Development of a machine learning model to predict mild cognitive impairment using natural language processing in the absence of screening.

BACKGROUND: Patients and their loved ones often report symptoms or complaints of cognitive decline that clinicians note in free clinical text, but no structured screening or diagnostic data are recorded. These symptoms/complaints may be signals that predict who will go on to be diagnosed with mild cognitive impairment (MCI) and ultimately develop Alzheimer's Disease or related dementias. Our objective was to develop a natural language processing system and prediction model for identification of MCI from clinical text in the absence of screening or other structured diagnostic information. METHODS: There were two populations of patients: 1794 participants in the Adult Changes in Thought (ACT) study and 2391 patients in the general population of Kaiser Permanente Washington. All individuals had standardized cognitive assessment scores. We excluded patients with a diagnosis of Alzheimer's Disease, Dementia or use of donepezil. We manually annotated 10,391 clinic notes to train the NLP model. Standard Python code was used to extract phrases from notes and map each phrase to a cognitive functioning concept. Concepts derived from the NLP system were used to predict future MCI. The prediction model was trained on the ACT cohort and 60% of the general population cohort with 40% withheld for validation. We used a least absolute shrinkage and selection operator logistic regression approach (LASSO) to fit a prediction model with MCI as the prediction target. Using the predicted case status from the LASSO model and known MCI from standardized scores, we constructed receiver operating curves to measure model performance. RESULTS: Chart abstraction identified 42 MCI concepts. Prediction model performance in the validation data set was modest with an area under the curve of 0.67. Setting the cutoff for correct classification at 0.60, the classifier yielded sensitivity of 1.7%, specificity of 99.7%, PPV of 70% and NPV of 70.5% in the validation cohort. DISCUSSION AND CONCLUSION: Although the sensitivity of the machine learning model was poor, negative predictive value was high, an important characteristic of models used for population-based screening. While an AUC of 0.67 is generally considered moderate performance, it is also comparable to several tests that are widely used in clinical practice.

Risk of lower extremity amputations in people with type 2 diabetes mellitus treated with sodium-glucose co-transporter-2 inhibitors in the USA: A retrospective cohort study.

AIMS: To examine the incidence of amputation in patients with type 2 diabetes mellitus (T2DM) treated with sodium glucose co-transporter 2 (SGLT2) inhibitors overall, and canagliflozin specifically, compared with non-SGLT2 inhibitor antihyperglycaemic agents (AHAs). MATERIALS AND METHODS: Patients with T2DM newly exposed to SGLT2 inhibitors or non-SGLT2 inhibitor AHAs were identified using the Truven MarketScan database. The incidence of below-knee lower extremity (BKLE) amputation was calculated for patients treated with SGLT2 inhibitors, canagliflozin, or non-SGLT2 inhibitor AHAs. Patients newly exposed to canagliflozin and non-SGLT2 inhibitor AHAs were matched 1:1 on propensity scores, and a Cox proportional hazards model was used for comparative analysis. Negative controls (outcomes not believed to be associated with any AHA) were used to calibrate P values. RESULTS: Between April 1, 2013 and October 31, 2016, 118 018 new users of SGLT2 inhibitors, including 73 024 of canagliflozin, and 226 623 new users of non-SGLT2 inhibitor AHAs were identified. The crude incidence rates of BKLE amputation were 1.22, 1.26 and 1.87 events per 1000 person-years with SGLT2 inhibitors, canagliflozin and non-SGLT2 inhibitor AHAs, respectively. For the comparative analysis, 63 845 new users of canagliflozin were matched with 63 845 new users of non-SGLT2 inhibitor AHAs, resulting in well-balanced baseline covariates. The incidence rates of BKLE amputation were 1.18 and 1.12 events per 1000 person-years with canagliflozin and non-SGLT2 inhibitor AHAs, respectively; the hazard ratio was 0.98 (95% confidence interval 0.68-1.41; P = .92, calibrated P = .95). CONCLUSIONS: This real-world study observed no evidence of increased risk of BKLE amputation for new users of canagliflozin compared with non-SGLT2 inhibitor AHAs in a broad population of patients with T2DM.

