Patients with unmet social needs are at higher risks of developing severe long COVID-19 symptoms and neuropsychiatric sequela.

This study investigated long COVID of patients in the Montefiore Health System COVID-19 (CORE) Clinics in the Bronx with an emphasis on identifying health related social needs (HRSNs). We analyzed a cohort of 643 CORE patients (6/26/2020-2/24/2023) and 52,089 non-CORE COVID-19 patients. Outcomes included symptoms, physical, emotional, and cognitive function test scores obtained at least three months post-infection. Socioeconomic variables included median incomes, insurance status, and HRSNs. The CORE cohort was older age (53.38 ± 14.50 vs. 45.91 ± 23.79 years old, p < 0.001), more female (72.47% vs. 56.86%, p < 0.001), had higher prevalence of hypertension (45.88% vs. 23.28%, p < 0.001), diabetes (22.86% vs. 13.83%, p < 0.001), COPD (7.15% vs. 2.28%, p < 0.001), asthma (25.51% vs. 12.66%, p < 0.001), lower incomes (53.81% vs. 43.67%, 1st quintile, p < 0.001), and more unmet social needs (29.81% vs. 18.49%, p < 0.001) compared to non-CORE COVID-19 survivors. CORE patients reported a wide range of severe long-COVID symptoms. CORE patients with unmet HRSNs experienced more severe symptoms, worse ESAS-r scores (tiredness, wellbeing, shortness of breath, and pain), PHQ-9 scores (12.5 (6, 17.75) vs. 7 (2, 12), p < 0.001), and GAD-7 scores (8.5 (3, 15) vs. 4 (0, 9), p < 0.001) compared to CORE patients without. Patients with unmet HRSNs experienced worse long-COVID outcomes compared to those without.

Long-term outcomes of hospitalized patients with SARS-CoV-2/COVID-19 with and without neurological involvement: 3-year follow-up assessment.

BACKGROUND: Acute neurological manifestation is a common complication of acute Coronavirus Disease 2019 (COVID-19) disease. This retrospective cohort study investigated the 3-year outcomes of patients with and without significant neurological manifestations during initial COVID-19 hospitalization. METHODS AND FINDINGS: Patients hospitalized for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection between 03/01/2020 and 4/16/2020 in the Montefiore Health System in the Bronx, an epicenter of the early pandemic, were included. Follow-up data was captured up to 01/23/2023 (3 years post-COVID-19). This cohort consisted of 414 patients with COVID-19 with significant neurological manifestations and 1,199 propensity-matched patients (for age and COVID-19 severity score) with COVID-19 without neurological manifestations. Neurological involvement during the acute phase included acute stroke, new or recrudescent seizures, anatomic brain lesions, presence of altered mentation with evidence for impaired cognition or arousal, and neuro-COVID-19 complex (headache, anosmia, ageusia, chemesthesis, vertigo, presyncope, paresthesias, cranial nerve abnormalities, ataxia, dysautonomia, and skeletal muscle injury with normal orientation and arousal signs). There were no significant group differences in female sex composition (44.93% versus 48.21%, p = 0.249), ICU and IMV status, white, not Hispanic (6.52% versus 7.84%, p = 0.380), and Hispanic (33.57% versus 38.20%, p = 0.093), except black non-Hispanic (42.51% versus 36.03%, p = 0.019). Primary outcomes were mortality, stroke, heart attack, major adverse cardiovascular events (MACE), reinfection, and hospital readmission post-discharge. Secondary outcomes were neuroimaging findings (hemorrhage, active and prior stroke, mass effect, microhemorrhages, white matter changes, microvascular disease (MVD), and volume loss). More patients in the neurological cohort were discharged to acute rehabilitation (10.39% versus 3.34%, p < 0.001) or skilled nursing facilities (35.75% versus 25.35%, p < 0.001) and fewer to home (50.24% versus 66.64%, p < 0.001) than matched controls. Incidence of readmission for any reason (65.70% versus 60.72%, p = 0.036), stroke (6.28% versus 2.34%, p < 0.001), and MACE (20.53% versus 16.51%, p = 0.032) was higher in the neurological cohort post-discharge. Per Kaplan-Meier univariate survival curve analysis, such patients in the neurological cohort were more likely to die post-discharge compared to controls (hazard ratio: 2.346, (95% confidence interval (CI) [1.586, 3.470]; p < 0.001)). Across both cohorts, the major causes of death post-discharge were heart disease (13.79% neurological, 15.38% control), sepsis (8.63%, 17.58%), influenza and pneumonia (13.79%, 9.89%), COVID-19 (10.34%, 7.69%), and acute respiratory distress syndrome (ARDS) (10.34%, 6.59%). Factors associated with mortality after leaving the hospital involved the neurological cohort (odds ratio (OR): 1.802 (95% CI [1.237, 2.608]; p = 0.002)), discharge disposition (OR: 1.508 (95% CI [1.276, 1.775]; p < 0.001)), congestive heart failure (OR: 2.281 (95% CI [1.429, 3.593]; p < 0.001)), higher COVID-19 severity score (OR: 1.177 (95% CI [1.062, 1.304]; p = 0.002)), and older age (OR: 1.027 (95% CI [1.010, 1.044]; p = 0.002)). There were no group differences in radiological findings, except that the neurological cohort showed significantly more age-adjusted brain volume loss (p = 0.045) than controls. The study's patient cohort was limited to patients infected with COVID-19 during the first wave of the pandemic, when hospitals were overburdened, vaccines were not yet available, and treatments were limited. Patient profiles might differ when interrogating subsequent waves. CONCLUSIONS: Patients with COVID-19 with neurological manifestations had worse long-term outcomes compared to matched controls. These findings raise awareness and the need for closer monitoring and timely interventions for patients with COVID-19 with neurological manifestations, as their disease course involving initial neurological manifestations is associated with enhanced morbidity and mortality.

