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Wang M, He Y, He Q, Di F, Zou K, Wang W, Sun X. Comparison of clinical characteristics and disease burden between early- and late-onset type 2 diabetes patients: a population-based cohort study. BMC Public Health 2023; 23:2411. [PMID: 38049796 PMCID: PMC10696789 DOI: 10.1186/s12889-023-17280-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 11/21/2023] [Indexed: 12/06/2023] Open
Abstract
BACKGROUND The clinical characteristics of early-onset type 2 diabetes (T2D) patients are not fully understood. To address this gap, we conducted a cohort study to evaluate clinical characteristics and disease burden in the new-onset T2D population, especially regarding the progression of diseases. METHODS This cohort study was conducted using a population-based database. Patients who were diagnosed with T2D were identified from the database and were classified into early- (age < 40) and late-onset (age ≥ 40) groups. A descriptive analysis was performed to compare clinical characteristics and disease burden between early- and late-onset T2D patients. The progression of disease was compared using Kaplan‒Meier analysis. RESULTS A total of 652,290 type 2 diabetic patients were included. Of those, 21,347 were early-onset patients, and 300,676 were late-onset patients. Early-onset T2D patients had poorer glycemic control than late-onset T2D patients, especially at the onset of T2D (HbA1c: 9.3 [7.5, 10.9] for early-onset vs. 7.7 [6.8, 9.2] for late-onset, P < 0.001; random blood glucose: 10.9 [8.0, 14.3] for early-onset vs. 8.8 [6.9, 11.8] for late-onset, P < 0.001). Insulin was more often prescribed for early-onset patients (15.2%) than for late-onset patients (14.8%). Hypertension (163.0 [28.0, 611.0] days) and hyperlipidemia (114.0 [19.0, 537.0] days) progressed more rapidly among early-onset patients, while more late-onset patients developed hypertension (72.7% vs. 60.1%, P < 0.001), hyperlipidemia (65.4% vs. 51.0%, P < 0.001), cardiovascular diseases (66.0% vs. 26.7%, P < 0.001) and chronic kidney diseases (5.5% vs. 2.1%, P < 0.001) than early-onset patients. CONCLUSIONS Our study results indicate that patients with newly diagnosed early-onset T2D had earlier comorbidities of hypertension and hyperlipidemia. Both clinical characteristics and treatment patterns suggest that the degree of metabolic disturbance is more severe in patients with early-onset type 2 diabetes. This highlights the importance of promoting healthy diets or lifestyles to prevent T2D onset in young adults.
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Affiliation(s)
- Mingqi Wang
- Chinese Evidence-based Medicine Center and Cochrane China Center, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
- NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, China
- Sichuan Center of Technology Innovation for Real World Data, Chengdu, 610041, China
| | - Yifei He
- Chinese Evidence-based Medicine Center and Cochrane China Center, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
- NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, China
- Sichuan Center of Technology Innovation for Real World Data, Chengdu, 610041, China
| | - Qiao He
- Chinese Evidence-based Medicine Center and Cochrane China Center, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
- NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, China
- Sichuan Center of Technology Innovation for Real World Data, Chengdu, 610041, China
| | - Fusheng Di
- Department of Endocrinology, Tianjin Third Central Hospital, Tianjin, 300000, China
| | - Kang Zou
- Chinese Evidence-based Medicine Center and Cochrane China Center, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
- NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, China
- Sichuan Center of Technology Innovation for Real World Data, Chengdu, 610041, China
| | - Wen Wang
- Chinese Evidence-based Medicine Center and Cochrane China Center, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
- NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, China.
- Sichuan Center of Technology Innovation for Real World Data, Chengdu, 610041, China.
| | - Xin Sun
- Chinese Evidence-based Medicine Center and Cochrane China Center, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
- NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, West China Hospital, Sichuan University, 37 Guo Xue Xiang, Chengdu, 610041, China.
- Sichuan Center of Technology Innovation for Real World Data, Chengdu, 610041, China.