Comparative effectiveness of canagliflozin, SGLT2 inhibitors and non-SGLT2 inhibitors on the risk of hospitalization for heart failure and amputation in patients with type 2 diabetes mellitus: A real-world meta-analysis of 4 observational databases (OBSERVE-4D).

AIMS: Sodium glucose co-transporter 2 inhibitors (SGLT2i) are indicated for treatment of type 2 diabetes mellitus (T2DM); some SGLT2i have reported cardiovascular benefit, and some have reported risk of below-knee lower extremity (BKLE) amputation. This study examined the real-world comparative effectiveness within the SGLT2i class and compared with non-SGLT2i antihyperglycaemic agents. MATERIALS AND METHODS: Data from 4 large US administrative claims databases were used to characterize risk and provide population-level estimates of canagliflozin's effects on hospitalization for heart failure (HHF) and BKLE amputation vs other SGLT2i and non-SGLT2i in T2DM patients. Comparative analyses using a propensity score-adjusted new-user cohort design examined relative hazards of outcomes across all new users and a subpopulation with established cardiovascular disease. RESULTS: Across the 4 databases (142 800 new users of canagliflozin, 110 897 new users of other SGLT2i, 460 885 new users of non-SGLT2i), the meta-analytic hazard ratio estimate for HHF with canagliflozin vs non-SGLT2i was 0.39 (95% CI, 0.26-0.60) in the on-treatment analysis. The estimate for BKLE amputation with canagliflozin vs non-SGLT2i was 0.75 (95% CI, 0.40-1.41) in the on-treatment analysis and 1.01 (95% CI, 0.93-1.10) in the intent-to-treat analysis. Effects in the subpopulation with established cardiovascular disease were similar for both outcomes. No consistent differences were observed between canagliflozin and other SGLT2i. CONCLUSIONS: In this large comprehensive analysis, canagliflozin and other SGLT2i demonstrated HHF benefits consistent with clinical trial data, but showed no increased risk of BKLE amputation vs non-SGLT2i. HHF and BKLE amputation results were similar in the subpopulation with established cardiovascular disease. This study helps further characterize the potential benefits and harms of SGLT2i in routine clinical practice to complement evidence from clinical trials and prior observational studies.

Depression among people with type 2 diabetes mellitus, US National Health and Nutrition Examination Survey (NHANES), 2005-2012.

BACKGROUND: Depression in people with diabetes can result in increased risk for diabetes-related complications. The prevalence of depression has been estimated to be 17.6 % in people with type 2 diabetes mellitus (T2DM), based on studies published between 1980 and 2005. There is a lack of more recent estimates of depression prevalence among the US general T2DM population. METHODS: The present study used the US National Health and Nutrition Examination Survey (NHANES) 2005-2012 data to provide an updated, population-based estimate for the prevalence of depression in people with T2DM. NHANES is a cross-sectional survey of a nationally representative sample of the civilian, non-institutionalized US population. Starting from 2005, the Patient Health Questionnaire (PHQ-9) was included to measure signs and symptoms of depression. We defined PHQ-9 total scores ≥ 10 as clinically relevant depression (CRD), and ≥ 15 as clinically significant depression (CSD). Self-reported current antidepressant use was also combined to estimate overall burden of depression. Predictors of CRD and CSD were investigated using survey logistic regression models. RESULTS: A total of 2182 participants with T2DM were identified. The overall prevalence of CRD and CSD among people with T2DM is 10.6 % (95 % confidence interval (CI) 8.9-12.2 %), and 4.2 % (95 % CI 3.4-5.1 %), respectively. The combined burden of depressive symptoms and antidepressants may be as high as 25.4 % (95 % CI 23.0-27.9 %). Significant predictors of CRD include age (younger than 65), sex (women), income (lower than 130 % of poverty level), education (below college), smoking (current or former smoker), body mass index (≥30 kg/m(2)), sleep problems, hospitalization in the past year, and total cholesterol (≥200 mg/dl). Significant predictors of CSD also include physical activity (below guideline) and cardiovascular diseases. CONCLUSIONS: The prevalence of CRD and CSD among people with T2DM in the US may be lower than in earlier studies, however, the burden of depression remains high. Further research with longitudinal follow-up for depression in people with T2DM is needed to understand real world effectiveness of depression management.