Machine learning prediction of pathological complete response and overall survival of breast cancer patients in an underserved inner-city population.

BACKGROUND: Generalizability of predictive models for pathological complete response (pCR) and overall survival (OS) in breast cancer patients requires diverse datasets. This study employed four machine learning models to predict pCR and OS up to 7.5 years using data from a diverse and underserved inner-city population. METHODS: Demographics, staging, tumor subtypes, income, insurance status, and data from radiology reports were obtained from 475 breast cancer patients on neoadjuvant chemotherapy in an inner-city health system (01/01/2012 to 12/31/2021). Logistic regression, Neural Network, Random Forest, and Gradient Boosted Regression models were used to predict outcomes (pCR and OS) with fivefold cross validation. RESULTS: pCR was not associated with age, race, ethnicity, tumor staging, Nottingham grade, income, and insurance status (p > 0.05). ER-/HER2+ showed the highest pCR rate, followed by triple negative, ER+/HER2+, and ER+/HER2- (all p < 0.05), tumor size (p < 0.003) and background parenchymal enhancement (BPE) (p < 0.01). Machine learning models ranked ER+/HER2-, ER-/HER2+, tumor size, and BPE as top predictors of pCR (AUC = 0.74-0.76). OS was associated with race, pCR status, tumor subtype, and insurance status (p < 0.05), but not ethnicity and incomes (p > 0.05). Machine learning models ranked tumor stage, pCR, nodal stage, and triple-negative subtype as top predictors of OS (AUC = 0.83-0.85). When grouping race and ethnicity by tumor subtypes, neither OS nor pCR were different due to race and ethnicity for each tumor subtype (p > 0.05). CONCLUSION: Tumor subtypes and imaging characteristics were top predictors of pCR in our inner-city population. Insurance status, race, tumor subtypes and pCR were associated with OS. Machine learning models accurately predicted pCR and OS.

COVID-19 Patients in the COVID-19 Recovery and Engagement (CORE) Clinics in the Bronx.

Background: Early in the pandemic, we established COVID-19 Recovery and Engagement (CORE) Clinics in the Bronx and implemented a detailed evaluation protocol to assess physical, emotional, and cognitive function, pulmonary function tests, and imaging for COVID-19 survivors. Here, we report our findings up to five months post-acute COVID-19. Methods: Main outcomes and measures included pulmonary function tests, imaging tests, and a battery of symptom, physical, emotional, and cognitive assessments 5 months post-acute COVID-19. Findings: Dyspnea, fatigue, decreased exercise tolerance, brain fog, and shortness of breath were the most common symptoms but there were generally no significant differences between hospitalized and non-hospitalized cohorts (p > 0.05). Many patients had abnormal physical, emotional, and cognitive scores, but most functioned independently; there were no significant differences between hospitalized and non-hospitalized cohorts (p > 0.05). Six-minute walk tests, lung ultrasound, and diaphragm excursion were abnormal but only in the hospitalized cohort. Pulmonary function tests showed moderately restrictive pulmonary function only in the hospitalized cohort but no obstructive pulmonary function. Newly detected major neurological events, microvascular disease, atrophy, and white-matter changes were rare, but lung opacity and fibrosis-like findings were common after acute COVID-19. Interpretation: Many COVID-19 survivors experienced moderately restrictive pulmonary function, and significant symptoms across the physical, emotional, and cognitive health domains. Newly detected brain imaging abnormalities were rare, but lung imaging abnormalities were common. This study provides insights into post-acute sequelae following SARS-CoV-2 infection in neurological and pulmonary systems which may be used to support at-risk patients and develop effective screening methods and interventions.