Application of a Standardized Treatment Paradigm as a Strategy to Achieve Optimal Onco-Functional Balance in Glioma Surgery.

BACKGROUND: Gliomas, characterized by their invasive persistence and tendency to affect critical brain regions, pose a challenge in surgical resection due to the risk of neurological deficits. This study focuses on a personalized approach to achieving an optimal onco-functional balance in glioma resections, emphasizing maximal tumor removal while preserving the quality of life. METHODS: A retrospective analysis of 57 awake surgical resections of gliomas at the National University Hospital, Singapore, was conducted. The inclusion criteria were based on diagnosis, functional boundaries determined by direct electrical stimulation, preoperative Karnofsky Performance Status score, and absence of multifocal disease on MRI. The treatment approach included comprehensive neuropsychological evaluation, determination of suitability for awake surgery, and standard asleep-awake-asleep anesthesia protocol. Tumor resection techniques and postoperative care were systematically followed. RESULTS: The study included 53 patients (55.5% male, average age 39 years), predominantly right-handed. Over half reported seizures as their chief complaint. Tumors were mostly low-grade gliomas. Positive mapping of the primary motor cortex was conducted in all cases, with awake surgery completed in 77.2% of cases. New neurological deficits were observed in 26.3% of patients at 1 month after operation; most showed significant improvement at 6 months. CONCLUSION: The standardized treatment paradigm effectively achieved an optimal onco-functional balance in glioma patients. While some patients experienced neurological deficits postoperatively, the majority recovered to their preoperative baseline within 3 months. The approach prioritizes patient empowerment and customized utilization of functional mapping techniques, considering the challenge of preserving diverse languages in a multilingual patient population.

Neurological diagnoses in hospitalized COVID-19 patients associated with adverse outcomes: A multinational cohort study.

Few studies examining the patient outcomes of concurrent neurological manifestations during acute COVID-19 leveraged multinational cohorts of adults and children or distinguished between central and peripheral nervous system (CNS vs. PNS) involvement. Using a federated multinational network in which local clinicians and informatics experts curated the electronic health records data, we evaluated the risk of prolonged hospitalization and mortality in hospitalized COVID-19 patients from 21 healthcare systems across 7 countries. For adults, we used a federated learning approach whereby we ran Cox proportional hazard models locally at each healthcare system and performed a meta-analysis on the aggregated results to estimate the overall risk of adverse outcomes across our geographically diverse populations. For children, we reported descriptive statistics separately due to their low frequency of neurological involvement and poor outcomes. Among the 106,229 hospitalized COVID-19 patients (104,031 patients ≥18 years; 2,198 patients <18 years, January 2020-October 2021), 15,101 (14%) had at least one CNS diagnosis, while 2,788 (3%) had at least one PNS diagnosis. After controlling for demographics and pre-existing conditions, adults with CNS involvement had longer hospital stay (11 versus 6 days) and greater risk of (Hazard Ratio = 1.78) and faster time to death (12 versus 24 days) than patients with no neurological condition (NNC) during acute COVID-19 hospitalization. Adults with PNS involvement also had longer hospital stay but lower risk of mortality than the NNC group. Although children had a low frequency of neurological involvement during COVID-19 hospitalization, a substantially higher proportion of children with CNS involvement died compared to those with NNC (6% vs 1%). Overall, patients with concurrent CNS manifestation during acute COVID-19 hospitalization faced greater risks for adverse clinical outcomes than patients without any neurological diagnosis. Our global informatics framework using a federated approach (versus a centralized data collection approach) has utility for clinical discovery beyond COVID-19.

Cognition, Emotional States and Health-Related Quality of Life in Awake Craniotomy for Glioma: A Case Series.

BACKGROUND: Awake craniotomy is an effective procedure for optimizing the onco-functional balance of resections in glioma. However, limited data exists on the cognition, emotional states, and health-related quality of life (HRQoL) of patients with glioma who undergo awake craniotomy. This study aims to describe 1) perioperative cognitive function and emotional states in a multilingual Asian population, 2) associations between perioperative cognitive function and follow-up HRQoL, and 3) associations between preoperative emotional states and follow-up HRQoL. METHODS: This is a case series of 14 adult glioma patients who underwent awake craniotomy in Singapore. Cognition was assessed with the Montreal Cognitive Assessment and the Repeatable Battery for the Assessment of Neuropsychological Status, emotional states with the Depression, Anxiety and Stress Scale-21 Items, and HRQoL using the EuroQol-5D-5L, the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30, and the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-BN20. RESULTS: Patients with better preoperative cognitive scores on all domains reported better HRQoL. Better postoperative immediate memory and language scores were associated with better HRQoL. Moderate preoperative depression scores and mild and moderate preoperative stress scores were associated with poorer HRQoL compared to scores within the normal range. Mild preoperative anxiety scores were associated with better HRQoL compared to scores within the normal range. CONCLUSION: This descriptive case series showed that patients with higher preoperative cognitive scores reported better follow-up HRQoL, while patients who reported more preoperative depressive and stress symptomatology reported worse follow-up HRQoL. Future analytical studies may help to draw conclusions about whether perioperative cognition and emotional states predict HRQoL on follow-up.

