Longitudinal Study on Psychological Distress Trajectory and Influencing Factors of Kidney Transplant Patients: A Potential Category Analysis Study

Psychological distress in KTRs exhibits significant population heterogeneity. Clinicians can utilize patients' distress trajectory patterns and temperament characteristics to implement personalized care protocols, thereby reducing distress levels.

Authors

Institutions

Publication Details

Journal
Clinical Transplantation
Published
2025-09-01
DOI
https://doi.org/10.1111/ctr.70296
Primary Topic
Family Caregiving in Mental Illness
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Longitudinal Study on Psychological Distress Trajectory and Influencing Factors of Kidney Transplant Patients: A Potential Category Analysis Study

Xingwang Yao, Xiaoting Zheng
Clinical Transplantation
Family Caregiving in Mental Illness
article

Longitudinal Study on Psychological Distress Trajectory and Influencing Factors of Kidney Transplant Patients: A Potential Category Analysis Study

Xingwang Yao, Xiaoting Zheng
article en

Abstract

Psychological distress in KTRs exhibits significant population heterogeneity. Clinicians can utilize patients' distress trajectory patterns and temperament characteristics to implement personalized care protocols, thereby reducing distress levels.

Clinical TransplantationVol. 39(9)
Central South University (CN), Changsha University (CN), Second Xiangya Hospital of Central South University (CN)
Openalex Percentile: Top 68%
Family Caregiving in Mental Illness
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.