COVID-19 is commonly mild and self-limiting, but in a considerable portion of patients the disease is severe and fatal. Determining which patients are at high risk of severe illness or mortality is essential for appropriate clinical decision making. We propose a novel severity score specifically for COVID-19 to help predict disease severity and mortality. 4711 patients with confirmed SARS-CoV-2 infection were included. We derived a risk model using the first half of the cohort (n = 2355 patients) by logistic regression and bootstrapping methods. The discriminative power of the risk model was assessed by calculating the area under the receiver operating characteristic curves (AUC). The severity score was validated in a second half of 2356 patients. Mortality incidence was 26.4% in the derivation cohort and 22.4% in the validation cohort. A COVID-19 severity score ranging from 0 to 10, consisting of age, oxygen saturation, mean arterial pressure, blood urea nitrogen, C-Reactive protein, and the international normalized ratio was developed. A ROC curve analysis was performed in the derivation cohort achieved an AUC of 0.824 (95% CI 0.814–0.851) and an AUC of 0.798 (95% CI 0.789–0.818) in the validation cohort. Furthermore, based on the risk categorization the probability of mortality was 11.8%, 39% and 78% for patient with low (0–3), moderate (4–6) and high (7–10) COVID-19 severity score. This developed and validated novel COVID-19 severity score will aid physicians in predicting mortality during surge periods.

Introduction: The increasing utilization of real-world data platforms in medical research necessitates a comprehensive understanding of their methodological strengths and limitations. TriNetX has emerged as a significant platform for exploring large healthcare datasets. This review aims to critically evaluate the methodological framework and limitations of TriNetX, assess the impact of electronic health record coding accuracy on data reliability, and analyze the platform's capacity for generating generalizable real-world evidence in clinical research. Methods: We conducted a comprehensive review examining TriNetX's data architecture, quality metrics, and research applications, focusing on data integrity, platform architecture, and the external validity of research findings. Results: The analysis reveals significant methodological considerations. TriNetX's reliance on retrospective data introduces biases such as selection bias and confounding variables. The coding accuracy of electronic health records, which have not been independently validated, is a critical determinant of data reliability. The demographic representation is limited, affecting the generalizability of results. Discussion: Despite its extensive use, TriNetX's effective utilization requires careful consideration of its inherent limitations. The platform's data, predominantly from insured populations in academic and acute care settings, may not fully represent broader demographic groups. Addressing these methodological constraints is crucial for enhancing the reliability and applicability of research findings derived from TriNetX. Conclusions: TriNetX is a valuable resource for healthcare research. However, its limitations must be acknowledged, and future research should focus on standardizing data collection and enhancing data validation processes to mitigate platform-specific biases and improve the quality and applicability of the findings.

OBJECTIVE: Postoperative urinary retention (POUR) is a common problem leading to morbidity and an increased hospital stay. There are limited data regarding its baseline incidence in patients undergoing spinal surgery and the risk factors with which it may be associated. The purpose of this study was to evaluate the incidence of POUR in elective spine surgery patients and determine the factors associated with its occurrence. METHODS: The authors retrospectively reviewed the records of patients who had undergone elective spine surgery and had been prospectively monitored for POUR during an 18-month period. Collected data included operative positioning, surgery duration, volume of intraoperative fluid, length of hospital stay, and patient characteristics such as age, sex, and medical comorbidities. Dialysis patients or those with complete urinary retention preoperatively were excluded from analysis. RESULTS: Of the 397 patients meeting the study inclusion criteria, 35 (8.8%) developed POUR. An increased incidence of POUR was noted in those who underwent posterior lumbar surgery, those with benign prostatic hypertrophy (BPH), those with chronic constipation or prior urinary retention, and those using a patient-controlled analgesia pump postoperatively. An increased incidence of POUR was seen with a longer operative time but not with intraoperative intravenous fluid administration. A significant relationship between the female sex and POUR was noted after controlling for BPH, yet there was no association between POUR and diabetes or intraoperative instrumentation. Postoperative retention significantly prolonged the hospital stay. Three patients developed epidural hematomas necessitating operative reexploration, and while they experienced POUR, they also developed the full constellation of cauda equina syndrome. CONCLUSIONS: Awareness of the risk factors for POUR may be useful in perioperative Foley catheter management and in identifying patients who need particular vigilance when they are due to void postprocedure. A greater understanding of POUR may also prevent longer hospital stays in select at-risk patients. Postoperative retention is rarely caused by a postoperative cauda equina syndrome due to epidural hematoma, which is also associated with saddle anesthesia, leg pain, and weakness, yet the delineation of isolated POUR from this urgent complication is necessary for optimal patient care.

