Please wait a minute...
Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Front. Med.    2020, Vol. 14 Issue (6) : 802-810    https://doi.org/10.1007/s11684-019-0723-7
RESEARCH ARTICLE
Serum uric acid and risk of incident diabetes in middle-aged and elderly Chinese adults: prospective cohort study
Di Cheng1, Chunyan Hu1, Rui Du1, Hongyan Qi1, Lin Lin1,2, Xueyan Wu1, Lina Ma1, Kui Peng1, Mian Li1, Min Xu1, Yu Xu1, Yufang Bi1, Weiqing Wang1, Yuhong Chen2(), Jieli Lu1()
1. Department of Endocrine and Metabolic Diseases, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
2. Department of Endocrine and Metabolic Diseases, Ruijin Hospital North, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 201821, China
 Download: PDF(315 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

The association between serum uric acid and the risk of incident diabetes in Chinese adults remains unknown. This study aimed to investigate this association in a community-dwelling population aged≥40 years in Shanghai, China. Oral glucose tole3rance test was conducted during baseline and follow-up visits. Relative risk regression was utilized to examine the associations between baseline gender-specific serum uric acid levels and incident diabetes risk. A total of 613 (10.3%) incident diabetes cases were identified during the follow-up visit after 4.5 years. Fasting plasma glucose, postload glucose, and glycated hemoglobin A1c during the follow-up visit progressively increased across the sex-specific quartiles of serum uric acid (all Ps<0.05). The incidence rate of diabetes increased across the quartiles of serum uric acid (7.43%, 8.77%, 11.47%, and 13.43%). Multivariate adjusted regression analysis revealed that individuals in the highest quartile had 1.36-fold increased risk of diabetes compared with those in the lowest quartile of serum uric acid (odds ratio (95% confidence interval) = 1.36 (1.06−1.73)). Stratified analysis indicated that the association was only observed in women. Accordingly, serum uric acid was associated with the increased risk of incident diabetes among middle-aged and elderly Chinese women.

Keywords incident diabetes      prospective study      uric acid     
Corresponding Author(s): Yuhong Chen,Jieli Lu   
Just Accepted Date: 10 January 2020   Online First Date: 30 April 2020    Issue Date: 24 December 2020
 Cite this article:   
Di Cheng,Chunyan Hu,Rui Du, et al. Serum uric acid and risk of incident diabetes in middle-aged and elderly Chinese adults: prospective cohort study[J]. Front. Med., 2020, 14(6): 802-810.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-019-0723-7
https://academic.hep.com.cn/fmd/EN/Y2020/V14/I6/802
Fig.1  Flowchart of the study participants.
Serum uric acid, μmol/L ?Ptrend
Quartile 1 Quartile 2 Quartile 3 Quartile 4
No. of participants, n (%) 1493 (25.06) 1493 (25.00) 1490 (25.01) 1489 (24.93)
Age (year) 56.40±9.12 56.69±8.47 57.79±8.84 59.48±9.08 ?<0.0001
BMI (kg/m2) 23.79±2.92 24.59±2.86 25.27±3.17 26.16±3.17 ?<0.0001
Waist circumference (cm) 78.07±8.13 80.78±7.90 82.85±8.66 85.14±8.26 ?<0.0001
Educational attainment (high school or above), n (%) 301 (20.23) 315 (21.23) 322 (21.68) 266 (17.97) ?0.09
Current smoker, n (%) 316 (22.33) 291 (20.98) 295 (20.85) 257 (18.29) ?0.20
Current drinker, n (%) 117 (8.22) 146 (10.45) 167 (11.79) 165 (11.69) ?0.01
Physically active, n (%) 186 (12.49) 214 (14.38) 231 (15.55) 235 (15.80) ?0.006
SBP (mmHg) 135.10±18.72 138.59±19.07 140.27±19.65 144.13±19.43 ?<0.0001
DBP (mmHg) 80.37±10.07 82.33±9.98 83.34±10.16 84.62±10.30 ?<0.0001
Family history of diabetes, n (%) 110 (7.39) 142 (9.54) 124 (8.34) 153 (10.28) ?0.02
FPG (mmol/L) 5.03±0.55 5.07±0.54 5.11±0.56 5.16±0.56 ?<0.0001
2-h PPG (mmol/L) 6.23±1.59 6.50±1.66 6.74±1.73 7.14±1.79 ?<0.0001
HbA1c (%) 5.5 (5.3–5.7) 5.5 (5.3–5.7) 5.6 (5.3–5.8) 5.6 (5.4-5.8) ?<0.0001
Fasting cholesterol (mmol/L) 5.14±0.93 5.33±0.92 5.35±0.98 5.53±1.08 ?<0.0001
Fasting HDL cholesterol (mmol/L) 1.44±0.34 1.36±0.31 1.32±0.30 1.27±0.31 ?<0.0001
Fasting LDL cholesterol (mmol/L) 3.01±0.80 3.19±0.80 3.22±0.85 3.33±0.89 ?<0.0001
Fasting TGs (mmol/L) 1.03 (0.78–1.41) 1.25 (0.94–1.76) 1.40 (1.03–1.93) 1.69 (1.24–2.38) ?<0.0001
eGFR 103.87±9.09 101.70±9.37 98.90±9.99 94.27±13.40 ?<0.0001
Tab.1  Baseline clinical and biochemical characteristics of participants stratified by using the sex-specific quartiles of serum uric acid levels
Fig.2  Associations between FPG, 2-h PPG, and HbA1c levels at 4.5-year follow-up visit with baseline serum uric acid levels. (A) FPG levels at 4.5-year follow-up point based on uric acid quartiles at baseline. (B) 2-h PPG levels in 75-g OGTT at 4.5-year follow-up point based on uric acid quartiles at baseline. (C) HbA1c levels at 4.5-year follow-up point based on uric acid quartiles at baseline. Note: data are expressed as mean±SD for FPG, 2-h PPG levels and median (interquartile range) for HbA1c levels.
Baseline Follow-up
R P value R P value
FPG 0.089 <0.0001 0.102 <0.0001
2-h PPG 0.118 <0.0001 0.123 <0.0001
HbA1c 0.065 <0.0001 0.072 <0.0001
TGs 0.303 <0.0001 0.187 <0.0001
TC 0.039 0.003 −0.010 0.48
LDL cholesterol 0.050 0.0001 −0.015 0.29
HDL cholesterol −0.268 <0.0001 −0.051 0.0002
eGFR −0.361 <0.0001 −0.215 <0.0001
Tab.2  Pearson’s correlation analysis for the relationship of baseline serum uric acid levels and biochemistry measurements at baseline and follow-up visits, respectively
RR (95% CI) Ptrend
Quartile 1 Quartile 2 Quartile 3 Quartile 4
Cases/N 111/1493 131/1493 171/1490 200/1489
Incidence of diabetes (%) 7.43 8.77 11.47 13.43 <0.0001
Model 1 1.00 1.18 (0.93–1.50) 1.54 (1.23–1.94) 1.81 (1.45–2.25) <0.0001
Model 2 1.00 1.17 (0.92–1.50) 1.50 (1.20–1.89) 1.70 (1.36–2.13) <0.0001
Model 3 1.00 1.12 (0.87–1.43) 1.26 (1.00–1.60) 1.30 (1.03–1.65) <0.0001
Model 4 1.00 1.15 (0.90–1.46) 1.25 (0.99–1.58) 1.36 (1.06–1.73) <0.0001
Tab.3  Relative risk (95% CI) of incident diabetes for baseline serum uric acid quartiles
Incidence of RR (95% CI) Ptrend P for interaction
diabetes (%) Quartile 1 Quartile 2a Quartile 3a Quartile 4a
Age (year)
<60 8.81 1.00 1.23 (0.88–1.72) 1.44 (1.04–1.99) 1.58 (1.13–2.21) <0.0001 0.03
≥60 12.80 1.00 1.02 (0.71–1.46) 1.03 (0.73–1.45) 1.06 (0.75–1.49) 0.02
Sex
