Sociodemographic Factors Associated with Loss to Follow-Up After Bariatric Surgery.

PURPOSE: Despite the importance of follow-up and multidisciplinary care after bariatric surgery, many patients do not attend postoperative appointments, particularly those with the medical team. The present study aimed to identify factors associated with loss to follow-up after bariatric surgery. MATERIALS AND METHODS: We recruited patients who underwent bariatric surgery between 01/01/2012 and 31/12/2013. Data were collected on demographic and socioeconomic information and comorbidities. Ten baseline psychological evaluations were blindly reviewed to evaluate the relationship between emotions and compliance with follow-up. During the 3-year postoperative period, we defined frequent attendees as those who attended at least two visits, whereas non-attendees were those who attended one visit or none. We evaluated baseline variables associated with non-adherence with follow-up schedules. RESULTS: Among 92 patients, 41 patients (44.6%) attended at least two postoperative appointments, while 51 (55.4%) were classified as non-attendees. Among the non-attendees, significantly more were younger than 45 years compared with attendees. No other statistically significant differences were found in terms of socioeconomic variables. Multivariate logistic regression revealed male gender and psychological issued related to obesity to be independent predictors of poor compliance with follow-up. Blinded psychological evaluation of ten patients did not suggest that psychological factors are predictive of follow-up attendance. CONCLUSION: Identifying factors associated with loss to follow-up after bariatric surgery is challenging. However, this is important in order to enable the design of personalized follow-up plans, especially for younger patients and those with psychological issues.

Poor Reliability and Poor Adherence to Self-Monitoring of Blood Glucose Are Common in Women With Gestational Diabetes Mellitus and May Be Associated With Poor Pregnancy Outcomes.

OBJECTIVE: To evaluate the compliance with self-monitoring of blood glucose (SMBG) and the reliability of diabetes logbooks in women with gestational diabetes mellitus (GDM), as well as the associated determinants and outcomes. RESEARCH DESIGN AND METHODS: We prospectively selected French-speaking women with newly diagnosed GDM who had been referred to our diabetes management program and understood SMBG principles. At the next follow-up visit, we collected SMBG results from glucose meters and logbooks. We analyzed pregnancy outcomes. RESULTS: Data were analyzed over 13 ± 3 days in 91 women. Only 61.5% had performed ≥80% of the required tests. Poor compliance was associated with a family history of diabetes, social deprivation, and non-European origin. The average time between pre- and postprandial tests was 141 ± 20 min, with 46.5% of women performing ≥80% of postprandial measurements 100-140 min after meals. Inadequate timing was associated with ethnicity and higher HbA1c at baseline. A total of 23.1% of women had <90% matched values in diary and meter memory, and a poor concordance was associated with a family history of diabetes. Poor adherence was associated with more preeclampsia (12.2 vs. 1.9%, P = 0.049), and inadequate postprandial test timing with a higher HbA1c at delivery (5.3 ± 0.4 vs. 5.0 ± 0.3% [34 ± 2 vs. 31 ± 2 mmol/mol], P < 0.01), despite more frequent insulin therapy. CONCLUSIONS: Although women with GDM are considered to be highly motivated, SMBG adherence and reliability are of concern and may be associated with poor gestational prognosis, suggesting that caregivers should systematically check the glucose meter memory to improve GDM management.

The diagnostic and prognostic performance of a selective screening strategy for gestational diabetes mellitus according to ethnicity in Europe.

CONTEXT: The performance of standard selective screening strategies for gestational diabetes mellitus (GDM) may vary according to ethnicity. OBJECTIVE: We aimed to evaluate the diagnostic and prognostic performance of a selective screening tool to determine whether it accurately predicts GDM and events in women of different ethnicities. The tool selectively screens based on patients having one or more of the following risk factors (RFs): body mass index ≥25 kg/m(2), age ≥35 years, family history of diabetes, and personal history of GDM or macrosomia. DESIGN AND SETTING: We conducted an observational prospective study at a university hospital. PARTICIPANTS: We included 17 344 women of European (30.9%), North African (29.6%), Sub-Saharan African (22.2%), Caribbean (8.7%), Indian-Pakistani-Sri Lankan (5.5%), and Asian (3.3%) ethnicities who were without pregravid diabetes and had singleton deliveries (2002-2010). MAIN OUTCOME MEASURES: We universally screened GDM and GDM-related events (pre-eclampsia, birth weight ≥4000 g, or dystocia). RESULTS: Independent of confounding factors, North African (odds ratio [OR], 1.35; 95% confidence interval [CI], 1.21-1.52; P < .001) and Indian-Pakistani-Sri Lankan (OR, 2.52; 95% CI, 2.13-3.00; P < .001) women had more GDM than Europeans, whereas Sub-Saharan African women had less (OR, 0.82; 95% CI, 0.71-0.94; P < .01). Having one or more RFs was associated with GDM among Europeans (OR, 1.45; 95% CI, 1.22-1.76), North African (OR, 1.33; 95% CI, 1.13-1.55), Sub-Saharan African (OR, 1.48; 95% CI, 1.20-1.83), and Caribbean (OR, 1.55; 95% CI, 1.12-2.14) women. Having one or more RFs was also associated with GDM-related events only in European (P < .01) and North African (P < .05) women, with the following incidences in Europeans: no GDM/no RF, 6.9%; no GDM/RF, 9.0%; GDM/no RF, 14.7%; and GDM/RF, 12.6%. CONCLUSION: Standard selective screening criteria were not predictive of GDM in women from India-Pakistan-Sri Lanka and Asia and were associated with GDM-related events only in European and North African women. However, the women with GDM, who were routinely treated, had a poor prognosis, even for those free of RFs. These results support universal screening, irrespective of ethnicity.

