Dataset Information

Prediction of remission after metabolic surgery using a novel scoring system in type 2 diabetes - a retrospective cohort study.

ABSTRACT:

Background

Remission of diabetes is seen in more than 60% of patients after bariatric surgery. There is extensive variability in the remission rates between different surgical procedures. We analyzed our database and aimed to develop an easy scoring system to predict the probability of diabetes remission after two surgical procedures i.e. Ileal Interposition coupled with Sleeve Gastrectomy (IISG) or Diverted Sleeve Gastrectomy (IIDSG).

Methods

In this retrospective study, we analyzed records pertaining to patients who underwent IISG (n = 46) and IIDSG (n = 29). The primary outcome measure was diabetes remission (A1c <6.5% and not requiring hypoglycemic drugs). We identified seven preoperative clinical variables (age, duration of diabetes, body mass index, micro and macrovascular complications, use of insulin and stimulated C-peptide) based on our previous reports to be included in the diabetes remission score (DRS). The DRS score (7 - 14) was compared between the patients with and without remission in both the surgery groups.

Results

Mean DRS in patients who underwent IISG was 9.2 ± 1.4. Twenty one (46%) had a remission in diabetes. DRS was significantly lower in patients with remission than patients without remission (8.1 ± 0.8 versus 10.2 ± 0.9, p < 0.0001). Mean DRS in patients who underwent IIDSG was 10.4 ± 1.3. Twenty one (72%) had a remission in diabetes. DRS was significantly lower in patients with remission than patients without remission (9.7 ± 0.8 versus 12.0 ± 0.5, p < 0.0001). Patients with a DRS ≥ 10 in IISG group and more than 12 in IIDSG group did not get into remission.

Conclusion

Preoperative DRS can be a useful tool to select the type of surgical procedure and to predict the postoperative diabetes remission.

Trial registration

NCT00834626.

SUBMITTER: Ugale S

PROVIDER: S-EPMC4243781 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Prediction of remission after metabolic surgery using a novel scoring system in type 2 diabetes - a retrospective cohort study.

Ugale Surendra S Gupta Neeraj N Modi Kirtikumar D KD Kota Sunil K SK Satwalekar Vasisht V Naik Vishwas V Swapna Modukuri M Kumar Kvs Hari KH

Journal of diabetes and metabolic disorders 20140822 1

<h4>Background</h4>Remission of diabetes is seen in more than 60% of patients after bariatric surgery. There is extensive variability in the remission rates between different surgical procedures. We analyzed our database and aimed to develop an easy scoring system to predict the probability of diabetes remission after two surgical procedures i.e. Ileal Interposition coupled with Sleeve Gastrectomy (IISG) or Diverted Sleeve Gastrectomy (IIDSG).<h4>Methods</h4>In this retrospective study, we analy ...[more]

PMID: 25426451

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Project description:About 60% of patients with type 2 diabetes achieve remission after Roux-en-Y gastric bypass (RYGB) surgery. No accurate method is available to preoperatively predict the probability of remission. Our goal was to develop a way to predict probability of diabetes remission after RYGB surgery on the basis of preoperative clinical criteria.In a retrospective cohort study, we identified individuals with type 2 diabetes for whom electronic medical records were available from a primary cohort of 2300 patients who underwent RYGB surgery at the Geisinger Health System (Danville, PA, USA) between Jan 1, 2004, and Feb 15, 2011. Partial and complete remission were defined according to the American Diabetes Association criteria. We examined 259 clinical variables for our algorithm and used multiple logistic regression models to identify independent predictors of early remission (beginning within first 2 months after surgery and lasting at least 12 months) or late remission (beginning more than 2 months after surgery and lasting at least 12 months). We assessed a final Cox regression model with a consistent subset of variables that predicted remission, and used the resulting hazard ratios (HRs) to guide creation of a weighting system to produce a score (DiaRem) to predict probability of diabetes remission within 5 years. We assessed the validity of the DiaRem score with data from two additional cohorts.Electronic medical records were available for 690 patients in the primary cohort, of whom 463 (63%) had achieved partial or complete remission. Four preoperative clinical variables were included in the final Cox regression model: insulin use, age, HbA1c concentration, and type of antidiabetic drugs. We developed a DiaRem score that ranges from 0 to 22, with the greatest weight given to insulin use before surgery (adding ten to the score; HR 5·90, 95% CI 4·41–7·90; p<0·0001). Kaplan-Meier analysis showed that 88% (95% CI 83–92%) of patients who scored 0–2, 64% (58–71%) of those who scored 3–7, 23% (13–33%) of those who scored 8–12, 11% (6–16%) of those who scored 13–17, and 2% (0–5%) of those who scored 18–22 achieved early remission (partial or complete). As in the primary cohort, the proportion of patients achieving remission in the replication cohorts was highest for the lowest scores, and lowest for the highest scores.The DiaRem score is a novel preoperative method to predict the probability of remission of type 2 diabetes after RYGB surgery.Geisinger Health System and the US National Institutes of Health.

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Dataset Information

Prediction of remission after metabolic surgery using a novel scoring system in type 2 diabetes - a retrospective cohort study.

Background

Methods

Results

Conclusion

Trial registration

Publications

Prediction of remission after metabolic surgery using a novel scoring system in type 2 diabetes - a retrospective cohort study.

Similar Datasets

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