Male 11.43 1.00 1.01 (0.71–1.46) 1.001 (0.70–1.42) 1.06 (0.73–1.52) 0.10 0.68
Female 9.65 1.00 1.28 (0.92–1.79) 1.46 (1.06–2.01) 1.58 (1.13–2.20) <0.0001
BMI (kg/m2)
<24 6.70 1.00 1.01 (0.67–1.52) 1.16 (0.77–1.77) 1.06 (0.65–1.73) 0.54 0.0001
≥24 12.61 1.00 1.29 (0.94–1.75) 1.41 (1.05–1.89) 1.60 (1.20–2.15) <0.0001
Physically active
No 10.29 1.00 1.17 (0.90–1.52) 1.31 (1.01–1.68) 1.40 (1.07–1.82) <0.0001 0.86
Yes 10.39 1.00 1.03 (0.53–1.98) 0.96 (0.52–1.78) 1.18 (0.66–2.12) 0.02
Current smoker
No 10.45 1.00 1.26 (0.95–1.66) 1.33 (1.01–1.74) 1.52 (1.16–2.00) <0.0001 0.08
Yes 9.58 1.00 0.83 (0.48–1.43) 1.01 (0.62–1.64) 0.81 (0.46–1.42) 0.48
Current drinker
No 10.09 1.00 1.15 (0.89–1.49) 1.21 (0.94–1.55) 1.41 (1.09–1.82) <0.0001 0.24
Yes 11.93 1.00 1.14 (0.53–2.49) 1.44 (0.75–2.76) 0.92 (0.44–1.93) 0.31
Hypertension
No 6.72 1.00 1.38 (0.92–2.06) 1.55 (1.03–2.32) 1.60 (1.04–2.45) 0.002 0.12
Yes 13.01 1.00 1.02 (0.75–1.38) 1.11 (0.84–1.47) 1.20 (0.90–1.60) 0.0009
Highschool or above educational attainment
No 10.29 1.00 1.11 (0.85–1.45) 1.23 (0.95–1.59) 1.29 (0.98–1.68) <0.0001 0.25
Yes 9.97 1.00 1.48 (0.81–2.71) 1.43 (0.80–2.53) 1.76 (1.004–3.08) <0.0001
Family history of diabetes
No 9.75 1.00 1.21 (0.93–1.56) 1.21 (0.94–1.56) 1.33 (1.02–1.73) <0.0001 <0.0001
Yes 15.88 1.00 0.87 (0.44–1.75) 1.62 (0.88–3.00) 1.53 (0.83–2.81) 0.005
IGR
No 2.24 1.00 0.91 (0.44–1.89) 0.97 (0.45–2.08) 1.14 (0.48–2.72) 0.54 <0.0001
Yes 17.01 1.00 1.16 (0.90–1.51) 1.31 (1.02–1.68) 1.30 (1.01–1.68) 0.0001
Tab.4  Subgroup analysis for the association between sex-specific serum uric acid levels and risk of incident diabetes
1 C Bommer, E Heesemann, V Sagalova, J Manne-Goehler, R Atun, T Bärnighausen, S Vollmer. The global economic burden of diabetes in adults aged 20–79 years: a cost-of-illness study. Lancet Diabetes Endocrinol 2017; 5(6): 423–430
https://doi.org/10.1016/S2213-8587(17)30097-9 pmid: 28456416
2 M Chen-Xu, C Yokose, SK Rai, MH Pillinger, HK Choi. Contemporary prevalence of gout and hyperuricemia in the United States and decadal trends: the National Health and Nutrition Examination Survey, 2007–2016. Arthritis Rheumatol 2019; 71(6): 991–999
https://doi.org/10.1002/art.40807 pmid: 30618180
3 SP Juraschek, M McAdams-Demarco, ER Miller, AC Gelber, JW Maynard, JS Pankow, H Young, J Coresh, E Selvin. Temporal relationship between uric acid concentration and risk of diabetes in a community-based study population. Am J Epidemiol 2014; 179(6): 684–691
https://doi.org/10.1093/aje/kwt320 pmid: 24418684
4 TJ Major, N Dalbeth, EA Stahl, TR Merriman. An update on the genetics of hyperuricaemia and gout. Nat Rev Rheumatol 2018; 14(6): 341–353
https://doi.org/10.1038/s41584-018-0004-x pmid: 29740155
5 J White, R Sofat, G Hemani, T Shah, J Engmann, C Dale, S Shah, FA Kruger, C Giambartolomei, DI Swerdlow, T Palmer, S McLachlan, C Langenberg, D Zabaneh, R Lovering, A Cavadino, B Jefferis, C Finan, A Wong, A Amuzu, K Ong, TR Gaunt, H Warren, TL Davies, F Drenos, J Cooper, S Ebrahim, DA Lawlor, PJ Talmud, SE Humphries, C Power, E Hypponen, M Richards, R Hardy, D Kuh, N Wareham, Y Ben-Shlomo, IN Day, P Whincup, R Morris, MWJ Strachan, J Price, M Kumari, M Kivimaki, V Plagnol, JC Whittaker, GD Smith, F Dudbridge, JP Casas, MV Holmes, AD Hingorani; UCLEB (University College London-London School of Hygiene & Tropical Medicine-Edinburgh-Bristol Consortium). Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis. Lancet Diabetes Endocrinol 2016; 4(4): 327–336
