Evidence map›Paper›PMID 35034618›Full record

ArticleBMC nephrology2022

Prediction of chronic kidney disease after orthotopic liver transplantation: development and validation of a nomogram model.

Dandan Guo, Huifang Wang, Jun Liu, Hang Liu, Ming Zhang, Zixuan Fu, Xuemei Liu

Abstract readValidation Study
In one paragraph

Article in BMC nephrology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Incidence and Risk Factors for Progression of Acute Kidney Injury to Chronic Kidney Disease After Liver Transplantation: A Retrospective Cohort Study.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025
    Article
4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Dandan GuoDepartment of Nephrology, The Affiliated Hospital of Qingdao University, No. 16 Jiangsu Road, Qingdao, 266003, Shandong, China.
Huifang WangDepartment of Nephrology, The Affiliated Hospital of Qingdao University, No. 16 Jiangsu Road, Qingdao, 266003, Shandong, China.
Jun LiuDepartment of Nephrology, The Affiliated Hospital of Qingdao University, No. 16 Jiangsu Road, Qingdao, 266003, Shandong, China.
Hang LiuDepartment of Nephrology, The Affiliated Hospital of Qingdao University, No. 16 Jiangsu Road, Qingdao, 266003, Shandong, China.
Ming ZhangDepartment of Nephrology, The Affiliated Hospital of Qingdao University, No. 16 Jiangsu Road, Qingdao, 266003, Shandong, China.
Zixuan FuDepartment of Nephrology, The Affiliated Hospital of Qingdao University, No. 16 Jiangsu Road, Qingdao, 266003, Shandong, China.
Xuemei LiuDepartment of Nephrology, The Affiliated Hospital of Qingdao University, No. 16 Jiangsu Road, Qingdao, 266003, Shandong, China. liuxuemei201718@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe aimed to develop and validate a nomogram model for predicting CKD after orthotopic liver transplantation (OLT).

methodsThe retrospective data of 399 patients who underwent transplantation and were followed in our centre were collected. They were randomly assigned to the training set (n = 293) and validation set (n = 106). Multivariable Cox regression analysis was performed in the training set to identify predictors of CKD. According to the Cox regression analysis results, a nomogram model was developed and validated. The renal function of recipients was monitored, and the long-term survival prognosis was assessed.

resultsThe incidence of CKD at 5 years after OLT was 25.6%. Cox regression analysis identified several predictors of post-OLT CKD, including recipient age at surgery (HR 1.036, 95% CI 1.006-1.068; p = 0.018), female sex (HR 2.867, 95% CI 1.709-4.810; p < 0.001), preoperative hypertension (HR 1.670, 95% CI 0.962-2.898; p = 0.068), preoperative eGFR (HR 0.996, 95% CI 0.991-1.001; p = 0.143), uric acid at 3 months (HR 1.002, 95% CI 1.001-1.004; p = 0.028), haemoglobin at 3 months (HR 0.970, 95% CI 0.956-0.983; p < 0.001), and average concentration of cyclosporine A at 3 months (HR 1.002, 95% CI 1.001-1.003; p < 0.001). According to these parameters, a nomogram model for predicting CKD after OLT was constructed and validated. The C-indices were 0.75 and 0.80 in the training and validation sets. The calibration curve of the nomogram showed that the CKD probabilities predicted by the nomogram agreed with the observed probabilities at 1, 3, and 5 years after OLT (p > 0.05). Renal function declined slowly year by year, and there were significant differences between patients divided by these predictors. Kaplan-Meier survival analysis showed that the survival prognosis of recipients decreased significantly with the progression of renal function.

conclusionsWith excellent predictive abilities, the nomogram may be a simple and reliable tool to identify patients at high risk for CKD and poor long-term prognosis after OLT.

Indexed as

Liver TransplantationNomogramsAdultFemaleHumansMaleMiddle AgedPostoperative ComplicationsRenal Insufficiency, ChronicRetrospective StudiesChronic kidney diseaseNomogram modelOrthotopic liver transplantationPrognosis

Identifiers

PMID35034618
PMCPMC8761273

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