Evidence map›Paper›PMID 29745979›Full record

ArticleClinical cardiology2018

Trends, etiologies, and predictors of 90-day readmission after percutaneous ventricular assist device implantation: A national population-based cohort study.

Hafeez Ul Hassan Virk, Byomesh Tripathi, Shuchita Gupta, Akanksha Agrawal, Sandeep Dayanand, Faisal Inayat, Chayakrit Krittanawong, Ali Raza Ghani, Mohammad Nour Zabad, Parasuram Melarcode Krishnamoorthy and 7 more

Abstract read
In one paragraph

Article in Clinical cardiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Hafeez Ul Hassan VirkDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.ORCID http://orcid.org/0000-0002-9835-942X
Byomesh TripathiDepartment of Imaging and Genomic Research, Geisinger Medical Center, Danville, Pennsylvania.
Shuchita GuptaDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Akanksha AgrawalDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Sandeep DayanandDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Faisal InayatDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Chayakrit KrittanawongDepartment of Medicine, Mount Sinai St. Luke's-Roosevelt Hospital Center, New York, New York.
Ali Raza GhaniDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Mohammad Nour ZabadDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Parasuram Melarcode KrishnamoorthyDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Aman AmanullahDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Gregg PressmanDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Christian WitzkeDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Sean JanzerDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Jon GeorgeDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Sanjog KalraDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.
Vincent FigueredoDepartment of Cardiovascular Diseases, Einstein Medical Center, Philadelphia, Pennsylvania.ORCID http://orcid.org/0000-0003-0301-5649

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Percutaneous ventricular assist devices (pVADs) are indicated to provide hemodynamic support in high-risk percutaneous interventions and cardiogenic shock. However, there is a paucity of published data regarding the etiologies and predictors of 90-day readmissions following pVAD use. We studied the data from the US Nationwide Readmissions Database (NRD) for the years 2013 and 2014. Patients with a primary discharge diagnosis of pVAD use were collected by searching the database for International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) procedural code 37.68 (Impella and TandemHeart devices). Amongst this group, we examined 90-day readmission rates. Comorbidities as identified by "CM_" variables provided by the NRD were also extracted. The Charlson Comorbidity Index was calculated using appropriate ICD-9-CM codes, as a secondary diagnosis. A 2-level hierarchical logistic regression model was then used to identify predictors of 90-day readmission following pVAD use. Records from 7074 patients requiring pVAD support during hospitalization showed that 1562 (22%) patients were readmitted within 90 days. Acute decompensated heart failure (22.6%) and acute coronary syndromes (11.2%) were the most common etiologies and heart failure (odds ratio [OR]: 1.39, 95% confidence interval [CI]: 1.17-1.67), chronic obstructive pulmonary disease (OR: 1.26, 95% CI: 1.07-1.49), peripheral vascular disease (OR: 1.305, 95% CI: 1.09-1.56), and discharge into short- or long-term facility (OR: 1.28, 95% CI: 1.08-1.51) were independently associated with an increased risk of 90-day readmission following pVAD use. This study identifies important etiologies and predictors of short-term readmission in this high-risk patient group that can be used for risk stratification, optimizing discharge, and healthcare transition decisions.

Indexed as

Heart-Assist DevicesHemodynamicsVentricular Function, LeftAdolescentAdultAgedAged, 80 and overCardiovascular DiseasesChi-Square DistributionComorbidityDatabases, FactualFemaleHospital MortalityHumansIncidenceLogistic ModelsImpellaNational Readmission DatabasePercutaneous Ventricular Assist DevicesReadmissionsTandemHeart

Identifiers

PMID29745979
PMCPMC6489734

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Registered trials

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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.