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BackgroundFifty percent of people living with dementia are undiagnosed. The electronic health record (EHR) Risk of Alzheimer's and Dementia Assessment Rule (eRADAR) was developed to identify older adults at risk of having undiagnosed dementia using routinely collected clinical data.ObjectiveTo externally validate eRADAR in two real-world healthcare systems, including examining performance over time and by race/ethnicity.DesignRetrospective cohort study PARTICIPANTS: 129,315 members of Kaiser Permanente Washington (KPWA), an integrated health system providing insurance coverage and medical care, and 13,444 primary care patients at University of California San Francisco Health (UCSF), an academic medical system, aged 65 years or older without prior EHR documentation of dementia diagnosis or medication.Main measuresPerformance of eRADAR scores, calculated annually from EHR data (including vital signs, diagnoses, medications, and utilization in the prior 2 years), for predicting EHR documentation of incident dementia diagnosis within 12 months.Key resultsA total of 7631 dementia diagnoses were observed at KPWA (11.1 per 1000 person-years) and 216 at UCSF (4.6 per 1000 person-years). The area under the curve was 0.84 (95% confidence interval: 0.84-0.85) at KPWA and 0.79 (0.76-0.82) at UCSF. Using the 90th percentile as the cut point for identifying high-risk patients, sensitivity was 54% (53-56%) at KPWA and 44% (38-51%) at UCSF. Performance was similar over time, including across the transition from International Classification of Diseases, version 9 (ICD-9) to ICD-10 codes, and across racial/ethnic groups (though small samples limited precision in some groups).ConclusionseRADAR showed strong external validity for detecting undiagnosed dementia in two health systems with different patient populations and differential availability of external healthcare data for risk calculations. In this study, eRADAR demonstrated generalizability from a research sample to real-world clinical populations, transportability across health systems, robustness to temporal changes in healthcare, and similar performance across larger racial/ethnic groups.

The association between current use of oral contraceptives (OCs) among women younger than 50 years (n  = 306 541), and hormone therapy (HT) among women aged 50 years or older (n  = 323 203), and coronavirus 2019 (COVID-19) infection and hospitalization was evaluated in this population-based cohort. Current OC/HT use was recorded monthly using prescription dispensing data. COVID-19 infections were identified from March 2020 through February 2021. COVID-19 infections and hospitalizations were identified through diagnosis codes and laboratory tests. We used weighted generalized estimating equations models to estimate multivariable adjusted odds ratios (aORs) for COVID-19 infection associated with time-varying OC/HT use. Among women with COVID-19, logistic regression models were used to evaluate OC/HT use and COVID-19 hospitalization. Over 12 months, 11 727 (3.8%) women younger than 50 years and 8661 (2.7%) women aged 50 years or older experienced COVID-19 infections. There was no evidence of an association between OC use and infection (aOR = 1.05; 95% CI, 0.97-1.12). There was a modest association between HT use and infection (aOR = 1.19; 95% CI, 1.03-1.38). Women using OCs had a 39% lower risk of hospitalization (aOR = 0.61; 95% CI, 0.38-1.00), but there was no association of HT use with hospitalization (aOR = 0.89; 95% CI, 0.51-1.53). These findings do not suggest a meaningfully greater risk of COVID-19 infection associated with OC or HT use. OC use may be associated with lower COVID-19 hospitalization risk. [ABSTRACT FROM AUTHOR]

Background: Fifty percent of people living with dementia are undiagnosed. The electronic health record (EHR) Risk of Alzheimer's and Dementia Assessment Rule (eRADAR) was developed to identify older adults at risk of having undiagnosed dementia using routinely collected clinical data. Objective: To externally validate eRADAR in two real-world healthcare systems, including examining performance over time and by race/ethnicity. Design: Retrospective cohort study Participants: 129,315 members of Kaiser Permanente Washington (KPWA), an integrated health system providing insurance coverage and medical care, and 13,444 primary care patients at University of California San Francisco Health (UCSF), an academic medical system, aged 65 years or older without prior EHR documentation of dementia diagnosis or medication. Main Measures: Performance of eRADAR scores, calculated annually from EHR data (including vital signs, diagnoses, medications, and utilization in the prior 2 years), for predicting EHR documentation of incident dementia diagnosis within 12 months. Key Results: A total of 7631 dementia diagnoses were observed at KPWA (11.1 per 1000 person-years) and 216 at UCSF (4.6 per 1000 person-years). The area under the curve was 0.84 (95% confidence interval: 0.84–0.85) at KPWA and 0.79 (0.76–0.82) at UCSF. Using the 90th percentile as the cut point for identifying high-risk patients, sensitivity was 54% (53–56%) at KPWA and 44% (38–51%) at UCSF. Performance was similar over time, including across the transition from International Classification of Diseases, version 9 (ICD-9) to ICD-10 codes, and across racial/ethnic groups (though small samples limited precision in some groups). Conclusions: eRADAR showed strong external validity for detecting undiagnosed dementia in two health systems with different patient populations and differential availability of external healthcare data for risk calculations. In this study, eRADAR demonstrated generalizability from a research sample to real-world clinical populations, transportability across health systems, robustness to temporal changes in healthcare, and similar performance across larger racial/ethnic groups. [ABSTRACT FROM AUTHOR]

