Evidence map›Paper›PMID 38813435›Full record

ArticleCritical care explorations2024

Development and Validation of a Prediction Model for 1-Year Mortality in Patients With a Hematologic Malignancy Admitted to the ICU.

Jan-Willem H L Boldingh, M Sesmu Arbous, Bart J Biemond, Nicole M A Blijlevens, Jasper van Bommel, Murielle G E C Hilkens, Nuray Kusadasi, Marcella C A Muller, Vera A de Vries, Ewout W Steyerberg and 2 more

Abstract readValidation StudyMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Critical care explorations, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

12 authors.

Jan-Willem H L BoldinghDepartment of Critical Care, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
M Sesmu ArbousDepartment of Critical Care, Leiden University Medical Center, Leiden, The Netherlands.
Bart J BiemondDepartment of Hematology, Amsterdam University Medical Center (location AMC), University of Amsterdam, Amsterdam, The Netherlands.
Nicole M A BlijlevensDepartment of Hematology, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands.
Jasper van BommelDepartment of Critical Care, Erasmus Medical Center, Rotterdam, The Netherlands.
Murielle G E C HilkensDepartment of Critical Care, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands.
Nuray KusadasiDepartment of Critical Care, Erasmus Medical Center, Rotterdam, The Netherlands.
Marcella C A MullerDepartment of Critical Care, Amsterdam University Medical Center (location AMC), University of Amsterdam, Amsterdam, The Netherlands.
Vera A de VriesDepartment of Critical Care, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Ewout W SteyerbergDepartment of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
Walter M van den BerghDepartment of Critical Care, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Hematologic Malignancy Admitted on the ICU (HEMA-ICU) Study Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo develop and validate a prediction model for 1-year mortality in patients with a hematologic malignancy acutely admitted to the ICU.

designA retrospective cohort study.

settingFive university hospitals in the Netherlands between 2002 and 2015. PATIENTS: A total of 1097 consecutive patients with a hematologic malignancy were acutely admitted to the ICU for at least 24 h.

interventionsNone. MEASUREMENTS AND MAIN

resultsWe created a 13-variable model from 22 potential predictors. Key predictors included active disease, age, previous hematopoietic stem cell transplantation, mechanical ventilation, lowest platelet count, acute kidney injury, maximum heart rate, and type of malignancy. A bootstrap procedure reduced overfitting and improved the model's generalizability. This involved estimating the optimism in the initial model and shrinking the regression coefficients accordingly in the final model. We assessed performance using internal-external cross-validation by center and compared it with the Acute Physiology and Chronic Health Evaluation II model. Additionally, we evaluated clinical usefulness through decision curve analysis. The overall 1-year mortality rate observed in the study was 62% (95% CI, 59-65). Our 13-variable prediction model demonstrated acceptable calibration and discrimination at internal-external validation across centers (

conclusionsOur newly developed 13-variable prediction model predicts 1-year mortality in hematologic malignancy patients admitted to the ICU more accurately than the Acute Physiology and Chronic Health Evaluation II model. This model may aid in shared decision-making regarding the continuation of ICU care and end-of-life considerations.

Indexed as

Hematologic NeoplasmsIntensive Care UnitsAdultAgedAPACHECohort StudiesFemaleHumansMaleMiddle AgedNetherlandsRetrospective Studiesclinical decision ruleshematologic neoplasmsintensive care unitsmortalityprognosis

Identifiers

PMID38813435
PMCPMC11132307

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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.