Diabetes research and clinical practice最新文献

{"title":"The potential of 1H NMR spectroscopy for diabetes diagnosis: a review of current applications and future directions","authors":"Ariane Schiavenin ,&nbsp;Letícia Bergoza ,&nbsp;Ru Angelie Edrada-Ebel ,&nbsp;Sidnei Moura","doi":"10.1016/j.diabres.2025.112380","DOIUrl":"10.1016/j.diabres.2025.112380","url":null,"abstract":"<div><div>By 2045, it is estimated that approximately 783 million, will be living with diabetes. The incidence of diabetes as well other types of is increasing annually and is associated with many adverse outcomes. Early prediction of the risk of hyperglycaemia and intervention are thus important to reduce adverse outcomes. Studies have revealed a correlation between the levels of amino acids, fatty acids, triglycerides, and other metabolites and the occurrence of diabetes. The development of high-throughput technologies used in metabolomics has enabled the detection of changes in the levels of small-molecule metabolites, which can help reflect the overall physiological and pathological status of the body and explore the underlying mechanisms of the development of diabetes. Thus, this review aims to explore the role of metabolomics as promising alternative for hyperglycaemia diagnoses using NMR, as a guide for researchers, as well as for routine method diagnostic users and to provide data for the development of strategies to manage diabetes.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"226 ","pages":"Article 112380"},"PeriodicalIF":6.1,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond glycemic metrics: Real-world benefits of connected insulin pens in type 1 diabetes.","authors":"A Chico, M Pazos-Couselo, L Nattero-Chavez, O Simó-Servat, M Durán-Martínez, E Ugarte-Abasolo, E Aguilera, V Andía, J Moreno-Fernández, M Granados, A Rebollo, E Fernandez-Rubio, C Quirós, M Alpañés, R Márquez, P Beato-Vibora, O Lado-Baleato, M J Picón-César","doi":"10.1016/j.diabres.2025.112377","DOIUrl":"https://doi.org/10.1016/j.diabres.2025.112377","url":null,"abstract":"<p><strong>Aims: </strong>To determine whether connected insulin pens can improve glucose control, variability and patient-reported outcomes in type 1 diabetes.</p><p><strong>Methods: </strong>Prospective, multicenter, real-life clinical practice study with 220 participants treated with multiple daily insulin injections and continuous glucose monitoring. HbA1c, glucometry, quality of life, awareness and fear of hypoglycemia, treatment satisfaction and glucose variability were analyzed before and 12 weeks after using connected pens, with no changes in the treatment regimen or the type of insulin during this period. Omitted basal and prandial insulin injections and delayed prandial doses were recorded and analyzed for their influence on glycemic control.</p><p><strong>Results: </strong>Time in range (TIR), hypoglycemia awareness and patient-reported outcomes improved and HbA1c decreased. Time spent with glucose 120-140 mg/dl increased, whereas time spent 240-300 mg/dl decreased. The omission of basal and prandial insulin doses was frequent (33.8 % and 65.7 %, respectively) as well delayed injections (90.5 %). The omission of basal insulin had a greater impact than prandial omissions: increase in 10/16 variability indexes examined and time above range, and decrease in TIR and TTIR. Delayed prandial doses elicited an increase in 7/16 analyzed variability parameters.</p><p><strong>Conclusions: </strong>Connected insulin pens enhanced glycemic control, mitigated glucose variability and improve patient-reported outcomes.</p>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":" ","pages":"112377"},"PeriodicalIF":6.1,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144689429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to \"Economic burden of podiatric care for diabetic foot ulcers in the Czech Republic: A prospective multicenter study\". [Diabetes Res. Clin. Pract. 223 (2025) 112141].","authors":"Vladimíra Fejfarová, Miroslav Koliba, Pavlína Piťhová, Milan Flekač, Věra Prýmková, Johana Venerová, Jan Stryja, Martina Košková, Hana Kůsová, Jan Mareš, Alexandra Jirkovská, Jarmila Jirkovská, Bedřich Sixta","doi":"10.1016/j.diabres.2025.112369","DOIUrl":"https://doi.org/10.1016/j.diabres.2025.112369","url":null,"abstract":"","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":" ","pages":"112369"},"PeriodicalIF":6.1,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144667327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of diabetic retinopathy using machine learning and its association with dementia risk in older adults with type 2 diabetes mellitus","authors":"So Hee Lee ,&nbsp;Gyubeom Hwang ,&nbsp;Dong Yun Lee ,&nbsp;Ja Young Jeon ,&nbsp;Seung-Jin Kwag ,&nbsp;Seo Young Sohn ,&nbsp;Sang Joon Park ,&nbsp;Dughyun Choi ,&nbsp;Sang Youl Rhee ,&nbsp;Rae Woong Park","doi":"10.1016/j.diabres.2025.112378","DOIUrl":"10.1016/j.diabres.2025.112378","url":null,"abstract":"<div><h3>Aims</h3><div>Diabetic Retinopathy (DR), a common microvascular complication of diabetes, has been associated with an increased risk of dementia. This study aimed to develop Machine Learning (ML) models to predict DR occurrence and evaluate its potential as a prognostic biomarker for dementia.