Parul Agarwal

Introduction: Black and Hispanic people are underrepresented in parkinsonism research leading to critical knowledge gaps and reduced quality of care. Methods: We developed a novel, comprehensive clinical registry in which research eligibility, interest, and participation are actively tracked for all patients at our site to reduce selection bias and streamline recruitment. We also implemented targeted approaches to reduce psychosocial and sociocultural barriers to research participation of Black and Hispanic people. We then performed a retrospective chart review to test the hypothesis that these combined strategies would be associated with racially/ethnically unbiased research recruitment. All follow-up patients with degenerative parkinsonism seen at the Bronx Veterans Affairs Medical Center over a 19-month period were included in the analysis. Primary outcome measures were the approach and acceptance rates for CANPARK, a single-center prospective observational cohort study of American military veterans with parkinsonism. Results: During the study window, 197 parkinsonism patients were seen, 192 were eligible for CANPARK [ages 53-91; 96.4% male; 29.7% Hoehn and Yahr ≥4; 25.0% atypical parkinsonism], 167 (87.0% of eligible patients) were invited to participate (similar in all racial/ethnic groups), and 128 of 159 patients who made a decision whether to participate (80.5%) agreed to enroll. Acceptance rates were comparable in Black (79.4%; p = 0.92) or Hispanic (87.5%; p = 0.43) versus White (80.2%) patients. Conclusions: Using a novel, real-time clinical registry and targeted approaches, we achieved unbiased recruitment and high participation of Black and Hispanic patients in parkinsonism research. Future studies are needed to evaluate these approaches in other clinical settings.

[This corrects the article DOI: 10.1212/CPJ.0000000000200467.].

Status epilepticus (SE) is a common, life‐threatening neurologic emergency. Understanding population‐level outcomes after SE requires a validated case definition, yet International Classification of Diseases, 10th Revision, Clinical Modification (ICD‐10‐CM) codes of SE have not been well‐validated in US populations since adoption in 2015. We aimed to determine whether the ICD‐10‐CM code‐based definitions accurately identify SE in the in‐hospital setting. The population included all ages (excluding neonates) admitted to a Mount Sinai Health System (MSHS) intensive care unit (ICU) in 2019. A data collection form was developed, tested, and used by trained reviewers. Every admission in a random month (November) was reviewed to determine whether all SE cases had at least one code for epilepsy, seizure, or convulsion followed by all charts with an ICD‐10‐CM diagnosis code for seizure/epilepsy/convulsion in 2019. Chart review data were linked to MSHS electronic medical record data. Sensitivity (Sn), specificity (Sp), negative predictive value (NPV), and positive predictive value (PPV) with 95% confidence intervals (CIs) and Youden index were calculated for ICD‐10 coding of SE (G40.xx1 or G40.xx3, as G41 was not adopted in the United States). MSHS had 13 694 ICU admissions in 2019, for which 1851 charts were reviewed and of which 173 were admissions with definite SE. The ICD‐10‐CM case definition (G40.xx1) has an Sn of 68.7% (95% CI = 61.5–75.8) and Sp of 92.6% (95% CI = 91.4–93.8). PPV was 47.4% (95% CI = 41–53.8), and NPV was 96.8% (95% CI = 95.9–97.6). Youden index was 61.3%. ICD‐10‐CM coding for SE has high specificity but limited sensitivity. These findings align with SE prevalence studies showing a decrease in prevalence with the change from ICD‐9‐CM to ICD‐10‐CM, which may be related to the United States' unique adoption of ICD‐10‐CM, which did not include the standalone SE code (G41). Our findings emphasize the importance of revision and improvement of coding practices to best represent the prevalence of SE, and of consideration when planning for the next iteration of ICD coding.