https://doi.org/10.1016/S2213-8587(15)00386-1 pmid: 26781229
6 V Bhole, JW Choi, SW Kim, M de Vera, H Choi. Serum uric acid levels and the risk of type 2 diabetes: a prospective study. Am J Med 2010; 123(10): 957–961
https://doi.org/10.1016/j.amjmed.2010.03.027 pmid: 20920699
7 CY Dai, WL Chuang, CK Ho, TT Ou, JF Huang, MY Hsieh, ML Yu. High serum uric acid as a novel risk factor for type 2 diabetes: response to Dehghan et al. Diabetes Care 2008; 31(9): e67
https://doi.org/10.2337/dc08-0038 pmid: 18753663
8 A Dehghan, M van Hoek, EJ Sijbrands, A Hofman, JC Witteman. High serum uric acid as a novel risk factor for type 2 diabetes. Diabetes Care 2008; 31(2): 361–362
https://doi.org/10.2337/dc07-1276 pmid: 17977935
9 G Boner. Uric acid and diabetes. Lancet 1982; 320(8309): 1224
https://doi.org/10.1016/S0140-6736(82)91249-1 pmid: 6128533
10 T Han, X Meng, R Shan, T Zi, Y Li, H Ma, Y Zhao, D Shi, R Qu, X Guo, L Liu, L Na, Y Li, C Sun. Temporal relationship between hyperuricemia and obesity, and its association with future risk of type 2 diabetes. Int J Obes 2018; 42(7): 1336–1344
https://doi.org/10.1038/s41366-018-0074-5 pmid: 29717279
11 J Liu, L Tao, Z Zhao, Y Mu, D Zou, J Zhang, X Guo. Two-year changes in hyperuricemia and risk of diabetes: a five-year prospective cohort study. J Diabetes Res 2018; 2018: 6905720
https://doi.org/10.1155/2018/6905720 pmid: 30693289
12 Y Wang, J Chi, K Che, Y Chen, X Sun, Y Wang, Z Wang. Fasting plasma glucose and serum uric acid levels in a general Chinese population with normal glucose tolerance: a U-shaped curve. PLoS One 2017; 12(6): e0180111
https://doi.org/10.1371/journal.pone.0180111 pmid: 28658284
13 J Tuomilehto, P Zimmet, E Wolf, R Taylor, P Ram, H King. Plasma uric acid level and its association with diabetes mellitus and some biologic parameters in a biracial population of Fiji. Am J Epidemiol 1988; 127(2): 321–336
https://doi.org/10.1093/oxfordjournals.aje.a114807 pmid: 3337086
14 T Keenan, W Zhao, A Rasheed, WK Ho, R Malik, JF Felix, R Young, N Shah, M Samuel, N Sheikh, ML Mucksavage, O Shah, J Li, M Morley, A Laser, NH Mallick, KS Zaman, M Ishaq, SZ Rasheed, FU Memon, F Ahmed, B Hanif, MS Lakhani, M Fahim, M Ishaq, NK Shardha, N Ahmed, K Mahmood, W Iqbal, S Akhtar, R Raheel, CJ O’Donnell, C Hengstenberg, W März, S Kathiresan, N Samani, A Goel, JC Hopewell, J Chambers, YC Cheng, P Sharma, Q Yang, J Rosand, GB Boncoraglio, SU Kazmi, H Hakonarson, A Köttgen, A Kalogeropoulos, P Frossard, A Kamal, M Dichgans, T Cappola, MP Reilly, J Danesh, DJ Rader, BF Voight, D Saleheen. Causal assessment of serum urate levels in cardiometabolic diseases through a Mendelian randomization study. J Am Coll Cardiol 2016; 67(4): 407–416
https://doi.org/10.1016/j.jacc.2015.10.086 pmid: 26821629
