Dataset Information

Secretory units of islets in transplantation index is a useful predictor of insulin requirement in Japanese type 2 diabetic patients.

ABSTRACT: AIMS/INTRODUCTION:The objective of the present study was to clarify the validity of ?-cell function-related parameters for predicting the insulin requirement of Japanese type 2 diabetic patients. MATERIALS AND METHODS:In 188 patients with type 2 diabetes who had been admitted to the University of Toyama Hospital (Toyama, Japan) without receiving insulin therapy, we carried out a cross-sectional study examining the relationship between the homeostasis model assessment of ?-cell function (HOMA-?) and C-peptide-based indices, and also carried out a retrospective study to examine the utility for predicting insulin requirement of several ? -cell function-related indices using a receiver operating characteristic (ROC) curve analysis. RESULTS:The secretory units of islets in transplantation index (SUIT) had the strongest correlation with HOMA-?, followed by the fasting serum C-peptide immunoreactivity index (CPI); the fasting serum C-peptide immunoreactivity itself (F-CPR) had the least correlation. The CPI, HOMA-? and SUIT were significantly lower in the insulin-requiring group than in the non-insulin-requiring group, even after adjustments for confounding factors (P < 0.01). The areas under the ROC curve for insulin requirement were 0.622, 0.774, 0.808, and 0.759 for F-CPR, CPI, SUIT, and HOMA-?, respectively. The cut-off values of SUIT, CPI, and HOMA-? for an over 80% specificity for the prediction of insulin therapy were 23.5, 1.00, and 14.9, respectively. CONCLUSIONS:The present study shows that SUIT is the best predictor of insulin requirement among these ?-cell function-related markers.

SUBMITTER: Iwata M

PROVIDER: S-EPMC4188116 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Secretory units of islets in transplantation index is a useful predictor of insulin requirement in Japanese type 2 diabetic patients.

Iwata Minoru M Matsushita Yumi Y Fukuda Kazuhito K Wakura Tatsurou T Okabe Keisuke K Koshimizu Yukiko Y Fukushima Yasuo Y Kobashi Chikaaki C Yamazaki Yu Y Honoki Hisae H Suzuki Hikari H Kigawa Mika M Tobe Kazuyuki K

Journal of diabetes investigation 20131226 5

<h4>Aims/introduction</h4>The objective of the present study was to clarify the validity of β-cell function-related parameters for predicting the insulin requirement of Japanese type 2 diabetic patients.<h4>Materials and methods</h4>In 188 patients with type 2 diabetes who had been admitted to the University of Toyama Hospital (Toyama, Japan) without receiving insulin therapy, we carried out a cross-sectional study examining the relationship between the homeostasis model assessment of β-cell fun ...[more]

PMID: 25411626

Similar Datasets

Project description:Malnutrition and immunologic derangement were not uncommon in patients with chronic kidney disease (CKD). However, the long-term effects of prognostic nutritional index (PNI), an immunonutrition indictor, on renal outcomes in patients with diabetic nephropathy (DN) and type 2 diabetes mellitus (T2DM) are unknown. In this retrospective cohort study, 475 patients with T2DM and biopsy-confirmed DN from West China Hospital between January 2010 and September 2019 were evaluated. PNI was evaluated as serum albumin (g/L) + 5 × lymphocyte count (109/L). The study endpoint was defined as progression to end-stage renal disease (ESRD). The Cox regression analysis was performed to investigate the risk factors of renal failure in DN patients. A total of 321 eligible individuals were finally included in this study. The patients with higher PNI had a higher eGFR and lower proteinuria at baseline. Correlation analysis indicated PNI was positively related eGFR (r = 0.325, p < 0.001), and negatively correlated with proteinuria (r = -0.68, p < 0.001), glomerular lesion (r = -0.412, p < 0.001) and interstitial fibrosis and tubular atrophy (r = -0.282, p < 0.001). During a median follow-up of 30 months (16-50 months), the outcome event occurred in 164(51.09%) of all the patients. After multivariable adjustment, each SD (per-SD) increment of PNI at baseline was associated with a lower incidence of ESRD (hazard ratio, 0.705, 95% CI, 0.523-0.952, p = 0.023), while the hypoalbuminemia and anemia were not. For the prediction of ESRD, the area under curves (AUC) evaluated with time-dependent receiver operating characteristics were 0.79 at 1 year, 0.78 at 2 years, and 0.74 at 3 years, respectively, and the addition of PNI could significantly improve the predictive ability of the model incorporating traditional risk factors. In summary, PNI correlated with eGFR and glomerular injury and was an independent predictor for DN progression in patients with T2DM. Thus, it may facilitate the risk stratification of DN patients and contribute to targeted management.

Project description:ObjectiveAcute respiratory distress syndrome trials powered for mortality require significant resources, limiting the number of evaluable therapies. Validation of intermediate endpoints would enhance the feasibility of testing novel acute respiratory distress syndrome therapies in pilot studies and potentially reduce the frequency of failed large clinical trials. We sought to determine whether a change in the oxygenation index over the first 7 days of acute respiratory distress syndrome could discriminate between therapies likely or unlikely to show benefit in larger clinical trials.DesignA derivation cohort from three acute respiratory distress syndrome studies was used to estimate the 7-day change in oxygenation index. Receiver operating characteristic curves were used to calculate optimal thresholds and predictability of the change in oxygenation index for 28-day mortality and ventilator-free days. The thresholds were then validated in two cohorts. Then, for each individual acute respiratory distress syndrome study, the threshold 7-day oxygenation index change was tested as an outcome measure and compared with mortality and ventilator-free days as reported in the original study.SettingMedical ICUs.PatientsAcute respiratory distress syndrome patients.InterventionsVarious.Measurements and main resultsChange in oxygenation index, 28-day mortality, and ventilator-free days. In the derivation cohort, the mean 7-day oxygenation index improved by 4.2 (± 11.7) in 28-day survivors compared with an increase of 2.4 (± 11.6) in 28-day nonsurvivors (p < 0.001). The mean 7-day oxygenation index decreased by 5.9 (± 8.4) in patients with more than 14 ventilator-free days, compared with a decrease of 1.9 (± 12.4) among those with less than 14 ventilator-free days (p = 0.001). The optimal 7-day oxygenation index threshold for predicting mortality was an increase of 1.71 and for predicting less than 14 ventilator-free days, a decrease of 2.34. When used as a surrogate endpoint, the optimal 7-day oxygenation index change closely approximated mortality and ventilator-free day outcomes in three Acute Respiratory Distress Syndrome Network studies used for the derivation cohort and a distinct study used for validation. The change in oxygenation index was a poor predictor of individual patient outcome.ConclusionsFailure to meet a threshold improvement in the oxygenation index over the first 7 days of therapy can be used to identify therapies unlikely to succeed in subsequent trials powered for mortality and ventilator-free days. By reducing trial time and costs, use of the 7-day oxygenation index change as an intermediate endpoint could increase the number of clinical trials of promising therapies for acute respiratory distress syndrome and reduce the number of large-scale trials of therapies unlikely to be of benefit.

Dataset Information

Secretory units of islets in transplantation index is a useful predictor of insulin requirement in Japanese type 2 diabetic patients.

Publications

Secretory units of islets in transplantation index is a useful predictor of insulin requirement in Japanese type 2 diabetic patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets