Evidence map›Paper›PMID 26921148›Full record

ArticleAnnals of intensive care2016

Risk factors for and prediction of mortality in critically ill medical-surgical patients receiving heparin thromboprophylaxis.

Guowei Li, Lehana Thabane, Deborah J Cook, Renato D Lopes, John C Marshall, Gordon Guyatt, Anne Holbrook, Noori Akhtar-Danesh, Robert A Fowler, Neill K J Adhikari and 8 more

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of intensive care, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00182143 (PROphylaxis for ThromboEmbolism in Critical Care Trial), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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.

NCT00182143 phase3completednot on this map

PROphylaxis for ThromboEmbolism in Critical Care Trial (PROTECT)

TypeinterventionalSponsorMcMaster UniversityRan2006 to 2010Enrolled3,659ConditionsCritical Illness, Deep Venous ThrombosisArmsLMWH (Fragmin, dalteparin), Unfractionated Heparin
3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
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  5. Article
  6. Review
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

18 authors.

Guowei LiDepartment of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.
Lehana ThabaneDepartment of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.
Deborah J CookDepartment of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.
Renato D LopesDuke Clinical Research Institute, Duke University, Durham, NC, USA.
John C MarshallInterdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada.
Gordon GuyattDepartment of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.
Anne HolbrookDepartment of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.
Noori Akhtar-DaneshDepartment of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.
Robert A FowlerInterdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada.
Neill K J AdhikariInterdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada.
Rob TaylorMercy Clinic Adult Critical Care, Mercy Hospital Saint Louis, Saint Louis, MO, USA.
Yaseen M ArabiKing Saud bin Abdulaziz University for Health Sciences and King Abdullah International Medical Research Center, Riyadh, Saudi Arabia.
Dean ChittockCritical Care Medicine, Vancouver Coastal Health Research Institute, Vancouver, BC, Canada.
Peter DodekCenter for Health Evaluation and Outcome Sciences and Division of Critical Care Medicine, St. Paul's Hospital and University of British Columbia, Vancouver, BC, Canada.
Andreas P FreitagDepartment of Medicine, McMaster University, Hamilton, ON, Canada.
Stephen D WalterDepartment of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.
Diane Heels-AnsdellDepartment of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.
Mitchell A H LevineDepartment of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada. levinem@mcmaster.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrevious studies have suggested that prediction models for mortality should be adjusted for additional risk factors beyond the Acute Physiology and Chronic Health Evaluation (APACHE) score. Our objective was to identify risk factors independent of APACHE II score and construct a prediction model to improve the predictive accuracy for hospital and intensive care unit (ICU) mortality.

methodsWe used data from a multicenter randomized controlled trial (PROTECT, Prophylaxis for Thromboembolism in Critical Care Trial) to build a new prediction model for hospital and ICU mortality. Our primary outcome was all-cause 60-day hospital mortality, and the secondary outcome was all-cause 60-day ICU mortality.

resultsWe included 3746 critically ill non-trauma medical-surgical patients receiving heparin thromboprophylaxis (43.3 % females) in this study. The new model predicting 60-day hospital mortality incorporated APACHE II score (main effect: hazard ratio (HR) = 0.97 for per-point increase), body mass index (BMI) (main effect: HR = 0.92 for per-point increase), medical admission versus surgical (HR = 1.67), use of inotropes or vasopressors (HR = 1.34), acetylsalicylic acid or clopidogrel (HR = 1.27) and the interaction term between APACHE II score and BMI (HR = 1.002 for per-point increase). This model had a good fit to the data and was well calibrated and internally validated. However, the discriminative ability of the prediction model was unsatisfactory (C index < 0.65). Sensitivity analyses supported the robustness of these findings. Similar results were observed in the new prediction model for 60-day ICU mortality which included APACHE II score, BMI, medical admission and invasive mechanical ventilation.

conclusionCompared with the APACHE II score alone, the new prediction model increases data collection, is more complex but does not substantially improve discriminative ability.

trial registrationClinicalTrials.gov Identifier: NCT00182143.

Indexed as

APACHECritical careIntensive care unitMortalityPrediction model

Identifiers

PMID26921148
PMCPMC4769241

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Registered trials

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.