15 S Kivity, E Kopel, S Steinlauf, S Segev, Y Sidi, D Olchovsky. The association between serum uric acid and diabetes mellitus is stronger in women. J Womens Health (Larchmt) 2013; 22(9): 782–789
https://doi.org/10.1089/jwh.2012.4043 pmid: 23805880
16 J Lu, J Zhang, R Du, T Wang, M Xu, Y Xu, W Wang, Y Bi, D Li, Y Chen, G Ning. Age at menarche is associated with the prevalence of non-alcoholic fatty liver disease later in life. J Diabetes 2017; 9(1): 53–60
https://doi.org/10.1111/1753-0407.12379 pmid: 26800495
17 M Li, Y Xu, M Xu, L Ma, T Wang, Y Liu, M Dai, Y Chen, J Lu, J Liu, Y Bi, G Ning. Association between nonalcoholic fatty liver disease (NAFLD) and osteoporotic fracture in middle-aged and elderly Chinese. J Clin Endocrinol Metab 2012; 97(6): 2033–2038
https://doi.org/10.1210/jc.2011-3010 pmid: 22466338
18 Y Chen, J Lu, Y Huang, T Wang, Y Xu, M Xu, M Li, W Wang, D Li, Y Bi, G Ning. Association of previous schistosome infection with diabetes and metabolic syndrome: a cross-sectional study in rural China. J Clin Endocrinol Metab 2013; 98(2): E283–E287
https://doi.org/10.1210/jc.2012-2517 pmid: 23275524
19 PH Lee, DJ Macfarlane, TH Lam, SM Stewart. Validity of the International Physical Activity Questionnaire Short Form (IPAQ-SF): a systematic review. Int J Behav Nutr Phys Act 2011; 8(1): 115
https://doi.org/10.1186/1479-5868-8-115 pmid: 22018588
20 DM Lloyd-Jones, Y Hong, D Labarthe, D Mozaffarian, LJ Appel, L Van Horn, K Greenlund, S Daniels, G Nichol, GF Tomaselli, DK Arnett, GC Fonarow, PM Ho, MS Lauer, FA Masoudi, RM Robertson, V Roger, LH Schwamm, P Sorlie, CW Yancy, WD Rosamond; American Heart Association Strategic Planning Task Force and Statistics Committee. Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association’s strategic Impact Goal through 2020 and beyond. Circulation 2010; 121(4): 586–613
https://doi.org/10.1161/CIRCULATIONAHA.109.192703 pmid: 20089546
21 TG Pickering, JE Hall, LJ Appel, BE Falkner, J Graves, MN Hill, DW Jones, T Kurtz, SG Sheps, EJ Roccella; Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research. Recommendations for blood pressure measurement in humans and experimental animals: Part 1: blood pressure measurement in humans: a statement for professionals from the Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research. Hypertension 2005; 45(1): 142–161
https://doi.org/10.1161/01.HYP.0000150859.47929.8e pmid: 15611362
22 L Lin, K Peng, R Du, X Huang, J Lu, Y Xu, M Xu, Y Chen, Y Bi, W Wang. Metabolically healthy obesity and incident chronic kidney disease: the role of systemic inflammation in a prospective study. Obesity (Silver Spring) 2017; 25(3): 634–641
https://doi.org/10.1002/oby.21768 pmid: 28160438
23 I Hertz-Picciotto, B Rockhill. Validity and efficiency of approximation methods for tied survival times in Cox regression. Biometrics 1997; 53(3): 1151–1156
https://doi.org/10.2307/2533573 pmid: 9333345
24 LA McNutt, C Wu, X Xue, JP Hafner. Estimating the relative risk in cohort studies and clinical trials of common outcomes. Am J Epidemiol 2003; 157(10): 940–943
https://doi.org/10.1093/aje/kwg074 pmid: 12746247