</div></div><div><h3>Methods</h3><div>We included 27,929 patients aged ≥ 50 years newly diagnosed with type 2 diabetes mellitus without prior dementia or eye disease. Prediction models for DR within one year were developed using three ML algorithms: extreme gradient boosting (XGBoost), random forest, and least absolute shrinkage and selection operator. The best-performing model was externally validated across eight institutions. Patients were followed for three years to assess dementia incidence. Dementia risk between ML-predicted DR and non-DR groups was compared using Kaplan-Meier and Cox regression, with results pooled via meta-analysis.</div></div><div><h3>Results</h3><div>XGBoost demonstrated the best performance (AUROC: 0.746), with external validation AUROCs ranging from 0.555 to 0.620. Predicted DR was significantly associated with increased all-cause dementia risk (HR: 1.32, 95% confidence interval [CI] 1.12–1.56), Alzheimer’s disease (HR: 1.30, 95% CI 1.07–1.58), and vascular dementia (HR: 1.38, 95% CI 1.12–1.69).</div></div><div><h3>Conclusions</h3><div>ML-predicted DR was significantly associated with future dementia, highlighting its value in early risk stratification among patients with diabetes.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"226 ","pages":"Article 112378"},"PeriodicalIF":6.1,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144658692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to \"Divergence in prediabetes guidelines - A global perspective\" [Diabetes Res. Clin. Pract. 223 (2025) 112142].","authors":"Gupta Pragati, Pozzilli Paolo","doi":"10.1016/j.diabres.2025.112370","DOIUrl":"https://doi.org/10.1016/j.diabres.2025.112370","url":null,"abstract":"","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":" ","pages":"112370"},"PeriodicalIF":6.1,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144648821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel data-driven pathophysiological phenotypes among women with prediabetes in an Indian population.","authors":"Elezebeth Mathews, Anjaly Joseph, Anand Nair, Brian Oldenburg, Kavumpurathu R Thankappan, K M Venkat Narayan","doi":"10.1016/j.diabres.2025.112374","DOIUrl":"https://doi.org/10.1016/j.diabres.2025.112374","url":null,"abstract":"<p><strong>Aims: </strong>Data on pathophysiological phenotypes for prediabetes in Indian ethnic populations are scarce. We investigated data-driven, pathophysiological phenotypes of prediabetes associated with the incidence of diabetes mellitus.</p><p><strong>Methods: </strong>We characterised pathophysiological prediabetes phenotypes in a survey sample (n = 1455), and its progression to diabetes at one year. Data-driven clusters were identified usingk-means cluster algorithm along with measures of glycaemia, adiposity, dyslipidaemia, beta-cell function, insulin resistance and blood pressure. Logistic regression analysis was employed to assess the risk of diabetes incidence.</p><p><strong>Results: </strong>Four distinct pathophysiological prediabetes phenotypes were identified: Phenotype 1 (Combined Insulin Resistant and Deficient Prediabetes- CIRDP) [n = 323, 22.2 %]; Phenotype 2 (Severe Insulin Resistant Obese Prediabetes- SIROP) [n = 290, 19.9 %]; Phenotype 3 (Severe Insulin Deficient Prediabetes- SIDP) [n = 544, 37.4 %] and Phenotype 4 (High Blood Pressure Moderate Insulin Deficient Prediabetes- HBPMIDP) [n = 298, 20.5 %]. At one year, the progression to diabetes was highest in Phenotype 1- CIRDP (OR: 6.07, 95 % CI: 3.59-10.65), followed by Phenotype 4- HBPMIDP (OR: 2.05, 95 % CI- 1.10, 3.87) compared to Phenotype 3- SIDP after adjusting for age, BMI, educational and marital status.</p><p><strong>Conclusions: </strong>CIRDP and HBPMIDP had higher progression rates to diabetes at one year compared to SIDP. Eighty percent of the pathophysiological prediabetes phenotypes displayed beta-cell dysfunction.</p>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":" ","pages":"112374"},"PeriodicalIF":6.