???? ??????, ???????? ??????, ???? ????, ????? ???????, ??????? ???????, ?????? ??????, ??? ?????, ???? ?????, ?????? ???????, ???? ??, ??? ???? ???????
??????? ???????? ?? ??????????? ???????? ???????? ?? ???????? ???????-?????????????? ?????? ??-?? ?????????? ??????????????? ?????????. ?? ??????? ?????????????? ???????????? ? 1 ?? 30 ?????? 2016 ???? ? ???????? 31 ???????? ???????? ?? ??????????? ? ?????? ??????????????? ???????? ????. ?? ???????????? ?????????, ????????? ?????? ???? 3 ?????? ?????? ???????, ? ?????? ingesta, ????????/??????????????? ?????????? ? ???????????? ?????????? ??????. ?? ????????? ??????? ?????? ??????? ????????, ????????? ????????????? ??????.
??????? ??????? ???????? 77,7 ± 7,07 ???, ??????????? ?/? — 0,63. ????????????????? ??????? ????????? ? ??????? 40,61 ± 67,88 ???????. ??????? ??? ???????? 26,67 ± 9,17 ??/?2. ?????????????? ??????????? ??????? ? ????? ????????? 1297,61 ± 321,73 ???? ? 52,87 ± 9,89 ? ??????????????. ??????? ???????? ???????????? ????? ???????? 27,53 ± 2,47 ??, ??????? ??????? ?????? ??????? ???????? — 9 ± 0,7. ?????????? ??????????? ?????, ????????? ? ??????? nPCR, ????????? 0,95 ± 0,21 ?/??/????. ??????? ??????? ????????? ? ???????????? ???????? 37,32 ± 1,41 ?/? ? 283,22 ± 35,35 ??/?. ??????? Kt/V ???????? 1,98 ± 0,35. ???????? SGA, 26 (83,87%) ????? ??????? ?????? ??????? (????????? 1), 3 (9,67%) ???????? ?? ?????? ??????????????? ??????? (????????? 2) ? 2 (6,46%) ????? ?????? ??????????????? ??????? (????????? 3). ???????? ?? ?????? ????????? ? ????????????, 18 (58,06%) ????? ??????? ?????? ???????, 6 (19,36%) ????? ?????? ??????????????? ??????? ? 7 (22,58%) ?????? ??????????????? ???????. ?? ?????? ingesta, 2 (6,46%) ???????? ???? ? ????????? 1, 8 (25,81%) ????????? ? ????????? 2 ? 21 (67,74%) ? ????????? 3. ?? ???? ?????????? ???????? ???????? ????? 3 ?????????? ??????? ??????? (????? ??? ?????? SGA ? ?????????? ????????-??????????? ?? ?????? -0,075 [95% ????????????? ????????: ?? -0,175 ?? 0,024]; ????? ??? ????????? ??? SGA ? ingesta ?? ?????? 0,073 [95% ????????: ?? -0,007 ?? 0,153], ????? ??? ?????????? ????????-??????????? ? ingesta ?? ?????? 0,034 [95% ????????????? ????????: ?? -0,058 ?? 0,126)].
???????? ????? ????? ?????????? ???????, ??????????????? ? ????? ????????????, ? ?????????? ? ???????? ?? ????????????, ????????? ? ????????? ??????????? ?????????, ???? ?????????? ? ????????? ??????? ??????? ?????????, ??????????? ?? ???????????, ? ?????????, ? ?????????? ??????????? ???????????? ??????? ? ????????? ???????????? ??????????? ???????, ??????? ?? ??????? ??????????????? ? ?????????-????????????? ?????????, ?????????????? ????????, ? ????? ?? ?????????? ??????? ? ?????????? ???????, ??????????? ??? ???? ????????? ?????????.
