Montori, Víctor M.

Abstract Context: The diagnosis of Cushing’s syndrome (CS) requires the use of tests of unregulated hypercortisolism that have unclear accuracy. Objective: Our objective was to summarize evidence on the accuracy of common tests for diagnosing CS. Data Sources: We searched electronic databases (MEDLINE, EMBASE, Web of Science, Scopus, and citation search for key articles) from 1975 through September 2007 and sought additional references from experts. Study Selection: Eligible studies reported on the accuracy of urinary free cortisol (UFC), dexamethasone suppression test (DST), and midnight cortisol assays vs. reference standard in patients suspected of CS. Data Extraction: Reviewers working in duplicate and independently extracted study characteristics and quality and data to estimate the likelihood ratio (LR) and the 95% confidence interval (CI) for each result. Data Synthesis: We found 27 eligible studies, with a high prevalence [794 (9.2%) of 8631 patients had CS] and severity of CS. The tests had similar accuracy: UFC (n = 14 studies; LR+ 10.6, CI 5.5–20.5; LR− 0.16, CI 0.08–0.33), salivary midnight cortisol (n = 4; LR+ 8.8, CI 3.5–21.8; LR− 0.07, CI 0–1.2), and the 1-mg overnight DST (n = 14; LR+ 16.4, CI 9.3–28.8; LR− 0.06, CI 0.03–0.14). Combined testing strategies (e.g. a positive result in both UFC and 1-mg overnight DST) had similar diagnostic accuracy (n = 3; LR+ 15.4, CI 0.7–358; LR− 0.11, CI 0.007–1.57). Conclusions: Commonly used tests to diagnose CS appear highly accurate in referral practices with samples enriched with patients with CS. Their performance in usual clinical practice remains unclear.

OBJECTIVE—To determine the efficacy of telecare (modem transmission of glucometer data and clinician feedback) to support intensive insulin therapy in patients with type 1 diabetes and inadequate glycemic control. RESEARCH DESIGN AND METHODS—Thirty-one patients with type 1 diabetes on intensive insulin therapy and with HbA1c >7.8% were randomized to telecare (glucometer transmission with feedback) or control (glucometer transmission without feedback) for 6 months. The primary end point was 6-month HbA1c. To place our findings in context, we pooled HbA1c change from baseline reported in randomized trials of telecare identified in a systematic review of the literature. RESULTS—Compared with the control group, telecare patients had a significantly lower 6-month HbA1c (8.2 vs. 7.8%, P = 0.03, after accounting for HbA1c at baseline) and a nonsignificant fourfold greater chance of achieving 6-month HbA1c ≤7% (29 vs. 7%; risk difference 21.9%, 95% CI −4.7 to 50.5). Nurses spent 50 more min/patient giving feedback on the phone with telecare patients than with control patients. Meta-analysis of seven randomized trials of adult patients with type 1 diabetes found a 0.4% difference (95% CI 0–0.8) in HbA1c mean change from baseline between the telecare and control groups. CONCLUSIONS—Telecare is associated with small effects on glycemic control in patients with type 1 diabetes on intensive insulin therapy but with inadequate glycemic control.

OBJECTIVE—The aim of this study was to determine personal characteristics and preferences that affect decision making (decisional attributes) in patients with diabetes. In particular, we were interested in relating these attributes to the choice of using aspirin to reduce cardiovascular risk. RESEARCH DESIGN AND METHODS—We conducted a cross-sectional survey (70% response rate) of 206 diabetic patients (median age, 63 years; 42% women; 91% completed high school; median HbA1c, 8%) attending a tertiary care diabetes clinic. Patients answered a 42-question survey exploring decisional attributes. Medical records provided the source of clinical information. We evaluated sociodemographic, clinical, and decisional predictors of aspirin use. We also conducted a multivariable analysis with aspirin use as a dependent variable. RESULTS—Sixty-seven percent of patients surveyed used aspirin. Patients using aspirin were at higher risk of cardiovascular disease (odds ratio 1.4, 95% CI 1.0–2.1), knew more about the benefits of aspirin (1.9, 1.4–2.6) and less about the risks of aspirin (1.4, 1.2–1.8), and were more certain about using aspirin (0.5, 0.3–0.8) than patients not using aspirin. Patients using aspirin placed a higher value on preventing cardiovascular events than on avoiding the side effects of aspirin. Patients perceived that their diabetes provider and the American Diabetes Association had greater influence on their decision to use aspirin than family members or other patients with diabetes. CONCLUSIONS—The decisional attributes of patients with diabetes are associated with aspirin use. Decisional attributes may be the target of research and interventions to reduce underutilization to levels consistent with patient preferences.