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144648822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-world implementation of a clinic-community Food is Medicine intervention for patients with type 2 diabetes","authors":"Marcela D. Radtke ,&nbsp;Lan Xiao ,&nbsp;Wei-ting Chen ,&nbsp;Michelle Castro ,&nbsp;Peter Mojarras ,&nbsp;Bill Gibbs ,&nbsp;Monica Parra ,&nbsp;Lisa G. Rosas","doi":"10.1016/j.diabres.2025.112376","DOIUrl":"10.1016/j.diabres.2025.112376","url":null,"abstract":"<div><h3>Aims</h3><div>To evaluate the impact of a real-world implementation of a Food is Medicine intervention on improvements in health outcomes for patients in a rural area.</div></div><div><h3>Methods</h3><div>Patients with type 2 diabetes and food insecurity were referred by their primary care provider to receive weekly vouchers redeemable at a local food bank. Outcomes, including Hemoglobin A1c (HbA1c), Body Mass Index (BMI), and blood pressure (BP), were measured at baseline and follow-up. Voucher redemption and attendance at health education sessions were recorded throughout the intervention (November 2023-April 2024). Linear mixed effects models were used to determine the association between voucher redemption and health outcomes.</div></div><div><h3>Results</h3><div>Patients (n = 165) identified as Latinx (86 %) and female (73 %), with a median of 17 weekly food voucher redemptions (IQR: 15–22). After controlling for the number of pickups and days between baseline and follow-up clinic visits, significant improvements in HbA1c were observed (−0.34 [-0.59, −0.09]; p = 0.008), with 38 % of patients demonstrating a clinically relevant decrease in HbA1c levels of 0.5 %. There were no significant improvements in BMI or BP.</div></div><div><h3>Conclusions</h3><div>Participation in this clinic-community Food is Medicine intervention was associated with improvements in HbA1c in Latinx patients and increased engagement in behavioral lifestyle choices for disease management.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"226 ","pages":"Article 112376"},"PeriodicalIF":6.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144648823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PhenoAgeAccel is associated with all-cause and cardiovascular mortality in patients with diabetes and prediabetes: A cohort study","authors":"Junyu Xi ,&nbsp;Zeyu Zhang ,&nbsp;Baoluo Hou ,&nbsp;Yuqi Wu ,&nbsp;Yifei Zhang ,&nbsp;Weijing Liu","doi":"10.1016/j.diabres.2025.112375","DOIUrl":"10.1016/j.diabres.2025.112375","url":null,"abstract":"<div><h3>Aims</h3><div>Phenotypic Age Acceleration (PhenoAgeAccel) is a measure of biological aging, with higher scores indicating faster aging. Few studies have explored its association with mortality in patients with diabetes or prediabetes. This study aimed to investigate the predictive value of PhenoAgeAccel for all-cause and cardiovascular mortality in these patients.</div></div><div><h3>Methods</h3><div>NHANES data (1999–2018) from 15,939 participants were analyzed. Phenotypic age was calculated from biomarkers such as albumin, creatinine, and glucose, and PhenoAgeAccel was defined as the residual from regressing phenotypic age on actual age. Mortality associations were assessed via Kaplan-Meier, Cox models, restricted cubic spline (RCS), and subgroup analyses.</div></div><div><h3>Results</h3><div>Per 1-year increase in PhenoAgeAccel was associated with a 5.1 % higher risk of all-cause mortality (HR = 1.051, 95 % CI: 1.046–1.057) and a 5.4 % increased risk of cardiovascular mortality (HR = 1.054, 95 % CI: 1.044–1.065) in patients with diabetes or prediabetes. Highest-quartile (Q4) patients had 191.9 % higher all-cause mortality and 192.6 % higher cardiovascular mortality versus Q1 (both p &lt; 0.001). RCS analysis revealed linear positive associations of PhenoAgeAccel with both all-cause and cardiovascular mortality (both P-nonlinear &gt; 0.05).</div></div><div><h3>Conclusion</h3><div>Higher PhenoAgeAccel is associated with increased all-cause and cardiovascular mortality in patients with diabetes and prediabetes.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"226 ","pages":"Article 112375"},"PeriodicalIF":6.1,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144636535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The necessity of strengthening glycemic and lipid metabolism management for improving brain structure and cognitive function in people with diabetes: A retrospective study based on UK Biobank","authors":"Li Han ,&nbsp;Qijun Li ,&nbsp;Lifan Zhang ,&nbsp;Jie Yu ,&nbsp;Yiwen Liu ,&nbsp;Wei Li ,&nbsp;Fan Ping ,&nbsp;Huabing Zhang ,&nbsp;Yuxiu Li ,&nbsp;Lingling Xu","doi":"10.1016/j.diabres.2025.112366","DOIUrl":"10.1016/j.diabres.2025.112366","url":null,"abstract":"<div><h3>Objective</h3><div>To investigate the relation of glycemic and lipid metabolism with brain structure and cognitive function in people with diabetes, so as to improve cognitive function in these individuals.