| Literature DB >> 30385449 |
Yusuke Okabayashi1, Nobuo Tsuboi1, Hoichi Amano1, Yoichi Miyazaki1, Tetsuya Kawamura1, Makoto Ogura1, Ichiei Narita2, Toshiharu Ninomiya3, Hitoshi Yokoyama4, Takashi Yokoo1.
Abstract
OBJECTIVES: The clinical severity of IgA nephropathy (IgAN) at the time of biopsy diagnosis differs significantly among cases. One possible determinant of any such difference is the time taken for referral from the primary care physician to a nephrologist, but the definitive cause remains unclear. This study examined the contribution of the number of nephrologists per regional population as a potential social factor influencing the clinical severity at diagnosis among patients with IgAN in Japan, which has an ethnically homogeneous population.Entities:
Keywords: IgA nephropathy; chronic kidney disease; glomerulonephritis; haematuria; proteinuria; renal biopsy
Mesh:
Year: 2018 PMID: 30385449 PMCID: PMC6224759 DOI: 10.1136/bmjopen-2018-024317
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 2.692
Clinical characteristics of the patients at biopsy diagnosis
| Variables | Total | Hokkaido | Tohoku | Kanto | Koshinetsu | Hokuriku | Tokai | Kinki | Chugoku | Shikoku | Kyushu | P values | Maximal fold among regions |
| Age, mean (SD), years | 39.5 (17.7) | 41.5 (16.6) | 42.5 (18.1) | 34.7 (17.5) | 39.2 (14.9) | 42.2 (16.8) | 41.4 (16.6) | 38.9 (17.1) | 39.4 (17.8) | 32.2 (20.2) | 40.8 (18.3) | <0.001 | 1.32 |
| Male, n (%) | 3297 (51.3) | 78 (52.7) | 488 (53.6) | 652 (53.1) | 96 (47.8) | 143 (55.4) | 707 (49.4) | 367 (52.0) | 255 (52.6) | 86 (47.0) | 425 (48.7) | 0.182 | 1.18 |
| BMI mean (SD), kg/m2 | 22.6 (4.0) | 23.4 (4.2) | 23.5 (4.2) | 22.0 (4.2) | 22.2 (3.7) | 22.8 (3.6) | 22.6 (3.7) | 22.4 (4.1) | 22.7 (4.2) | 21.7 (4.0) | 22.7 (4.0) | <0.001 | 1.08 |
| SBP, mean (SD), mm Hg | 124 (18) | 126 (19) | 126 (17) | 120 (18) | 120 (16) | 122 (17) | 127 (18) | 122 (18) | 124 (18) | 117 (16) | 126 (19) | <0.001 | 1.09 |
| DBP, mean (SD), mm Hg | 74 (13) | 76 (13) | 76 (13) | 72 (13) | 75 (13) | 74 (13) | 76 (13) | 73 (12) | 74 (13) | 69 (12) | 75 (13) | <0.001 | 1.10 |
| Hypertension, n (%) | 2790 (43.4) | 82 (55.4) | 403 (44.2) | 457 (37.2) | 93 (46.3) | 127 (49.2) | 709 (49.5) | 279 (39.5) | 203 (41.9) | 49 (26.8) | 388 (44.4) | <0.001 | 2.07 |
| eGFR, mean (SD), mL/min/1.73 m2 | 74.4 (30.3) | 67.5 (31.3) | 73.3 (29.6) | 79.6 (31.5) | 71.3 (27.7) | 73.2 (27.0) | 69.0 (27.8) | 74.8 (29.3) | 78.0 (30.9) | 91.4 (35.2) | 73.5 (31.2) | <0.001 | 1.35 |
| Serum albumin, mean (SD), g/dL | 3.9 (0.6) | 3.7 (0.7) | 4.0 (0.7) | 4.0 (0.6) | 4.0 (0.7) | 3.8 (1.0) | 3.9 (0.6) | 3.9 (0.6) | 4.0 (0.6) | 4.0 (0.6) | 3.9 (0.6) | <0.001 | 1.08 |
| Total cholesterol, mean (SD), mg/dL | 194 (59) | 198 (45) | 182 (68) | 186 (71) | 188 (71) | 198 (60) | 204 (47) | 199 (49) | 197 (47) | 189 (55) | 198 (59) | <0.001 | 1.12 |
| UPE, mean (SD), g/day | 1.16 (1.62) | 1.93 (2.63) | 1.00 (1.55) | 0.97 (1.25) | 0.93 (1.22) | 1.00 (1.23) | 1.42 (1.72) | 1.04 (1.46) | 0.97 (1.43) | 1.08 (2.31) | 1.35 (1.83) | <0.001 | 2.08 |
| Haematuria grade 2/3, n (%) | 4313 (67.1) | 101 (68.2) | 598 (65.6) | 801 (65.2) | 142 (70.6) | 170 (65.9) | 1024 (71.5) | 454 (64.3) | 327 (67.4) | 94 (51.4) | 602 (69.0) | <0.001 | 1.39 |
| KDIGO prognosis risk of CKD, n (%) | |||||||||||||
| Very high risk | 1813 (28.2) | 59 (39.9) | 265 (29.1) | 289 (23.5) | 61 (30.3) | 64 (24.8) | 495 (34.6) | 175 (24.8) | 117 (24.1) | 20 (10.9) | 268 (30.7) | <0.001 | 3.66 |
| High risk | 2353 (36.6) | 48 (32.4) | 272 (29.9) | 446 (36.3) | 66 (32.8) | 100 (38.8) | 623 (43.5) | 248 (35.1) | 157 (32.4) | 66 (36.1) | 327 (37.5) | <0.001 | 1.45 |
| Moderately increased risk | 1412 (22.0) | 24 (16.2) | 199 (21.8) | 322 (26.2) | 53 (26.4) | 54 (20.9) | 228 (15.9) | 183 (25.9) | 122 (25.2) | 43 (23.5) | 184 (21.1) | <0.001 | 1.66 |
| Low risk | 849 (13.2) | 17 (11.5) | 175 (19.2) | 172 (14.0) | 21 (10.4) | 40 (15.5) | 86 (6.0) | 100 (14.2) | 89 (18.4) | 54 (29.5) | 94 (10.8) | <0.001 | 4.92 |
BMI, body mass index; CKD, chronic kidney disease; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; KDIGO, Kidney Disease Improving Global Outcomes; SBP, systolic blood pressure; UPE, urinary protein excretion.