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Sidoli C, Zambon A, Tassistro E, Rossi E, Mossello E, Inzitari M, Cherubini A, Marengoni A, Morandi A, Bellelli G, Tarasconi A, Sella M, Paternò G, Faggian G, Lucarelli C, De Grazia N, Alberto C, Porcella L, Nardiello I, Chimenti E, Zeni M, Romairone E, Minaglia C, Ceccotti C, Guerra G, Mantovani G, Monacelli F, Minaglia C, Candiani T, Santolini F, Minaglia C, Rosso M, Bono V, Sibilla S, Dal Santo P, Ceci M, Barone P, Schirinzi T, Formenti A, Nastasi G, Isaia G, Gonella D, Battuello A, Casson S, Calvani D, Boni F, Ciaccio A, Rosa R, Sanna G, Manfredini S, Cortese L, Rizzo M, Prestano R, Greco A, Lauriola M, Gelosa G, Piras V, Arena M, Cosenza D, Bellomo A, LaMontagna M, Gabbani L, Lambertucci L, Perego S, Parati G, Basile G, Gallina V, Pilone G, Giudice C, Pietrogrande L, Mosca M, Corazzin I, Rossi P, Nunziata V, D’Amico F, Grippa A, Giardini S, Barucci R, Cossu A, Fiorin L, Arena M, Distefano M, Lunardelli M, Brunori M, Ruffini I, Abraham E, Varutti A, Fabbro E, Catalano A, Martino G, Leotta D, Marchet A, Dell’Aquila G, Scrimieri A, Davoli M, Casella M, Cartei A, Polidori G, Basile G, Brischetto D, Motta S, Saponara R, Perrone P, Russo G, Del D, Car C, Pirina T, Franzoni S, Cotroneo A, Ghiggia F, Volpi G, Menichetti C, Bo M, Panico A, Calogero P, Corvalli G, Mauri M, Lupia E, Manfredini R, Fabbian F, March A, Pedrotti M, Veronesi M, Strocchi E, Borghi C, Bianchetti A, Crucitti A, DiFrancesco V, Fontana G, Geriatria A, Bonanni L, Barbone F, Serrati C, Ballardini G, Simoncelli M, Ceschia G, Scarpa C, Brugiolo R, Fusco S, Ciarambino T, Biagini C, Tonon E, Porta M, Venuti D, DelSette M, Poeta M, Barbagallo G, Trovato G, Delitala A, Arosio P, Reggiani F, Zuliani G, Ortolani B, Mussio E, Girardi A, Coin A, Ruotolo G, Castagna A, Masina M, Cimino R, Pinciaroli A, Tripodi G, Cassadonte F, Vatrano M, Scaglione L, Fogliacco P, Muzzuilini C, Romano F, Padovani A, Rozzini L, Cagnin A, Fragiacomo F, Desideri G, Liberatore E, Bruni A, Orsitto G, Franco M, Bonfrate L, Bonetto M, Pizio N, Magnani G, Cecchetti G, Longo A, Bubba V, Marinan L, Cotelli M, Turla M, Brunori M, Sessa M, Abruzzi L, Castoldi G, LoVetere D, Musacchio C, Novello M, Cavarape A, Bini A, Leonardi A, Seneci F, Grimaldi W, Seneci F, Fimognari F, Bambar V, Saitta A, Corica F, Braga M, Servi, Ettorre E, Camellini Bellelli CG, Annoni G, Marengoni A, Bruni A, Crescenzo A, Noro G, Turco R, Ponzetto M, Giuseppe L, Mazzei B, Maiuri G, Costaggiu D, Damato R, Fabbro E, Formilan M, Patrizia G, Santuar L, Gallucci M, Minaglia C, Paragona M, Bini P, Modica D, Abati C, Clerici M, Barbera I, NigroImperiale F, Manni A, Votino C, Castiglioni C, Di M, Degl’Innocenti M, Moscatelli G, Guerini S, Casini C, Dini D, DeNotariis S, Bonometti F, Paolillo C, Riccardi A, Tiozzo A, SamySalamaFahmy A, Riccardi A, Paolillo C, DiBari M, Vanni S, Scarpa A, Zara D, Ranieri P, Alessandro M, Calogero P, Corvalli G, Di F, Pezzoni D, Platto C, D’Ambrosio V, Ivaldi C, Milia P, DeSalvo F, Solaro C, Strazzacappa M, Bo M, Panico A, Cazzadori M, Bonetto M, Grasso M, Troisi E, Magnani G, Cecchetti G, Guerini V, Bernardini B, Corsini C, Boffelli S, Filippi A, Delpin K, Faraci B, Bertoletti E, Vannucci M, Crippa P, Malighetti A, Caltagirone C, DiSant S, Bettini D, Maltese F, Formilan M, Abruzzese G, Minaglia C, Cosimo D, Azzini M, Cazzadori M, Colombo M, Procino G, Fascendini S, Barocco F, Del P, D’Amico F, Grippa A, Mazzone A, Cottino M, Vezzadini G, Avanzi S, Brambilla C, Orini S, Sgrilli