6 results on '"Blacketer, Clair"'
Search Results
2. Characteristics and outcomes of patients with COVID-19 with and without prevalent hypertension: a multinational cohort study
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Reyes, Carlen, Pistillo, Andrea, Fernández-Bertolín, Sergio, Recalde, Martina, Roel, Elena, Puente, Diana, Sena, Anthony G, Blacketer, Clair, Lai, Lana, Alshammari, Thamir M, Ahmed, Waheed-UI-Rahman, Alser, Osaid, Alghoul, Heba, Areia, Carlos, Dawoud, Dalia, Prats-Uribe, Albert, Valveny, Neus, de Maeztu, Gabriel, Redó, Luisa Sorlí, Roldan, Jordi Martinez, Montesinos, Inmaculada Lopez, Schilling, Lisa M, Golozar, Asieh, Reich, Christian, Posada, Jose D, Shah, Nigam, You, Seng Chan, Lynch, Kristine E, DuVall, Scott L, Matheny, Michael E, Nyberg, Fredrik, Ostropolets, Anna, Hripcsak, George, Rijnbeek, Peter R, Suchard, Marc A, Ryan, Patrick, Kostka, Kristin, and Duarte-Salles, Talita
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Clinical Research ,Cardiovascular ,Aetiology ,2.4 Surveillance and distribution ,Good Health and Well Being ,COVID-19 ,COVID-19 Testing ,Cohort Studies ,Comorbidity ,Female ,Hospitalization ,Humans ,Hypertension ,Middle Aged ,Retrospective Studies ,SARS-CoV-2 ,epidemiology ,hypertension ,Clinical Sciences ,Public Health and Health Services ,Other Medical and Health Sciences - Abstract
ObjectiveTo characterise patients with and without prevalent hypertension and COVID-19 and to assess adverse outcomes in both inpatients and outpatients.Design and settingThis is a retrospective cohort study using 15 healthcare databases (primary and secondary electronic healthcare records, insurance and national claims data) from the USA, Europe and South Korea, standardised to the Observational Medical Outcomes Partnership common data model. Data were gathered from 1 March to 31 October 2020.ParticipantsTwo non-mutually exclusive cohorts were defined: (1) individuals diagnosed with COVID-19 (diagnosed cohort) and (2) individuals hospitalised with COVID-19 (hospitalised cohort), and stratified by hypertension status. Follow-up was from COVID-19 diagnosis/hospitalisation to death, end of the study period or 30 days.OutcomesDemographics, comorbidities and 30-day outcomes (hospitalisation and death for the 'diagnosed' cohort and adverse events and death for the 'hospitalised' cohort) were reported.ResultsWe identified 2 851 035 diagnosed and 563 708 hospitalised patients with COVID-19. Hypertension was more prevalent in the latter (ranging across databases from 17.4% (95% CI 17.2 to 17.6) to 61.4% (95% CI 61.0 to 61.8) and from 25.6% (95% CI 24.6 to 26.6) to 85.9% (95% CI 85.2 to 86.6)). Patients in both cohorts with hypertension were predominantly >50 years old and female. Patients with hypertension were frequently diagnosed with obesity, heart disease, dyslipidaemia and diabetes. Compared with patients without hypertension, patients with hypertension in the COVID-19 diagnosed cohort had more hospitalisations (ranging from 1.3% (95% CI 0.4 to 2.2) to 41.1% (95% CI 39.5 to 42.7) vs from 1.4% (95% CI 0.9 to 1.9) to 15.9% (95% CI 14.9 to 16.9)) and increased mortality (ranging from 0.3% (95% CI 0.1 to 0.5) to 18.5% (95% CI 15.7 to 21.3) vs from 0.2% (95% CI 0.2 to 0.2) to 11.8% (95% CI 10.8 to 12.8)). Patients in the COVID-19 hospitalised cohort with hypertension were more likely to have acute respiratory distress syndrome (ranging from 0.1% (95% CI 0.0 to 0.2) to 65.6% (95% CI 62.5 to 68.7) vs from 0.1% (95% CI 0.0 to 0.2) to 54.7% (95% CI 50.5 to 58.9)), arrhythmia (ranging from 0.5% (95% CI 0.3 to 0.7) to 45.8% (95% CI 42.6 to 49.0) vs from 0.4% (95% CI 0.3 to 0.5) to 36.8% (95% CI 32.7 to 40.9)) and increased mortality (ranging from 1.8% (95% CI 0.4 to 3.2) to 25.1% (95% CI 23.0 to 27.2) vs from 0.7% (95% CI 0.5 to 0.9) to 10.9% (95% CI 10.4 to 11.4)) than patients without hypertension.ConclusionsCOVID-19 patients with hypertension were more likely to suffer severe outcomes, hospitalisations and deaths compared with those without hypertension.