Regional variation in social factors
| Regions | Number of nephrologists per 100 000 populations | Proportion of participants who received a health check-up, % | Proportion of elderly persons relative to the general population, % |
| Hokkaido | 1.58 | 36.7 | 26.0 |
| Tohoku | 2.73 | 46.5 | 26.5 |
| Kanto | 4.03 | 46.4 | 22.1 |
| Koshinetsu | 3.26 | 50.5 | 27.0 |
| Hokuriku | 4.24 | 48.7 | 26.2 |
| Tokai | 2.87 | 47.2 | 23.3 |
| Kinki | 3.46 | 40.7 | 24.2 |
| Chugoku | 3.07 | 41.1 | 26.8 |
| Shikoku | 3.05 | 43.1 | 28.1 |
| Kyushu | 3.20 | 43.2 | 25.4 |
| Total mean | 3.40 | 45.0 | 24.2 |
| Maximal fold among regions | 2.68 | 1.38 | 1.27 |
| P values | <0.001 | <0.001 | <0.001 |
Comparison of patient clinical characteristics among regions categorised according to the number of nephrologists
| Variables | Category of the number of nephrologists | P values for trend | ||
| Lowest three regions (n=2491) | Intermediate four regions (n=1742) | Highest three regions (n=2193) | ||
| Nephrologists per 100 000 populations | 2.59 | 3.16 | 3.86 | |
| Age, mean (SD), year | 41.8 (17.2) | 39.3 (18.2) | 36.9 (17.5) | <0.001 |
| Hypertension, n (%) | 1194 (47.9) | 733 (42.1) | 863 (39.4) | <0.001 |
| eGFR, mean (SD), mL/min/1.73 m2 | 70.5 (28.7) | 77.3 (30.4) | 77.3 (30.4) | <0.001 |
| UPE, mean (SD), g/day | 1.30 (1.75) | 1.17 (1.74) | 0.99 (1.32) | <0.001 |
| Haematuria grade 2/3, n (%) | 1723 (69.2) | 1165 (66.9) | 1425 (65.0) | 0.002 |
| KDIGO renal prognosis risk, n (%) | ||||
| Very high risk | 819 (32.9) | 465 (26.7) | 528 (24.1) | <0.001 |
| High risk | 943 (37.9) | 616 (35.4) | 794 (36.2) | 0.226 |
| Moderately increased risk | 451 (18.1) | 402 (23.1) | 559 (25.5) | <0.001 |
| Low risk | 278 (11.2) | 259 (14.9) | 312 (14.2) | 0.001 |
eGFR, estimated glomerular filtration rate; KDIGO, Kidney Disease Improving Global Outcomes; UPE, urinary protein excretion.
Figure 1Distributions of patients with IgA nephropathy (IgAN) with a very-high-risk renal prognosis and nephrologists. Regional differences of the rate of patients with IgAN with a very-high-risk renal prognosis at biopsy diagnosis, which was adjusted for age, sex and hypertension (A), and the number of board-certified nephrologists per regional population (B). Based on the ranking of each factor, 10 regions of Japan were divided into three groups as follows: the three lowest, four intermediate and three highest groups. The numbers indicate the following regions: 1, Hokkaido; 2, Tohoku; 3, Kanto; 4, Koshinetsu; 5, Hokuriku; 6, Tokai; 7, Kinki; 8, Chugoku; 9, Shikoku; 10, Kyushu.
Social factors and regional variation in patients with IgA nephropathy (IgAN) with very-high-risk renal prognosis
| Fixed effects | f values | Regression coefficient | 95% CI | P values |
| Number of nephrologists (/100 000 populations) | 4.022 | −0.489 | −0.967 to −0.011 | 0.045 |
| Proportion of patients who received a health check-up (%) | 0.521 | 0.033 | −0.056 to 0.122 | 0.471 |
| Proportion of elderly persons relative to the general population (%) | 3.512 | −0.140 | −0.287 to 0.006 | 0.061 |
Covariates: age, sex, hypertension. Random effects: region, Japan Renal Biopsy Registry (J-RBR) registration facility.
Structure for the random effects: first-order autoregressive.
Figure 2Relationship between the rate of patients with IgA nephropathy (IgAN) with a very-high-risk renal prognosis and the number of nephrologists per regional population. Circles indicate each region and the areas of the circles are proportional to the regional populations. The rate of patients with IgAN with a very-high-risk renal prognosis in each region was adjusted by age, sex and hypertension. The regression line was obtained from the generalised linear mixed model in table 4.