Evidence map›Paper›PMID 23776691›Full record

ArticlePloS one2013

Risk of hospitalization for acute cardiovascular events among subjects with lower urinary tract symptoms: a nationwide population-based study.

Huey-Juan Lin, Shih-Feng Weng, Chun-Ming Yang, Ming-Ping Wu

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Huey-Juan LinDepartment of Neurology, Chi Mei Medical Center, Tainan, Taiwan.
Shih-Feng Weng
Chun-Ming Yang
Ming-Ping Wu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeLower urinary tract symptoms (LUTS) have been reported to be associated with metabolic syndrome and may predispose subjects to cardiovascular disease. The magnitude of the impact on the medical care remains to be elucidated. Based on a population-based claims dataset in Taiwan, we explored the association between LUTS and the risk of subsequent hospitalization for acute cardiovascular events. MATERIALS AND

methodsAmong a representative sample of one million subjects from nationwide health insurance enrollees, subjects with codes of LUTS in service claims and without previous cardiovascular diseases including stroke were compared with age- and sex-matched non-LUTS subjects in subsequent hospitalization for acute coronary syndrome or stroke from the recruited date (between 2001-2004) to 2009. The risk of outcomes was assessed with Kaplan-Meier curves and the impact of LUTS was estimated with Poison regression analysis and Cox proportional hazards models.

resultsWe included 4,553 LUTS subjects and 22,765 matched non-LUTS subjects, with a mean age of 47 years and 43% of men. Hypertension, diabetes, and hyperlipidemia were more prevalent in the LUTS group. The incidence rate of the composite endpoint was significantly higher in the LUTS group than in the non-LUTS group (5.4/1000 vs. 4.0/1000 person-years). The difference mainly derived from stroke rather than acute coronary syndrome. After adjusting for age, sex, diabetes, hypertension, and hyperlipidemia in multivariable analysis, LUTS remained a significant predictor (hazard ratio, 1.29; 95% confidence incidence, 1.06-1.50).

conclusionSubjects free of cardiovascular disease and presenting with LUTS are at risk of subsequent hospitalization for acute cardiovascular events, mainly stroke. The information might prompt practitioners encountering such patients to undergo appropriate diagnostic and preventive measures.

Indexed as

AdultCardiovascular DiseasesFemaleHospitalizationHumansKaplan-Meier EstimateLower Urinary Tract SymptomsMaleMiddle AgedPoisson DistributionProportional Hazards ModelsRegression AnalysisTaiwan

Identifiers

PMID23776691
PMCPMC3680437

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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.