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Heart failure (HF) hospitalization length of stay (LOS) has been associated with the risk of subsequent readmission and mortality. We identified 19,927 hospitalized patients with HF who were discharged alive from 2008 to 2011 from 3 Kaiser Permanente regions. In adjusted Cox models using LOS 3 to 4 days as the reference category, shorter LOS was not significantly associated with hospital readmissions. LOS of 5 to 10 days was associated with 17% greater risk of readmission within 30 days (hazard ratio [HR] 1.17, 95% confidence interval [CI] 1.07 to 1.28) and 9% greater risk within 1 year (HR 1.09, 95% CI 1.03 to 1.15). LOS of 11 to 29 days was associated with increased readmission risk of 52% at 30 days (HR 1.52, 95% CI 1.30 to 1.76) and 25% at 1 year (HR 1.25, 95% CI 1.16 to 1.35). Mortality risk within 30 days among those with LOS of 1 day was 47% lower (HR 0.53, 95% CI 0.43 to 0.65) and 32% lower at 1 year (HR 0.68, 95% CI 0.62 to 0.74). LOS of 2 days was associated with lower mortality risk of 17% (HR 0.83, 95% CI 0.76 to 0.90) at 1 year. At LOS 5 to 10 days, 30-day and 1-year risk of mortality was increased by 52% (HR 1.52, 95% CI 1.30 to 1.76) and 25% (HR 1.25, 95% CI 1.16 to 1.35), respectively. LOS of 11 to 29 days was associated with 171% higher mortality risk at 30 days (HR 2.71, 95% CI 2.19 to 3.35) and 73% at 1 year (HR 1.73, 95% CI 1.53 to 1.97). Longer LOS during the index HF hospitalization was associated with readmission and mortality within 30 days and 1 year independent of co-morbidities and cardiovascular risk factors. These results suggest that LOS may be a proxy for the severity of HF during the index hospitalization.

OBJECTIVE We sought to document the secondary failure rate of metformin monotherapy in a clinical practice setting and to explore factors that predict therapeutic failure. RESEARCH DESIGN AND METHODS We studied 1,799 type 2 diabetic patients who, between 2004 and 2006, lowered their A1C to <7% after initiating metformin monotherapy as their first-ever anti-hyperglycemic drug. We examined all A1C values recorded through 31 December 2008 (2-5 years of follow-up), defining secondary failure as a subsequent A1C > or =7.5% or the addition or substitution of another anti-hyperglycemic agent. We used logistic regression to identify factors associated with the probability of secondary failure. RESULTS Of the 1,799 patients studied, 42% (n = 748) experienced secondary failure; the mean failure rate was 17% per year. However, patients who initiated metformin within 3 months of diabetes diagnosis failed at an age-and A1C-adjusted rate of 12.2% (10.5-14.4%) per year, and patients who initiated while A1C was <7% failed at an adjusted rate of 12.3% per year. An interaction term between duration of diagnosed diabetes and A1C was not significant. Age, duration, and A1C at initiation were the only factors that predicted secondary failure. CONCLUSIONS Although metformin failure may occur more rapidly in clinical practice than in clinical trails, initiating it soon after diabetes diagnosis and while A1C is low might preserve beta-cell function, prolong the effectiveness of metformin, reduce lifetime glycemic burden, and prevent diabetes complications. Our findings support the current treatment algorithm for hyperglycemia management that recommends metformin initiation when diabetes is first diagnosed.

Because heart failure (HF) with reduced ejection fraction (HFrEF) and preserved ejection fraction (HFpEF) are different clinical entities with differing demographic characteristics, common HF outcomes may occur at different rates. Comparative outcome studies have been equivocal, and studies comparing resource utilization are scant. We used an observational cohort design to study 6,513 patients hospitalized for HF who had an EF measured during the hospitalization and were discharged alive within 30 days. We excluded 677 patients with borderline EF values (41% to 49%) and categorized the remaining as HFrEF (EF ≤40%, n = 2,205) and HFpEF (EF >50%, n = 3,631). Patients were followed for up to 1 year for all-cause re-hospitalization and mortality and annualized medical resource utilization. Patients with HFrEF and HFpEF experienced similar adjusted incidence rates of re-hospitalization, but those with HFrEF had a 39% increased risk of mortality at 30 days (rate ratio 1.39, 95% confidence interval 1.10 to 1.76) and 25% greater risk at 1 year (rate ratio1.25, 95% confidence interval 1.12 to 1.41). After adjustment for covariates, patients with HFpEF incurred significantly more annualized outpatient visits (21.5 vs 20.1, p = 0.002) and emergency room visits (3.24 vs 2.94, p = 0.002) than those with HFrEF, but absolute differences were small. High inpatient and pharmacy utilization did not differ. Our study suggests that whether a patient has HFrEF or HFpEF has little bearing on risk of re-hospitalization or inpatient resource utilization in the year after an HF hospitalization. Both groups experienced high mortality, but those with HFrEF had greater risk. In conclusion, from the standpoint of resource use, HF can be considered a single entity.