Evaluating the impact of database heterogeneity on observational study results.

Clinical studies that use observational databases to evaluate the effects of medical products have become commonplace. Such studies begin by selecting a particular database, a decision that published papers invariably report but do not discuss. Studies of the same issue in different databases, however, can and do generate different results, sometimes with strikingly different clinical implications. In this paper, we systematically study heterogeneity among databases, holding other study methods constant, by exploring relative risk estimates for 53 drug-outcome pairs and 2 widely used study designs (cohort studies and self-controlled case series) across 10 observational databases. When holding the study design constant, our analysis shows that estimated relative risks range from a statistically significant decreased risk to a statistically significant increased risk in 11 of 53 (21%) of drug-outcome pairs that use a cohort design and 19 of 53 (36%) of drug-outcome pairs that use a self-controlled case series design. This exceeds the proportion of pairs that were consistent across databases in both direction and statistical significance, which was 9 of 53 (17%) for cohort studies and 5 of 53 (9%) for self-controlled case series. Our findings show that clinical studies that use observational databases can be sensitive to the choice of database. More attention is needed to consider how the choice of data source may be affecting results.

A survey of adult awareness and use of medicine containing acetaminophen.

PURPOSE: To compare awareness, use of acetaminophen, and preferences for receiving information aimed at reducing acetaminophen overdose. METHODS: A survey of health plan enrollees identified from automated pharmacy data who were long-term and acute users of opioids with acetaminophen (n = 720 each cohort), and a general population cohort (n = 360) during the 2010-2011 cold/flu season. A 74% response rate was achieved. Differences were tested across the three cohorts, and by level of education, using age-adjusted regression models. RESULTS: Use of over-the-counter or prescription medicine containing acetaminophen in the prior 2 weeks was reported by 84% in the long-term opioid cohort, 76% in the acute opioid cohort, and 36% in the general population, but use of over-the-counter medicine with acetaminophen did not differ across the cohorts (30-34%). All three cohorts were unlikely to correctly identify drugs containing acetaminophen, but the opioid cohorts performed slightly better than the general population. Those with higher education performed slightly better when asked to identify acetaminophen products than those with no college education. The average usual daily acetaminophen dose (mg/day) reported was highest in the long-term opioid cohort (1185), followed by the acute opioid cohort (1010), and the general population (891)-p < 0.001. Estimated supratherapeutic exposure (>4000 mg/day) was rare but three to five times more common in the opioid cohorts than in the general population. CONCLUSIONS: Acetaminophen use is common, and supratherapeutic exposure may be of concern in users of opioids. Knowledge of which drugs contain acetaminophen appears inadequate; better labeling and proactive education from professionals may be impactful.

Empirical assessment of methods for risk identification in healthcare data: results from the experiments of the Observational Medical Outcomes Partnership.

BACKGROUND: Expanded availability of observational healthcare data (both administrative claims and electronic health records) has prompted the development of statistical methods for identifying adverse events associated with medical products, but the operating characteristics of these methods when applied to the real-world data are unknown. METHODS: We studied the performance of eight analytic methods for estimating of the strength of association-relative risk (RR) and associated standard error of 53 drug-adverse event outcome pairs, both positive and negative controls. The methods were applied to a network of ten observational healthcare databases, comprising over 130 million lives. Performance measures included sensitivity, specificity, and positive predictive value of methods at RR thresholds achieving statistical significance of p < 0.05 or p < 0.001 and with absolute threshold RR > 1.5, as well as threshold-free measures such as area under receiver operating characteristic curve (AUC). RESULTS: Although no specific method demonstrated superior performance, the aggregate results provide a benchmark and baseline expectation for risk identification method performance. At traditional levels of statistical significance (RR > 1, p < 0.05), all methods have a false positive rate >18%, with positive predictive value <38%. The best predictive model, high-dimensional propensity score, achieved an AUC = 0.77. At 50% sensitivity, false positive rate ranged from 16% to 30%. At 10% false positive rate, sensitivity of the methods ranged from 9% to 33%. CONCLUSIONS: Systematic processes for risk identification can provide useful information to supplement an overall safety assessment, but assessment of methods performance suggests a substantial chance of identifying false positive associations.

Evaluation of alternative standardized terminologies for medical conditions within a network of observational healthcare databases.

Large electronic databases of health care information, such as administrative claims and electronic health records, are available and are being used in a number of public health settings, including drug safety surveillance. However, because of a lack of standardization, clinical terminologies may differ across databases. With the aid of existing resources and expert coders, we have developed mapping tables to convert ICD-9-CM diagnosis codes used in some existing databases to SNOMED-CT and MedDRA. In addition, previously developed definitions for specific health outcomes of interest were mapped to the same standardized vocabularies. We evaluated how vocabulary mapping affected (1) the retention of clinical data from two test databases, (2) the semantic space of outcome definitions, (3) the prevalence of each outcome in the test databases, and (4) the reliability of analytic methods designed to detect drug-outcome associations in the test databases. Although vocabulary mapping affected the semantic space of some outcome definitions, as well as the prevalence of some outcomes in the test databases, it had only minor effects on the analysis of drug-outcome associations. Furthermore, both SNOMED-CT and MedDRA were viable for use as standardized vocabularies in systems designed to perform active medical product surveillance using disparate sources of observational data.

Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership.

The U.S. Food and Drug Administration (FDA) Amendments Act of 2007 mandated that the FDA develop a system for using automated health care data to identify risks of marketed drugs and other medical products. The Observational Medical Outcomes Partnership is a public-private partnership among the FDA, academia, data owners, and the pharmaceutical industry that is responding to the need to advance the science of active medical product safety surveillance by using existing observational databases. The Observational Medical Outcomes Partnership's transparent, open innovation approach is designed to systematically and empirically study critical governance, data resource, and methodological issues and their interrelationships in establishing a viable national program of active drug safety surveillance by using observational data. This article describes the governance structure, data-access model, methods-testing approach, and technology development of this effort, as well as the work that has been initiated.

Resource use and cost of diagnostic workup of women with suspected breast cancer.

We estimated resource use and costs associated with a diagnostic workup for suspected breast cancer among Medicare beneficiaries. Using Medicare claims data, we found that the average cost of a diagnostic workup for suspected breast cancer--whether it eventuated in a breast cancer diagnosis or not--was $361, and did not vary by presentation (signs/symptoms or screening mammography). In the aggregate, we estimate that Medicare spends approximately $679 million annually on diagnostic workups for women with suspected breast cancer, and that false positive mammograms result in diagnostic costs of approximately $250 million.

Inferring disease severity in rheumatoid arthritis using predictive modeling in administrative claims databases.

BACKGROUND: Confounding by disease severity is an issue in pharmacoepidemiology studies of rheumatoid arthritis (RA), due to channeling of sicker patients to certain therapies. To address the issue of limited clinical data for confounder adjustment, a patient-level prediction model to differentiate between patients prescribed and not prescribed advanced therapies was developed as a surrogate for disease severity, using all available data from a US claims database. METHODS: Data from adult RA patients were used to build regularized logistic regression models to predict current and future disease severity using a biologic or tofacitinib prescription claim as a surrogate for moderate-to-severe disease. Model discrimination was assessed using the area under the receiver (AUC) operating characteristic curve, tested and trained in Optum Clinformatics® Extended DataMart (Optum) and additionally validated in three external IBM MarketScan® databases. The model was further validated in the Optum database across a range of patient cohorts. RESULTS: In the Optum database (n = 68,608), the AUC for discriminating RA patients with a prescription claim for a biologic or tofacitinib versus those without in the 90 days following index diagnosis was 0.80. Model AUCs were 0.77 in IBM CCAE (n = 75,579) and IBM MDCD (n = 7,537) and 0.75 in IBM MDCR (n = 36,090). There was little change in the prediction model assessing discrimination 730 days following index diagnosis (prediction model AUC in Optum was 0.79). CONCLUSIONS: A prediction model demonstrated good discrimination across multiple claims databases to identify RA patients with a prescription claim for advanced therapies during different time-at-risk periods as proxy for current and future moderate-to-severe disease. This work provides a robust model-derived risk score that can be used as a potential covariate and proxy measure to adjust for confounding by severity in multivariable models in the RA population. An R package to develop the prediction model and risk score are available in an open source platform for researchers.

The impact of comorbidity of mental and physical conditions on role disability in the US adult household population.

CONTEXT: There is limited information that accounts for comorbidity on the impact of role disability associated with a wide range of mental and physical disorders in population-based samples. OBJECTIVE: To estimate the comparative effects of common mental and physical conditions on role disability in the general population using a novel method that accounts for comorbidity. DESIGN: Direct interviews about physical and mental conditions during the past year. SETTING: The National Comorbidity Survey Replication, a nationally representative series of face-to-face interviews. PATIENTS: A nationally representative sample of adults living in households (N = 5962 respondents, 18 years and older). MAIN OUTCOME MEASURE: Disability in major life roles was assessed with the World Health Organization Disability Assessment Schedule. Simulations that allow for complex interactions among conditions were used to estimate the conditions' effects on disability days, when respondents were completely unable to carry out their usual daily activities because of problems with mental or physical health, in the past 12 months. RESULTS: An estimated 53.4% of US adults have 1 or more of the mental or physical conditions assessed in the survey. These respondents report an average 32.1 more role-disability days in the past year than demographically matched controls, equivalent to nearly 3.6 billion days of role disability in the population. Musculoskeletal disorders and major depression had the greatest effects on disability days. Mental conditions accounted for more than half as many disability days as all physical conditions at the population level. Associations of specific conditions with disability decreased substantially after controlling for comorbidity, suggesting that prior studies, which generally did not control for comorbidity, overestimated disease-specific effects. CONCLUSION: The staggering amount of health-related disability associated with mental and physical conditions should be considered in establishing priorities for the allocation of health care and research resources.

The identification of benefit in medical intervention: an overview and suggestions for process.

Benefit and risk assessments are not only important to regulatory authorities but also important to the providers, patients, pharmaceutical industry, and payers. In order for patients and providers to continue to have access to new innovative medicines, which have some level of inherent risk, it is critical to have a systematic and balanced focus on understanding the safety risks and benefits to the patient during drug development, at the time of approval and postmarketing. There has been a significant amount of activity around efforts to improve the ability to assess risks in the postmarketing environment. However, there is no widely accepted, systematic approach or process for the ongoing evaluation of benefit. This article introduces 4 critical components in the process of identifying and assessing benefit with a goal of providing a framework that is transparent, comprehensive, applicable to various perspectives, and simple to communicate and implement. We propose the development of a catalog applied to a particular disease to identify the optimal data sources and methods to address the interests of a given perspective. Two key resources will need to be developed to support the catalog development: (1) a summary of benefit measures and preferences by disease and from various perspectives and (2) an investment in a simple visual communication mechanism with minimal statistical language. As the emphasis is on transparency, relevance, applicability, and communication, this approach to assessing benefit should maximize the impact of these data to all stakeholders and decision makers.

The effects of rheumatoid arthritis on labor force participation, work performance, and healthcare costs in two workplace samples.

