Disparities in COVID-19 hospitalizations and mortality among black and Hispanic patients: cross-sectional analysis from the greater Houston metropolitan area.

BACKGROUND: Disparate racial/ethnic burdens of the Coronavirus Disease 2019 (COVID-19) pandemic may be attributable to higher susceptibility to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) or to factors such as differences in hospitalization and care provision. METHODS: In our cross-sectional analysis of lab-confirmed COVID-19 cases from a tertiary, eight-hospital healthcare system across greater Houston, multivariable logistic regression models were fitted to evaluate hospitalization and mortality odds for non-Hispanic Blacks (NHBs) vs. non-Hispanic Whites (NHWs) and Hispanics vs. non-Hispanics. RESULTS: Between March 3rd and July 18th, 2020, 70,496 individuals were tested for SARS-CoV-2; 12,084 (17.1%) tested positive, of whom 3536 (29.3%) were hospitalized. Among positive cases, NHBs and Hispanics were significantly younger than NHWs and Hispanics, respectively (mean age NHBs vs. NHWs: 46.0 vs. 51.7 years; p < 0.001 and Hispanic vs. non-Hispanic: 44.0 vs. 48.7 years; p < 0.001). Despite younger age, NHBs (vs. NHWs) had a higher prevalence of diabetes (25.2% vs. 17.6%; p < 0.001), hypertension (47.7% vs. 43.1%; p < 0.001), and chronic kidney disease (5.0% vs. 3.3%; p = 0.001). Both minority groups resided in lower median income (median income [USD]; NHBs vs. NHWs: 63,489 vs. 75,793; p < 0.001, Hispanic vs. non-Hispanic: 59,104 vs. 68,318; p < 0.001) and higher population density areas (median population density [per square mile]; NHBs vs. NHWs: 3257 vs. 2742; p < 0.001, Hispanic vs. non-Hispanic: 3381 vs. 2884; p < 0.001). In fully adjusted models, NHBs (vs. NHWs) and Hispanics (vs. non-Hispanic) had higher likelihoods of hospitalization, aOR (95% CI): 1.42 (1.24-1.63) and 1.61 (1.46-1.78), respectively. No differences were observed in intensive care unit (ICU) utilization or treatment parameters. Models adjusted for demographics, vital signs, laboratory parameters, hospital complications, and ICU admission vital signs demonstrated non-significantly lower likelihoods of in-hospital mortality among NHBs and Hispanic patients, aOR (95% CI): 0.65 (0.40-1.03) and 0.89 (0.59-1.31), respectively. CONCLUSIONS: Our data did not demonstrate racial and ethnic differences in care provision and hospital outcomes. Higher susceptibility of racial and ethnic minorities to SARS-CoV-2 and subsequent hospitalization may be driven primarily by social determinants.

Poor haemorrhagic stroke outcomes during the COVID-19 pandemic are driven by socioeconomic disparities: analysis of nationally representative data.

Background: Nationally representative studies evaluating the impact of the COVID-19 pandemic on haemorrhagic stroke outcomes are lacking. Methods: In this pooled cross-sectional analysis, we identified adults (≥18 years) with primary intracerebral haemorrhage (ICH) or subarachnoid haemorrhage (SAH) from the National Inpatient Sample (2016-2020). We evaluated differences in rates of in-hospital outcomes between the prepandemic (January 2016-February 2020) and pandemic (March-December 2020) periods using segmented logistic regression models. We used multivariable logistic regression to evaluate differences in mortality between patients admitted from April to December 2020, with and without COVID-19, and those admitted from April to December 2019. Stratified analyses were conducted among patients residing in low-income and high-income zip codes, as well as among patients with extreme loss of function (E-LoF) and those with minor to major loss of function (MM-LoF). Results: Overall, 309 965 patients with ICH (47% female, 56% low income) and 112 210 patients with SAH (62% female, 55% low income) were analysed. Prepandemic, ICH mortality decreased by ~1% per month (adjusted OR, 95% CI: 0.99 (0.99 to 1.00); p<0.001). However, during the pandemic, the overall ICH mortality rate increased, relative to prepandemic, by ~2% per month (1.02 (1.00 to 1.04), p<0.05) and ~4% per month (1.04 (1.01 to 1.07), p<0.001) among low-income patients. There was no significant change in trend among high-income patients with ICH (1.00 (0.97 to 1.03)). Patients with comorbid COVID-19 in 2020 had higher odds of mortality (versus 2019 cohort) only among patients with MM-LoF (ICH, 2.15 (1.12 to 4.16), and SAH, 5.77 (1.57 to 21.17)), but not among patients with E-LoF. Conclusion: Sustained efforts are needed to address socioeconomic disparities in healthcare access, quality and outcomes during public health emergencies.