OBJECTIVE: Diabetes has long been recognized as a risk factor for atrial fibrillation, but its independent contribution to atrial fibrillation has not been fully evaluated. We sought to compare the prevalence and incidence of atrial fibrillation in age- and sex-matched patients with and without type 2 diabetes. RESEARCH DESIGN AND METHODS: Using an observational cohort design, we selected 10,213 members of an HMO diabetes registry as of 1 January 1999 plus 7,159 patients who entered the registry by 31 December 2004 and matched them to patients without diabetes on year of birth and sex. All patients were followed until they died, left the health plan, or until 31 December 2008. We compared the baseline prevalence of atrial fibrillation and then followed patients without atrial fibrillation to compare atrial fibrillation incidence while controlling for known risk factors. RESULTS: Atrial fibrillation prevalence was significantly greater among patients with diabetes (3.6 vs. 2.5%, P < 0.0001). Over a mean follow-up of 7.2 ± 2.8 years, diabetic patients without atrial fibrillation at baseline developed atrial fibrillation at an age- and sex-adjusted rate of 9.1 per 1,000 person-years (95% CI 8.6-9.7) compared with a rate of 6.6 (6.2-7.1) among nondiabetic patients. After full adjustment for other risk factors, diabetes was associated with a 26% increased risk of atrial fibrillation among women (hazard ratio 1.26 [95% CI 1.08-1.46]), but diabetes was not a statistically significant factor among men (1.09 [0.96-1.24]). CONCLUSIONS: In this population, diabetes was an independent determinant of atrial fibrillation prevalence but predicted incidence only among women. These findings have potential public health implications and emphasize the need for further investigation of the mechanistic links between diabetes and atrial fibrillation.

IntroductionType 2 diabetes (T2D) is a common condition that, if left untreated or poorly managed, can lead to adverse microvascular and macrovascular complications. We estimated the prevalence and incidence of microvascular and macrovascular complications among patients newly diagnosed with T2D within a US integrated healthcare system.Research design and methodsWe conducted a retrospective cohort study among patients newly diagnosed with T2D between 2003 and 2014. We evaluated 13 complications, including chronic kidney disease (CKD), cardiovascular disease (CVD), and all-cause mortality through 2018. Multivariable Cox proportional hazards models were used to study factors associated with complications.ResultsWe identified 135 199 patients with incident T2D. The mean age was 58 years, and 48% were women. The prevalence of CKD was the highest of the complications at the time of T2D diagnosis (prevalence=12.3%, 95% CI 12.2% to 12.5%), while the prevalence of CVD was among the lowest at 3.3% (95% CI 3.2% to 3.3%). The median time to incidence of a T2D complication ranged from 3.0 to 5.2 years. High incidence rates (95% CI) of T2D complications included peripheral neuropathy (26.9, 95% CI 26.5 to 27.3 per 1000 person-years (PY)), CKD (21.2, 95% CI 20.9 to 21.6 per 1000 PY), and CVD (11.9, 95% CI 11.7 to 12.2 per 1000 PY). The trend of 5-year incidence rates of T2D complications by diagnosis year decreased over time (p value<0.001). Older age, non-Hispanic white race/ethnicity, sex, higher A1C, smoking, and hypertension were associated with increased CKD and CVD incidence.ConclusionThough incidence rates of T2D complications were lower in more recent years (2010–2014), a significant proportion of patients had complications at T2D diagnosis. Earlier preventive therapies as well as managing modifiable factors may help delay the development and progression of T2D complications.

