Evidence map›Paper›PMID 31276175›Full record

ArticleJAMA network open2019

Factors Associated With Unplanned 30-Day Readmissions After Hematopoietic Cell Transplantation Among US Hospitals.

Binod Dhakal, Smith Giri, Adam Levin, Lisa Rein, Timothy S Fenske, Saurabh Chhabra, Nirav N Shah, Aniko Szabo, Anita D'Souza, Marcelo Pasquini and 2 more

Abstract read
In one paragraph

Article in JAMA network open, 2019. 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. Article
  2. Article
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  4. Oral foci of infection and their relationship with hospital stay after haematopoietic cell transplantation.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
    Article
  5. Article
  6. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Binod DhakalDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee.
Smith GiriDivision of Hematology and Oncology, Yale University, New Haven, Connecticut.
Adam LevinDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee.
Lisa ReinDivision of Biostatistics, Medical College of Wisconsin, Milwaukee.
Timothy S FenskeDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee.
Saurabh ChhabraDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee.
Nirav N ShahDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee.
Aniko SzaboDivision of Biostatistics, Medical College of Wisconsin, Milwaukee.
Anita D'SouzaDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee.
Marcelo PasquiniDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee.
Parameswaran HariDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee.
Mehdi HamadaniDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Hematopoietic cell transplantation (HCT) is a therapeutic strategy in the management of several hematological cancers. Limited data exist on the incidence and predictors of 30-day readmission after HCT. Objective: To measure the incidence of and risk factors associated with 30-day readmission following HCT in the United States. Design, Setting, and Participants: This cohort study examined patient data from the US population-based Nationwide Readmissions Database. All adults (age ≥18 years) who underwent autologous (auto-) or allogenic (allo-) HCT in US hospitals between January 1, 2012, and November 30, 2014, were included. The analysis was performed from June 2018 to February 2019. Main Outcomes and Measures: The main outcome was 30-day readmission rates for auto-HCT and allo-HCT. Factors associated with readmission, including baseline demographic characteristics and disease- and hospital-related characteristics (including annual case volume), were measured. Results: A total of 28 356 index admissions for auto-HCT in 244 centers (191 low-volume, 38 medium-volume, and 15 high-volume centers) and 17 217 index admissions for allo-HCT in 211 centers (161 low-volume, 37 medium-volume, and 13 high-volume centers) were identified during the study period. The overall 30-day readmission rates were 11.6% for auto-HCT and 24.4% for allo-HCT. The odds of readmission were significantly higher in low-volume hospitals compared with high-volume hospitals (adjusted odds ratio [aOR], 1.69; 95% CI, 1.08-2.64 for auto-HCT and aOR, 1.41; 95% CI, 1.09-1.82 for allo-HCT) but comparable to medium-volume hospitals (aOR, 1.06; 95% CI, 0.62-1.83 for auto-HCT and aOR, 1.19; 95% CI, 0.90-1.57 for allo-HCT). Other factors associated with readmission for auto-HCT included younger age (aOR for age ≥50 vs <49 years, 0.82; 95% CI, 0.68-0.98), female sex (aOR, 1.21; 95% CI, 1.06-1.36), disease type (aOR for other vs myeloma, 1.37; 95% CI, 1.06-1.77), and Elixhauser comorbidity index score (aOR for ≥20 vs 0, 1.5; 95% CI, 1.17-1.93). For allo-HCT, factors associated with readmission included disease type (aOR for acute lymphoblastic leukemia vs acute myelogenous leukemia, 1.30; 95% CI, 1.04-1.62), insurance (aOR for Medicare vs private, 1.18; 95% CI, 1.02-1.36), and Elixhauser comorbidity index score (aOR for 1-9 vs 0, 1.2; 95% CI, 1.04-1.39). Infections, neutropenic fever, and gastrointestinal symptoms were the most common reasons for readmission for both types of HCT. Conclusions and Relevance: This study found substantial rates of readmission for both types of HCT and an inverse association between hospital HCT volume and 30-day readmission. These results may provide guidance when developing quality indicators and policies penalizing hospitals for HCT readmission.

Indexed as

Febrile NeutropeniaGastrointestinal DiseasesHospitalsInfectionsAdultCohort StudiesFemaleHematologic NeoplasmsHematopoietic Stem Cell TransplantationHumansInsurance, HealthMalePatient ReadmissionPostoperative ComplicationsRisk FactorsUnited States

Identifiers

PMID31276175
PMCPMC12124690

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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.