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- 2021
3. Characteristics and Outcomes of Over 300,000 Patients with COVID-19 and History of Cancer in the United States and SpainCharacteristics of 300,000 COVID-19 Individuals with Cancer
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Roel, Elena, Pistillo, Andrea, Recalde, Martina, Sena, Anthony G, Fernández-Bertolín, Sergio, Aragón, Maria, Puente, Diana, Ahmed, Waheed-Ul-Rahman, Alghoul, Heba, Alser, Osaid, Alshammari, Thamir M, Areia, Carlos, Blacketer, Clair, Carter, William, Casajust, Paula, Culhane, Aedin C, Dawoud, Dalia, DeFalco, Frank, DuVall, Scott L, Falconer, Thomas, Golozar, Asieh, Gong, Mengchun, Hester, Laura, Hripcsak, George, Tan, Eng Hooi, Jeon, Hokyun, Jonnagaddala, Jitendra, Lai, Lana YH, Lynch, Kristine E, Matheny, Michael E, Morales, Daniel R, Natarajan, Karthik, Nyberg, Fredrik, Ostropolets, Anna, Posada, José D, Prats-Uribe, Albert, Reich, Christian G, Rivera, Donna R, Schilling, Lisa M, Soerjomataram, Isabelle, Shah, Karishma, Shah, Nigam H, Shen, Yang, Spotniz, Matthew, Subbian, Vignesh, Suchard, Marc A, Trama, Annalisa, Zhang, Lin, Zhang, Ying, Ryan, Patrick B, Prieto-Alhambra, Daniel, Kostka, Kristin, and Duarte-Salles, Talita
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Biomedical and Clinical Sciences ,Health Services and Systems ,Health Sciences ,Clinical Sciences ,Oncology and Carcinogenesis ,Breast Cancer ,Patient Safety ,Infectious Diseases ,Rare Diseases ,Hematology ,Cancer ,Urologic Diseases ,Prevention ,Clinical Research ,Aetiology ,2.4 Surveillance and distribution ,Good Health and Well Being ,Adolescent ,Adult ,Aged ,Aged ,80 and over ,COVID-19 ,Child ,Cohort Studies ,Comorbidity ,Databases ,Factual ,Female ,Hospitalization ,Humans ,Immunosuppression Therapy ,Influenza ,Human ,Male ,Middle Aged ,Neoplasms ,Outcome Assessment ,Health Care ,Pandemics ,Prevalence ,Risk Factors ,SARS-CoV-2 ,Spain ,United States ,Young Adult ,Medical and Health Sciences ,Epidemiology ,Biomedical and clinical sciences ,Health sciences - Abstract
BackgroundWe described the demographics, cancer subtypes, comorbidities, and outcomes of patients with a history of cancer and coronavirus disease 2019 (COVID-19). Second, we compared patients hospitalized with COVID-19 to patients diagnosed with COVID-19 and patients hospitalized with influenza.MethodsWe conducted a cohort study using eight routinely collected health care databases from Spain and the United States, standardized to the Observational Medical Outcome Partnership common data model. Three cohorts of patients with a history of cancer were included: (i) diagnosed with COVID-19, (ii) hospitalized with COVID-19, and (iii) hospitalized with influenza in 2017 to 2018. Patients were followed from index date to 30 days or death. We reported demographics, cancer subtypes, comorbidities, and 30-day outcomes.ResultsWe included 366,050 and 119,597 patients diagnosed and hospitalized with COVID-19, respectively. Prostate and breast cancers were the most frequent cancers (range: 5%-18% and 1%-14% in the diagnosed cohort, respectively). Hematologic malignancies were also frequent, with non-Hodgkin's lymphoma being among the five most common cancer subtypes in the diagnosed cohort. Overall, patients were aged above 65 years and had multiple comorbidities. Occurrence of death ranged from 2% to 14% and from 6% to 26% in the diagnosed and hospitalized COVID-19 cohorts, respectively. Patients hospitalized with influenza (n = 67,743) had a similar distribution of cancer subtypes, sex, age, and comorbidities but lower occurrence of adverse events.ConclusionsPatients with a history of cancer and COVID-19 had multiple comorbidities and a high occurrence of COVID-19-related events. Hematologic malignancies were frequent.ImpactThis study provides epidemiologic characteristics that can inform clinical care and etiologic studies.