Background: Estimates of myopathy rates in the literature are based on adverse events reported in clinical trials, which may not be representative of the clinical practice setting. Objective: The objective of this study was to estimate the prevalence of myopathic events, particularly myalgia, myositis, and rhabdomyolysis in a community-based practice among a cohort of subjects with or without diabetes, some of whom received statin treatment. Methods: In this retrospective data analysis, we identified members of a health maintenance organization (HMO) who initiated statin treatment between 1997 and 2004 and classified them into 2 groups: those subjects with diabetes and those without. We matched them to an equal number of health plan members based on age group, diabetes diagnosis, and year of health plan enrollment. We defined 4 levels of myopathic events according to the American College of Cardiology, the American Heart Association, and the National Heart, Lung, and Blood Institute's definitions as follows: myalgia, mild myositis, severe myositis, and rhabdomyolysis. Subjects were observed for ∼9 years. Prevalence rates were calculated by adjusting for known myopathic risk factors and also by utilizing Cox regression models to identify predictors of time for myopathic events. Results: Of the 35,413 HMO members initially assessed for inclusion, 32,225 were identified and clas sified into the 2 cohorts: diabetes (n = 10,247) and nondiabetes (n = 21,978). A greater proportion of statin initiators in both the diabetes (7.9% vs 5.5%; P < 0.001) and nondiabetes cohorts (9.0% vs 3.7%; P < 0.001) experienced myopathic events. However, 95% of events were myalgia or mild myositis. The prevalence of severe myositis was 0.4 per 1000 person-years (95% CI, 0.2–0.7) and 0.8 per 1000 person-years (95% CI, 0.6-1.1) among statin initiators with or without diabetes, respectively. By comparison, rates were 0.3 (95% CI, 0.1–0.5) and 0.2 (95% CI, 0.1–0.4) per 1000 person-years among nonstatin users with or without diabetes, respectively. Rates of rhabdomyolysis were 0.1 (95% CI, 0.1–0.3) and 0.2 (95% CI, 0.1–0.5) per 1000 person-years among statin and non-statin users with diabetes, respectively, and 0.2 (95% CI, 0.1–0.4) in both groups without diabetes. Conclusions: Statin initiation was associated with an approximate doubling of the risk for any myopathic event but did not appear to be associated with an increased risk for rhabdomyolysis in these patients. Because clinically significant elevations of creatine kinase levels were rare, statins appeared to be well tolerated in diabetic and nondiabetic patients who used them.

OBJECTIVE:--We sought to estimate the rate of progression from newly acquired (incident) impaired fasting glucose (IFG) to diabetes under the old and new IFG criteria and to identify predictors of progression to diabetes. RESEARCH DESIGN AND METHODS--We identified 5,452 members of an HMO with no prior history of diabetes, with at least two elevated fasting glucose tests (100-125 mg/dl) measured between 1 January 1994 and 31 December 2003, and with a normal fasting glucose test before the two elevated tests. All data were obtained from electronic records of routine clinical care. Subjects were followed until they developed diabetes, died, left the health plan, or until 31 December 2005. RESULTS:--Overall, 8.1% of subjects whose initial abnormal fasting glucose was 100-109 mg/dl (added IFG subjects) and 24.3% of subjects whose initial abnormal fasting glucose was 110-125 mg/dl (original IFG subjects) developed diabetes (P < 0.0001). Added IFG subjects who progressed to diabetes did so within a mean of 41.4 months, a rate of 1.34% per year. Original IFG subjects converted at a rate of 5.56% per year after an average of 29.0 months. A steeper rate of increasing fasting glucose; higher BMI, blood pressure, and triglycerides; and lower HDL cholesterol predicted diabetes development. CONCLUSIONS:--To our knowledge, these are the first estimates of diabetes incidence from a clinical care setting when the date of IFG onset is approximately known under the new criterion for IFG. The older criterion was more predictive of diabetes development. Many newly identified IFG patients progress to diabetes in <3 years, which is the currently recommended screening interval.

The Burden of Treatment Failure in Type 2 Diabetes Jonathan B. Brown , PHD, MPP 1 , Gregory A. Nichols , PHD 1 and Andrew Perry , MA HONS, MSC 2 1 Kaiser Permanente Center for Health Research, Portland, Oregon 2 GlaxoSmithKline Research & Development, Philadelphia, Pennsylvania Address correspondence and reprint requests to Jonathan B. Brown, PhD, Center for Health Research, 3800 N. Interstate Ave., Portland, OR 97227-1110. E-mail: jonathan.brown{at}kpchr.org Abstract OBJECTIVE —In type 2 diabetes, therapies to maintain blood glucose control usually fail after several years. We estimated the glycemic burden that accumulates from treatment failure and describe the time course and predictors of failure. RESEARCH DESIGN AND METHODS —A prospective, population-based study using retrospective observational data. We identified all 7,208 complete courses of treatment with nondrug therapy, sulfonylurea monotherapy, metformin monotherapy, and combination oral antihyperglycemic therapy between 1994 and 2002, inclusive, among members of the Kaiser Permanente Northwest Region. We calculated mean cumulative glycemic burden, defined as HbA 1c -months >8.0 or 7.0% for each treatment. We then measured the likelihood that the next HbA 1c would exceed 8.0 and 7.0% after HbA 1c exceeded each of ten hypothetical treatment thresholds. Finally, we estimated multivariate logistic regression models to predict when HbA 1c would continue to deteriorate. RESULTS —In this well-controlled population, the average patient accumulated nearly 5 HbA 1c -years of excess glycemic burden >8.0% from diagnosis until starting insulin and about 10 HbA 1c -years of burden >7.0%. Whenever patients crossed the American Diabetes Association-recommended treatment threshold of 8.0%, their next HbA 1c result was as likely to be <8.0 as >8.0%. Multivariate prediction models had highly statistically significant coefficients, but predicted <10% of the variation in future HbA 1c results. CONCLUSIONS —Clinicians should change glucose-lowering treatments in type 2 diabetes much sooner or use treatments that are less likely to fail. An action point at 7.0% or lower is more likely to prevent additional deterioration than the traditional action point of 8.0%. ADA, American Diabetes Association KPNW, Kaiser Permanente Northwest Footnotes J.B.B. and G.A.N. have received research support from Eli Lilly and Wyeth. A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances. Accepted April 15, 2004. Received December 31, 2003. DIABETES CARE