Acute respiratory distress syndrome after SARS-CoV-2 infection on young adult population: International observational federated study based on electronic health records through the 4CE consortium.

PURPOSE: In young adults (18 to 49 years old), investigation of the acute respiratory distress syndrome (ARDS) after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been limited. We evaluated the risk factors and outcomes of ARDS following infection with SARS-CoV-2 in a young adult population. METHODS: A retrospective cohort study was conducted between January 1st, 2020 and February 28th, 2021 using patient-level electronic health records (EHR), across 241 United States hospitals and 43 European hospitals participating in the Consortium for Clinical Characterization of COVID-19 by EHR (4CE). To identify the risk factors associated with ARDS, we compared young patients with and without ARDS through a federated analysis. We further compared the outcomes between young and old patients with ARDS. RESULTS: Among the 75,377 hospitalized patients with positive SARS-CoV-2 PCR, 1001 young adults presented with ARDS (7.8% of young hospitalized adults). Their mortality rate at 90 days was 16.2% and they presented with a similar complication rate for infection than older adults with ARDS. Peptic ulcer disease, paralysis, obesity, congestive heart failure, valvular disease, diabetes, chronic pulmonary disease and liver disease were associated with a higher risk of ARDS. We described a high prevalence of obesity (53%), hypertension (38%- although not significantly associated with ARDS), and diabetes (32%). CONCLUSION: Trough an innovative method, a large international cohort study of young adults developing ARDS after SARS-CoV-2 infection has been gather. It demonstrated the poor outcomes of this population and associated risk factor.

Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort study.

Background: While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking. Methods: A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1-365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021. Findings: Advanced age (HR 2.77, 95%CI 2.53-3.04, p < 0.0001), severe COVID-19 (HR 2.91, 95%CI 2.03-4.17, p < 0.0001), severe AKI (KDIGO stage 3: HR 4.22, 95%CI 3.55-5.00, p < 0.0001), and ischemic heart disease (HR 1.26, 95%CI 1.14-1.39, p < 0.0001) were associated with worse mortality outcomes. AKI severity (KDIGO stage 3: HR 0.41, 95%CI 0.37-0.46, p < 0.0001) was associated with worse kidney function recovery, whereas remdesivir use (HR 1.34, 95%CI 1.17-1.54, p < 0.0001) was associated with better kidney function recovery. In a subset of patients without chronic kidney disease, advanced age (HR 1.38, 95%CI 1.20-1.58, p < 0.0001), male sex (HR 1.67, 95%CI 1.45-1.93, p < 0.0001), severe AKI (KDIGO stage 3: HR 11.68, 95%CI 9.80-13.91, p < 0.0001), and hypertension (HR 1.22, 95%CI 1.10-1.36, p = 0.0002) were associated with post-AKI kidney function impairment. Furthermore, patients with COVID-19-associated AKI had significant and persistent elevations of baseline serum creatinine 125% or more at 180 days (RR 1.49, 95%CI 1.32-1.67) and 365 days (RR 1.54, 95%CI 1.21-1.96) compared to COVID-19 patients with no AKI. Interpretation: COVID-19-associated AKI was associated with higher mortality, and severe COVID-19-associated AKI was associated with worse long-term post-AKI kidney function recovery. Funding: Authors are supported by various funders, with full details stated in the acknowledgement section.

Awake craniotomy for brain tumor resection: Patient experience and acceptance in an Asian population.

INTRODUCTION: Awake craniotomy is well-established for resection of brain tumor in the eloquent areas. Previous studies from Western countries have reported good level of patient tolerance and acceptance. However, its acceptability in non-Western populations, with different ethnic, social, cultural, religious, and linguistic backgrounds, has not been studied systematically. This study aims to evaluate the experience of patients from an Asian population who underwent awake craniotomy for tumor resection. METHODS: Data on patient experience were collected by interviewing patients using a structured questionnaire at follow-up appointment. Data on patient demographics and diagnosis were collected from medical records. RESULTS: Eighteen patients (age 16-68 years) who underwent 20 awake craniotomies were recruited. Preoperatively, all (100%) patients understood the indication for awake craniotomy. Almost all felt fully counseled by the neurosurgeon (90%), anesthetist (100%), and neuropsychologist (95%). Ninety-five percent reported their family to be supportive of awake craniotomy. Seventy-five percent felt adequately prepared on operation day. Intraoperatively, most patients did not experience pain/discomfort (55%) or anxiety (65%). Nearly all found intraoperative motor and language testing to be easy (100% and 90%, respectively). Postoperatively, 100% were satisfied with their care. One hundred percent rated their overall experience as good or excellent. Eighty percent were willing to undergo awake craniotomy again if indicated. CONCLUSION: Awake craniotomy is well-accepted in an Asian population. All patients had good-to-excellent overall experience, with most willing to undergo awake craniotomy again. Our findings underscore the generalizability of awake craniotomy across different socio-cultural backgrounds and support its utilization in countries with a significant Asian population.