F, Mello A, Lombardi Muti LE, Dijk B, Fenu S, Pes C, Gareri P, Castagna A, Passamonte M, Rigo R, Locusta L, Caser L, Rosso G, Cesarini S, Cozzi R, Santini C, Carbone P, Cazzaniga I, Lovati R, Cantoni A, Ranzani P, Barra D, Pompilio G, Dimori S, Cernesi S, Riccò C, Piazzolla F, Capittini E, Rota C, Gottardi F, Merla L, Barelli A, Millul A, De G, Morrone G, Bigolari M, Minaglia C, Macchi M, Zambon F, D’Amico F, D’Amico F, Pizzorni C, DiCasaleto G, Menculini G, Marcacci M, Catanese G, Sprini D, DiCasalet T, Bocci M, Borga S, Caironi P, Cat C, Cingolani E, Avalli L, Greco G, Citerio G, Gandini L, Cornara G, Lerda R, Brazzi L, Simeone F, Caciorgna M, Alampi D, Francesconi S, Beck E, Antonini B, Vettoretto K, Meggiolaro M, Garofalo E, Bruni A, Notaro S, Varutti R, Bassi F, Mistraletti G, Marino A, Rona R, Rondelli E, Riva I, Cortegiani A, Pistidda L, D’Andrea R, Querci L, Gnesin P, Todeschini M, Lugano M, Castelli G, Ortolani M, Cotoia A, Maggiore S, DiTizio L, Graziani R, Testa I, Ferretti E, Castioni C, Lombardi F, Caserta R, Pasqua M, Simoncini S, Baccarini F, Rispoli M, Grossi F, Cancelliere L, Carnelli M, Puccini F, Biancofiore G, Siniscalchi A, Laici C, Mossello E, Torrini M, Pasetti G, Palmese S, Oggioni R, Mangani V, Pini S, Martelli M, Rigo E, Zuccalà F, Cherri A, Spina R, Calamai I, Petrucci N, Caicedo A, Ferri F, Gritti P, Brienza N, Fonnesu R, Dessena M, Fullin G, Saggioro D. Prevalence and features of delirium in older patients admitted to rehabilitation facilities: a multicenter study. Aging Clin Exp Res 2022; 34:1827-1835. [PMID: 35396698 DOI: 10.1007/s40520-022-02099-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 02/16/2022] [Indexed: 11/01/2022]
Abstract
BACKGROUND Delirium is thought to be common across various settings of care; however, still little research has been conducted in rehabilitation. AIM We investigated the prevalence of delirium, its features and motor subtypes in older patients admitted to rehabilitation facilities during the three editions of the "Delirium Day project". METHODS We conducted a cross-sectional study in which 1237 older patients (age ≥ 65 years old) admitted to 50 Italian rehabilitation wards during the three editions of the "Delirium Day project" (2015 to 2017) were included. Delirium was evaluated through the 4AT and its motor subtype with the Delirium Motor Subtype Scale. RESULTS Delirium was detected in 226 patients (18%), and the most recurrent motor subtype was mixed (37%), followed by hypoactive (26%), hyperactive (21%) and non-motor one (16%). In a multivariate Poisson regression model with robust variance, factors associated with delirium were: disability in basic (PR 1.48, 95%CI: 1.17-1.9, p value 0.001) and instrumental activities of daily living (PR 1.58, 95%CI: 1.08-2.32, p value 0.018), dementia (PR 2.10, 95%CI: 1.62-2.73, p value < 0.0001), typical antipsychotics (PR 1.47, 95%CI: 1.10-1.95, p value 0.008), antidepressants other than selective serotonin reuptake inhibitors (PR 1.3, 95%CI: 1.02-1.66, p value 0.035), and physical restraints (PR 2.37, 95%CI: 1.68-3.36, p value < 0.0001). CONCLUSION This multicenter study reports that 2 out 10 patients admitted to rehabilitations had delirium on the index day. Mixed delirium was the most prevalent subtype. Delirium was associated with unmodifiable (dementia, disability) and modifiable (physical restraints, medications) factors. Identification of these factors should prompt specific interventions aimed to prevent or mitigate delirium.
