Evidence map›Paper›PMID 38597157›Full record

ArticleThe Journal of clinical endocrinology and metabolism2024

Cystatin C Is a Predictor for Long-Term, All-Cause, and Cardiovascular Mortality in US Adults With Metabolic Syndrome.

Xiaoying Song, Lijiao Xiong, Tianting Guo, Xue Chen, Pinjun Zhang, Xiaoan Zhang, Zhen Liang

Open access · hybridAbstract read
In one paragraph

Article in The Journal of clinical endocrinology and metabolism, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
5.4field-weighted citation impact, top 3% 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

15 citing papers in PubMed, 16 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Xiaoying SongMedical Department, Ganzhou People's Hospital, Ganzhou, Jiangxi Province, 341000, China.
Lijiao XiongDepartment of Geriatrics, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518000, China.
Tianting GuoGanzhou Hospital of Guangdong Provincial People's Hospital (Ganzhou Municipal Hospital), Ganzhou, Jiangxi Province, 341000, China.
Xue ChenDepartment of Geriatrics, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518000, China.
Pinjun ZhangGannan Medical University, Ganzhou, Jiangxi Province, 341000, China.ORCID 0009-0001-4882-8646
Xiaoan ZhangGanzhou Hospital of Guangdong Provincial People's Hospital (Ganzhou Municipal Hospital), Ganzhou, Jiangxi Province, 341000, China.ORCID 0009-0008-7820-566X
Zhen LiangDepartment of Geriatrics, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518000, China.ORCID 0000-0003-4700-0203
Ganzhou People's Hospital · CNSouthern University of Science and Technology · CNGannan Medical University · CN

Funding

Ganzhou Municipal Science and Technology Plan Project 2023LNS26841Science and Technology Planning Project of Jiangxi Provincial Health Commission 202312146Science and Technology Planning Project of Shenzhen City, Guangdong Province, China JCYJ20200109142610136Science and Technology Program of Jiangxi Provincial Administration of Traditional Chinese Medicine 2020A0042
6 · The paper itself

Abstract

objectiveThis study examined the relationship between cystatin C (CysC) levels and all-cause, cardiovascular disease (CVD), and cancer mortality in US metabolic syndrome (MetS) patients.

methodsThe 1999-2002 National Health and Nutrition Examination Survey (NHANES) prospective cohort research included 1980 MetS participants. To assess CysC levels and all-cause, CVD, and cancer mortality, fitted curves, Kaplan-Meier survival curves, Cox regression analysis, and receiver operating characteristic curves were performed.

resultsDuring a mean follow-up of 15.3 ± 5.4 years, a total of 819 deaths occurred. The fitted and Kaplan-Meier survival curves revealed that greater CysC levels were linked to higher all-cause, CVD, and cancer mortality rates (P < .05). After adjusting for variables, CysC level was associated with all-cause, CVD, and cancer mortality at 1.63 (1.42-1.88), 1.53 (1.19-1.95), and 1.53 (1 ∼ 2.32), respectively (P < .05). Tertile models showed consistent results: high CysC Tertile participants showed higher risk of all-cause mortality (HR 1.87; 1.43-2.45), CVD mortality (HR 1.97, 1.15 ∼ 3.38), and cancer mortality (HR 1.72, 1.01 ∼ 2.91) compared to those in the lowest tertile (P < .05). Subgroup studies by sex and other characteristics confirmed the findings. CysC demonstrated the higher predictive efficacy across mortality outcomes, followed by eGFR, outperforming urea nitrogen, creatinine, uric acid, and C-reactive protein. CysC alone exhibited substantial predictive value for all-cause (AUC 0.773; P < .05) and CVD mortality (AUC 0.726; P < .05). Combining CysC with age enhanced predictive value for all-cause mortality to 0.861 and CVD mortality to 0.771 (P < .05).

conclusionMetS patients with elevated CysC levels have a higher risk of all-cause, CVD, and cancer death. CysC may predict MetS all-cause and CVD mortality.

Indexed as

Cardiovascular DiseasesCystatin CMetabolic SyndromeNeoplasmsNutrition SurveysAdultAgedBiomarkersCause of DeathFemaleFollow-Up StudiesHumansMaleMiddle AgedPredictive Value of TestsPrognosisBiomarkersCST3 protein, humanCystatin Call-cause mortalitycancer mortalityCVD mortalityCystatin Cmetabolic syndromeprognostic marker

Identifiers

PMID38597157
PMCPMC11479697
OpenAlexW4394653847

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.