OBJECTIVE: To assess the workplace costs of rheumatoid arthritis (RA) from the employer perspective. METHOD: Samples included 4485 manufacturing firm (MF) employees (109 with RA) and 915 commercially insured (CO) subscribers (333 with RA). Respondents completed the Health and Work Performance Questionnaire (HPQ) and the Health Assessment Questionnaire (HAQ). The effects of RA were estimated using regression analysis. RESULTS: RA was associated with increased probability of no longer working (CO), increased effort to maintain work performance (CO), increased sickness absence (MF), and increased non-RA pharmacy costs (CO). RA was not associated with hours worked or hourly wage. Indirect costs of RA did not exceed direct medical costs. CONCLUSIONS: Indirect costs of RA to employers are significant and warrant further research to increase our understanding of the contribution of different RA treatment interventions to optimizing workforce productivity.

Rhinitis symptoms and comorbidities in the United States: burden of rhinitis in America survey.

OBJECTIVE: To assess the burden of nasal symptoms in the United States (U.S.) and the comorbid conditions associated with nasal symptoms. SUBJECTS AND METHODS: A self-administered screening questionnaire and follow-up survey was sent to targeted households from a representative sample of 15,000 households in the U.S. Subjects with comorbid asthma completed the Asthma Control Test (ACT). RESULTS: Out of 7024 evaluable subjects who responded, 3831 subjects were classified as rhinitis "sufferers." Individuals with active rhinitis symptoms were 1.5 to 4.5 times more likely to suffer from comorbid conditions including asthma, conjunctivitis, otitis media, sinusitis, eczema, food and insect bite allergies, migraine, and depression. Almost half of all respondents with moderate or severe rhinitis symptoms and comorbid asthma had poorly controlled asthma as defined by an ACT score of < or =19. CONCLUSIONS: A strong relationship exists between rhinitis symptoms and various comorbidities, including asthma, in the U.S. population. Poorly controlled rhinitis contributes to the public health burden of rhinitis and asthma.

Broadening the definition of generalized anxiety disorder: effects on prevalence and associations with other disorders in the National Comorbidity Survey Replication.

Concerns have been raised that the DSM-IV requirements of 6-month duration, excessive worry, and three associated symptoms exclude a substantial number of people with clinically significant anxiety from a diagnosis of generalized anxiety disorder (GAD). We examined the implications of relaxing these three criteria for the estimated prevalence and predictive validity of GAD using nationally representative data from the US National Comorbidity Survey Replication. Relaxing all three criteria more than doubles the estimated prevalence of GAD. Broadly defined GAD significantly predicts the subsequent first onset of a wide range of temporally secondary disorders. The odds of secondary disorders are somewhat smaller for broadly defined than DSM-IV GAD, though few of these differences are statistically significant. Results suggest that subthreshold manifestations of GAD are significantly related to elevated risk of subsequent psychopathology. Further research is needed to determine whether broadening the current diagnostic criteria results in a more valid characterization of GAD.

Atypical Antipsychotics and the Risks of Acute Kidney Injury and Related Outcomes Among Older Adults: A Replication Analysis and an Evaluation of Adapted Confounding Control Strategies.