Association of Preoperative Hyponatremia With Surgical Outcomes: A Systematic Review and Meta-analysis of 32 Observational Studies.

BACKGROUND: Preoperative hyponatremia is prevalent in patients undergoing surgical procedures, but it is uncertain if hyponatremia will lead to increased risk of surgical mortality and morbidity. METHODS: A systematic search of Medline (PubMed), Embase, and Cochrane Library from inception through July 2, 2021, was performed. Full-length articles that reported on the association between surgical outcomes among adults aged ≥18 years with documented preoperative hyponatremia were included. FINDINGS: We identified 32 observational studies comprising 1 301 346 participants. All studies had low risk of bias. When adjusted for covariates, patients with hyponatremia had significantly higher odds of developing major complications (defined as a composite measure of 9 major complications) compared with patients with normal sodium concentrations (adjusted odds ratio = 1.37; 95% CI, 1.23-1.53; I2 = 78%; N = 10). Additionally, patients with preoperative hyponatremia also significantly higher hazards of early mortality (<90 days) compared with patients with normonatremia (adjusted hazard ratio = 1.27; 95% CI, 1.13-1.43; I2 = 97%; N = 10) after adjustment for covariates. Preoperative hyponatremia also had significant associations with respiratory, renal, and septic complications. In terms of prognostic performance, preoperative hyponatremia performed adequately in predicting major complications in surgical patients (area under the curve = 0.70; negative likelihood ratio, 0.90) with a specificity of 88% and a sensitivity of 25%. INTERPRETATION: Our meta-analysis suggests that preoperative hyponatremia is associated with poorer early mortality and major morbidity outcomes in surgical patients. Hyponatremia is also a specific prognosticator for major complications in surgical patients, reiterating its potential use as a clinical indicator of poor outcomes.

Risk factors of post-anaesthesia care unit delirium in patients undergoing non-cardiac surgery in Singapore.

Introduction: Post-anaesthesia care unit (PACU) delirium affects 5%-45% of patients after surgery and is associated with postoperative delirium and increased mortality. Up to 40% of PACU delirium is preventable, but it remains under-recognised due to a lack of awareness of its diagnosis. The nursing delirium screening scale (Nu-DESC) has been validated for diagnosing PACU delirium, but is not routinely used locally. This study aimed to use Nu-DESC to establish the incidence and risk factors of PACU delirium in patients undergoing non-cardiac surgery in the surgical population. Methods: We conducted an audit of eligible patients undergoing major surgery in three public hospitals in Singapore over 1 week. Patients were assessed for delirium 30-60 min following their arrival in PACU using Nu-DESC, with a total score of ≥2 indicative of delirium. Results: A total of 478 patients were assessed. The overall incidence rate of PACU delirium was 18/478 (3.8%), and the incidence was 9/146 (6.2%) in patients aged > 65 years. Post-anaesthesia care unit delirium was more common in females, patients with malignancy and those who underwent longer operations. Logistic regression analysis showed that the use of bispectral index (P < 0.001) and the presence of malignancy (P < 0.001) were significantly associated with a higher incidence of PACU delirium. Conclusion: In this first local study, the incidence of PACU delirium was 3.8%, increasing to 6.2% in those aged > 65 years. Understanding these risk factors will form the basis for which protocols can be established to optimise resource management and prevent long-term morbidities and mortality in PACU delirium.

Hospitalizations Associated With Mental Health Conditions Among Adolescents in the US and France During the COVID-19 Pandemic.

