| Literature DB >> 33466123 |
Sheng Wan1, Hongdan Tian, Li Cheng, Yanqiong Ding, Qing Luo, Yanmin Zhang.
Abstract
ABSTRACT: We aimed to investigate the hypothesis that serum triglyceride (TG) may be an independent predictor of early-onset peritonitis and prognosis in incident continuous ambulatory peritoneal dialysis (CAPD) patients.In this retrospective, observational study, we screened 291 adults admitted to the PD center of the Wuhan No. 1 hospital from August 1, 2013 to November 31, 2017. All biochemical data were collected at the first 1 to 3 months after the initiation of CAPD. Early-onset peritonitis was defined as peritonitis occurring within 6 months after the initiation of PD. All of PD patients were followed up to July 31, 2018. The primary endpoint was the incidence of early-onset peritonitis while the second endpoints included overall mortality and technical failure.A total of 38 patients occurred early-onset PD peritonitis and the Lasso logistic regression selected TG and age in the final model for early-onset peritonitis. We divided patients into two groups based on the median baseline TG levels: TG ≥ 1.4mmo/L group (n = 143) and TG < 1.4mmol/L group (n = 148). There were 34 (11.7%) patients died and 33 (11.3%) patients transferred to hemodialysis during the follow-up, Moreover, a level of TG ≥ 1.4mmol/L at the initiation of CAPD was associated with a significantly increased probability of technical failure (hazard ratio, HR, 1.30; 95% confidence interval, 95% CI, 1.09 to 2.19, P = .043) and overall mortality (HR, 2.33; 95% CI, 1.16-4.72, P = .018).Serum TG levels measured at the initiation of PD therapy is an independent predictor of early-onset peritonitis and prognosis of CAPD patients.Entities:
Mesh:
Substances:
Year: 2021 PMID: 33466123 PMCID: PMC7808518 DOI: 10.1097/MD.0000000000023673
Source DB: PubMed Journal: Medicine (Baltimore) ISSN: 0025-7974 Impact factor: 1.817
Figure 1Study flow, including patient enrollment and outcomes.
Baseline characteristics of the CAPD patients.
| Characteristics | TG ≧ 1.4mmol/L (n = 143) | TG < 1.4mmol/L (n = 148) | |
| Age, year | 54.5 ± 13.9 | 51.5 ± 14.3 | .078 |
| Gender, male, n (%) | 85 (59.4) | 66 (44.6) | .054 |
| BMI, kg/m2 | 22.8 ± 4.2 | 22.2 ± 3.6 | .182 |
| Primary cause of ESRD | .326 | ||
| Glomerulonephritis, n (%) | 63 (42.6) | ||
| Diabetic nephropathy, n (%) | 25 (17.5) | 23 (15.5) | |
| Hypertension, n (%) | 28 (19.6) | 25 (16.9) | |
| Reflux nephropathy, n (%) | 10 (7.0) | 9 (6.1) | |
| Other or unknown, n (%) | 22 (15.4) | 28 (18.9) | |
| Comorbidities | |||
| Coronary artery disease, n (%) | 57 (39.9) | 59 (39.9) | .634 |
| Hypertension, n (%) | 117 (81.8) | 122 (82.4) | .164 |
| Diabetes, n (%) | 29 (20.3) | 40 (27.0) | .094 |
| Treatments | |||
| Statin/fibrate, n (%) | 17 (11.9) | 19 (12.8) | .762 |
| ACEI/ARB, n (%) | 47 (32.9) | 42 (28.4) | .660 |
| β-blockers, n (%) | 73 (51.0) | 77 (52.0) | .442 |
| CCB, n (%) | 105 (70.9) | 111 (77.6) | .194 |
| Diuretic, n (%) | 38 (25.7) | 31 (21.7) | .425 |
| SBP, mmHg | 141.5 ± 14.4 | 144.9 ± 16.1 | .064 |
| DBP, mmHg | 82.9 ± 10.7 | 84.0 ± 11.2 | .390 |
| MAP, mmHg | 102.4 ± 10.2 | 104.3 ± 11.1 | .140 |
| Dialysis dose | |||
| Weekly total Ccr | 71.8 ± 11.7 | 72.8 ± 15.5 | .349 |
| Weekly kidney Ccr | 36.7 ± 10.7 | 34.6 ± 10.5 | .609 |
| Weekly total Kt/Vurea | 2.5 ± 0.6 | 2.1 ± 0.6 | .354 |
| Weekly peritoneal Kt/Vurea | 0.6 ± 0.1 | 0.7 ± 0.2 | .855 |
| Residual GFR (ml/min/1.73m2) | 5.3 ± 1.0 | 4.8 ± 0.9 | .386 |
| PET at baseline | 0.7 ± 0.1 | 0.7 ± 0.2 | .542 |
| Laboratory variables | |||
| Leukocyte, × 109/L | 5.9 ± 1.8 | 6.7 ± 2.2 | <.001 |
| Erythrocyte, × 1012/L | 3.3 ± 0.6 | 3.5 ± 0.7 | .012 |