25 G Zoppini, G Targher, C Negri, V Stoico, F Perrone, M Muggeo, E Bonora. Elevated serum uric acid concentrations independently predict cardiovascular mortality in type 2 diabetic patients. Diabetes Care 2009; 32(9): 1716–1720
https://doi.org/10.2337/dc09-0625 pmid: 19542211
26 C Meisinger, B Thorand, A Schneider, J Stieber, A Döring, H Löwel. Sex differences in risk factors for incident type 2 diabetes mellitus: the MONICA Augsburg cohort study. Arch Intern Med 2002; 162(1): 82–89
https://doi.org/10.1001/archinte.162.1.82 pmid: 11784224
27 T Yamada, M Fukatsu, S Suzuki, T Wada, T Joh. Elevated serum uric acid predicts impaired fasting glucose and type 2 diabetes only among Japanese women undergoing health checkups. Diabetes Metab 2011; 37(3): 252–258
https://doi.org/10.1016/j.diabet.2010.10.009 pmid: 21377910
28 N Nakanishi, M Okamoto, H Yoshida, Y Matsuo, K Suzuki, K Tatara. Serum uric acid and risk for development of hypertension and impaired fasting glucose or type II diabetes in Japanese male office workers. Eur J Epidemiol 2003; 18(6): 523–530
https://doi.org/10.1023/A:1024600905574 pmid: 12908717
29 W Levine, AR Dyer, RB Shekelle, JA Schoenberger, J Stamler. Serum uric acid and 11.5-year mortality of middle-aged women: findings of the Chicago Heart Association Detection Project in Industry. J Clin Epidemiol 1989; 42(3): 257–267
https://doi.org/10.1016/0895-4356(89)90061-9 pmid: 2709083
30 CS Wingrove, C Walton, JC Stevenson. The effect of menopause on serum uric acid levels in non-obese healthy women. Metabolism 1998; 47(4): 435–438
https://doi.org/10.1016/S0026-0495(98)90056-7 pmid: 9550542
31 P Chou, KC Lin, HY Lin, ST Tsai. Gender differences in the relationships of serum uric acid with fasting serum insulin and plasma glucose in patients without diabetes. J Rheumatol 2001; 28(3): 571–576
pmid: 11296961
32 RJ Johnson, T Nakagawa, LG Sanchez-Lozada, M Shafiu, S Sundaram, M Le, T Ishimoto, YY Sautin, MA Lanaspa. Sugar, uric acid, and the etiology of diabetes and obesity. Diabetes 2013; 62(10): 3307–3315
https://doi.org/10.2337/db12-1814 pmid: 24065788
33 Y Zhou, L Fang, L Jiang, P Wen, H Cao, W He, C Dai, J Yang. Uric acid induces renal inflammation via activating tubular NF-kB signaling pathway. PLoS One 2012; 7(6): e39738
https://doi.org/10.1371/journal.pone.0039738 pmid: 22761883
34 M Mazzali, J Hughes, YG Kim, JA Jefferson, DH Kang, KL Gordon, HY Lan, S Kivlighn, RJ Johnson. Elevated uric acid increases blood pressure in the rat by a novel crystal-independent mechanism. Hypertension 2001; 38(5): 1101–1106
https://doi.org/10.1161/hy1101.092839 pmid: 11711505
35 T Nakagawa, KR Tuttle, RA Short, RJ Johnson. Hypothesis: fructose-induced hyperuricemia as a causal mechanism for the epidemic of the metabolic syndrome. Nat Clin Pract Nephrol 2005; 1(2): 80–86
https://doi.org/10.1038/ncpneph0019 pmid: 16932373
36 C Li, MC Hsieh, SJ Chang. Metabolic syndrome, diabetes, and hyperuricemia. Curr Opin Rheumatol 2013; 25(2): 210–216
https://doi.org/10.1097/BOR.0b013e32835d951e pmid: 23370374
[1] FMD-19032-OF-CYL_suppl_1 Download
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed