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Background: Reports of adverse outcomes with use of Proton Pump Inhibitors (PPIs) and recent associations between PPI use and Chronic Kidney Disease (CKD) suggest the need to examine PPI use in the general population.Objectives: The purpose of this study was to examine PPI use in the general U.S. population with a focus on CKD stages.Methods: This was a retrospective database study of the National Health and Nutrition Examination Survey (NHANES) for years 2009-2013. Inclusion criteria were age ≥ 18 years and having a serum creatinine value. The Andersen Behavioral Model of Health Services Utilization and previous research were used to identify the independent variables. Dependent variable was self-reported prescription medication use. Multinomial logistic regression models were used to examine factors associated with PPI use.Results: Overall, the weighted prevalence of PPI use was 8.7%. Only 4.5% of the sample had stage 3 or 4 CKD. PPI use was highest among whites (10.5%) compared to minorities. PPI users were significantly older (mean = 59.8years), with a majority (80%) being 50 years and over. In multivariate analyses, PPI use was associated with having two or more comorbidities (OR = 3.8, CI: 2.85-5.13), and having fair/poor health (OR 4.6 (3.5-5.9). Stage 3 and 4 CKD patients had higher odds of using PPIs (stage 3 OR = 3.8 CI: 2.5-5.8, stage 4 OR = 6.5 CI: 1.6-25.8) compared to stage 1 patients.Conclusion: /Relevance: This is the first study to examine both predictors and racial disparities in PPI use in the general US population. While PPI use was low, there were racial disparities in PPI use. Multiple comorbid conditions, lower quality of life, and stage 3/4 CKD were associated with PPI use. Awareness of these predictors will enable clinicians to target key patient groups for tailored education and closer monitoring of PPI use. [ABSTRACT FROM AUTHOR]

Background Tuberous Sclerosis Complex (TSC) is a multi-system genetic disorder characterised by the development of benign growths and diverse clinical manifestations, varying in severity, age at onset and with high clinical burden. Aims This longitudinal study aims to describe the broad spectrum of clinical manifestation profiles in a large, representative cohort of TSC patients in the UK in order to better understand disease complexity. Methods TSC patients in the Clinical Practice Research Datalink (CPRD) and linked Hospital Episodes Statistics (CPRD-HES) were retrospectively identified between 1987 and 2013. Available history was extracted for each patient and clinical diagnosis, procedure and medication records reviewed. A random selection of patients from the CPRD-HES was used as a Comparator cohort. Results Three hundred and thirty-four TSC patients with a mean (SD) age of 30.3 (18.6) years were identified (53% female). TSC was diagnosed at mean age 3.2 (4.2) years. Epilepsy and psychiatric manifestations were reported frequently in paediatric (77% and 55%, respectively) and adult patients (66% and 68%, respectively). The prevalence of manifestations in the TSC cohort was markedly higher versus the Comparator cohort. The majority of paediatric (46%) and adult TSC patients (62%) developed clinical manifestations affecting at least three organ systems and forty-nine distinctive organ system manifestation profiles were identified. Conclusions TSC patients present with multiple and complex clinical manifestations and profiles that necessitate the co-ordinated action of a multidisciplinary team in order to improve the quality and efficiency of care. [ABSTRACT FROM AUTHOR]

Total Knee Arthroplasty (TKA) is a common orthopaedic surgery to treat advanced knee arthritis. Post-operative complications can be affected by obesity, defined as a body mass index of 30 kg/m2 or higher. We examine the rates of specific complications, revision rates, and costs of care following TKA and compare them between multifactor matched obese and non-obese patients. We hypothesize these outcomes will be worse in obese patients than in non-obese patients. This retrospective study of the PearlDiver database queries for patients who underwent TKA under Current Procedural Terminology (CPT) and International Statistical Classification of Diseases (ICD-9) codes between January 2011 and January 2020. Patients were matched based on age, gender, and comorbidity indices, and various complications, revision rates, and costs were compared between the matched obese and non-obese patient groups. Obesity was associated with higher rates of surgical complications, such as wound complications, surgical site infections, need for revision, and higher total cost of care one year after TKA, and medical complications such as, acute kidney injury, deep vein thrombosis, urinary tract infection, and narcotics use, but significantly lower rates of anemia, arrhythmia, cardiac arrest, pneumonia, and transfusion. Obese patients also experienced significantly lower drug costs of care. Outcomes were not definitively worse in obese patients when compared to matched non-obese patients. Nevertheless, understanding the complications that can arise following TKA will assist in educating patients about potential risks from surgery and guide surgeons in caring for their patients as obesity is predicted to continue increasing in prevalence. As such, future studies should examine underlying mechanisms that cause these complications to develop potential therapies. [ABSTRACT FROM AUTHOR]