ABSTRACT BACKGROUND Cardiovascular disease (CVD) prevention in diabetes requires broad-based treatment of dyslipidemia, hypertension, and hyperglycemia. The independent contribution of all combinations of risk factor control to CVD risk has not been evaluated. OBJECTIVE To estimate the independent association of control of glycosylated hemoglobin (A1C), systolic blood pressure (SBP), and low-density lipoprotein cholesterol (LDL-C) with risk of cardiovascular disease hospitalization. DESIGN Non-concurrent longitudinal cohort study. PATIENTS The study included 26,636 patients with type 2 diabetes who were members of an integrated group model HMO with multiple A1C, SBP, and LDL-C measurements. MAIN MEASURES Patients were followed for a mean (SD) of 5.6 (2.5) years until they died or disenrolled, or until 31 December 2010. The outcome was a first-observed CVD hospitalization. Using the mean of all A1C, SBP, and LDL-C measures during follow-up, we created dichotomous categories of A1C control (< 7 %), SBP control (< 130 mmHg), and LDL-C control (< 100 mg/dL) to estimate the incidence rate of CVD hospitalization associated with all combinations of risk factor control adjusting for demographic and clinical characteristics. KEY RESULTS Patients with no controlled risk factors (18.2/1,000 person-years, 95 % CI 16.5−20.2) or with only A1C in control (16.9, 15.0−19.0) had the highest rate of CVD hospitalization, whereas those with all three risk factors controlled (7.2, 6.2−8.4) or with SBP and LDL-C in control (6.1, 5.1−7.2) had the lowest rates. Those with only SBP or LDL-C in control, A1C and SBP controlled, or A1C and LDL-C controlled had statistically similar incidence between the highest and lowest rates. CONCLUSIONS Maintaining SBP < 130 mmHg or LDL-C < 100 mg/dL was significantly associated with reduced CVD hospitalization risk, especially when both risk factors were well controlled. Maintaining A1C < 7 % was not independently associated with reduced CVD hospitalization risk.

Background Studies of progression of kidney dysfunction typically focus on renal replacement therapy or percentage decline in estimated glomerular filtration rate (eGFR) as outcomes. Our aim was to compare real-world patients with and without T2D to estimate progression from and to clinically defined categories of kidney disease and all-cause mortality. Methods This was an observational cohort study of 31,931 patients with and 33,201 age/sex matched patients without type 2 diabetes (T2D) who had a serum creatinine and urine albumin-to-creatinine ratio (UACR) or dipstick proteinuria (DP) values. We used the first available serum creatinine value between 2006 and 2012 to calculate baseline eGFR and categorized them and the corresponding UACR/DP values using the Kidney Disease Improving Global Outcomes (KDIGO) categories. To assess our primary outcomes, we extracted probabilities of eGFR progression or mortality from life-table analyses and conducted multivariable Cox regression analyses of relative risk adjusted for age, sex, race/ethnicity, smoking, ischemic heart disease, heart failure, and use of renal-angiotensin-aldosterone system inhibitors. Results Patterns of eGFR decline were comparable among patients with vs. without T2D with larger percentage declines at higher albuminuria levels across all eGFR categories. eGFR decline was generally larger among T2D patients, particularly in those with severely increased albuminuria. Across all CKD categories, risk of progression to the next higher category of eGFR was substantially increased with increasing albuminuria. For example, the risk was 23.5, 36.2, and 65.1% among T2D patients with eGFR 30–59 ml/min/1.73m 2 and UACR < 30, 30–299, and > 300 mg/dL, respectively ( p  < 0.001). Other comparisons were similarly significant. Among patients with low eGFR and normal to mildly increased albuminuria, the relative risk was up to 8-fold greater for all-cause mortality compared with the non-CKD subgroup (eGFR> 60 ml/min/1.73m 2 with normal to mildly increased albuminuria). Conclusions Presence of albuminuria was associated with accelerated eGFR decline independent of T2D. Risk for adverse outcomes was remarkably high among patients with CKD and normal to mildly increased albuminuria levels. Independent of T2D or albuminuria, a substantial risk for adverse outcomes exists for CKD patients in a routine care setting.