There is longstanding evidence that the presence of psychosis in neurocognitive disorders (NCDs) is associated with faster cognitive and functional decline. The goal of this study was to examine how clinician-diagnosed psychosis differs among ethnoracial groups with NCDs (including early onset) and to explore whether these differences exist even for those without advanced dementia. This is an IRB-approved retrospective analysis. Data are from the National Alzheimer's Coordinating Center Uniform Dataset from 42 Alzheimer's Disease Research Centers. Participants aged 40–95 years as of June 2023 with mild cognitive impairment (MCI) or dementia on baseline evaluation were included. Psychosis was defined as clinician-diagnosed visual or auditory hallucinations or delusions manifesting at the time of baseline evaluation. Ethnoracial groups were self-reported. Associations between ethnoracial groups and psychosis in NCDs were estimated using adjusted multivariable logistic regression with dichotomous measures of outcomes. Covariates included age, sex, years of education, severity of cognitive impairment (Clinical Dementia Rating scale), and presence or absence of any self-reported preexisting psychiatric illness. An analysis by age younger than 65 years was also conducted. Exploratory multivariable logistic regression analyses were performed for participants with milder stages of dementia (Clinical Dementia Rating 0.5 or 1) and for the subset of participants diagnosed with MCI. A total of 22,854 participants were included. The mean age was 73 + 9.7 years, and 50% were women. A total of 8,352 (37%) had MCI and 14,502 (63%) had dementia. In adjusted analysis, American Indian/Alaska Native (AI/AN) (OR 2.70, 1.75–4.17, p < 0.0001), Black-Latino (OR 2.33, 1.25–4.35, p = 0.0076), Other-Latino (OR 1.82, 1.42–2.33, p < 0.0001), Black, non-Latino (NL) (OR 1.66,1.47–1.87, p < 0.0001), and White-Latino (OR 1.42, 1.21–1.67, p < 0.0001) participants had greater odds of any psychotic symptom than White-NL participants. For age groups 40 to younger than 65 years, only Black-NL participants (OR 1.56, 1.13–2.14, p = 0.0064) were more likely to be diagnosed with any psychotic symptoms. For milder stages of dementia, Black-Latino (OR 3.44, 1.58–7.48, p = 0.0018), AI/AN (OR 2.73, 1.66–4.48, p < 0.0001), Other-Latino (OR 2.38, 1.72–3.30, p < 0.0001), Black-NL (OR 2.08,1.77–2.45, p < 0.0001), and White-Latino (OR 1.55, 1.23–1.95, p = 0.0002) participants had greater odds of psychosis in NCDs when compared with White-NL participants. For MCI alone, there were no significant differences. Black-NL, Latino, and AI/AN individuals were more likely to be diagnosed with psychosis in NCDs when compared with White-NL participants. More research is needed to explore sociocultural, psychosocial, and neuropathologic factors involved.

Older adults are expected to have higher readmission rates after seizure-related hospitalization. We sought to define the 30-day readmission rate for older adults after seizure hospitalization and to examine whether occurrence, timing, or specialization of follow-up with primary or neuro-related care is associated with lower readmission risk. This is a retrospective cohort study using 2016-2019 Medicare claims data, including adults aged older than 65 years hospitalized with a primary diagnosis of seizure/epilepsy. The primary outcome was readmission within 30 days. Exposure of interest was presence or absence of follow-up and specialty of the follow-up provider. Beneficiaries were followed from 90 days before admission to 30 days after discharge. We defined variables a priori based on literature/clinical judgment and used a least absolute shrinkage and selection operator (LASSO) method to determine factors that were contributing to the data's variance for inclusion in the final model. Of 80,620 beneficiaries with admissions for seizure/epilepsy, 17.72% were readmitted within 30 days. Overall, 20.6% saw only primary care, 2.5% neurology only, 0.3% neurosurgery only, and 0.1% epilepsy only, and 5.4% had a combination of visits. Readmission rates differed by follow-up visit status: 22% readmission rate for those with no follow-up and only 6% with any health care visit. Among those with a visit, the readmission rates by specialty were as follows: 8% for primary care alone, 5% for neurology alone, 16% for neurosurgery alone, 1% for epileptology alone, and 2% for those who had seen a combination of these specialties. In our LASSO-selected multivariable model, outpatient follow-up was associated with lower odds of readmission: early (days 1-15) primary care visit (adjusted odds ratio [aOR] 0.49; 95% CI 0.45-0.52, p < 0.001); early neurology visit (aOR 0.39; 95% CI 0.33-0.46, p < 0.001); and later (days 16-30) neurosurgery visit (aOR 0.42; 95% CI 0.27-0.67, p < 0.001), later neurology visit (aOR 0.16; 95% CI 0.13-0.21, p < 0.001), or later primary care visit (aOR 0.16; 95% CI 0.14-0.17, <0.001), all associated with reduced odds of readmission. We found high rates of readmission in older adults. Outpatient follow-up was associated with reduced odds of readmission. These findings reinforce the importance of discharge planning and suggest that ensuring outpatient follow-up with either primary care or neurology may be an easy intervention to reduce readmissions.

