Evidence map›Paper›PMID 38540653›Full record

ArticleHealthcare (Basel, Switzerland)2024

Factors Influencing Morbidity and Mortality Rates in Tertiary Intensive Care Units in Turkey: A Retrospective Cross-Sectional Study.

Ümit Murat Parpucu, Onur Küçük, Semih Aydemir

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 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

3 authors.

Ümit Murat ParpucuDepartment of Anesthesiology and Reanimation, Gülhane Faculty of Health Sciences, University of Health Sciences, 06010 Ankara, Türkiye.
Onur KüçükDepartment of Anesthesiology and Reanimation, Ankara Atatürk Sanatoryum Training and Research Hospital, University of Health Sciences, 06290 Ankara, Türkiye.ORCID 0000-0001-5534-7579
Semih AydemirDepartment of Anesthesiology and Reanimation, Yenimahalle Training and Research Hospital, University of Yıldırım Beyazıt, 06370 Ankara, Türkiye.ORCID 0000-0002-1087-3070

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesThe objective of this study was to determine the correlation between the prognosis of patients admitted to a tertiary intensive care unit (ICU) and the admitted patient population, intensive care conditions, and the workload of intensive care staff. MATERIALS AND

methodsThis was a retrospective cross-sectional study that analyzed data from all tertiary ICUs (a minimum of 40 and a maximum of 59 units per month) of eight training and research hospitals between January 2022 and May 2023. We compared monthly data across hospitals and analyzed factors associated with patient prognosis, including mortality and pressure injuries (PIs).

resultsThis study analyzed data from 54,312 patients, of whom 51% were male and 58.8% were aged 65 or older. The median age was 69 years. The average number of tertiary ICU beds per unit was 15 ± 6 beds, and the average occupancy rate was 83.57 ± 19.28%. On average, 7 ± 9 pressure injuries (PI) and 10 ± 7 patient deaths per unit per month were reported. The mortality rate (18.66%) determined per unit was similar to the expected rate (15-25%) according to the Acute Physiology and Chronic Health Evaluation (APACHE) II score. There was a statistically significant difference among hospitals on a monthly basis across various aspects, including bed occupancy rate, length of stay (LOS), number of patients per ICU bed, number of patients per nurse in a shift, rate of patients developing PI, hospitalization rate from the emergency department, hospitalization rate from wards, hospitalization rate from the external center, referral rate, and mortality rate (

conclusionsAlthough generally reliable in predicting prognosis in tertiary ICUs, the APACHE II scoring system may have limitations when analyzed on a unit-specific basis. ICU-related conditions have an impact on patient prognosis. ICU occupancy rate, work intensity, patient population, and number of working nurses are important factors associated with ICU mortality. In particular, data on the patient population admitted to the unit (emergency patients and patients with a history of malignancy) were most strongly associated with unit mortality.

Indexed as

APACHEcritical careintensive care units/standardsintensive care units/statistics and numerical datamortalitynurse–patient ratiospressure injury

Identifiers

PMID38540653
PMCPMC10969906

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