Incidental Risk of Type 2 Diabetes Mellitus among Patients with Confirmed and Unconfirmed Prediabetes

<div><p>Objective</p><p>To determine the risk of type 2 diabetes (T2DM) diagnosis among patients with confirmed and unconfirmed prediabetes (preDM) relative to an at-risk group receiving care from primary care physicians over a 5-year period.</p><p>Study Design</p><p>Utilizing data from the Intermountain Healthcare (IH) Enterprise Data Warehouse (EDW) from 2006–2013, we performed a prospective analysis using discrete survival analysis to estimate the time to diagnosis of T2DM among groups.</p><p>Population Studied</p><p>Adult patients who had at least one outpatient visit with a primary care physician during 2006–2008 at an IH clinic and subsequent visits through 2013. Patients were included for the study if they were (a) at-risk for diabetes (BMI ≥ 25 kg/m2 and one additional risk factor: high risk ethnicity, first degree relative with diabetes, elevated triglycerides or blood pressure, low HDL, diagnosis of gestational diabetes or polycystic ovarian syndrome, or birth of a baby weighing >9 lbs); or (b) confirmed preDM (HbA1c ≥ 5.7–6.49% or fasting blood glucose 100–125 mg/dL); or (c) unconfirmed preDM (documented fasting lipid panel and glucose 100–125 mg/dL on the same day).</p><p>Principal Findings</p><p>Of the 33,838 patients who were eligible for study, 57.0% were considered at-risk, 38.4% had unconfirmed preDM, and 4.6% had confirmed preDM. Those with unconfirmed and confirmed preDM tended to be Caucasian and a greater proportion were obese compared to those at-risk for disease. Patients with unconfirmed and confirmed preDM tended to have more prevalent high blood pressure and depression as compared to the at-risk group. Based on the discrete survival analyses, patients with unconfirmed preDM and confirmed preDM were more likely to develop T2DM when compared to at-risk patients.</p><p>Conclusions</p><p>Unconfirmed and confirmed preDM are strongly associated with the development of T2DM as compared to patients with only risk factors for disease.</p></div

Repeated Measurement of the Intermountain Risk Score Enhances Prognostication for Mortality

<div><p>Background</p><p>The Intermountain Risk Score (IMRS), composed of the complete blood count (CBC) and basic metabolic profile (BMP), predicts mortality and morbidity in medical and general populations. Whether longitudinal repeated measurement of IMRS is useful for prognostication is an important question for its clinical applicability.</p><p>Methods</p><p>Females (N = 5,698) and males (N = 5,437) with CBC and BMP panels measured 6 months to 2.0 years apart (mean 1.0 year) had baseline and follow-up IMRS computed. Survival analysis during 4.0±2.5 years (maximum 10 years) evaluated mortality (females: n = 1,255 deaths; males: n = 1,164 deaths) and incident major events (myocardial infarction, heart failure [HF], and stroke).</p><p>Results</p><p>Both baseline and follow-up IMRS (categorized as high-risk vs. low-risk) were independently associated with mortality (all p<0.001) in bivariable models. For females, follow-up IMRS had hazard ratio (HR) = 5.23 (95% confidence interval [CI] = 4.11, 6.64) and baseline IMRS had HR = 3.66 (CI = 2.94, 4.55). Among males, follow-up IMRS had HR = 4.28 (CI = 3.51, 5.22) and baseline IMRS had HR = 2.32 (CI = 1.91, 2.82). IMRS components such as RDW, measured at both time points, also predicted mortality. Baseline and follow-up IMRS strongly predicted incident HF in both genders.</p><p>Conclusions</p><p>Repeated measurement of IMRS at baseline and at about one year of follow-up were independently prognostic for mortality and incident HF among initially hospitalized patients. RDW and other CBC and BMP values were also predictive of outcomes. Further research should evaluate the utility of IMRS as a tool for clinical risk adjustment.</p></div

Association of follow-up IMRS and baseline IMRS, modeled as continuous variables, with mortality in Cox regression.

*<p>Adjusted for baseline IMRS;</p>†<p>Adjusted for follow-up IMRS. CI: confidence interval.</p

Mean IMRS at baseline and follow-up, and the change (ΔIMRS) over that time.

<p>Data in parentheses are the percentage of patients in the corresponding baseline category.</p>*<p>p<0.001 vs. baseline IMRS of the same gender,</p>†<p>p-trend<0.001 (across low-, moderate-, and high-risk categories within the same gender).</p

Distribution of females and males by age decade.

*<p>p-trend = 0.11 for males vs. females.</p

Females.

<p>Kaplan-Meier survival curves for the association of follow-up IMRS (low- [solid line], moderate- [dashed], and high-risk [dotted]) with mortality among females within strata defined by: <b>A</b>) low-risk baseline IMRS, <b>B</b>) moderate-risk baseline IMRS, and <b>C</b>) high-risk baseline IMRS (all p<0.001).</p

Males.

<p>Kaplan-Meier survival curves for the association of follow-up IMRS (low- [solid line], moderate- [dashed], and high-risk [dotted]) with mortality among males within strata defined by: <b>A</b>) low-risk baseline IMRS, <b>B</b>) moderate-risk baseline IMRS, and <b>C</b>) high-risk baseline IMRS (all p<0.001).</p