Objective: Electronic health records (EHRs) are increasingly used to conduct research and evaluate epilepsy quality of care. We examined the accuracy of International Classification of Diseases, 9th and 10th Revision, Clinical Modification (ICD‐9‐CM, ICD‐10‐CM)‐ and antiseizure medicine (ASM)‐based algorithms for adult epilepsy.Methods: Data from a diverse New York multicenter EHR were queried to identify encounters between January 1, 2012 and September 20, 2018 coded with an epilepsy/seizure ICD‐CM code or an ASM. Eight hundred adults were randomly selected (350 with epilepsy‐related codes, 150 with an ASM, and 300 with drug‐resistant epilepsy codes). With chart review defined as the reference standard, sensitivity (Sn), specificity (Sp), negative predictive value (NPV), positive predictive value (PPV), and Youden index (YI) were calculated to evaluate various ICD‐9‐CM‐, ICD‐10‐CM‐, ± ASM‐based algorithms' accuracy in predicting epilepsy.Results: Ninety‐four algorithms were tested. A total of 435 (54.4%) patients had definite epilepsy. Estimates ranged as follows: YI = .18–.68, Sn = .59–.95, Sp = .52–.97, PPV = .67–.92, and NPV = .51–.93. The best algorithms were as follows. Highest YI for ICD‐9‐CM was single encounter with 345 (except 345.2 or 345.3) or 345.2, 345.3, or 780.3 with an ASM (Sn = .95, Sp = .73, PPV = .81, NPV = .92, YI = .68). Highest Y1 for ICD‐10‐CM was one encounter with G40 in primary diagnostic position or ≥2 encounters with G40 in any diagnostic position (Sn = .82, Sp = .85, PPV = .87, NPV = .80, YI = .67). Highest sensitivity was any encounter with ICD‐9‐CM 345 or 780.39 or ICD‐10‐CM G40, G41, or R56.9 (Sn = .96, Sp = .57, PPV = .73, NPV = .93, YI = .53). Highest specificity was ≥1 hospitalization with ICD‐9‐CM 345.x (except 345.2 and 345.3) or ICD‐10‐CM G40.x (Sn = .21, Sp = .97, PPV = .89, NPV = .51, YI = .18).Significance: We identified ICD‐9/10‐CM‐based case definitions (with and without ASM) that were sensitive and specific for epilepsy. Ultimately, extensive algorithms are provided to help inform case definition selection according to future study aims.

Objective: Epilepsy is primarily treated with antiseizure medications (ASMs). The recommendations for first ASM in newly diagnosed epilepsy are inconsistently followed, and we sought to examine whether nonrecommended first ASM was associated with acute care utilization.Methods: We conducted a retrospective cohort study of adults (≥18 years old) with newly diagnosed epilepsy (identified using validated epilepsy/convulsion International Classification of Diseases, Clinical Modification codes) in 2015–2019, sampled from Marketscan's Commercial and Medicare Databases. Exposure of interest was receipt of a non‐guideline‐recommended ASM, and the primary outcome was acute care utilization (an emergency department visit or hospitalization after the first ASM claim). Descriptive statistics characterized covariates, and multivariable negative binominal regression models were built adjusting for age, sex, Elixhauser Comorbidity Index, comorbid neurologic disease (e.g., stroke), and ASM polypharmacy.Results: Approximately 14 681 people with new epilepsy were prescribed an ASM within 1 year. The three most prescribed medications were levetiracetam (54%, n = 7912), gabapentin (10%, n = 1462), and topiramate (7%, n = 1022). Approximately 4% (n = 648) were prescribed an ASM that should be avoided, and ~74% of people with new epilepsy had an acute care visit during the follow‐up period. Mean number of acute care visits during follow‐up was 3.34 for “recommended” ASMs and 4.42 for ASMs that “should be avoided.” Prescription of a recommended/neutral ASM as compared to an ASM that should be avoided was associated with reduced likelihood of acute care utilization (incidence rate ratio [IRR] = .85, 95% confidence interval [CI] = .77–.94). The recommended/neutral category of ASMs was not statistically significantly associated with seizure‐ or epilepsy‐specific acute care utilization (IRR = .93, 95% CI = .79–1.09).Significance: Adults with new epilepsy are frequent users of acute care. There remain a proportion of persons with epilepsy prescribed ASMs that guidelines suggest avoiding, and these ASMs are associated with increased likelihood of emergency department visit or hospitalization. These findings reinforce the importance of optimizing the choice of first ASM in epilepsy.

Objective To describe the frequency of neuropsychiatric complications among hospitalized patients with coronavirus disease 2019 (COVID-19) and their association with pre-existing comorbidities and clinical outcomes. Methods We retrospectively identified all patients hospitalized with COVID-19 within a large multicenter New York City health system between March 15, 2020 and May 17, 2021 and randomly selected a representative cohort for detailed chart review. Clinical data, including the occurrence of neuropsychiatric complications (categorized as either altered mental status [AMS] or other neuropsychiatric complications) and in-hospital mortality, were extracted using an electronic medical record database and individual chart review. Associations between neuropsychiatric complications, comorbidities, laboratory findings, and in-hospital mortality were assessed using multivariate logistic regression. Results Our study cohort consisted of 974 patients, the majority were admitted during the first wave of the pandemic. Patients were treated with anticoagulation (88.4%), glucocorticoids (24.8%), and remdesivir (10.5%); 18.6% experienced severe COVID-19 pneumonia (evidenced by ventilator requirement). Neuropsychiatric complications occurred in 58.8% of patients; 39.8% experienced AMS; and 19.0% experienced at least one other complication (seizures in 1.4%, ischemic stroke in 1.6%, hemorrhagic stroke in 1.0%) or symptom (headache in 11.4%, anxiety in 6.8%, ataxia in 6.3%). Higher odds of mortality, which occurred in 22.0%, were associated with AMS, ventilator support, increasing age, and higher serum inflammatory marker levels. Anticoagulant therapy was associated with lower odds of mortality and AMS. Conclusion Neuropsychiatric complications of COVID-19, especially AMS, were common, varied, and associated with in-hospital mortality in a diverse multicenter cohort at an epicenter of the COVID-19 pandemic.