Real-world effectiveness of COVID-19 vaccines and anti-SARS-CoV-2 monoclonal antibodies against postacute sequelae of SARS-CoV-2: analysis of a COVID-19 observational registry for a diverse US metropolitan population.

OBJECTIVES: We evaluated the effectiveness of COVID-19 vaccines and monoclonal antibodies (mAbs) against postacute sequelae of SARS-CoV-2 infection (PASC). DESIGN AND SETTING: A retrospective cohort study using a COVID-19 specific, electronic medical record-based surveillance and outcomes registry from an eight-hospital tertiary hospital system in the Houston metropolitan area. Analyses were replicated across a global research network database. PARTICIPANTS: We identified adult (≥18) patients with PASC. PASC was defined as experiencing constitutional (palpitations, malaise/fatigue, headache) or systemic (sleep disorder, shortness of breath, mood/anxiety disorders, cough and cognitive impairment) symptoms beyond the 28-day postinfection period. STATISTICAL ANALYSIS: We fit multivariable logistic regression models and report estimated likelihood of PASC associated with vaccination or mAb treatment as adjusted ORs with 95% CIs. RESULTS: Primary analyses included 53 239 subjects (54.9% female), of whom 5929, 11.1% (95% CI 10.9% to 11.4%), experienced PASC. Both vaccinated breakthrough cases (vs unvaccinated) and mAb-treated patients (vs untreated) had lower likelihoods for developing PASC, aOR (95% CI): 0.58 (0.52-0.66), and 0.77 (0.69-0.86), respectively. Vaccination was associated with decreased odds of developing all constitutional and systemic symptoms except for taste and smell changes. For all symptoms, vaccination was associated with lower likelihood of experiencing PASC compared with mAb treatment. Replication analysis found identical frequency of PASC (11.2%, 95% CI 11.1 to 11.3) and similar protective effects against PASC for the COVID-19 vaccine: 0.25 (0.21-0.30) and mAb treatment: 0.62 (0.59-0.66). CONCLUSION: Although both COVID-19 vaccines and mAbs decreased the likelihood of PASC, vaccination remains the most effective tool for the prevention of long-term consequences of COVID-19.

Minimally Invasive Surgery With Thrombolysis for Intracerebral Hemorrhage Evacuation: Bayesian Reanalysis of a Randomized Controlled Trial.