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- 2021
4. Characteristics and outcomes of COVID-19 patients with and without asthma from the United States, South Korea, and Europe.
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Morales, Daniel R., Ostropolets, Anna, Lai, Lana, Sena, Anthony, Duvall, Scott, Suchard, Marc, Verhamme, Katia, Rjinbeek, Peter, Posada, Joe, Ahmed, Waheed, Alshammary, Thamer, Alghoul, Heba, Alser, Osaid, Areia, Carlos, Blacketer, Clair, Burn, Edward, Casajust, Paula, You, Seng Chan, Dawoud, Dalia, and Golozar, Asieh
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COVID-19 ,ASTHMATICS ,ADULT respiratory distress syndrome ,COUGH - Abstract
Objective: Large international comparisons describing the clinical characteristics of patients with COVID-19 are limited. The aim of the study was to perform a large-scale descriptive characterization of COVID-19 patients with asthma. Methods: We included nine databases contributing data from January to June 2020 from the US, South Korea (KR), Spain, UK and the Netherlands. We defined two cohorts of COVID-19 patients ('diagnosed' and 'hospitalized') based on COVID-19 disease codes. We followed patients from COVID-19 index date to 30 days or death. We performed descriptive analysis and reported the frequency of characteristics and outcomes in people with asthma defined by codes and prescriptions. Results: The diagnosed and hospitalized cohorts contained 666,933 and 159,552 COVID-19 patients respectively. Exacerbation in people with asthma was recorded in 1.6–8.6% of patients at presentation. Asthma prevalence ranged from 6.2% (95% CI 5.7–6.8) to 18.5% (95% CI 18.2–18.8) in the diagnosed cohort and 5.2% (95% CI 4.0–6.8) to 20.5% (95% CI 18.6–22.6) in the hospitalized cohort. Asthma patients with COVID-19 had high prevalence of comorbidity including hypertension, heart disease, diabetes and obesity. Mortality ranged from 2.1% (95% CI 1.8–2.4) to 16.9% (95% CI 13.8–20.5) and similar or lower compared to COVID-19 patients without asthma. Acute respiratory distress syndrome occurred in 15–30% of hospitalized COVID-19 asthma patients. Conclusion: The prevalence of asthma among COVID-19 patients varies internationally. Asthma patients with COVID-19 have high comorbidity. The prevalence of asthma exacerbation at presentation was low. Whilst mortality was similar among COVID-19 patients with and without asthma, this could be confounded by differences in clinical characteristics. Further research could help identify high-risk asthma patients. KEY MESSAGES Asthma prevalence in COVID-19 patients varied internationally (5.2–20.5%).The prevalence of asthma exacerbation at presentation with COVID-19 in diagnosed and hospitalized patients was low.Comorbidities were common in COVID-19 patients with asthma. Supplemental data for this article is available online at https://doi.org/10.1080/02770903.2021.2025392. [ABSTRACT FROM AUTHOR]
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- 2023
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5. Stroke Risk Among Elderly Users of Haloperidol and Typical Antipsychotics Versus Atypical Antipsychotics: A Real-World Study From a US Health Insurance Claims Database.
