Evidence map›Paper›PMID 27409676›Full record

ArticleOncotarget2016

Sitagliptin and heart failure hospitalization in patients with type 2 diabetes.

Chin-Hsiao Tseng

Abstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
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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

1 author.

Chin-Hsiao TsengDepartment of Internal Medicine, National Taiwan University College of Medicine, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study evaluated the risk of heart failure hospitalization in a 1:1 matched pair sample of sitagliptin ever and never users derived from the Taiwan's National Health Insurance. A total of 85,859 ever users and 85,859 never users matched on 8 digits of propensity score were followed for the first event of heart failure hospitalization until December 31, 2011. The treatment effect (for ever versus never users, and for tertiles of cumulative duration of therapy) was estimated by Cox regression incorporated with the inverse probability of treatment weighting using propensity score. Additionally, adjusted hazard ratios for heart failure were estimated for the baseline characteristics in sitagliptin ever users. Results showed that the incidence of heart failure hospitalization was 1,020.16 and 832.54 per 100,000 person-years, respectively, for ever and never users, with an overall hazard ratio (95% confidence intervals) of 1.262 (1.167-1.364). While compared to never users, the respective hazard ratio for the first, second, and third tertile of cumulative duration < 3.7, 3.7-10.3 and >10.3 months was 2.721 (2.449-3.023), 1.472 (1.318-1.645) and 0.515 (0.447-0.594). Older age, longer diabetes duration, male sex, and use of insulin, sulfonylurea, calcium channel blockers, aspirin, ticlopidine, clopidogrel and dipyridamole were significantly associated with a higher risk in sitagliptin users, but dyslipidemia and use of metformin and statin were protective. In conclusion, sitagliptin increases the risk of heart failure hospitalization within one year of its use, but reduces the risk thereafter. Some factors predisposing to sitagliptin-related heart failure are worthy of attention in clinical practice.

Indexed as

AdultAgedCohort StudiesDiabetes ComplicationsDiabetes Mellitus, Type 2FemaleHeart FailureHospitalizationHumansHypoglycemic AgentsIncidenceInsurance, HealthMaleMiddle AgedProbabilityProportional Hazards ModelsHypoglycemic AgentsSitagliptin Phosphateheart failurehospitalizationincretinsitagliptinTaiwan

Identifiers

PMID27409676
PMCPMC5308758

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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.