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Yu H, Liu H, Zhang J, Jia G, Yang L, Zhang Q, Li G, Liu F, Di F, Wang F. Accuracy of FibroTouch in assessing liver steatosis and fibrosis in patients with metabolic-associated fatty liver disease combined with type 2 diabetes mellitus. Ann Palliat Med 2021; 10:9702-9714. [PMID: 34628896 DOI: 10.21037/apm-21-2339] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 09/10/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND Metabolic-associated fatty liver disease (MAFLD) is highly prevalent in type 2 diabetes mellitus (T2DM) patients and can rapidly progress to steatohepatitis, liver fibrosis, and hepatocellular carcinoma (HCC). Accurate evaluation and proper management of MAFLD can help prevent adverse liver outcomes. Here we evaluated the precision of the FibroTouch (FT) in the staging of liver steatosis and fibrosis in patients with MAFLD combined with T2DM using two indicators: controlled attenuation parameter (CAP) and liver stiffness measurement (LSM). METHODS Eighty-five adult MAFLD combined with T2DM patients were selected at our center from July 2016 to July 2019 and underwent liver puncture biopsy for histopathology and the FT assay simultaneously. Two blinded pathologists independently reviewed the samples. The severity of fatty liver was classified using two scoring systems: the nonalcoholic fatty liver disease activity score (NAS) and the fibrosis score. Scores were then assessed following the Pathology Working Group of the NASH Clinical Research Network of the National Institutes of Health. Similarly, the severity of nonalcoholic steatohepatitis (NASH) was classified using the European Steatosis Activity Fibrosis (SAF) system. The FT assay was applied to obtain the LSM and the CAP. FT accuracy in diagnosing steatosis and fibrosis was determined by the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUROC). RESULTS Using biopsy analysis as the gold standard, the AUROCs and cutoff values of CAP in diagnosing liver steatosis were as follows: 0.84 (95% CI: 0.67-1.01) and 278 dB/m for S ≥ S1, 0.88 (95% CI: 0.81-0.95) and 305 dB/m for S ≥ S2, 0.89 (95% CI: 0.82-0.95) and 307 dB/m for S ≥ S3. The AUROCs and cutoff values of LSM in diagnosing liver fibrosis were as follows: 0.76 (95% CI: 0.66-0.86) for F ≥ F2, 0.81 (95% CI: 0.71-0.91) and 13.8 kPa for F ≥ F3, 0.92 (95% CI: 0.85-1.00) and 20.1 kPa for F ≥ F4. CONCLUSIONS In patients of MAFLD with T2DM, CAP and LSM obtained by FT are highly accurate in assess liver steatosis and fibrosis, respectively, with AUROC values ranging from 0.76 to 0.92.
