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Analysis of risk factors and establishment of a risk prediction model for post-transplant diabetes mellitus after kidney transplantation.
Cheng, Fang; Li, Qiang; Wang, Jinglin; Wang, Zhendi; Zeng, Fang; Zhang, Yu.
Afiliación
  • Cheng F; Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
  • Li Q; Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, Wuhan 430022, China.
  • Wang J; Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
  • Wang Z; Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, Wuhan 430022, China.
  • Zeng F; Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
  • Zhang Y; Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, Wuhan 430022, China.
Saudi Pharm J ; 30(8): 1088-1094, 2022 Aug.
Article en En | MEDLINE | ID: mdl-36164572
ABSTRACT

Introduction:

Post-transplant diabetes mellitus (PTDM) is a known side effect in transplant recipients administered immunosuppressant drugs, such as tacrolimus. This study aimed to investigate the risk factors related to PTDM, and establish a risk prediction model for PTDM. In addition, we explored the effect of PTDM on the graft survival rate of kidney transplantation recipients.

Methods:

Patients with pre-diabetes mellitus before kidney transplant were excluded, and 495 kidney transplant recipients were included in our study, who were assigned to the non-PTDM and PTDM groups. The cumulative incidence was calculated at 3 months, 6 months, 1 year, 2 years, and 3 years post-transplantation. Laboratory tests were performed and the tacrolimus concentration, clinical prognosis, and adverse reactions were analyzed. Furthermore, binary logistic regression analysis was used to identify the independent risk factors of PTDM.

Results:

Age ≥ 45 years (adjusted odds ratio [aOR] 2.25, 95% confidence interval [CI] 1.14-3.92; P = 0.015), body mass index (BMI) > 25 kg/m2 (aOR 3.12, 95% CI 2.29-5.43, P < 0.001), tacrolimus concentration > 10 ng/mL during the first 3 months post-transplantation (aOR 2.46, 95%CI 1.41-7.38; P < 0.001), transient hyperglycemia (aOR 4.53, 95% CI 1.86-8.03; P < 0.001), delayed graft function (DGF) (aOR 1.31, 95% CI 1.05-2.39; P = 0.019) and acute rejection (aOR 2.16, 95% CI 1.79-4.69; P = 0.005) were identified as independent risk factors of PTDM. The PTDM risk prediction model was developed by including the above six risk factors, and the area under the receiver operating characteristic curve was 0.916 (95% CI 0.862-0.954, P < 0.001). Furthermore, the cumulative graft survival rate was significantly higher in the non- PTDM group than in the PTDM group.

Conclusions:

Risk factors related to PTDM were age ≥ 45 years, BMI > 25 kg/m2, tacrolimus concentration > 10 ng/mL during the first 3 months post-transplantation, transient hyperglycemia, DGF and acute rejection.
Palabras clave

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Saudi Pharm J Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Saudi Pharm J Año: 2022 Tipo del documento: Article País de afiliación: China