Abstract: Đái tháo đường (ĐTĐ) tuýp 2 là một trong những căn bệnh có xu hướng ngày càng tăng với nhiều biến chứng nguy hiểm, trong đó có nguy cơ gia tăng các tổn thương hệ tim mạch. Ước tính khoảng 75% bệnh nhân ĐTĐ tuýp 2 tử vong do hậu quả của các bệnh tim mạch. Tuy nhiên, ở Việt Nam chưa có nhiều nghiên cứu đánh giá nguy cơ mắc bệnh tim mạch trong 10 năm theo thang điểm Framingham (Framingham Risk Score - FRS) ở bệnh nhân ĐTĐ tuýp 2. Để dự đoán nguy cơ mắc bệnh tim mạch trong 10 năm và các yếu tố liên quan đến tình trạng này, chúng tôi tiến hành nghiên cứu theo phương pháp mô tả, cắt ngang trên 139 bệnh nhân (62 nam và 77 nữ) ĐTĐ tuýp 2, có độ tuổi trung bình 66,31 ± 8,88, cho thấy chủ yếu các bệnh nhân thuộc nhóm nguy cơ rất cao (41,7%), nguy cơ cao (17,3%), nguy cơ trung bình (20,9%) và nguy cơ thấp (20,1%). Nguy cơ mắc bệnh tim mạch cao hơn ở bệnh nhân nam, trên 60 tuổi, chỉ số khối cơ thể cao, có tình trạng rối loạn lipid máu. Với bệnh nhân ĐTĐ tuýp 2 kèm theo tăng huyết áp có khả năng làm tăng nguy cơ ở mức rấtcao lên 10,784 lần.

Abstract: Today, the incidence of type 2 diabetes mellitus is increasing rapidly on global. This disease is shown with many complications that significantly affect public health. One of them is kidney complications, which have a high incidence among diabetic patients in Vietnam (25.6-33.1%). Age, history of hypertension, and dyslipidemia are considered to be the main risk factors for diabetic nephropathy. Thus, early detection of these factors for kidney damage is significant for diagnosing, monitoring, treatment, and prognosis of diabetic patients. Our descriptive, cross-sectional study conducting on 120 diabetic patients at E Hospital has observed that blood cholesterol levels, HbA1c levels were independently related to eGFR decline below 60 mL/min/1.73m2. From those data, an equation to predict the risk of diabetic kidney disease was estimated as p =  with k = Keyword: Type 2 diabetes, Diabetic nephropathy, Risk factor Today, the incidence of type 2 diabetes mellitus is increasing rapidly on global. This disease is shown with many complications that significantly affect public health. One of them is kidney complications, which have a high incidence among diabetic patients in Vietnam (25.6-33.1%). Age, history of hypertension, and dyslipidemia are considered to be the main risk factors for diabetic nephropathy. Thus, early detection of these factors for kidney damage is significant for diagnosing, monitoring, treatment, and prognosis of diabetic patients. Our descriptive, cross-sectional study conducting on 120 diabetic patients at E Hospital has observed that blood cholesterol levels, HbA1c levels were independently related to eGFR decline below 60 mL/min/1.73m2. 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Abstract:  The incidence of type 2 diabetes mellitus is rapidly increasing, with many complications pressured on the health care system. Complications of diabetes due to chronic hyperglycemia related to other metabolic disorders, causing damage to the microvascular system. Among them, damaged kidney vessels lead to impair the renal function as diabetic nephropathy is the most common cause of end-stage renal disease. Measurement of glomerular filtration rate (GFR) is an important parameter in assessing renal function. In Vietnam’s hospital, serum creatinine is the biomarker mostly used to assess GFR. However, this biomarker is affected many factors such as gender, age, ... Many studies showed that serum Cystatin C is another biomarker that can detect early decline in GFR, less affected by other factors. Therefore, we conducted this study to explore serum cystatin C and creatinine levels in patients with type 2 diabetes and initially compare GFR in applying formulas of CKD.EPI 2012 and age and sex factors with these two biomarkers on those patient groups. The prospective, descriptive, cross-sectional study was performed on 50 patients with type 2 diabetes. Serum Cystatin C, serum creatinine test was performed and GFR was estimated by CKD.EPI 2012 equation. The results showed that the average serum Cystatin C level of the study group was 0.87 ± 0.24 mg/L that expressed no difference between two genders, and significant difference between age groups. Whereas, the average serum creatinine level of the study group was 81.30 ± 19.70 µmol/L, significant difference between male and female but not difference between age groups. In patients with GFR 〈 60 mL/min/1.73m2, serum creatinine and cystatin C levels were higher than normal but there was no difference with the upper limit in the normal reference range of the two indications. Keyword Type 2 diabetes, serum cystatin C, serum creatinine, glomerular filtration rate. References [1] N.H. Cho, J. Kirigia, J.C. Mnanya, K. Ogurstova, L. Gủaiguata, W. Rathmann, G. Roglic, N. Forouhi, R. Dajani, A. Esteghmati, E. Boyko, L. Hambleton, O.L.M. Neto, P.A. Montoya, S. Joshi, J. Chan, J. Shaw, T.A. Samuels, M. Pavkov, A. Reja, IDF Diabetes Atlas eight edition, International Diabete Federation, 2017. http://fmdiabetes.org/wp-content/uploads/2018/03/IDF-2017.pdf (access 15 july 2019).