BACKGROUND AND OBJECTIVES: Bayesian analysis of randomized controlled trials (RCTs) can extend the value of trial data beyond interpretations based on conventional p value-based binary cutoffs. We conducted an exploratory post hoc Bayesian reanalysis of the minimally invasive surgery with thrombolysis for intracerebral hemorrhage (ICH) evacuation (MISTIE-3) trial and derived probabilities of potential intervention effect on functional and survival outcomes. METHODS: MISTIE-3 was a multicenter phase 3 RCT designed to evaluate the efficacy and safety of the MISTIE intervention. Five hundred and six adults (18 years or older) with spontaneous, nontraumatic, supratentorial ICH of ≥30 mL were randomized to receive either the MISTIE intervention (n = 255) or standard medical care (n = 251). We provide Bayesian-derived estimates of the effect of the MISTIE intervention on achieving a good 365-day modified Rankin Scale score (mRS score 0-3) as relative risk (RR) and absolute risk difference (ARD), and the probabilities that these treatment effects are greater than prespecified thresholds. We used 2 sets of prior distributions: (1) reference priors, including minimally informative, enthusiastic, and skeptical priors, and (2) data-derived prior distribution, using a hierarchical random effects model. We additionally evaluated the potential effects of the MISTIE intervention on 180-day and 30-day mRS and 365-, 180-, and 30-day mortality using data-derived priors. RESULTS: The Bayesian-derived probability that MISTIE intervention has any beneficial effect (RR >1) on achieving a good 365-day mRS score was 70% using minimally informative prior, 87% with enthusiastic prior, 68% with skeptical prior, and 73% with data-derived prior. However, these probabilities were ≤55% for RR >1.10 and 0% for RR >1.52 across a range of priors. The probabilities of achieving RR >1 for 180- and 30-day mRS scores are 65% and 80%, respectively. Furthermore, the probabilities of achieving RR <1 for 365-, 180-, and 30-day mortality are 93%, 98%, and 99%, respectively. DISCUSSION: Our exploratory analyses indicate that across a range of priors, the Bayesian-derived probability of MISTIE intervention having any beneficial effect on 365-day mRS for patients with ICH is between 68% and 87%. These analyses do not change the frequentist-based interpretation of the trial. However, unlike the frequentist p values, which indirectly evaluate treatment effects and only provide an arbitrary binary cutoff (such as 0.05), the Bayesian framework directly estimates the probabilities of potential treatment effects. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov/ct2/show/NCT01827046. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that minimally invasive surgery (MIS) + recombinant tissue plasminogen activator (rt-PA) does not significantly improve functional outcome in patients with ICH. However, this study lacks the precision to exclude a potential benefit of MIS + rt-PA.

Lifelong cerebrovascular disease burden among CADASIL patients: analysis from a global health research network.

Introduction: Data reporting on patients with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) within the United States population is limited. We sought to evaluate the overt cerebrovascular disease burden among patients with CADASIL. Methods: Harmonized electronic medical records were extracted from the TriNetX global health research network. CADASIL patients were identified using diagnostic codes and those with/without history of documented stroke sub-types (ischemic stroke [IS], intracerebral hemorrhage [ICH], subarachnoid hemorrhage [SAH] and transient ischemic attack [TIA]) were compared. Adjusted odds ratios (OR) and 95% confidence intervals (CI) of stroke incidence and mortality associated with sex were computed. Results: Between September 2018 and April 2020, 914 CADASIL patients were identified (median [IQR] age: 60 [50-69], 61.3% females); of whom 596 (65.2%) had documented cerebrovascular events (i.e., CADASIL-Stroke patients). Among CADASIL-Stroke patients, 89.4% experienced an IS, co-existing with TIAs in 27.7% and hemorrhagic strokes in 6.2%; initial stroke events occurred ≤65 years of age in 71% of patients. CADASIL-Stroke patients (vs. CADASIL-non-Stroke) had higher cardiovascular and neurological (migraines, cognitive impairment, epilepsy/seizures, mood disorders) burden. In age- and comorbidity-adjusted models, males had higher associated risk of stroke onset (OR: 1.37, CI: 1.01-1.86). Mortality risk was higher for males (OR: 2.72, CI: 1.53-4.84). Discussion: Early screening and targeted treatment strategies are warranted to help CADASIL patients with symptom management and risk mitigation.

Extraction of Radiological Characteristics From Free-Text Imaging Reports Using Natural Language Processing Among Patients With Ischemic and Hemorrhagic Stroke: Algorithm Development and Validation.

