Evidence map›Paper›PMID 37227680›Full record

Observational studyInternal and emergency medicine2023

Association between input/weight ratio and acute kidney injury in obese critical ill patients: a propensity analysis of multicenter clinical databases.

Jiang Du, Dan Zhang, Jie Xie, Liu Wang, Yun Xie, Daonan Chen, Xiaoyin She, Jiang Hong, Ruilan Wang

Abstract readObservational StudyMulticenter Study
PubMed Publisher
In one paragraph

Observational study in Internal and emergency medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 90% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

9 authors at 1 institution in 1 country.

Jiang Du *Emergency & Critical Care Department, Shanghai General Hospital of Shanghai Jiaotong University School of Medicine, 650 Xin Songjiang Rd, Shanghai, China. gowindj@163.com.ORCID 0000-0002-8297-5359
Dan Zhang *Emergency & Critical Care Department, Shanghai General Hospital of Shanghai Jiaotong University School of Medicine, 650 Xin Songjiang Rd, Shanghai, China.
Jie Xie *Emergency & Critical Care Department, Shanghai General Hospital Jiading Branch of Shanghai Jiaotong University School of Medicine, 800 Huangjiahuayuan RD, 650 Xin Songjiang Rd, Shanghai, China.
Liu WangEmergency & Critical Care Department, Shanghai General Hospital of Shanghai Jiaotong University School of Medicine, 650 Xin Songjiang Rd, Shanghai, China.
Yun XieEmergency & Critical Care Department, Shanghai General Hospital of Shanghai Jiaotong University School of Medicine, 650 Xin Songjiang Rd, Shanghai, China.
Daonan ChenEmergency & Critical Care Department, Shanghai General Hospital of Shanghai Jiaotong University School of Medicine, 650 Xin Songjiang Rd, Shanghai, China.
Xiaoyin SheEmergency & Critical Care Department, Shanghai General Hospital Jiading Branch of Shanghai Jiaotong University School of Medicine, 800 Huangjiahuayuan RD, 650 Xin Songjiang Rd, Shanghai, China. 18917444639@163.com.
Jiang HongEmergency & Critical Care Department, Shanghai General Hospital of Shanghai Jiaotong University School of Medicine, 650 Xin Songjiang Rd, Shanghai, China. jhong.pku@163.com.
Ruilan WangEmergency & Critical Care Department, Shanghai General Hospital of Shanghai Jiaotong University School of Medicine, 650 Xin Songjiang Rd, Shanghai, China.
XinHua Hospital · CN

Funding

Clinical Research Innovation Plan of Shanghai General Hospital CTCCR-2018C10Interdisciplinary Program of Shanghai Jiao Tong University 06N1801046Research Program of Jading District Health Commission of Shanghai in 2022 2022-20
6 · The paper itself

Abstract

Rehydration volume may be underestimated in obese critically ill patients, which can lead to acute kidney injury (AKI). This study aimed to investigate the association between input/weight ratio (IWR) and AKI risk in obese critical patients. This retrospective observational study analyzed data from three large open databases. Patients were divided into lean and obese groups and matched 1:1 based on age, sex, APACHE II score, SOFA score, sepsis status, mechanical ventilation status, renal replacement therapy status, and hospital type. The exposure of interest was the mean IWR during the first three ICU admission days. The primary outcome was the incidence of AKI within 28 days after ICU admission. Cox regression analysis was used to evaluate the association between IWR and AKI risk. A total of 82,031 eligible patients were included in the study, with 25,427 obese patients matched with 25,427 lean patients. The IWRs were significantly lower in the obese groups in both the unmatched cohort (35.85 ± 19.05 vs. 46.01 ± 30.43 ml/kg, p < 0.01) and the matched cohort (36.13 ± 19.16 vs. 47.34 ± 31.13 ml/kg, p < 0.01). An increase in IWR was significantly associated with decreased creatinine levels, increased urine output and a lower AKI risk. The interaction terms of IWR and obesity were significantly associated with decreased AKI incidence in both the unmatched cohort (hazard ratio [HR] = 0.97, 95% CI 0.96-0.97, p < 0.01) and the matched cohort (HR = 0.97, 95% CI 0.96-0.97, p < 0.01). Inadequate rehydration of patients with obesity may contribute to an increased risk of AKI in patients with obesity. These results highlight the need for better rehydration management in patients with obesity.

Indexed as

Acute Kidney InjuryIntensive Care UnitsCritical IllnessHospitalizationHumansObesityRetrospective StudiesRisk FactorsAcute kidney injuryAcute renal failureBody mass indexObesityRehydration volumeSurvival

Identifiers

PMID37227680
OpenAlexW4378173533

What OpenQuestion holds

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Registered trials

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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.