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Affiliation(s)
- Hongyan Yu
- Department of Endocrinology and Metabolism, The Third Central Clinical College of Tianjin Medical University, Tianjin, China; Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, The Third Central Hospital of Tianjin, Tianjin, China
| | - Hui Liu
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, The Third Central Hospital of Tianjin, Tianjin, China
| | - Jie Zhang
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, The Third Central Hospital of Tianjin, Tianjin, China
| | - Guoyu Jia
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, The Third Central Hospital of Tianjin, Tianjin, China
| | - Ling Yang
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, The Third Central Hospital of Tianjin, Tianjin, China
| | - Qin Zhang
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, The Third Central Hospital of Tianjin, Tianjin, China; Department of Pathology, Teda Hospital of Tianjin University, Tianjin, China
| | - Ge Li
- Public Health Science and Engineering College, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Fang Liu
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, The Third Central Hospital of Tianjin, Tianjin, China
| | - Fusheng Di
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, The Third Central Hospital of Tianjin, Tianjin, China
| | - Fengmei Wang
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, The Third Central Hospital of Tianjin, Tianjin, China; Department of Gastroenterology and Hepatology, The Third Central Clinical College of Tianjin Medical University, Tianjin, China
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Xia M, Sun X, Zheng L, Bi Y, Li Q, Sun L, Di F, Li H, Zhu D, Gao Y, Bao Y, Wang Y, He L, Wu B, Wang S, Gao J, Gao X, Bian H. Regional difference in the susceptibility of non-alcoholic fatty liver disease in China. BMJ Open Diabetes Res Care 2020; 8:8/1/e001311. [PMID: 32522731 PMCID: PMC7287499 DOI: 10.1136/bmjdrc-2020-001311] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 04/13/2020] [Accepted: 05/05/2020] [Indexed: 02/05/2023] Open
Abstract
INTRODUCTION Non-alcoholic fatty liver disease (NAFLD) is a global health problem with high geographic heterogeneity. We aimed to investigate regional-specific concomitant rate of NAFLD and quantitative relationship between liver fat content (LFC) and glucose metabolism parameters in representative clinical populations from six provinces/municipalities of China. RESEARCH DESIGN AND METHODS A total of 2420 eligible Han Chinese were enrolled consecutively from 10 clinics of obesity, diabetes and metabolic diseases located at six provinces/municipalities of China, and divided into North (Tianjin, Shandong and Heilongjiang) and South (Shanghai, Jiangsu and Henan) groups according to their geographical latitude and proximity of NAFLD concomitant rate. LFC was assessed by a quantitative ultrasound method. Multivariate regression models and analysis of covariance were used to assess the regional difference in the risk of NAFLD. RESULTS The concomitant rate of NAFLD was 23.3%, 44.0% and 55.3% in individuals with normal glucose tolerance (NGT), pre-diabetes and diabetes, respectively. A higher concomitant rate of NAFLD was found in the participants from the North comparing with the South group, regardless of glucose metabolism status (34.7% vs 16.2% in NGT, 61.5% vs 34.7% in pre-diabetes and 67.1% vs 48.1% in diabetes). This regional difference remained significant after adjustment for age, gender, alcohol drinking, cigarette smoking, confounding metabolic parameters and liver enzymes. For any given blood glucose, participants from the North had higher LFC than those from the South group. CONCLUSIONS Half of Han Chinese with pre-diabetes/type 2 diabetes had NAFLD, and the individuals from the North cities were more susceptible to NAFLD.
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Affiliation(s)
- Mingfeng Xia
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan Institute of Metabolic Disease, Fudan University, Shanghai, China
| | - Xiaoyang Sun
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan Institute of Metabolic Disease, Fudan University, Shanghai, China
| | - Lili Zheng
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yufang Bi
- Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory for Endocrine Tumors of Ministry of Shanghai, Shanghai Institute for Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Qiang Li
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
- Department of Endocrinology and Metabolism, Shenzhen University General Hospital, Shenzhen, China
| | - Lirong Sun
- Key Laboratory of Hormones and Development (Ministry of Health), Tianjin Key Laboratory of Metabolic Diseases, Tianjin Metabolic Diseases Hospital and Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China
| | - Fusheng Di
- Department of Endocrinology and Metabolism, The Third Central Hospital of Tianjin, Tianjin, China
| | - Hong Li
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Dalong Zhu
- Department of Endocrinology and Metabolism, Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing, Jiangsu, China
| | - Yanyan Gao
- Department of Endocrinology and Metabolism, Affiliated Hospital of Medical College, Qingdao University, Qingdao, China
| | - Yuqian Bao
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Department of Endocrinology and Metabolism, Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yao Wang
- Department of Endocrinology and Metabolism, Zhongda Hospital Affiliated to Southeast University Medical School, Nanjing, China
| | - Lanjie He
- Endocrine Testing Center, General Hospital of Ningxia Medical University, Yinchuan, China
- Department of Endocrinology, Qilu Hospital of Shandong University, Qingdao, China
| | - Bingjie Wu
- Department of Rheumatology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Shanshan Wang
- Department of Nephrology, West China Hospital, Sichuan University, Chengdu, China
| | - Jian Gao
- Department of Clinical Nutrition, Zhongshan Hospital, Center of Clinical Epidemiology, EBM of Fudan University, Fudan University, Shanghai, China
| | - Xin Gao
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan Institute of Metabolic Disease, Fudan University, Shanghai, China
| | - Hua Bian
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan Institute of Metabolic Disease, Fudan University, Shanghai, China
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