BACKGROUND: Neuroimaging is the gold-standard diagnostic modality for all patients suspected of stroke. However, the unstructured nature of imaging reports remains a major challenge to extracting useful information from electronic health records systems. Despite the increasing adoption of natural language processing (NLP) for radiology reports, information extraction for many stroke imaging features has not been systematically evaluated. OBJECTIVE: In this study, we propose an NLP pipeline, which adopts the state-of-the-art ClinicalBERT model with domain-specific pretraining and task-oriented fine-tuning to extract 13 stroke features from head computed tomography imaging notes. METHODS: We used the model to generate structured data sets with information on the presence or absence of common stroke features for 24,924 patients with strokes. We compared the survival characteristics of patients with and without features of severe stroke (eg, midline shift, perihematomal edema, or mass effect) using the Kaplan-Meier curve and log-rank tests. RESULTS: Pretrained on 82,073 head computed tomography notes with 13.7 million words and fine-tuned on 200 annotated notes, our HeadCT_BERT model achieved an average area under receiver operating characteristic curve of 0.9831, F1-score of 0.8683, and accuracy of 97%. Among patients with acute ischemic stroke, admissions with any severe stroke feature in initial imaging notes were associated with a lower probability of survival (P<.001). CONCLUSIONS: Our proposed NLP pipeline achieved high performance and has the potential to improve medical research and patient safety.

Stroke severity mediates the effect of socioeconomic disadvantage on poor outcomes among patients with intracerebral hemorrhage.

Background: Socioeconomic deprivation drives poor functional outcomes after intracerebral hemorrhage (ICH). Stroke severity and background cerebral small vessel disease (CSVD) burden have each been linked to socioeconomic status and independently contribute to worse outcomes after ICH, providing distinct, plausible pathways for the effects of deprivation. We investigate whether admission stroke severity or cerebral small vessel disease (CSVD) mediates the effect of socioeconomic deprivation on 90-day functional outcomes. Methods: Electronic medical record data, including demographics, treatments, comorbidities, and physiological data, were analyzed. CSVD burden was graded from 0 to 4, with severe CSVD categorized as ≥3. High deprivation was assessed for patients in the top 30% of state-level area deprivation index scores. Severe disability or death was defined as a 90-day modified Rankin Scale score of 4-6. Stroke severity (NIH stroke scale (NIHSS)) was classified as: none (0), minor (1-4), moderate (5-15), moderate-severe (16-20), and severe (21+). Univariate and multivariate associations with severe disability or death were determined, with mediation evaluated through structural equation modelling. Results: A total of 677 patients were included (46.8% female; 43.9% White, 27.0% Black, 20.7% Hispanic, 6.1% Asian, 2.4% Other). In univariable modelling, high deprivation (odds ratio: 1.54; 95% confidence interval: [1.06-2.23]; p = 0.024), severe CSVD (2.14 [1.42-3.21]; p < 0.001), moderate (8.03 [2.76-17.15]; p < 0.001), moderate-severe (32.79 [11.52-93.29]; p < 0.001), and severe stroke (104.19 [37.66-288.12]; p < 0.001) were associated with severe disability or death. In multivariable modelling, severe CSVD (3.42 [1.75-6.69]; p < 0.001) and moderate (5.84 [2.27-15.01], p < 0.001), moderate-severe (27.59 [7.34-103.69], p < 0.001), and severe stroke (36.41 [9.90-133.85]; p < 0.001) independently increased odds of severe disability or death; high deprivation did not. Stroke severity mediated 94.1% of deprivation's effect on severe disability or death (p = 0.005), while CSVD accounted for 4.9% (p = 0.524). Conclusion: CSVD contributed to poor functional outcome independent of socioeconomic deprivation, while stroke severity mediated the effects of deprivation. Improving awareness and trust among disadvantaged communities may reduce admission stroke severity and improve outcomes.

A Neuro-Informatics Pipeline for Cerebrovascular Disease: Research Registry Development.

