Evidence map›Paper›PMID 33841963›Full record

ArticleJournal of thoracic disease2021

Serum creatinine as a predictor of mortality in patients readmitted to the intensive care unit after cardiac surgery: a retrospective cohort study in China.

Jun Zhong, Jian Gao, Jing-Chao Luo, Ji-Li Zheng, Guo-Wei Tu, Yan Xue

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 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

6 authors.

Jun ZhongDepartment of Nursing, Zhongshan Hospital, Fudan University, Shanghai, China.
Jian GaoDepartment of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai, China.
Jing-Chao LuoDepartment of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Ji-Li ZhengDepartment of Nursing, Zhongshan Hospital, Fudan University, Shanghai, China.
Guo-Wei TuDepartment of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Yan XueDepartment of Nursing, Zhongshan Hospital, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients readmitted to the intensive care unit (ICU) after cardiac surgery have a high mortality rate. The relationship between renal function and in-hospital mortality in readmitted patients has not been well demonstrated.

methodsWe retrospectively evaluated cardiac surgery patients who were readmitted to the ICU at least once. Data on serum creatinine levels before surgery and on the day of ICU readmission were collected. The estimated glomerular filtration rate (eGFR) was calculated according to the creatinine-based Chronic Kidney Disease-Epidemiology Collaboration equation. We used logistic regression models and restricted cubic spline curves with four knots (5%, 35%, 65%, 95%) to investigate the relationship between renal function indicators and mortality.

resultsOf the 184 patients evaluated, 30 patients died during hospitalization, yielding a mortality rate of 16.30%. Cardiac dysfunction (n=84, 45.65%) and respiration disorder (n=51, 27.72%) were the most common reasons for ICU readmission. Creatinine [odds ratio (OR): 1.14, 95% confidence interval (CI): 1.07-1.25] and eGFR (OR: 0.95, 95% CI: 0.93-0.98) were independently associated with in-hospital mortality after adjusting for various confounders. Both creatinine level and eGFR had a linear association with in-hospital mortality (P for non-linearity ˃0.05).

conclusionRenal function is significantly associated with the in-hospital mortality of patients readmitted to the ICU after cardiac surgery, as evidenced by the independent correlation of both creatinine and eGFR with in-hospital mortality.

Indexed as

cardiac surgeryintensive care unit (ICU)mortalityReadmissionserum creatinine (SCR)

Identifiers

PMID33841963
PMCPMC8024843

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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.