| Hemoglobin, g/L | 95.5 ± 16.8 | 101.4 ± 19.3 | .006 |
| Serum albumin, g/L | 34.7 ± 5.3 | 36.9 ± 5.2 | <.001 |
| Total cholesterol, mmol/L | 5.2 ± 1.8 | 4.3 ± 1.1 | <.001 |
| Serum triglyceride, mmol/L | 2.4 ± 0.6 | 1.0 ± 0.3 | <.001 |
| HDL-C, mmol/L | 1.1 ± 0.2 | 1.2 ± 0.3 | .390 |
| LDL-C, mmol/L | 3.5 ± 0.6 | 2.6 ± 0.5 | .023 |
| Calcium, mmol/L | 2.2 ± 0.3 | 3.4 ± 0.5 | .363 |
| Phosphorus, mmol/L | 1.5 ± 0.4 | 1.5 ± 0.5 | .706 |
| Potassium, mmol/L | 4.1 ± 0.7 | 4.1 ± 0.6 | .856 |
| Sodium, mmol/L | 151.1 ± 29.1 | 142.3 ± 23.1 | .335 |
| Alkaline phosphatase, U/L | 97.3 ± 17.1 | 79.0 ± 10.1 | .150 |
| Blood urea nitrogen, mmol/L | 17.7 ± 6.7 | 20.7 ± 12.0 | .397 |
| Serum creatinine, umol/L | 759.9 ± 212.6 | 718.0 ± 215.7 | .137 |
| Uric acid, umol/L | 408.8 ± 99.0 | 422.3 ± 85.9 | .214 |
| Outcomes | |||
| Early peritonitis | 28 (18.9) | 10 (7.0) | .015 |
| Overall mortality | 23 (16.1) | 11 (7.4) | .022 |
| Technical failure | 47 (31.8) | 20 (14.0) | .018 |
ACEI/ARB = angiotensin-converting enzyme inhibitors/ angiotensin receptor blocker, BMI = body mass index, CCB = calcium channel blockers, CRP = c-reactive protein, DBP = diastolic blood pressure, GFR = glomerular filtration rate, HDL-C = high-density lipoprotein cholesterol, iPTH = intact parathyroid hormone, LDL-C = low-density lipoprotein cholesterol, MAP = mean arterial pressure, PET = peritoneal equilibration test, SBP = systolic blood pressure.
Figure 2Selection of informative factors associated with early-onset peritonitis using the LASSO logistic regression model. (A) LASSO coefficient profiles of the 37 clinical features. (B) Selection of the tuning parameter (λ). (C) Histogram shows the coefficients of individual features that contribute to the final logistic model.
Figure 3ROC analyses for predicting early-onset peritonitis (A), technical failure (B) and overall mortality (C).
Cox proportional hazards analysis for overall mortality and technical failure.
| Unadjusted | Model 1 | Model 2 | Model 3 | |||||
| TG levels | HR (95% CI) | HR (95% CI) | HR (95% CI) | HR (95% CI) | ||||
| For overall mortality | ||||||||
| Continuous | 1.54 (1.19–1.99) | <.001 | 1.35 (1.17–1.56) | <.001 | 1.26 (1.13–1.40) | <.001 | 1.22 (1.10–1.35) | <.001 |
| hypertriglyceridemia | 2.22 (1.10–4.50) | .027 | 1.81 (0.85–3.82) | .123 | 1.38 (0.26–5.22) | .633 | 1.26 (0.32–4.89) | .739 |
| TG ≥ 1.4mmol/L | 2.16 (1.05–4.43) | .001 | 1.82 (1.61–2.07) | .029 | 1.48 (1.20–1.84) | .035 | 1.30 (1.09–2.19) | .043 |
| For technical failure | ||||||||
| Continuous | 1.28 (1.08–1.51) | .004 | 1.18 (1.04–1.33) | .012 | 1.13 (1.02–1.25) | .022 | 1.04 (1.01–1.06) | .031 |
| hypertriglyceridemia | 1.44 (0.84–2.47) | .189 | 1.38 (0.79–2. 42) | .263 | 1.26 (0.45–3.52) | .670 | 1.11 (0.37–3.32) | .846 |
| TG ≥ 1.4mmol/L | 2.37 (1.40–4.02) | <.001 | 2.49 (1.46–4.24) | .001 | 2.30 (1.21–4.39) | .012 | 2.33 (1.16–4.72) | .018 |
95%CI = 95% confidence index, HR = hazard ratio, TG = triglyceride.
Adjustment in Model 1: age, sex, major comorbid conditions (diabetes, hypertension, cardiovascular disease) and medication use (ACEI/ARB, β-blockers, CCB and Statin/fibrate); Model 2: Model 1 plus malnutrition and inflammation indices that included BMI, MAP, serum total cholesterol, HDL-C, LDL-C, serum albumin, ferritin, CRP levels and serum electrolyte; Model 3 (fully adjusted model): Model 2 plus residual GFR and dialysis dose (total and peritoneal Kt/Vurea).
Figure 4Kaplan-Meier estimates of technical survival, overall survival, and subgroup analyses at the second interim analysis in all participants in this study. Shown are hazard ratios and number of event among TG ≥ 1.4mmol/L group and TG < 1.4mmol/L group.