Evidence map›Paper›PMID 29561421›Full record

ArticleMedicine2018

Patient and hospital characteristics predictive of inferior vena cava filter usage in venous thromboembolism patients: A study from the 2013 to 2014 Nationwide Readmissions Database.

Amie Goodin, Ming Chen, Driss Raissi, Qiong Han, Hong Xiao, Joshua Brown

Abstract read
In one paragraph

Article in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Amie GoodinUniversity of Florida College of Pharmacy, Pharmaceutical Outcomes and Policy, Gainesville, FL.
Ming ChenUniversity of Florida College of Pharmacy, Pharmaceutical Outcomes and Policy, Gainesville, FL.
Driss RaissiUniversity of Kentucky College of Medicine, Lexington, KY.
Qiong HanUniversity of Kentucky College of Medicine, Lexington, KY.
Hong XiaoUniversity of Florida College of Pharmacy, Pharmaceutical Outcomes and Policy, Gainesville, FL.
Joshua BrownUniversity of Florida College of Pharmacy, Pharmaceutical Outcomes and Policy, Gainesville, FL.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To examine the association between patient and hospital characteristics and inferior vena cava filter (IVCF) utilization in patients with venous thromboembolism (VTE).The 2013 to 2014 Nationwide Readmissions Database was used to define a cohort of patients with VTE aged ≥18 after a primary VTE diagnosis. Comorbidities of interest were classified via diagnosis codes and IVCF placement was identified via procedure code. Chi square analysis tested differences between patient and hospital-level characteristics and whether or not IVCFs were placed. A hierarchical logistic regression model estimated the relationship between patient-level factors (demographics, socioeconomic status, comorbidities), hospital-level factors (bed size, teaching status, urbanity) and whether or not IVCFs were placed. Additional models were specified to examine goodness of fit across methodological alternatives.There were 212,395 VTE hospitalizations, with 12.18% (n = 25,877) receiving IVCF placement. There were significant differences between those who did and did not receive IVCF placement; notably, those receiving IVCFs were older (P < .001), had Medicare insurance more than private (P < .001), longer lengths of stay (P < .001), and were in privately owned hospitals (P < .001). IVCF placement remained significantly associated with patient and hospital-level characteristics following multivariate adjustment via hierarchical logistic regression; notably, age >80 (adjusted Odds Ratio [aOR]: 2.53, 95% confidence interval [CI]: 2.25-2.85), ≥13 comorbid conditions (aOR: 3.85, 95% CI: 3.25-4.27), and privately owned hospitals (aOR: 1.21, 95% CI: 1.08-1.36). Optimal goodness-of-fit was achieved with a combination of random effects and patient-level fixed effects.These findings provide evidence that combinations of patient and hospital-level factors are related to whether patients with VTE receive IVCFs.

Indexed as

AdolescentAdultAgedAged, 80 and overAge FactorsComorbidityFemaleHealth Facility SizeHumansLength of StayMaleMedicareMiddle AgedPatient ReadmissionRetrospective StudiesSocioeconomic Factors

Identifiers

PMID29561421
PMCPMC5895325

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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.