BACKGROUND: Although stroke is well recognized as a critical disease, treatment options are often limited. Inpatient stroke encounters carry critical information regarding the mechanisms of stroke and patient outcomes; however, these data are typically formatted to support administrative functions instead of research. To support improvements in the care of patients with stroke, a substantive research data platform is needed. OBJECTIVE: To advance a stroke-oriented learning health care system, we sought to establish a comprehensive research repository of stroke data using the Houston Methodist electronic health record (EHR) system. METHODS: Dedicated processes were developed to import EHR data of patients with primary acute ischemic stroke, intracerebral hemorrhage (ICH), transient ischemic attack, and subarachnoid hemorrhage under a review board-approved protocol. Relevant patients were identified from discharge diagnosis codes and assigned registry patient identification numbers. For identified patients, extract, transform, and load processes imported EHR data of primary cerebrovascular disease admissions and available data from any previous or subsequent admissions. Data were loaded into patient-focused SQL objects to enable cross-sectional and longitudinal analyses. Primary data domains (admission details, comorbidities, laboratory data, medications, imaging data, and discharge characteristics) were loaded into separate relational tables unified by patient and encounter identification numbers. Computed tomography, magnetic resonance, and angiography images were retrieved. Imaging data from patients with ICH were assessed for hemorrhage characteristics and cerebral small vessel disease markers. Patient information needed to interface with other local and national databases was retained. Prospective patient outreach was established, with patients contacted via telephone to assess functional outcomes 30, 90, 180, and 365 days after discharge. Dashboards were constructed to provide investigators with data summaries to support access. RESULTS: The Registry of Neurological Endpoint Assessments among Patients with Ischemic and Hemorrhagic Stroke (REINAH) database was constructed as a series of relational category-specific SQL objects. Encounter summaries and dashboards were constructed to draw from these objects, providing visual data summaries for investigators seeking to build studies based on REINAH data. As of June 2022, the database contains 18,061 total patients, including 1809 (10.02%) with ICH, 13,444 (74.43%) with acute ischemic stroke, 1221 (6.76%) with subarachnoid hemorrhage, and 3165 (17.52%) with transient ischemic attack. Depending on the cohort, imaging data from computed tomography are available for 85.83% (1048/1221) to 98.4% (1780/1809) of patients, with magnetic resonance imaging available for 27.85% (340/1221) to 85.54% (11,500/13,444) of patients. Outcome assessment has successfully contacted 56.1% (240/428) of patients after ICH, with 71.3% (171/240) of responders providing consent for assessment. Responders reported a median modified Rankin Scale score of 3 at 90 days after discharge. CONCLUSIONS: A highly curated and clinically focused research platform for stroke data will establish a foundation for future research that may fundamentally improve poststroke patient care and outcomes.

Sex differences in post-stroke cognitive decline: A population-based longitudinal study of nationally representative data.

BACKGROUND: Sex differences in post-stroke cognitive decline have not been systematically evaluated in a nationally representative cohort. We use a quasi-experimental design to investigate sex differences in rate of post-stroke cognitive decline. METHODS: Utilizing the event study design, we use the Health and Retirement Study (HRS) data (1996-2016) to evaluate the differences (percentage points [95% Confidence interval]) in the rate of change in cognitive function, measured using the modified version of the Telephone Interview for Cognitive Status (TICS-m) score, before and after incident stroke, and among patients with and without incident stroke. We estimated this event study model for the overall study population and separately fit the same model for male and female participants. RESULTS: Of 25,872 HRS participants included in our study, 14,459 (55.9%) were females with an overall mean age (SD) of 61.2 (9.3) years. Overall, 2,911 (11.3%) participants reported experiencing incident stroke. Participants with incident stroke (vs. no stroke) had lower baseline TICS-m score (15.6 vs. 16.1). Among participants with incident stroke, the mean pre-stroke TICS-m score was higher than the mean post-stroke TICS-m score (14.9 vs. 12.7). Event study revealed a significant short-term acceleration of cognitive decline for the overall population (4.2 [1.7-6.6] percentage points, p value = 0.001) and among female participants (5.0 [1.7-8.3] percentage points, p value = 0.003). We, however, found no evidence of long-term acceleration of cognitive decline after stroke. Moreover, among males, incident stroke was not associated with significant changes in rate of post-stroke cognitive decline. CONCLUSION: Females, in contrast to males, experience post-stroke cognitive deficits, particularly during early post-stroke period. Identifying the sex-specific stroke characteristics contributing to differences in post stroke cognitive decline may inform future strategies for reducing the burden of post-stroke cognitive impairment and dementia.

Impact of mRNA vaccines in curtailing SARS-CoV-2 infection and disability leave utilisation among healthcare workers during the COVID-19 pandemic: cross-sectional analysis from a tertiary healthcare system in the Greater Houston metropolitan area.

