Evidence map›Paper›PMID 28392700›Full record

ArticleTherapeutics and clinical risk management2017

Urinary cadmium levels predict mortality of patients with acute heart failure.

Ching-Wei Hsu, Cheng-Hao Weng, Cheng-Chia Lee, Dan-Tzu Lin-Tan, Pao-Hsien Chu, Kuan-Hsing Chen, Tzung-Hai Yen, Wen-Hung Huang

Abstract read
In one paragraph

Article in Therapeutics and clinical risk management, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

8 authors.

Ching-Wei HsuDepartment of Nephrology, Division of Clinical Toxicology, Chang Gung Memorial Hospital, Taipei, Taiwan, ROC; Department of Nephrology, Division of Clinical Toxicology, Linkou Medical Center, Taoyuan, Taiwan, ROC; Chang Gung University and School of Medicine, Taoyuan, Taiwan, ROC.
Cheng-Hao WengDepartment of Nephrology, Division of Clinical Toxicology, Chang Gung Memorial Hospital, Taipei, Taiwan, ROC; Department of Nephrology, Division of Clinical Toxicology, Linkou Medical Center, Taoyuan, Taiwan, ROC; Chang Gung University and School of Medicine, Taoyuan, Taiwan, ROC.
Cheng-Chia LeeDepartment of Nephrology, Division of Clinical Toxicology, Chang Gung Memorial Hospital, Taipei, Taiwan, ROC; Department of Nephrology, Division of Clinical Toxicology, Linkou Medical Center, Taoyuan, Taiwan, ROC; Chang Gung University and School of Medicine, Taoyuan, Taiwan, ROC.
Dan-Tzu Lin-TanDepartment of Nephrology, Division of Clinical Toxicology, Chang Gung Memorial Hospital, Taipei, Taiwan, ROC; Department of Nephrology, Division of Clinical Toxicology, Linkou Medical Center, Taoyuan, Taiwan, ROC; Chang Gung University and School of Medicine, Taoyuan, Taiwan, ROC.
Pao-Hsien ChuChang Gung University and School of Medicine, Taoyuan, Taiwan, ROC; Division of Cardiology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan, ROC.
Kuan-Hsing ChenDepartment of Nephrology, Division of Clinical Toxicology, Chang Gung Memorial Hospital, Taipei, Taiwan, ROC; Department of Nephrology, Division of Clinical Toxicology, Linkou Medical Center, Taoyuan, Taiwan, ROC; Chang Gung University and School of Medicine, Taoyuan, Taiwan, ROC.
Tzung-Hai YenDepartment of Nephrology, Division of Clinical Toxicology, Chang Gung Memorial Hospital, Taipei, Taiwan, ROC; Department of Nephrology, Division of Clinical Toxicology, Linkou Medical Center, Taoyuan, Taiwan, ROC; Chang Gung University and School of Medicine, Taoyuan, Taiwan, ROC.
Wen-Hung HuangDepartment of Nephrology, Division of Clinical Toxicology, Chang Gung Memorial Hospital, Taipei, Taiwan, ROC; Department of Nephrology, Division of Clinical Toxicology, Linkou Medical Center, Taoyuan, Taiwan, ROC; Chang Gung University and School of Medicine, Taoyuan, Taiwan, ROC.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute heart failure (AHF) is a serious condition that is associated with increased mortality in critically ill patients. Previous studies indicated that environmental exposure to cadmium increases mortality of general populations. However, the relationship of cadmium exposure and mortality is unclear for AHF patients. MATERIALS AND

methodsA total of 153 patients with AHF in intensive care units (ICUs) met the inclusion criteria and were followed up for 6 months. Demographic data, AHF etiology, hematological and biochemical data, and hospital mortality were recorded. The scores of two predictive systems (Sequential Organ Failure Assessment [SOFA], Acute Physiology and Chronic Health Evaluation II [APACHE II]) for mortality in critically ill patients were calculated, and urinary cadmium levels were recorded.

resultsAt the end of the follow-up period, the mortality rate was 24.8%. The survivors (n=115) had higher urinary cadmium levels on day 1 (D1UCd) of ICU admission than non-survivors (n=38). A multiple linear regression analysis revealed a positive correlation between D1UCd and acute kidney injury, but a negative correlation between D1UCd and the level of serum albumin. A multivariate Cox analysis indicated that D1UCd was an independent predictor of mortality in AHF patients. For each increment of 1 μg of D1UCd, the hazard ratio for ICU mortality was 1.20 (95% confidence interval [CI]: 1.09-1.32,

conclusionThe D1UCd may serve as a single predictor of hospital mortality for AHF patients in the ICU. Because of the high mortality and smaller sample size, more investigations are required to confirm these observations and elucidate the underlying mechanisms.

Indexed as

acute heart failurecadmiumhospital mortalityintensive care unit

Identifiers

PMID28392700
PMCPMC5375634

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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.