| Literature DB >> 33148691 |
Sadanori Okada1,2, Ken-Ichi Samejima3, Masaru Matsui4, Katsuhiko Morimoto5, Riri Furuyama6, Kaori Tanabe6, Masahiro Eriguchi6, Yasuhiro Akai1,6, Yoshihiko Saito7, Kazuhiko Tsuruya6.
Abstract
INTRODUCTION: There are fewer reports about whether the presence of hematuria affects the progression of chronic kidney disease in patients with diabetic nephropathy. We analyzed whether microscopic hematuria in diabetic nephropathy is a risk factor for end-stage kidney disease (ESKD). RESEARCH DESIGN AND METHODS: The present study was a retrospective cohort study of patients with biopsy-proven diabetic nephropathy. We recruited 397 patients with diabetic nephropathy, which was confirmed by renal biopsy between June 1981 and December 2014 and followed them until October 2018 or death. Patients with microscopic hematuria before renal biopsy were defined as the hematuria group (n=91), and the remainder as the no-hematuria group (n=306). The main outcome was the occurrence of ESKD, which was defined by the requirement of permanent renal replacement therapies.Entities:
Keywords: biopsy; chronic; diabetes mellitus; kidney failure; observational study; type 2
Mesh:
Year: 2020 PMID: 33148691 PMCID: PMC7643490 DOI: 10.1136/bmjdrc-2020-001863
Source DB: PubMed Journal: BMJ Open Diabetes Res Care ISSN: 2052-4897
Baseline characteristics of the patients with/without hematuria
| Total | Hematuria | No-hematuria | No. of | P value | |
| N=397 | N=91 | N=306 | missing values | ||
| Age, years | 57.7±11.3 | 59.1±10.8 | 57.3±11.5 | 0 | 0.2 |
| Men, n (%) | 249 (63) | 65 (60) | 184 (71) | 0 | 0.05 |
| BMI, kg/m2 | 24.1±3.8 | 24.7±4.0 | 23.9±3.7 | 0 | 0.08 |
| Blood pressure, mm Hg | |||||
| Systole | 135±24 | 145±27 | 132±22 | 0 | <0.0001 |
| Diastole | 75±13 | 78±15 | 75±13 | 0 | 0.04 |
| Smoking, n (%) | 0 | 0.4 | |||
| Never | 154 (39) | 30 (33) | 124 (41) | ||
| Past | 61 (15) | 14 (15) | 47 (15) | ||
| Current | 182 (46) | 47 (52) | 135 (44) | ||
| Diabetic retinopathy, n (%) | 175 (45) | 58 (65) | 117 (39) | 10 | <0.0001 |
| Laboratory findings | |||||
| Serum creatinine, mg/dL | 0.99 | 1.23 | 0.90 | 0 | <0.0001 |
| Serum creatinine, μmol/L | 87.5 | 108.7 | 79.6 | 0 | <0.0001 |
| eGFR, mL/min/1.73m2 | 57.6 | 45.4 | 61.2 | 0 | <0.0001 |
| Proteinuria, g/day | 0.4 (0.2–2.5) | 3.1 (0.5–6.8) | 0.3 (0.1–1.0) | 8 | <0.0001 |
| HbA1c, % | 8.3±2.4 | 7.9±2.2 | 8.4±2.4 | 36 | 0.1 |
| HbA1c, mmol/mol | 67±26 | 63±24 | 68±26 | 36 | 0.1 |
| Pathological findings | |||||
| Glomerular lesion class, n (%) | 0 | <0.0001 | |||
| IIa | 127 (32) | 12 (13) | 115 (38) | ||
| IIb | 148 (37) | 25 (27) | 123 (40) | ||
| III | 99 (25) | 40 (44) | 59 (19) | ||
| IV | 23 (6) | 14 (15) | 9 (3) | ||
| IFTA score, n (%) | 0 | <0.0001 | |||
| 0 | 32 (8) | 4 (4) | 28 (9) | ||
| 1 | 220 (55) | 31 (34) | 189 (62) | ||
| 2 | 66 (17) | 22 (24) | 44 (14) | ||
| 3 | 79 (20) | 34 (37) | 45 (15) | ||
| Arteriolar hyalinosis score, n (%) | 0 | <0.02 | |||
| 0 | 55 (14) | 7 (8) | 48 (16) | ||
| 1 | 120 (30) | 22 (24) | 98 (32) | ||
| 2 | 222 (56) | 62 (68) | 160 (52) | ||
| Arteriosclerosis score, n (%) | 31 | 0.9 | |||
| 0 | 78 (21) | 17 (20) | 61 (22) | ||
| 1 | 123 (34) | 30 (36) | 93 (33) | ||
| 2 | 165 (45) | 36 (43) | 129 (46) |
BMI, body mass index; eGFR, estimated glomerular filtration rate; HbA1c, hemoglobin A1c; IFTA, intestinal fibrosis and tubular atrophy.
Figure 1The incidence of ESKD in patients with/without hematuria. The survival curves showed that the incidence of ESKD was significantly higher in the hematuria group (log-rank, p<0.0001). The crude HR (95% CI) of hematuria for the incidence of ESKD was 4.11 (2.73 to 6.18). The association remains significant after adjusting for clinically relevant factors. Model 1 was adjusted for sex and age. Model 2 was adjusted for model 1 plus eGFR, proteinuria, systolic blood pressure and BMI. Model 3 was adjusted for model 2 plus pathological findings (glomerular lesion class and IFTA score). BMI, body mass index; eGFR, estimated glomerular filtration rate; ESKD, end-stage kidney disease; IFTA, interstitial fibrosis and tubular atrophy.
Figure 2Subgroup analyses. We dichotomized age, proteinuria, eGFR, BMI and SBP by median values. In each subgroup, we used the multivariable Cox proportional hazard model (model 3) to assess the association between hematuria and ESKD. BMI, body mass index; eGFR, estimated glomerular filtration rate; ESKD, end-stage kidney disease; IFTA, intestinal fibrosis and tubular atrophy; SBP, systolic blood pressure.
Figure 3The incidence of ESKD and all-cause death in patients with/without hematuria. As a sensitivity analysis, we evaluated the composite end point of ESKD and all-cause death. The survival curves showed that the incidence of ESKD and death was significantly higher in the hematuria group (log-rank, p<0.0001), and the crude and adjusted HRs (95% CI) of hematuria were 2.93 (2.08 to 4.13) and 1.41 (0.96 to 2.08) (model 3), respectively. Model 1 was adjusted for sex and age. Model 2 was adjusted for model 1 plus eGFR, proteinuria, systolic blood pressure and BMI. Model 3 was adjusted for model 2 plus pathological findings (glomerular lesion class and IFTA score). BMI, body mass index; eGFR, estimated glomerular filtration rate; ESKD, end-stage kidney disease; IFTA, intestinal fibrosis and tubular atrophy.