OBJECTIVES: We provide an account of real-world effectiveness of COVID-19 vaccines among healthcare workers (HCWs) at a tertiary healthcare system and report trends in SARS-CoV-2 infections and subsequent utilisation of COVID-19-specific short-term disability leave (STDL). DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: Summary data on 27 291 employees at a tertiary healthcare system in the Greater Houston metropolitan area between 15 December 2020 and 5 June 2021. The initial 12-week vaccination programme period (15 December 2020 to 6 March 2021) was defined as a rapid roll-out phase. MAIN OUTCOMES AND MEASURES: At the pandemic onset, HCW testing and surveillance was conducted where SARS-CoV-2-positive HCWs were offered STDL. Deidentified summary data of SARS-CoV-2 infections and STDL utilisation among HCWs were analysed. Prevaccination and postvaccination trends in SARS-CoV-2 positivity and STDL utilisation rates were evaluated. RESULTS: Updated for 5 June 2021, 98.2% (n=26 791) of employees received a full or partial dose of one of the approved mRNA COVID-19 vaccines. The vaccination rate during the rapid roll-out phase was approximately 3700 doses/7 days. The overall mean weekly SARS-CoV-2 positivity rates among HCWs were significantly lower following vaccine roll-out (2.4%), compared with prevaccination period (11.8%, p<0.001). An accompanying 69.8% decline in STDL utilisation was also observed (315 to 95 weekly leaves). During the rapid roll-out phase, SARS-CoV-2 positivity rate among Houston Methodist HCWs declined by 84.3% (8.9% to 1.4% positivity rate), compared with a 54.7% (12.8% to 5.8% positivity rate) decline in the Houston metropolitan area. CONCLUSION: Despite limited generalisability of regional hospital-based studies-where factors such as the emergence of viral variants and population-level vaccine penetrance may differ-accounts of robust HCW vaccination programmes provide important guidance for sustaining a critical resource to provide safe and effective care for patients with and without COVID-19 across healthcare systems.

SARS-CoV-2 Susceptibility and COVID-19 Mortality Among Older Adults With Cognitive Impairment: Cross-Sectional Analysis From Hospital Records in a Diverse US Metropolitan Area.

Introduction: Persistent knowledge gaps exist as to the extent that preexisting cognitive impairment is a risk factor for susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and mortality from the coronavirus disease 2019 (COVID-19). Methods: We conducted a cross-sectional analysis of adults tested for SARS-CoV-2 at a tertiary healthcare system. Cognitive impairment was identified utilizing diagnosis codes (mild cognitive impairment, Alzheimer's disease, vascular, and other dementias) or cognitive impairment-specific medication use. Propensity score (PS) matched analyses were utilized to report odds ratios (OR) and 95% confidence intervals (CI) for association of cognitive impairment with SARS-CoV-2 susceptibility and COVID-19 mortality. Results: Between March-3rd and December-11th, 2020, 179,979 adults were tested, of whom 21,607 (12.0%) tested positive. We identified 6,364 individuals with preexisting cognitive impairment (mean age: 78.5 years, 56.8% females), among whom 843 (13.2%) tested positive and 139 (19.5%) of those hospitalized died. In the pre-PS matched cohort, cognitive impairment was significantly associated with increased SARS-CoV-2 susceptibility (OR, CI: 1.12, 1.04-1.21) and COVID-19 mortality (OR, CI: 2.54, 2.07-3.12). One-to-one matches were identified for 6,192 of 6,364 (97.3%) individuals with prior cognitive impairment and 687 of 712 (96.5%) hospitalized patients with prior cognitive impairment. In the fully balanced post-matched cohort, preexisting cognitive impairment was significantly associated with higher likelihood of SARS-CoV-2 infection (OR, CI: 1.51, 1.35-1.70); however, cognitive impairment did not confer higher risk of COVID-19 mortality (OR, CI: 0.96, 0.73-1.25). Discussion: To mitigate the effects of healthcare catastrophes such as the COVID-19 pandemic, strategies for targeted prevention and risk-stratified comorbidity management are warranted among the vulnerable sub-population living with cognitive impairment.