Objective Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is protean in its manifestations, affecting nearly every organ system. However, nervous system involvement and its effect on disease outcome are poorly characterized. The objective of this study was to determine whether neurologic syndromes are associated with increased risk of inpatient mortality. Methods A total of 581 hospitalized patients with confirmed SARS-CoV-2 infection, neurologic involvement, and brain imaging were compared to hospitalized non-neurologic patients with coronavirus disease 2019 (COVID-19). Four patterns of neurologic manifestations were identified: acute stroke, new or recrudescent seizures, altered mentation with normal imaging, and neuro-COVID-19 complex. Factors present on admission were analyzed as potential predictors of in-hospital mortality, including sociodemographic variables, preexisting comorbidities, vital signs, laboratory values, and pattern of neurologic manifestations. Significant predictors were incorporated into a disease severity score. Patients with neurologic manifestations were matched with patients of the same age and disease severity to assess the risk of death. Results A total of 4,711 patients with confirmed SARS-CoV-2 infection were admitted to one medical system in New York City during a 6-week period. Of these, 581 (12%) had neurologic issues of sufficient concern to warrant neuroimaging. These patients were compared to 1,743 non-neurologic patients with COVID-19 matched for age and disease severity admitted during the same period. Patients with altered mentation (n = 258, p = 0.04, odds ratio [OR] 1.39, confidence interval [CI] 1.04–1.86) or radiologically confirmed stroke (n = 55, p = 0.001, OR 3.1, CI 1.65–5.92) had a higher risk of mortality than age- and severity-matched controls. Conclusions The incidence of altered mentation or stroke on admission predicts a modest but significantly higher risk of in-hospital mortality independent of disease severity. While other biomarker factors also predict mortality, measures to identify and treat such patients may be important in reducing overall mortality of COVID-19.

Background: Though primarily a pulmonary disease, Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus can generate devastating disease states that affect multiple organ systems including the central nervous system (CNS). The various neurological disorders associated with COVID-19 range in severity from mild symptoms such as headache, or myalgias to more severe symptoms such as stroke, psychosis, and anosmia. While some of the COVID-19 associated neurological complications are mild and reversible, a significant number of patients suffer from stroke. Studies have shown that COVID-19 infection triggers a wave of inflammatory cytokines that induce endothelial cell dysfunction and generate coagulopathy that increases the risk of stroke or thromboses. Inflammation of the endothelium following infection may also destabilize atherosclerotic plaque and induce thrombotic stroke. Although uncommon, there have also been reports of hemorrhagic stroke associated with COVID-19. The proposed mechanisms include a blood pressure increase caused by infection leading to a reduction in angiotensin converting enzyme-2 (ACE-2) levels that results in an imbalance of the renin-angiotensin system ultimately manifesting inflammation and vasoconstriction. Coagulopathy, as demonstrated by elevated prothrombin time (PT), has also been posited as a factor contributing to hemorrhagics stroke in patients with COVID-19. Other neurological conditions associated with COVID-19 include encephalopathy, anosmia, encephalitis, psychosis, brain fog, headache, depression, and anxiety. Though there are several hypotheses reported in the literature, a unifying pathophysiological mechanism of many of these disorders remains unclear. Pulmonary dysfunction leading to poor oxygenation of the brain may explain encephalopathy and other disorders in COVID-19 patients. Alternatively, a direct invasion of the CNS by the virus or breach of the blood-brain barrier by the systemic cytokines released during infection may be responsible for these conditions. Notwithstanding, the relationship between the inflammatory cytokine levels and conditions such as depression and anxiety is contradictory and perhaps the social isolation during the pandemic may in part be a contributing factor to some of the reported CNS disorders. Objective: In this article, we review the current literature pertaining to some of the most significant and common neurological disorders such as ischemic and hemorrhagic stroke, encephalopathy, encephalitis, brain fog, Long COVID, headache, Guillain-Barre syndrome, depression, anxiety, and sleep disorders in the setting of COVID-19. We summarize some of the most relevant literature to provide a better understanding of the mechanistic details regarding these disorders in order to help physicians monitor and treat patients for significant COVID-19 associated neurologic impairments. Methods: A literature review was carried out by the authors using PubMed with the search terms “COVID-19” and “Neurology”, “Neurological Manifestations”, “Neuropsychiatric Manifestations”, “Stroke”, “Encephalopathy”, “Headache”, “Guillain-Barre syndrome”, “Depression”, “Anxiety”, “Encephalitis”, “Seizure”, “Spasm”, and “ICUAW”. Another search was carried out for “Long-COVID” and “Post-Acute COVID-19” and “Neurological Manifestations” or “Neuropsychiatric Manifestations”. Articles such as case reports, case series, and cohort studies were included as references. No language restrictions were enforced. In the case of anxiety and depression, attempts were made to focus mainly on articles describing these conditions in infected patients. Results: A total of 112 articles were reviewed. The incidence, clinical outcomes, and pathophysiology of selected neurological disorders are discussed below. Given the recent advent of this disease, the incidence of certain neurologic sequelae was not always available. Putative mechanisms for each condition in the setting of COVID-19 are outlined.