K Vara Prasada Rao and K Praveen Kumar
Aim: New Onset Diabetes after Transplantation (NODAT) is one of the medical complications after kidney transplantation which affects adversely the allograft kidney and patient outcomes. The aim of this study was to know the incidence of development of NODAT, investigate risk factors and its effects on allograft kidney in our centre.
Material and methods: This is a retrospective observational study of the patients who underwent the kidney transplant at the Narayana Medical College & Hospital from June 2009 to May 2016. Patients were divided into NODAT and non NODAT groups.
Results: 21 out of 84 patients (25%) developed NODAT during the follow up period of 1st year post transplantation. We found age >30 years (OR: 3.8; P=0.012), family history of diabetes (OR: 8.6; P=0.0004), impaired fasting glucose (OR: 7.27; P=0.0003), postoperative hyperglycaemia (OR: 2.83; P=0.04), fasting triglycerides >150 mg/dl. (OR: 8.0 P=0.0001) and VLDL levels (42.52 ± 30.81 mg/dl. vs. 24.24 ± 5.51 mg/dl; P= 0.01) were risk factors for NODAT. Mean serum creatinine values were 1.23 ± 0.25 mg/dl vs.1.16 ± 0.35mg/dl (P= 0.42) and 1.61 ± 0.53 mg/dl vs. 1.44 ± 0.54 mg/dl (P= 0.24) at the end of 1st month and 1st year post-transplantation in NODAT and non NODAT groups respectively.
Conclusion: The cumulative incidence of NODAT was 25% by the end of the1st post-transplantation year. Increasing age, family history of diabetes, dyslipidemia, pre-transplantation impaired fasting glucose and postoperative hyperglycaemia were considered as risk factors, some of which can be quite modifiable.
Tia Weu Mélanie, Tsevi Yawovi Mawufemo, Hien Siebou, Dassé Seri Romuald, Richard Yeboua
Objective: We undertook this study to analyze the T CD4 subset of non-HIV CKD patients and to investigate factors that may influence their rate.
Materials and methods: It was a cross-sectional, three-month study, on the determination of T CD4, count by Flow Cytometry (FACS Calibur), in patients aged 18 to 65 years, chronic kidney disease according to KDOQI and non-HIV.
Results: Sixty-three cases were collected with an average age of 41 years and sex ratio of 1.79. The median BMI was 22.9 kg/m2 and 69.9% had normal weight. 36 of patients (69.2%) were at stage 5 of chronic kidney disease. CD4 rate was low in 23 patients (36.5%), normal in 37 patients (58.7%) and high in 3 patients (4.8). There was a significant correlation between the decrease in absolute CD4 rate and the grade of chronic kidney failure (CKD) (p=0.02). In linear regression, a statistically significant correlation was observed between changes in absolute CD4 values and white blood cell level (p=0.000003), total lymphocyte rate (p=0,0006) and urea rate (p=0.04); on the other hand between changes in the absolute values of CD3 and the levels of white blood cells (p=0.000001) and lymphocytes rate (p=0.000002).
Conclusion: The decrease in GFR is accompanied by a decrease in CD4 rate, which increases the risk of infections. This situation could contribute significantly to the morbidity and mortality of chronic kidney disease patients.
DarÃÂÂo Jiménez, Jiménez Fernando, Aguilar Ana, Dueñas Anunciata, Castillo MarÃÂÂa, Morales Miguel, Herrera Bernardo, Gahona Junior, Parra Diego, Serpa Frans, Suarez Juan José
Severe acute liver failure in adults is a condition that may lead to several complications such as cerebral edema and acute kidney injury requiring liver transplant. Few studies analyze the benefit of dialysis therapies for decreasing bilirubin and ammonia levels to achieve metabolic compensation. In Ecuador there are no case reports of treatment with combined hemoperfusion and online hemodiafiltration. We report the case of a patient who was diagnosed with fulminant hepatic failure due to acute alcoholic hepatitis and concomitant acute kidney injury. We include the clinical course after adding two sessions of combined hemoperfusion and online hemodiafiltration to the conventional treatment.