Evidence map›Paper›PMID 36117592›Full record

ArticleFrontiers in public health2022

A simple nomogram for predicting infectious diseases in adult kidney transplantation recipients.

Ruo-Yang Chen, Sheng Zhang, Shao-Yong Zhuang, Da-Wei Li, Ming Zhang, Cheng Zhu, Yue-Tian Yu, Xiao-Dong Yuan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 30% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
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 at 3 institutions in 1 country.

Ruo-Yang ChenDepartment of Urology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
Sheng ZhangDepartment of Critical Care Medicine, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Shao-Yong ZhuangDepartment of Urology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
Da-Wei LiDepartment of Urology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
Ming ZhangDepartment of Urology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
Cheng ZhuDepartment of Disease Prevention and Control, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Yue-Tian YuDepartment of Critical Care Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Xiao-Dong YuanDepartment of Urology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
Renji Hospital · CNRuijin Hospital · CNShanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the risk factors of infectious diseases in adult kidney transplantation recipients and to establish a simple and novel nomogram to guide the prophylactic antimicrobial therapy. Methods: Patients who received kidney transplantation between January 2018 and October 2021 were included in the study and were divided into a training and a testing set at a 1:1 ratio. Risk factors correlated to infectious diseases were selected using a Least Absolute Shrinkage and Selection Operator (LASSO) regression model. The prediction model was built by incorporating the variables selected by the LASSO model into a logistic regression equation. Calibration curves and receiver operating characteristic (ROC) curves were also applied to assess the model calibration and discrimination. A nomogram consisting of the selected factors was established to provide individualized risks of developing infections. Decision curve analysis (DCA) was adopted to estimate the net benefit and reduction in interventions for a range of clinically reasonable risk thresholds. Results: In all, 863 adult kidney recipients were included in the study, and 407 (47.16%) of them developed infectious diseases during the 3-year follow-up period. A total of 8 variables were selected using LASSO regression and were retained for subsequent model construction and infection prediction. The area under the curve (AUC) was 0.83 and 0.81 in the training and testing sets, with high F scores of 0.76 and 0.77, sensitivity of 0.76 and 0.81, and specificity of 0.88 and 0.74, respectively. A novel nomogram was developed based on 8 selected predictors (requirement for albumin infusion, requirement for red blood cell infusion, triglyceride, uric acid, creatinine, globulin, neutrophil percentage, and white blood cells). The net benefit indicated that the nomogram would reduce unnecessary interventions at a wide range of threshold probabilities in both sets. Conclusions: Adult kidney transplantation recipients are high-risk hosts for infectious diseases. The novel nomogram consisting of 8 factors reveals good predictive performance and may promote the reasonable antimicrobial prescription. More external validations are required to confirm its effectiveness for further clinical application.

Indexed as

Communicable DiseasesKidney TransplantationAdultAlbuminsCreatinineHumansNomogramsTriglyceridesUric AcidAlbuminsCreatinineTriglyceridesUric Acidinfectious diseasekidney transplantationnomogramprediction modelsolid organ transplantation

Identifiers

PMID36117592
PMCPMC9471136
OpenAlexW4293727934

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.