Decade-Long Nationwide Trends and Disparities in Use of Comfort Care Interventions for Patients With Ischemic Stroke.

Background Stroke remains one of the leading causes of disability and death in the United States. We characterized 10-year nationwide trends in use of comfort care interventions (CCIs) among patients with ischemic stroke, particularly pertaining to acute thrombolytic therapy with intravenous tissue-type plasminogen activator and endovascular thrombectomy, and describe in-hospital outcomes and costs. Methods and Results We analyzed the National Inpatient Sample from 2006 to 2015 and identified adult patients with ischemic stroke with or without thrombolytic therapy and CCIs using validated International Classification of Diseases, Ninth Revision (ICD-9) codes. We report adjusted odds ratios (ORs) and 95% CI of CCI usage across five 2-year periods. Of 4 249 201 ischemic stroke encounters, 3.8% had CCI use. CCI use increased over time (adjusted OR, 4.80; 95% CI, 4.15-5.55) regardless of acute treatment type. Advanced age, female sex, White race, non-Medicare insurance, higher income, disease severity, comorbidity burden, and discharge from non-northeastern teaching hospitals were independently associated with receiving CCIs. In the fully adjusted model, thrombolytic therapy and endovascular thrombectomy, respectively, conferred a 6% and 10% greater likelihood of receiving CCIs. Among CCI users, there was a significant decline in in-hospital mortality compared with all other dispositions over time (adjusted OR, 0.46; 95% CI, 0.38-0.56). Despite longer length of stay, CCI hospitalizations incurred 16% lower adjusted costs. Conclusions CCI use among patients with ischemic stroke has increased regardless of acute treatment type. Nonetheless, considerable disparities persist. Closing the disparities gap and optimizing access, outcomes, and costs for CCIs among patients with stroke are important avenues for further research.

Sex differences in susceptibility, severity, and outcomes of coronavirus disease 2019: Cross-sectional analysis from a diverse US metropolitan area.

INTRODUCTION: Sex is increasingly recognized as an important factor in the epidemiology and outcome of many diseases. This also appears to hold for coronavirus disease 2019 (COVID-19). Evidence from China and Europe has suggested that mortality from COVID-19 infection is higher in men than women, but evidence from US populations is lacking. Utilizing data from a large healthcare provider, we determined if males, as compared to females have a higher likelihood of SARS-CoV-2 susceptibility, and if among the hospitalized COVID-19 patients, male sex is independently associated with COVID-19 severity and poor in-hospital outcomes. METHODS AND FINDINGS: Using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines, we conducted a cross-sectional analysis of data from a COVID-19 Surveillance and Outcomes Registry (CURATOR). Data were extracted from Electronic Medical Records (EMR). A total of 96,473 individuals tested for SARS-CoV-2 RNA in nasopharyngeal swab specimens via Polymerized Chain Reaction (PCR) tests were included. For hospital-based analyses, all patients admitted during the same time-period were included. Of the 96,473 patients tested, 14,992 (15.6%) tested positive, of whom 4,785 (31.9%) were hospitalized and 452 (9.5%) died. Among all patients tested, men were significantly older. The overall SARS-CoV-2 positivity among all tested individuals was 15.5%, and was higher in males as compared to females 17.0% vs. 14.6% [OR 1.20]. This sex difference held after adjusting for age, race, ethnicity, marital status, insurance type, median income, BMI, smoking and 17 comorbidities included in Charlson Comorbidity Index (CCI) [aOR 1.39]. A higher proportion of males (vs. females) experienced pulmonary (ARDS, hypoxic respiratory failure) and extra-pulmonary (acute renal injury) complications during their hospital course. After adjustment, length of stay (LOS), need for mechanical ventilation, and in-hospital mortality were significantly higher in males as compared to females. CONCLUSIONS: In this analysis of a large US cohort, males were more likely to test positive for COVID-19. In hospitalized patients, males were more likely to have complications, require ICU admission and mechanical ventilation, and had higher mortality than females, independent of age. Sex disparities in COVID-19 vulnerability are present, and emphasize the importance of examining sex-disaggregated data to improve our understanding of the biological processes involved to potentially tailor treatment and risk stratify patients.

