Evidence map›Paper›PMID 34333619›Full record

ArticleCritical care nurse2021

Intensive Care Unit Scoring Systems.

Tiffany Purcell Pellathy, Michael R Pinsky, Marilyn Hravnak

Abstract read
In one paragraph

Article in Critical care nurse, 2021. 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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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

3 authors.

Tiffany Purcell PellathyTiffany Purcell Pellathy is a postdoctoral research fellow at the Veterans Administration Center for Health Equity Research and Promotion in Pittsburgh, Pennsylvania.
Michael R PinskyMichael R. Pinsky is a professor of critical care medicine, bioengineering, cardiovascular diseases, clinical and translational science, and anesthesiology at the University of Pittsburgh, Pittsburgh, Pennsylvania.
Marilyn HravnakMarilyn Hravnak is a professor of nursing at the University of Pittsburgh School of Nursing.

Funding

Predicting Patient Instability Noninvasively for Nursing Care-Two (PPINNC-2)R01NR013912 · NINR · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI AL-ZAITI, SALAH S, CLERMONT, GILLES · 2012 to 2025
$7.0M
Machine Learning to Determine Dynamically Evolving New-Onset Venous Thromboembolic (VTE) Event Risk in Hospitalized PatientsF31NR018102 · NINR · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI PELLATHY, TIFFANY PURCELL · 2018 to 2020
$107k
NINR NIH HHS F31 NR018102NINR NIH HHS R01 NR013912
6 · The paper itself

Abstract

backgroundIllness severity scoring systems are commonly used in critical care. When applied to the populations for whom they were developed and validated, these tools can facilitate mortality prediction and risk stratification, optimize resource use, and improve patient outcomes.

objectiveTo describe the characteristics and applications of the scoring systems most frequently applied to critically ill patients.

methodsA literature search was performed using MEDLINE to identify original articles on intensive care unit scoring systems published in the English language from 1980 to 2020. Search terms associated with critical care scoring systems were used alone or in combination to find relevant publications.

resultsTwo types of scoring systems are most frequently applied to critically ill patients: those that predict risk of in-hospital mortality at the time of intensive care unit admission (Acute Physiology and Chronic Health Evaluation, Simplified Acute Physiology Score, and Mortality Probability Models) and those that assess and characterize current degree of organ dysfunction (Multiple Organ Dysfunction Score, Sequential Organ Failure Assessment, and Logistic Organ Dysfunction System). This article details these systems' differing features and timing of use, score calculation, patient populations, and comparative performance data.

conclusionCritical care nurses must be aware of the strengths, limitations, and specific characteristics of severity scoring systems commonly used in intensive care unit patients to effectively employ these tools in clinical practice and critically appraise research findings based on their use.

Indexed as

Critical IllnessIntensive Care UnitsCritical CareHospital MortalityHumansPrognosisSeverity of Illness Index

Identifiers

PMID34333619
PMCPMC8378550

What OpenQuestion holds

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Registered trials

None linked

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.