Background Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) may increase the risk of coronavirus disease 2019 (COVID-19) infection or affect disease severity. Prior studies have not examined risks by medication dose. Methods This retrospective cohort study included people aged ≥18 years enrolled in a US integrated healthcare system for at least 4 months as of 2/29/2020. Current ACEI and ARB use was identified from pharmacy data, and the estimated daily dose was calculated and standardized across medications. COVID-19 infections and hospitalizations were identified through 6/14/2020 from laboratory and hospitalization data. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for race/ethnicity, obesity, and other covariates. Results Among 322,044 individuals, 826 developed COVID-19 infection. Among people using ACEI/ARBs, 204/56,105 developed COVID-19 (3.6 per 1,000 individuals) compared with 622/265,939 without ACEI/ARB use (2.3 per 1,000), yielding an adjusted OR of 0.91 (95% CI 0.74–1.12). For use of <1 defined daily dose (DDD) vs. nonuse, the adjusted OR for infection was 0.92 (95% CI 0.66–1.28); for 1 to <2 DDDs, 0.89 (95% CI 0.66–1.19); and for ≥2 DDDs, 0.92 (95% CI 0.72–1.18). The OR was similar for ACEIs and ARBs and in subgroups by age and sex. 26% of people with COVID-19 infection were hospitalized; the adjusted OR for hospitalization in relation to ACEI/ARB use was 0.98 (95% CI 0.63–1.54), and there was no association with dose. Conclusions These findings support current recommendations that individuals on these medications continue their use. [ABSTRACT FROM AUTHOR]

Through the sharing of personal commentaries about our doctoral fieldwork experiences, this paper contributes to decolonial literatures about academic knowledge generation in settler-colonial societies. The commentaries each illustrate shifting understandings of our roles in perpetuating the colonial knowledge-violence and material power of the academy, and our personal ethics to do something useful in response. Such experiences are often unreported or under reported for diverse reasons. Seeking to address injustice, and to move away from extractive research relationships, we highlight four matters: consent and risk; the resource gap in research collaborations; the consequences of not collaborating with Indigenous people; and, the importance of examining knowledge frames. As constrained and compromised as it is, we argue the doctoral experience is an important opportunity for decolonising the academy. Whilst we appreciate that this paper does not address the material circumstances that perpetuate colonial privilege, we go beyond descriptive reflection to offer prescriptions for change. [ABSTRACT FROM AUTHOR]

Objective  Women with prediabetes are identified from screening for overt diabetes in early pregnancy, but the clinical significance of prediabetes in pregnancy is unclear. We examined whether prediabetes in early pregnancy was associated with risks of adverse outcomes. Study Design  We conducted a retrospective cohort study of pregnant women enrolled in Kaiser Permanente Washington from 2011 to 2014. Early pregnancy hemoglobin A1C (A1C) values, covariates, and outcomes were ascertained from electronic medical records and state birth certificates. Women with prediabetes (A1C of 5.7–6.4%) were compared with those with normal A1C levels (<5.7%) for risk of gestational diabetes mellitus (GDM) and other outcomes including preeclampsia, primary cesarean delivery, induction of labor, large/small for gestational age, preterm birth, and macrosomia. We used modified Poisson's regression to calculate adjusted relative risks (RRs) and 95% confidence intervals (CIs). Results  Of 7,020 women, 239 (3.4%) had prediabetes. GDM developed in 48% of prediabetic women compared with 11% of women with normal A1C levels (adjusted RR: 2.8, 95% CI: 2.4–3.3). Prediabetes was not associated with all other adverse maternal and neonatal outcomes. Conclusion  Prediabetes in early pregnancy is a risk factor for GDM. Future research is needed to elucidate whether early intervention may reduce this risk. [ABSTRACT FROM AUTHOR]

Rationale: Mechanistic target of rapamycin inhibitors reduce loss of lung function in lymphangioleiomyomatosis (LAM), although their benefit varies between individuals. We examined lung function response and side effects to rapamycin in a national cohort.Methods: Subjects were receiving rapamycin for progressive lung disease. Clinical evaluation, detailed phenotyping, serial lung function, rapamycin and safety monitoring were performed according to a clinical protocol. Lung function change, measured as FEV1 slope (ΔFEV1), was reported for those treated for 1 year or longer.Results: Rapamycin was associated with improved ΔFEV1 in 21 individuals where pretreatment data were available (p<0.0001). In 47 treated for a mean duration of 35.8 months, mean ΔFEV1 was +11 (SD 75) mL/year, although it varied from +254 to -148 mL/year. The quartile with the highest positive ΔFEV1 had greater pretreatment FEV1 (p=0.02) and shorter disease durations (p=0.02) than the lowest quartile. Serum rapamycin level was positively associated with side effects (p=0.02) but not ΔFEV1 over 1 year. Within the first month of therapy, apthous ulcers, nausea and diarrhoea were associated with higher rapamycin levels. Acne, oedema and menstrual irregularities tended to increase over the first year of therapy. At the end of observation, the prevalence of side effects was 5% or less.Conclusions: Rapamycin reduces lung function loss in LAM, although in some, ΔFEV1 continues to fall at an accelerated rate. Poor response to rapamycin was associated with lower pretreatment lung function and longer disease duration but not serum level. Early intervention with low-dose rapamycin may preserve lung function and reduce side effects. [ABSTRACT FROM AUTHOR]