[2] G. Xu, B. Liu, Y. Sun, Y. Du, L.G. Snetselaar, F.B. Hu, W. Bao, Prevalence of diagnosed type 1 and type 2 diabetes among US adults in 2016 and 2017: population based study, British Medical Journal 361 (2018) k1497. https://doi.org/ 10.1136/bmj.k1497.[3] N.T.T. Minh, N.K. Luong, N.K. Son, The clinical and subclinical characteristics in patients with diabetes mellitus treated at Thai Nguyen General hospital, Journal of pratical medicine 787 (2011) 25-8.[4] N.T.H. Lan, L.D. Tuan, Survey characteristics of renal complication in elderly type 2 diabetes outpatients treated at National Hospital of Endocrinology, Journal of Military Pharmaco-medicine 6 2017 55-62. [5] Mohsen Pourghasem, Hamid Shafi, Zahra, Histological changes of kidney in diabetic nephropathy, Caspian J Intern Med 6(3) (2015) 120-7. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4650785/pdf/cjim-6-120.pdf (access 16 july 2019).[6] D.W. Powell, D.N. Kenagy, S. Zheng, S.C. Coventry, J. Xu, L. Cai, E.C. Carlson, P.N. Epstein, Associations between Structural and Functional Changes to the Kidney in Diabetic Humans and Mice, Life Sci 93(7) (2013) 257-64. https://doi.org/ 10.1016/j.lfs.2013.06.016.[7] Natalie Ebert, Elke Schaeffner, New biomarkers for estimating glomerular filtration rate, Journal of Laboratory and Precision Medicine 3(75) (2018. https://doi.org/10.21037/jlpm.2018.08.07.[8] L.A. Inker, C.H. Schmid, H. Tighiouart, J.H. Eckfeldt, H.I. Feldman, T. Greene, J.W. Kusek, J. Manzi, F.V. Lente, Y.L. Zhang, J. Coresh, A.S. Levey, Estimating Glomerular Filtration Rate from Serum Creatinine and Cystatin C, The new England Journal of Medicine 367 (2012) 20-9. https://doi.org/ 10.1056/NEJMoa1114248.[9] Ashwin Kumar, Anil Kumar, Serum cystatin C and serum creatinine levels in type 2 diabetes mellitus, International Journal of Research in Medical Sciences 3(1) (2015) 174-7. https://doi.org/10.5455/2320-6012.ijrms20150130.[10] X. Jianguo, D.I. Broadhurst, M. Wilson, D.S. Wishart, Translational biomarker discovery in clinical metabolomics:an introductory tutorial, Metabolomics 9 (2013) 280–99. https://doi.org/ 10.1007/s11306-012-0482-9.[11] B.T. Anh, Estimate the glomerular filtration rate by plasma creatinine and cystatin C concentration, Journal of Vietnam Medicine 2 (2012) 12-18.[12] S. Kakde, S. Alexander, V.G. David, S. Jacob, A. Mohapatra, A.T. Valson, B. Gopal, C.K. Jacob, J. Hephzibah, V. Tamilarasi, S. Varughese, Relationship of creatinine and cystatin C-based estimated glomerular filtration rates with measured glomerular filtration rate in healthy kidney donors from South Asia, Indian J Nephrol 28 (2018) 345-50. https://doi.org/ 0.4103/ijn.IJN 249_17[13] Olympus life science research europa GmbH, Olympus clinical chemistry reagent guide, Olympus Diagnostic, American, 2009.[14] International Society of Nephrology, KDIGO 2012 clinical practice guideline for the evaluation and Management of chronic kidney disease, Kidney Int, Kidney International Supplements 3(1) (2012) 5-14. https://kdigo.org/wp-content/uploads/2017/02/KDIGO_2012_CKD_GL.pdf (access 19 july 2019).[15] American Diabete Association, Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes 2018. Diabetes Care, (41(Supplement 1)) (2018) S13-S27. https://diabetesed.net/wp-content/uploads/2017/12/2018-ADA-Standards-of-Care.pdf (access 18 july 2019).[16] L.S. Weinert, A.B. Prates, F.B. do Amaral, M.Z. Vaccoro, J.L. Camargo, S.P. Silveiro, Gender does not influence cystatin C concentrations in healthy volunteers, Clin Chem Lab Med 48(3) (2010) 405-8. https://doi.org/10.1515/CCLM.2010.068.[17] N.T. Ly, T.T.C. Mai, Serum cystatin C and renal function in type 2 diabetic patients, Journal of medical Research 80(3B) (2012) 17-O.Al.[18] Musaimia, A.H. Abu-Nawwas, D.Al. Shaera, N.Y.Khaleela, M.Fawzi, Influence of age, gender, smoking, diabetes, thyroid and cardiac dysfunctions on cystatin C biomarker, Medicina de Familia Semergen 45(1) (2019) 44-51. https://doi.org/ 10.1016/j.semerg.2018.07.005.[19] M.C. Odden, I.B. Tager, R.T. Gansevoort, S.J.L. Bakker, R. Katz, L.F. Fried, et al, Age and cystatin C in healthy adults: a collaborative study, Nephrol Dial Transplant 25(2) (2010) 463-9. https://doi.org/10.1093/ndt/gfp474.[20] E.D. O’ Sullivan, J. Hughes, D.A. Ferenbach, Renal Aging: Causes and Consequences, J Am Soc Nephrol 28 (2017) 407–20. https://doi.org/10.1681/ASN.2015121308.[21] E.D. O’ Sullivan, J. Hughes, D.A. Ferenbach, Renal Aging: Causes and Consequences, J Am Soc Nephrol 28 (2017) 407–20. https://doi.org/10.1681/ASN.2015121308.[22] Christiane Oddoze, Henri Portugal, Yvon Berland, Bertrand Dussol, Cystatin C Is Not More Sensitive Than Creatinine for Detecting Early Renal Impairment in Patients With Diabetes. American Journal of Kidney Diseases, 38(2 (August)), (2001) 310-6. https://doi.org/ 10.1053/ajkd.2001.26096.      