</div></div><div><h3>Methods</h3><div>Based on the UK Biobank, 26,394 patients, who were diagnosed with diabetes by doctors between 2006 and 2010, were included in the study. The demographic information, clinical data of glycemic and lipid metabolism and cognitive function (brain MRI and cognitive function scores) were collected. Multiple linear regression and non-restricted cubic spline analyses were used to investigate the relations of glycemic and lipid metabolism with brain structure and cognitive function.</div></div><div><h3>Results</h3><div>In this study, the mean age of people with diabetes (containing 39 % females) was 59.58 ± 7.21 years. Higher random blood glucose (β = −0.116, p &lt; 0.001) and glycosylated hemoglobin (HbA1c) (β = −0.062, p = 0.051) were associated with a smaller brain volume. Higher HbA1c (β = 0.036, p &lt; 0.001; β = 0.023, p = 0.021) was related with worse cognitive function. Further analysis showed that HbA1c &lt; 6.5 % had a protective effect on cognitive function, and HbA1c = 6.5 %∼8.5 % and &gt;8.5 % was unrelated and negatively related with cognitive function, respectively. Different types of lipids had varying effects on cognitive function. Higher total cholesterol (TC) (β = 0.125, p = 0.008), low density lipoprotein-cholesterol (LDL-C) (β = 0.086, p = 0.025), and ApoB (β = 0.092, p = 0.026) were associated with more significant brain structural abnormalities. Conversely, triglyceride (TG) = 0.75∼8.0 mmol/L was positively correlated with cognitive function (β = −0.036, p &lt; 0.001; β = −0.044, p &lt; 0.001; β = 0.058, p = 0.001), and higher ApoA (β = −0.032, p &lt; 0.001; β = −0.033, p &lt; 0.001; β = 0.047, p = 0.004) was associated with better cognitive function. The age-stratified analysis revealed that the impact of lipids on cognitive function was age-dependent. TC and LDL-C were related to brain structural abnormalities in the 55–60 age group, while TG had a stronger protective effect on cognitive function in older adults, particularly those aged 65–70 years.</div></div><div><h3>Conclusion</h3><div>In people with diabetes, higher HbA1c (&gt;8.5 %), as well as elevated TC, LDL-C, and ApoB, are associated with worse brain structure and cognitive function. Conversely, HbA1c &lt; 6.5 % and elevated TG within the range of 0.75∼8.0 mmol/L have a protective effect on cognitive function, and the later exhibited more evident impact in older adults. To prevent or delay the onset of dementia in people with diabetes, it may be necessary to intensify glycemic control, targeting an HbA1c level of &lt;6.5 %. Additionally, the age-specific lipid-lowering strategies shall be considered, with more flexible triglyceride-lowering goals for elderly patients.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"226 ","pages":"Article 112366"},"PeriodicalIF":6.1,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144636536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diabetic retinopathy and chronic kidney disease synergistically increase the risk of incident cardiovascular disease in type 2 diabetes: Insights from two cohort studies","authors":"Yeon Soo Park ,&nbsp;Kyu Na Lee ,&nbsp;Bo Kyung Koo ,&nbsp;Soo Heon Kwak ,&nbsp;Kyung Do Han ,&nbsp;Min Kyong Moon","doi":"10.1016/j.diabres.2025.112373","DOIUrl":"10.1016/j.diabres.2025.112373","url":null,"abstract":"<div><h3>Aims</h3><div>Chronic kidney disease (CKD) is a well-established cardiovascular risk factor for type 2 diabetes (T2D); however, the role of diabetic retinopathy (DR) remains unclear. This study evaluated the individual and combined effects of DR and CKD on cardiovascular disease (CVD) in T2D.</div></div><div><h3>Methods</h3><div>We analyzed individuals with T2D and no prior CVD from the Korean NHIS cohort (n = 2,064,406) and the UK Biobank (n = 21,350). The primary outcome was a composite of cardiovascular death, nonfatal myocardial infarction, and nonfatal stroke.</div></div><div><h3>Results</h3><div>In the Korean cohort, adjusted hazard ratios (aHRs) for the primary outcome were elevated in those with PDR (aHR 1.37), CKD (aHR 1.36), and even more so when both were present (aHR 2.21), compared to individuals without DR or CKD. Similar results were observed in the UK Biobank. The effect of PDR on CVD was strongest in younger individuals, with aHRs of 3.28 (&lt;40 years), 1.77 (40–64 years), and 1.29 (≥65 years) (Reference: No DR in each age group).</div></div><div><h3>Conclusions</h3><div>PDR and CKD, both independently and in combination, increase cardiovascular risk in individuals with T2D, particularly among younger age groups. These findings support incorporating PDR into cardiovascular risk assessment and management.</div></div>","PeriodicalId":11249,"journal":{"name":"Diabetes research and clinical practice","volume":"226 ","pages":"Article 112373"},"PeriodicalIF":6.1,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}