Rapid Response to Drive COVID-19 Research in a Learning Health Care System: Rationale and Design of the Houston Methodist COVID-19 Surveillance and Outcomes Registry (CURATOR).

BACKGROUND: The COVID-19 pandemic has exacerbated the challenges of meaningful health care digitization. The need for rapid yet validated decision-making requires robust data infrastructure. Organizations with a focus on learning health care (LHC) systems tend to adapt better to rapidly evolving data needs. Few studies have demonstrated a successful implementation of data digitization principles in an LHC context across health care systems during the COVID-19 pandemic. OBJECTIVE: We share our experience and provide a framework for assembling and organizing multidisciplinary resources, structuring and regulating research needs, and developing a single source of truth (SSoT) for COVID-19 research by applying fundamental principles of health care digitization, in the context of LHC systems across a complex health care organization. METHODS: Houston Methodist (HM) comprises eight tertiary care hospitals and an expansive primary care network across Greater Houston, Texas. During the early phase of the pandemic, institutional leadership envisioned the need to streamline COVID-19 research and established the retrospective research task force (RRTF). We describe an account of the structure, functioning, and productivity of the RRTF. We further elucidate the technical and structural details of a comprehensive data repository-the HM COVID-19 Surveillance and Outcomes Registry (CURATOR). We particularly highlight how CURATOR conforms to standard health care digitization principles in the LHC context. RESULTS: The HM COVID-19 RRTF comprises expertise in epidemiology, health systems, clinical domains, data sciences, information technology, and research regulation. The RRTF initially convened in March 2020 to prioritize and streamline COVID-19 observational research; to date, it has reviewed over 60 protocols and made recommendations to the institutional review board (IRB). The RRTF also established the charter for CURATOR, which in itself was IRB-approved in April 2020. CURATOR is a relational structured query language database that is directly populated with data from electronic health records, via largely automated extract, transform, and load procedures. The CURATOR design enables longitudinal tracking of COVID-19 cases and controls before and after COVID-19 testing. CURATOR has been set up following the SSoT principle and is harmonized across other COVID-19 data sources. CURATOR eliminates data silos by leveraging unique and disparate big data sources for COVID-19 research and provides a platform to capitalize on institutional investment in cloud computing. It currently hosts deeply phenotyped sociodemographic, clinical, and outcomes data of approximately 200,000 individuals tested for COVID-19. It supports more than 30 IRB-approved protocols across several clinical domains and has generated numerous publications from its core and associated data sources. CONCLUSIONS: A data-driven decision-making strategy is paramount to the success of health care organizations. Investment in cross-disciplinary expertise, health care technology, and leadership commitment are key ingredients to foster an LHC system. Such systems can mitigate the effects of ongoing and future health care catastrophes by providing timely and validated decision support.

Path toward Precision Oncology: Review of Targeted Therapy Studies and Tools to Aid in Defining "Actionability" of a Molecular Lesion and Patient Management Support.

Precision medicine trials and targeted therapies have shifted to the forefront of oncology. Although targeted therapies have shown initial promise, implementation across the broad landscape of oncology has many challenges. These limitations include an incomplete understanding of the functional significance of variant alleles as well as the need for clinical research and practice models that are more patient-centered and account for the complexity of individual patient tumors. Furthermore, successful implementation of targeted therapies will also be predicated on efforts to standardize the framework for patient management support. Here, we review current implementations of targeted therapies in precision oncology and discuss how "actionability" is defined for molecular targets in cancer therapeutics. We also comment on the growing need for bioinformatics tools and data platforms to complement advances in precision oncology. Finally, we discuss current frameworks for integrating precision oncology into patient management and propose an integrated model that combines features of molecular tumor boards and decision support systems. Mol Cancer Ther; 16(12); 2645-55. ©2017 AACRSee related article by Pilié et al., p. 2641.