Evidence map›Paper›PMID 33267777›Full record

Observational studyBMC anesthesiology2020

Validation of APACHE II, APACHE III and SAPS II scores in in-hospital and one year mortality prediction in a mixed intensive care unit in Poland: a cohort study.

Szymon Czajka, Katarzyna Ziębińska, Konstanty Marczenko, Barbara Posmyk, Anna J Szczepańska, Łukasz J Krzych

Registry-linked trialAbstract readObservational StudyValidation Study
In one paragraph

Observational study in BMC anesthesiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07768410 (Supply Induced Demand in Intensive Care Unit), which is not on this map. Cited by 42 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 2 pooled it
–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.

NCT07768410 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

Supply Induced Demand in Intensive Care Unit: a Retrospective Trial

TypeobservationalSponsorSaint Camillus International University of Health SciencesRan2026 to 2026Enrolled1,500ConditionsIntensive Care (ICU), Intensive Care Unit (ICU) Admission, Intensive Care Unit Survivors, SID
3 · Its place in the literature

Who cites it

42 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  7. Development and Validation of a Multivariable Machine Learning Model for Mortality Prediction among Intensive Care Unit Patients.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2026
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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

6 authors.

Szymon CzajkaDepartment of Anesthesiology and Intensive Care, School of Medicine in Katowice, Medical University of Silesia, Katowice, Poland. szymon_czajka@wp.pl.ORCID 0000-0001-8942-6371
Katarzyna ZiębińskaStudents' Scientific Society, Department of Anesthesiology and Intensive Care, School of Medicine in Katowice, Medical University of Silesia, Katowice, Poland.
Konstanty MarczenkoStudents' Scientific Society, Department of Anesthesiology and Intensive Care, School of Medicine in Katowice, Medical University of Silesia, Katowice, Poland.
Barbara PosmykStudents' Scientific Society, Department of Anesthesiology and Intensive Care, School of Medicine in Katowice, Medical University of Silesia, Katowice, Poland.
Anna J SzczepańskaDepartment of Anesthesiology and Intensive Care, School of Medicine in Katowice, Medical University of Silesia, Katowice, Poland.
Łukasz J KrzychDepartment of Anesthesiology and Intensive Care, School of Medicine in Katowice, Medical University of Silesia, Katowice, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere are several scores used for in-hospital mortality prediction in critical illness. Their application in a local scenario requires validation to ensure appropriate diagnostic accuracy. Moreover, their use in assessing post-discharge mortality in intensive care unit (ICU) survivors has not been extensively studied. We aimed to validate APACHE II, APACHE III and SAPS II scores in short- and long-term mortality prediction in a mixed adult ICU in Poland. APACHE II, APACHE III and SAPS II scores, with corresponding predicted mortality ratios, were calculated for 303 consecutive patients admitted to a 10-bed ICU in 2016. Short-term (in-hospital) and long-term (12-month post-discharge) mortality was assessed.

resultsMedian APACHE II, APACHE III and SAPS II scores were 19 (IQR 12-24), 67 (36.5-88) and 44 (27-56) points, with corresponding in-hospital mortality ratios of 25.8% (IQR 12.1-46.0), 18.5% (IQR 3.8-41.8) and 34.8% (IQR 7.9-59.8). Observed in-hospital mortality was 35.6%. Moreover, 12-month post-discharge mortality reached 17.4%. All the scores predicted in-hospital mortality (p < 0.05): APACHE II (AUC = 0.78; 95%CI 0.73-0.83), APACHE III (AUC = 0.79; 95%CI 0.74-0.84) and SAPS II (AUC = 0.79; 95%CI 0.74-0.84); as well as mortality after hospital discharge (p < 0.05): APACHE II (AUC = 0.71; 95%CI 0.64-0.78), APACHE III (AUC = 0.72; 95%CI 0.65-0.78) and SAPS II (AUC = 0.69; 95%CI 0.62-0.76), with no statistically significant difference between the scores (p > 0.05). The calibration of the scores was good.

conclusionsAll the scores are acceptable predictors of in-hospital mortality. In the case of post-discharge mortality, their diagnostic accuracy is lower and of borderline clinical relevance. Further studies are needed to create scores estimating the long-term prognosis of subjects successfully discharged from the ICU.

Indexed as

APACHEHospital MortalityIntensive Care UnitsAgedCohort StudiesCritical IllnessFemaleHumansMaleMiddle AgedPolandPredictive Value of TestsProspective StudiesReproducibility of Results

Identifiers

PMID33267777
PMCPMC7709291

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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.