Glycation gap is associated with macroproteinuria but not with other complications in patients with type 2 diabetes.

OBJECTIVE: We investigated whether glycation gap (G-Gap), an index of intracellular glycation of proteins, was associated with diabetes complications. RESEARCH DESIGN AND METHODS: We measured concomitantly HbA1c and fructosamine in 925 patients with type 2 diabetes to calculate the G-Gap, defined as the difference between measured HbA1c, and fructosamine-based predicted HbA1c. Patients were explored for retinopathy, nephropathy, peripheral neuropathy, cardiac autonomic neuropathy (n = 512), and silent myocardial ischemia (n = 506). RESULTS: Macroproteinuria was the only complication that was associated with G-Gap (prevalence in the first, second, and third tertile of G-Gap: 2.9, 6.2, and 11.0%, respectively; P < 0.001). The G-Gap was higher in patients with macroproteinuria than in those without (1.06 ± 1.62 vs. 0.03 ± 1.30%; P < 0.0001). Because HbA1c was associated with both G-Gap (HbA1c 7.0 ± 1.4, 7.9 ± 1.4, and 10.1 ± 1.8% in the first, second, and third G-Gap tertile, respectively; P < 0.0001) and macroproteinuria (HbA1c 8.8 ± 2.2% if macroproteinuria, 8.3 ± 2.0% if none; P < 0.05), and because it could have been a confounder, we matched 54 patients with macroproteinuria and 200 patients without for HbA1c. Because macroproteinuria was associated with lower serum albumin and fructosamine levels, which might account for higher G-Gap, we calculated in this subpopulation albumin-indexed fructosamine and G-Gap; macroproteinuria was independently associated with male sex (odds ratio [OR] 3.2 [95% CI 1.5-6.7]; P < 0.01), hypertension (2.9 [1.1-7.5]; P < 0.05), and the third tertile of albumin-indexed G-Gap (2.3 [1.1-4.4]; P < 0.05) in multivariate analysis. CONCLUSIONS: In type 2 diabetic patients, G-Gap was associated with macroproteinuria, independently of HbA1c, albumin levels, and confounding factors, suggesting a specific role of intracellular glycation susceptibility on kidney glomerular changes.

Diagnostic and prognostic performances over 9 years of a selective screening strategy for gestational diabetes mellitus in a cohort of 18,775 subjects.

OBJECTIVE: We aimed to evaluate a selective screening strategy for gestational diabetes mellitus (GDM) based on the presence of risk factors: BMI ≥25 kg/m(2), age ≥35 years, family history of diabetes, personal history of GDM, or birth of a child with macrosomia. RESEARCH DESIGN AND METHODS: Of 20,630 deliveries between 2002 and 2010, we selected 18,775 deliveries in women with no known diabetes and for whom all risk factors were known. GDM was universally screened and defined as fasting plasma glucose level ≥5.3 mmol/L and/or 2-h postload (75 g) glucose level ≥7.8 mmol/L. RESULTS: The prevalence of at least one risk factor has increased since 2002 (P < 0.001) from 51.7 to 61.5%, with no change in the GDM prevalence (mean 14.4%, intention to screen). At least one risk factor was present in 58.5% of women who represented 65.3% of all those with GDM. The presence of risk factors was significantly associated with GDM (odds ratio 1.4 [95% CI 1.3-1.5], P < 0.001) and with GDM-related events (preeclampsia/large for gestational age/dystocia) (P < 0.001) with the following incidences: no GDM/no risk factor 8.8%, no GDM/risk factor 11.1%, GDM/no risk factor 16.7%, and GDM/risk factor 18.2%. CONCLUSIONS: The presence of risk factors increased during the last decade. This condition is predictive of GDM and GDM-related events. However, a selective screening would lead to missing one-third of the women with GDM who, even without risk factors, had more events than women without GDM. Therefore, these data stand against the present selective screening currently proposed in the French guidelines.