| Literature DB >> 32349684 |
Yanan Shi1, Jiajie Cai1, Chunxia Shi1, Conghui Liu1, Zhongxin Li2.
Abstract
BACKGROUND: Dialysis patients are at high risk of developing glucose metabolism disturbances (GMDs), such as diabetes mellitus (DM), impaired fast glucose (IFG), and impaired glucose tolerance (IGT). However, it is unclear about the incidence of GMDs in Chinese patients with peritoneal dialysis (PD), as well as the influence of new-onset DM (NODM) on the prognosis of PD patients. Therefore, we conducted this meta-analysis to address these issues.Entities:
Keywords: Diabetes mellitus; Glucose metabolism disturbances; Meta-analysis; Peritoneal dialysis
Year: 2020 PMID: 32349684 PMCID: PMC7191695 DOI: 10.1186/s12882-020-01820-x
Source DB: PubMed Journal: BMC Nephrol ISSN: 1471-2369 Impact factor: 2.388
Fig. 1Eligibility of studies for inclusion in meta-analysis
Baseline characteristics of patients in the trials included in the meta-analysis
| Study | Study design | Dialysis modality | No. of patients | Male/female | Age (mean ± SD, y) | Follow-up (months) | NOS score |
|---|---|---|---|---|---|---|---|
| Tien KJ [ | Cohort | PD/HD | 3346 | 1398/1948 | NA | 53.2 | 7 |
| 22,820 | 10,784/12036 | NA | |||||
| Szeto CC [ | Cohort | CAPD | 252 | 135/117 | 59 ± 13 | 45.4 ± 26.5 | 6 |
| Yu XF [ | Cohort | CAPD | 145 | 60/85 | 62 ± 15 | 48 | 6 |
| Wang IK [ | Cohort | PD/HD | 6177 | 2665/3512 | 51.0 | 49.44 ± 34.32 | 8 |
| 6177 | 2726/3451 | 51.2 | 52.36 ± 37.2 | 7 | |||
| Wu PP [ | Cohort | PD/HD | 2228 | 1096/1132 | 60.29 ± 16.43 | 64.2 ± 47.04 | 7 |
| 8912 | 4384/4528 | 60.29 ± 16.43 | 73.68 ± 47.4 | ||||
| Dong J [ | Cohort | PD | 32 | 9/23 | 61 ± 12.5 | 32.4 (12.9–60.8) | 6 |
| 580 | 256/324 | 55.2 ± 15.4 | |||||
| Chou CY [ | Cohort | PD/HD | 2548 | 916/1632 | 50.2 ± 14.7 | 70 | 7 |
| 10,192 | 3692/6500 | 50.3 ± 14.5 | |||||
| Cheng SC [ | Cohort | CAPD | 14 | 5/9 | 46.4 ± 12.0 | 39.9 ± 28.3 | 6 |
| 21 | 7/14 | 42.4 ± 9.4 | 60.5 ± 37.8 | ||||
| Song ZP [ | Cohort | PD | 42 | NA | 60.2 ± 2.3 | NA | 6 |
| 42 | NA | 60.2 ± 2.3 | |||||
| Yang G [ | Cohort | PD | 40 | NA | 58.4 ± 4.7 | NA | 6 |
| 42 | NA | 58.4 ± 4.7 | |||||
| Ye SH [ | Cohort | PD | 44 | 24/20 | 60.14 ± 2.69 | NA | 6 |
| 44 | 25/19 | 60.78 ± 2.98 | |||||
| Peng XY [ | Cohort | CAPD | 138 | 83/55 | 57 (46–71) | NA | 7 |
| 69 | 38/31 | 56 (42–71) | |||||
| Xia P [ | Cohort | CAPD/APD | 442 | 228/214 | 58.4 ± 15.6 | NA | 6 |
| 92 | 53/39 | 56.7 ± 16.0 | NA | ||||
| Fei JY [ | Cohort | CAPD | 286 | 148/138 | 58 (13–85) | 3–120 | 6 |
| Li Y [ | Cohort | PD | 577 | 280/297 | 58.9 ± 15.5 | NA | 6 |
: SD standard deviation, PD Peritoneal dialysis, HD hemodialysis, CAPD continuous ambulatory PD, APD, automated PD
Fig. 2Forest plot showing the incidence of glucose metabolism disturbances in dialysis patients
Fig. 3Forest plot showing the influence of NODM on the prognosis of PD patients
Fig. 4Forest plot showing the comparison between PD and HD in the incidence of NODM
Outcome comparison between this and previous studies
| Xue C, et al. | Our study | |
|---|---|---|
| Number of included studies | 9 | 15 |
| Total sample size | 13,879 | 56,390 |
| Population | Dialysis patients | Chinese dialysis patients |
| Incidence of NODM | 8% (95%CI: 4, 12%) | 12% (95%CI: 9, 15%) |
| Incidence of NOIGT | 15% (95%CI: 3, 31%) | 17% (95%CI: 4, 10%) |
| Incidence of NOIFG | 32% (95%CI: 27, 37%) | 32% (95%CI: 3, 30%) |
| Mortality rate in PD patients | HR = 1.06, 95%CI: 1.01, 1.44 | HR = 1.59, 95%CI: 1.28, 1.98 |
| Incidence of NODM between PD and HD | RR = 0.99, 95%CI: 0.69, 1.40 | RR = 1.23, 95%CI: 0.61, 2.51 |
: PD Peritoneal dialysis, HD hemodialysis, NODM new-onset diabetes mellitus, NOIFG new-onset impaired fast glucose, NOIGT new-onset impaired glucose tolerance, RR risk ratio, HR hazard ratio, CI confidence intervals