Abstract: Little is known about the natural history of asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Methods We conducted a prospective study at a quarantine center for coronavirus disease 2019 in Ho Chi Minh City, Vietnam. We enrolled quarantined people with reverse-transcription polymerase chain reaction (RT-PCR)–confirmed SARS-CoV-2 infection, collecting clinical data, travel and contact history, and saliva at enrollment and daily nasopharyngeal/throat swabs (NTSs) for RT-PCR testing. We compared the natural history and transmission potential of asymptomatic and symptomatic individuals. Results Between 10 March and 4 April 2020, 14 000 quarantined people were tested for SARS-CoV-2; 49 were positive. Of these, 30 participated in the study: 13 (43%) never had symptoms and 17 (57%) were symptomatic. Seventeen (57%) participants imported cases. Compared with symptomatic individuals, asymptomatic people were less likely to have detectable SARS-CoV-2 in NTS collected at enrollment (8/13 [62%] vs 17/17 [100%] ; P = .02). SARS-CoV-2 RNA was detected in 20 of 27 (74%) available saliva samples (7 of 11 [64%] in the asymptomatic group and 13 of 16 [81%] in the symptomatic group; P = .56). Analysis of RT-PCR positivity probability showed that asymptomatic participants had faster viral clearance than symptomatic participants (P  & lt; .001 for difference over the first 19 days). This difference was most pronounced during the first week of follow-up. Two of the asymptomatic individuals appeared to transmit SARS-CoV-2 to 4 contacts. Conclusions Asymptomatic SARS-CoV-2 infection is common and can be detected by analysis of saliva or NTSs. The NTS viral loads fall faster in asymptomatic individuals, but these individuals appear able to transmit the virus to others.

Abstract: The AFFINITY trial (Assessment of Fluoxetine in Stroke Recovery) reported that oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and seizures. After trial medication was ceased at 6 months, survivors were followed to 12 months post-randomization. This preplanned secondary analysis aimed to determine any sustained or delayed effects of fluoxetine at 12 months post-randomization. Methods: AFFINITY was a randomized, parallel-group, double-blind, placebo-controlled trial in adults (n=1280) with a clinical diagnosis of stroke in the previous 2 to 15 days and persisting neurological deficit who were recruited at 43 hospital stroke units in Australia (n=29), New Zealand (4), and Vietnam (10) between 2013 and 2019. Participants were randomized to oral fluoxetine 20 mg once daily (n=642) or matching placebo (n=638) for 6 months and followed until 12 months after randomization. The primary outcome was function, measured by the modified Rankin Scale, at 6 months. Secondary outcomes for these analyses included measures of the modified Rankin Scale, mood, cognition, overall health status, fatigue, health-related quality of life, and safety at 12 months. Results: Adherence to trial medication was for a mean 167 (SD 48) days and similar between randomized groups. At 12 months, the distribution of modified Rankin Scale categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio, 0.93 [95% CI, 0.76–1.14]; P =0.46). Compared with placebo, patients allocated fluoxetine had fewer recurrent ischemic strokes (14 [2.18%] versus 29 [4.55%] ; P =0.02), and no longer had significantly more falls (27 [4.21%] versus 15 [2.35%] ; P =0.08), bone fractures (23 [3.58%] versus 11 [1.72%] ; P =0.05), or seizures (11 [1.71%] versus 8 [1.25%] ; P =0.64) at 12 months. Conclusions: Fluoxetine 20 mg daily for 6 months after acute stroke had no delayed or sustained effect on functional outcome, falls, bone fractures, or seizures at 12 months poststroke. The lower rate of recurrent ischemic stroke in the fluoxetine group is most likely a chance finding. Registration: URL: http://www.anzctr.org.au/ ; Unique identifier: ACTRN12611000774921.