• The multiple sclerosis Medicare disability-eligible and medicare age-eligible populations are considerably different in disease severity, comorbidities, and healthcare utilization. • Risk for MS-related hospitalizations and relapses are significantly higher in the medicare disability-eligible population than the age-eligible population. • Accounting for eligibility type is important when examining MS disease severity and comorbidity. To compare algorithm determined disease severity, risk of multiple sclerosis (MS) relapse, and MS-related hospitalization between the age-eligible and disability-eligible MS Medicare populations. Using the Humana claims dataset (2013 - 2015), patients were divided into Medicare age-eligible and disability-eligible groups. A previously developed algorithm, which used MS symptoms and healthcare utilization to categorize MS disease severity into three groups (low, moderate, high) at baseline was employed. Flexible parametric and Cox proportional hazard models were used to estimate the risk for MS relapses and MS-related hospitalizations among the MS disease severity groups and the two eligibility cohorts in the follow-up period. Of the overall sample (N = 6,559), the majority (N = 4,813, 73.4%) were disability-eligible and in the low disease severity group (N = 4,468, 68.1%). In 10 of 16 disease severity algorithm predictors, the prevalence of these predictors was significantly (p <0.001) higher in the disability-eligible group compared to the age-eligible group. Survival analyses revealed that the disability-eligible group had a significantly higher risk for follow-up MS relapses and follow-up MS-related hospitalizations (HR = 1.79 [CI 1.54 - 2.08] and HR = 1.38 [CI 1.11–1.72], respectively) compared to those in the age-eligible group. When both eligibility and disease severity were considered in the model increases in hazard ratios corresponded generally to increases in disease severity. However, the type of Medicare eligibility does not appear to have a clear pattern across MS disease severity groups for either MS relapse or hospitalizations, The disability-eligible Medicare population had a significantly higher prevalence of MS comorbidities and higher MS severity scores at baseline. In addition, they had a higher risk for MS-related relapses and MS-related hospitalizations in the follow-up period. It is important to account for disability status when assessing disease severity and healthcare utilization. [ABSTRACT FROM AUTHOR]

• Retrospective administrative data were helpful in predicting future healthcare costs among MS patients • Total healthcare costs were strongly correlated with disease severity scores and categorization. • Algorithm determined disease severity aligns with tradition claims-based measured of MS disease severity. • The use of retrospective administrative data was useful in estimating multiple sclerosis disease severity. Patients with multiple sclerosis (MS) tend to have significantly lower health-related quality of life, increased mortality and morbidity, and increased healthcare costs. The lack of a claims-based algorithm to correctly identify disease severity makes targeted selection of the MS patients for specific interventions an important limitation in real-world MS research. Using the Optum claims dataset (2016 -2018), 11,429 persons with MS and >= 24 months of eligibility were identified. A previously developed claims-based algorithm was employed to categorize MS disease severity (low, moderate, high), using MS symptoms and healthcare utilization. Linear regression analysis was used to determine the relationship between disease severity and total cost, a proxy for disease severity. Flexible parametric models were used to determine the risk of 12-month follow-up MS-related relapses and MS-related hospitalizations among the MS disease severity groups. The risk of both MS-related relapses and MS-related hospitalizations increased as MS disease severity increased. The risk for MS-related relapses was significantly higher in the moderate (HR = 2.43, 95% CI 1.24 -2.64, P < 0.001) and high (HR = 5.97, 95% CI 5.19-6.83, P < 0.001) disease severity groups compared to the low disease severity group. The same trend is observed concerning MS-related hospitalization risk. Both the moderate (HR = 3.16, 95% CI 2.73-3.63, P> 0.001) and high disease severity (HR =12.70, 95% CI 10.57-15.09, P < 0.001) groups had significantly higher risk of MS-related hospitalization compared to the low disease severity group. The claims-based disease severity algorithm performed well in explaining the total healthcare cost (excluding DMTs). The algorithm-determined disease severity categorization appears consistent with traditional measures of disease severity (MS relapse and hospitalizations). This claims-based algorithm may be a useful tool in determining MS disease severity in claims data. [ABSTRACT FROM AUTHOR]