reports2021

Joint modeling of blood pressure measurement and survival time of hypertension patients.

Hakime Ayele Kosa, Markos Abiso Erango

Abstract read
In one paragraph

Article in Scientific reports, 2021. 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
–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

2 citing papers in PubMed.

  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

2 authors.

Hakime Ayele KosaDepartment of Statistics, Collage of Natural Science, Arba Minch University, Arba Minch, Ethiopia.
Markos Abiso ErangoDepartment of Statistics, Collage of Natural Science, Arba Minch University, Arba Minch, Ethiopia. markos.erango73@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypertension is a chronic disease that has a major health problem over the centuries due to its significant contribution to the global burden. The objective of this study was to examine the association of survival time and longitudinal Systolic Blood Pressure (SBP) measurement and finding potential barrier that affects SBP measurement and the survival time of hypertension patients. The study considered a cohort of 318 hypertension patients who were aged 18 years or older and were under follow-up from January 1, 2012, to February 30, 2020, at Arba Minch General Hospital. To analyze the data we employed linear mixed effect model, Weibull model, and joint modeling approach for longitudinal and survival data. The results from joint model analysis indicate that systolic blood pressure measurement is significantly associated with survival time of hypertension patients. The results from the longitudinal sub-model reveals that alcohol use, Khat intake, smoking tobacco, stages of hypertension diseases, adherence to treatment, related diseases, and family history had statistical significant relationship with mean change in the [Formula: see text] measurement. Furthermore, from the survival sub-model, we found the survival probability of hypertension patients was determined by family history, stages of hypertension disease, related diseases, and smoking tobacco. The analysis suggests that there is a strong association between SBP measurement and survival time of hypertension patients. Thus we recommend aggressive work by all concerned bodies towards awareness creation about the effect of potential barriers.

Indexed as

Models, StatisticalBlood PressureFemaleHumansHypertensionLongitudinal StudiesMaleMiddle AgedPrognosisSurvival Rate

Identifiers

PMID34344914
PMCPMC8333259

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.