Evidence map›Paper›PMID 30444743›Full record

Observational studyCritical care medicine2019

Risk Factors for 1-Year Mortality and Hospital Utilization Patterns in Critical Care Survivors: A Retrospective, Observational, Population-Based Data Linkage Study.

Tamas Szakmany, Angharad M Walters, Richard Pugh, Ceri Battle, Damon M Berridge, Ronan A Lyons

Abstract readObservational Study
In one paragraph

Observational study in Critical care medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

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  7. Observational
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Tamas SzakmanyDivision of Population Medicine, Department of Anaesthesia, Intensive Care and Pain Medicine, Cardiff University, Heath Park Campus, Cardiff, United Kingdom.
Angharad M WaltersHealth Data Research UK, Swansea University Medical School, Data Science Building, Swansea, United Kingdom.
Richard PughDepartment of Anaesthetic, Glan Clywdd Hospital, Betsi Cadwaladar University Health Board, Bodelwyddan, Rhyl, United Kingdom.
Ceri BattleMorriston Hospital, Abertawe Bro Morgannwg University Health Board, Heol Maes Eglwys, Swansea, United Kingdom.
Damon M BerridgeHealth Data Research UK, Swansea University Medical School, Data Science Building, Swansea, United Kingdom.
Ronan A LyonsHealth Data Research UK, Swansea University Medical School, Data Science Building, Swansea, United Kingdom.

Funding

Wellcome Trust
6 · The paper itself

Abstract

objectivesClear understanding of the long-term consequences of critical care survivorship is essential. We investigated the care process and individual factors associated with long-term mortality among ICU survivors and explored hospital use in this group.

designPopulation-based data linkage study using the Secure Anonymised Information Linkage databank.

settingAll ICUs between 2006 and 2013 in Wales, United Kingdom. PATIENTS: We identified 40,631 patients discharged alive from Welsh adult ICUs.

interventionsNone. MEASUREMENTS AND MAIN

resultsPrimary outcome was 365-day survival. The secondary outcomes were 30- and 90-day survival and hospital utilization in the 365 days following ICU discharge. Kaplan-Meier curves were plotted to compare survival rates. Cox proportional hazards regression models were used to determine risk factors of mortality. Seven-thousand eight-hundred eighty-three patients (19.4%) died during the 1-year follow-up period. In the multivariable Cox regression analysis, advanced age and comorbidities were significant determinants of long-term mortality. Expedited discharge due to ICU bed shortage was associated with higher risk. The rate of hospitalization in the year prior to the critical care admission was 28 hospitalized days/1,000 d; post critical care was 88 hospitalized days/1,000 d for those who were still alive; and 57 hospitalized days/1,000 d and 412 hospitalized days/1,000 d for those who died by the end of the study, respectively.

conclusionsOne in five ICU survivors die within 1 year, with advanced age and comorbidity being significant predictors of outcome, leading to high resource use. Care process factors indicating high system stress were associated with increased risk. More detailed understanding is needed on the effects of the potentially modifiable factors to optimize service delivery and improve long-term outcomes of the critically ill.

Indexed as

Intensive Care UnitsMortalitySurvivorsAge FactorsComorbidityHospitalizationHumansProportional Hazards ModelsRetrospective StudiesRisk FactorsWales

Identifiers

PMID30444743
PMCPMC6330072

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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.