OBJECTIVE: A recently published analysis of population-based claims data from Ontario, Canada reported higher risks of acute kidney injury (AKI) and related outcomes among older adults who were new users of atypical antipsychotics (AAPs) compared with unexposed patients. In light of these findings, the objective of the current study was to further investigate the risks of AKI and related outcomes among older adults receiving AAPs. METHODS: A replication of the previously published analysis was performed using the US Truven MarketScan Medicare Supplemental database (MDCR) among patients aged 65 years and older. Compared with non-users of AAPs, the study compared the risk of AKI and related outcomes with users of AAPs (quetiapine, risperidone, olanzapine, aripiprazole, or paliperidone) using a 1-to-1 propensity score matched analysis. In addition, we performed adapted analyses that: (1) included all covariates used to fit propensity score models in outcome models; and (2) required patients to have a diagnosis of schizophrenia, bipolar disorder, or major depression and a healthcare visit within 90 days prior to the index date. RESULTS: AKI effect estimates [as odds ratios (ORs) with 95% confidence intervals (CIs)] were significantly elevated in our MDCR replication analyses (OR 1.45, 95% CI 1.32-1.60); however, in adapted analyses, associations were not significant (OR 0.91, 95% CI 0.78-1.07)). In analyses of AKI and related outcomes, results were mostly consistent between the previously published and the MDCR replication analyses. The primary change that attenuated associations in adapted analyses was the requirement for patients to have a mental health condition and a healthcare visit prior to the index date. CONCLUSIONS: The MDCR analysis yielded similar results when the methodology of the previously published analysis was replicated, but, in adapted analyses, we did not find significantly higher risks of AKI and related outcomes. The contrast of results between our replication and adapted analyses may be due to the analytic approach used to compare patients (and potential confounding by indication). Further research is warranted to evaluate these associations, while also examining methods to account for differences in older adults who do and do not use these medications.

Incidence of diabetic ketoacidosis among patients with type 2 diabetes mellitus treated with SGLT2 inhibitors and other antihyperglycemic agents.

AIMS: To estimate and compare incidence of diabetes ketoacidosis (DKA) among patients with type 2 diabetes who are newly treated with SGLT2 inhibitors (SGLT2i) versus non-SGLT2i antihyperglycemic agents (AHAs) in actual clinical practice. METHODS: A new-user cohort study design using a large insurance claims database in the US. DKA incidence was compared between new users of SGLT2i and new users of non-SGLT2i AHAs pair-matched on exposure propensity scores (EPS) using Cox regression models. RESULTS: Overall, crude incidence rates (95% CI) per 1000 patient-years for DKA were 1.69 (1.22-2.30) and 1.83 (1.58-2.10) among new users of SGLT2i (n=34,442) and non-SGLT2i AHAs (n=126,703). These rates more than doubled among patients with prior insulin prescriptions but decreased by more than half in analyses that excluded potential autoimmune diabetes (PAD). The hazard ratio (95% CI) for DKA comparing new users of SGLT2i to new users of non-SGLT2i AHAs was 1.91 (0.94-4.11) (p=0.09) among the 30,196 EPS-matched pairs overall, and 1.13 (0.43-3.00) (p=0.81) among the 27,515 EPS-matched pairs that excluded PAD. CONCLUSIONS: This was the first observational study that compared DKA risk between new users of SGLT2i and non-SGLT2i AHAs among patients with type 2 diabetes, and overall no statistically significant difference was detected.

Sleep problems, comorbid mental disorders, and role functioning in the national comorbidity survey replication.

BACKGROUND: Little is known about the population prevalence of sleep problems or whether the associations of sleep problems with role impairment are due to comorbid mental disorders. METHODS: The associations of four 12-month sleep problems (difficulty initiating or maintaining sleep, early morning awakening, nonrestorative sleep) with role impairment were analyzed in the National Comorbidity Survey Replication controlling 12-month DSM-IV anxiety, mood, impulse-control, and substance disorders. The WHO Composite International Diagnostic Interview was used to assess sleep problems and DSM-IV disorders. The WHO Disability Schedule-II (WHO-DAS) was used to assess role impairment. RESULTS: Prevalence estimates of the separate sleep problems were in the range 16.4-25.0%, with 36.3% reporting at least one of the four. Mean 12-month duration was 24.4 weeks. All four problems were significantly comorbid with all the 12-month DMS-IV disorders assessed in the survey (median OR: 3.4; 25(th)-75(th) percentile: 2.8-3.9) and significantly related to role impairment. Relationships with role impairment generally remained significant after controlling comorbid mental disorders. Nonrestorative sleep was more strongly and consistently related to role impairment than were the other sleep problems. CONCLUSIONS: The four sleep problems considered here are of public health significance because of their high prevalence and significant associations with role impairment.