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Fife, Daniel, Blacketer, Clair, Knight, R. Karl, and Weaver, James
- Abstract
Background: We estimated stroke risk associated with new exposure to haloperidol, or any typical antipsychotic, versus atypical antipsychotic among patients aged ≥65 years regardless of dementia status.Methods: IBM MarketScan Medicare Supplemental Database data (January 1, 2001 to December 31, 2017) were used. Stroke risk for new users of typical antipsychotics (T1 cohort) or haloperidol (T2 cohort) was compared with new users of atypical antipsychotics (C1 cohort) aged ≥65 years. Crude incidence rate (IR) and incidence proportion of stroke were estimated within each cohort and gender subgroup. Three propensity score (PS) matching strategies were employed: Unadjusted (crude), Sentinel PS replication, and a large-scale regularized regression model (adapted PS).Results: Overall, 36,734 (T1), 24,074 (T2), and 226,990 (C1) patients were included. Crude IRs for stroke per 1000 person-years were 17.67 (T1), 23.74 (T2), and 14.17 (C1). In preplanned analyses, PS-matched calibrated hazard ratio (cHR) for stroke T1 versus C1 cohort was 1.08 (95% calibrated confidence interval [cCI] = 0.75, 1.55) with Sentinel PS strategy and 1.31 (95% cCI = 1.07, 1.60) with adapted PS strategy. The cHR for stroke in patients of T2 versus C1 was 1.69 (95% cCI = 1.08, 2.75) with Sentinel PS strategy and 1.45 (95% cCI = 1.17, 1.80) with adapted PS strategy.Conclusion: Stroke risk in elderly new users of haloperidol was elevated compared to new users of atypical antipsychotics and was elevated for typical antipsychotics using the adapted PS strategy. [ABSTRACT FROM AUTHOR]- Published
- 2021
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6. Finding treatment-resistant depression in real-world data: How a data-driven approach compares with expert-based heuristics.
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Cepeda, M. Soledad, Reps, Jenna, Fife, Daniel, Blacketer, Clair, Stang, Paul, and Ryan, Patrick
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THERAPEUTICS ,MENTAL depression ,CHILD psychology ,MENTAL health ,MENTAL health facilities ,ANTIDEPRESSANTS ,PSYCHIATRIC drugs - Abstract
Background: Depression that does not respond to antidepressants is treatment-resistant depression (TRD). TRD definitions include assessments of treatment response, dose and duration, and implementing these definitions in claims databases can be challenging. We built a data-driven TRD definition and evaluated its performance.Methods: We included adults with depression, ≥1 antidepressant, and no diagnosis of mania, dementia, or psychosis. Subjects were stratified into those with and without proxy for TRD. Proxies for TRD were electroconvulsive therapy, deep brain, or vagus nerve stimulation. The index date for subjects with proxy for TRD was the procedure date, and for subjects without, the date of a randomly selected visit. We used three databases. We fit decision tree predictive models. We included number of distinct antidepressants, with and without adequate doses and duration, number of antipsychotics and psychotherapies, and expert-based definitions, 3, 6, and 12 months before index date. To assess performance, we calculated area under the curve (AUC) and transportability.Results: We analyzed 33,336 subjects with no proxy for TRD, and 3,566 with the proxy. Number of antidepressants and antipsychotics were selected in all periods. The best model was at 12 months with an AUC = 0.81. The rule transported well and states that a subject with ≥1 antipsychotic or ≥3 antidepressants in the last year has TRD. Applying this rule, 15.8% of subjects treated for depression had TRD.Conclusion: The definition that best discriminates between subjects with and without TRD considers number of distinct antidepressants (≥3) or antipsychotics (≥1) in the last year. [ABSTRACT FROM AUTHOR]- Published
- 2018
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