Importance: The COVID-19 pandemic has been associated with an increase in mental health diagnoses among adolescents, though the extent of the increase, particularly for severe cases requiring hospitalization, has not been well characterized. Large-scale federated informatics approaches provide the ability to efficiently and securely query health care data sets to assess and monitor hospitalization patterns for mental health conditions among adolescents. Objective: To estimate changes in the proportion of hospitalizations associated with mental health conditions among adolescents following onset of the COVID-19 pandemic. Design, Setting, and Participants: This retrospective, multisite cohort study of adolescents 11 to 17 years of age who were hospitalized with at least 1 mental health condition diagnosis between February 1, 2019, and April 30, 2021, used patient-level data from electronic health records of 8 children's hospitals in the US and France. Main Outcomes and Measures: Change in the monthly proportion of mental health condition-associated hospitalizations between the prepandemic (February 1, 2019, to March 31, 2020) and pandemic (April 1, 2020, to April 30, 2021) periods using interrupted time series analysis. Results: There were 9696 adolescents hospitalized with a mental health condition during the prepandemic period (5966 [61.5%] female) and 11 101 during the pandemic period (7603 [68.5%] female). The mean (SD) age in the prepandemic cohort was 14.6 (1.9) years and in the pandemic cohort, 14.7 (1.8) years. The most prevalent diagnoses during the pandemic were anxiety (6066 [57.4%]), depression (5065 [48.0%]), and suicidality or self-injury (4673 [44.2%]). There was an increase in the proportions of monthly hospitalizations during the pandemic for anxiety (0.55%; 95% CI, 0.26%-0.84%), depression (0.50%; 95% CI, 0.19%-0.79%), and suicidality or self-injury (0.38%; 95% CI, 0.08%-0.68%). There was an estimated 0.60% increase (95% CI, 0.31%-0.89%) overall in the monthly proportion of mental health-associated hospitalizations following onset of the pandemic compared with the prepandemic period. Conclusions and Relevance: In this cohort study, onset of the COVID-19 pandemic was associated with increased hospitalizations with mental health diagnoses among adolescents. These findings support the need for greater resources within children's hospitals to care for adolescents with mental health conditions during the pandemic and beyond.

Point-of-care platelet function testing for guided transfusion in neurosurgical management of intracranial hemorrhage: a systematic review.

Given the rising prevalence of antiplatelet therapy, rapid preoperative identification of patients with bleeding diathesis is necessary for the guidance of blood product administration. This is especially relevant in neurosurgery for intracranial hemorrhage (ICH), where indiscriminate transfusions may lead to further hemorrhagic or thromboembolic injury. Point-of-care (POC) testing of platelet function is a promising solution to this dilemma, as it has been proven effective in cardiac surgery. However, to date, POC platelet function testing in neurosurgery has not been extensively evaluated. This systematic review appraises the use of POC platelet function test (PFT) in emergency neurosurgery in terms of its impact on patient outcomes.A comprehensive search was conducted on four electronic databases (Pubmed, MEDLINE, Embase, and Cochrane) for relevant English language articles from their respective inceptions until 1 June 2022. We included all randomized controlled trials and cohort studies that met the following inclusion criteria: (i) involved adult patients undergoing neurosurgery for ICH; (ii) evaluated platelet function via POC PFT; (iii) reported a change in perioperative blood loss; and/or (iv) reported data on treatment-related adverse events and mortality. Assessment of study quality was conducted using the Newcastle Ottawa Quality Assessment Scale for Cohort Studies and Case-Control Studies, and the JBI Critical Appraisal Checklist for Case Series.The search yielded 2,835 studies, of which seven observational studies comprising 849 patients met the inclusion criteria for this review. Overall, there is evidence that the use of POC PFT to assess bleeding risk reduced bleeding events, thromboembolic adverse outcomes, and the length of hospitalization. However, there is currently insufficient evidence to suggest that using POC PFT improves blood product use, functional outcomes or mortality.

International electronic health record-derived post-acute sequelae profiles of COVID-19 patients.

The risk profiles of post-acute sequelae of COVID-19 (PASC) have not been well characterized in multi-national settings with appropriate controls. We leveraged electronic health record (EHR) data from 277 international hospitals representing 414,602 patients with COVID-19, 2.3 million control patients without COVID-19 in the inpatient and outpatient settings, and over 221 million diagnosis codes to systematically identify new-onset conditions enriched among patients with COVID-19 during the post-acute period. Compared to inpatient controls, inpatient COVID-19 cases were at significant risk for angina pectoris (RR 1.30, 95% CI 1.09-1.55), heart failure (RR 1.22, 95% CI 1.10-1.35), cognitive dysfunctions (RR 1.18, 95% CI 1.07-1.31), and fatigue (RR 1.18, 95% CI 1.07-1.30). Relative to outpatient controls, outpatient COVID-19 cases were at risk for pulmonary embolism (RR 2.10, 95% CI 1.58-2.76), venous embolism (RR 1.34, 95% CI 1.17-1.54), atrial fibrillation (RR 1.30, 95% CI 1.13-1.50), type 2 diabetes (RR 1.26, 95% CI 1.16-1.36) and vitamin D deficiency (RR 1.19, 95% CI 1.09-1.30). Outpatient COVID-19 cases were also at risk for loss of smell and taste (RR 2.42, 95% CI 1.90-3.06), inflammatory neuropathy (RR 1.66, 95% CI 1.21-2.27), and cognitive dysfunction (RR 1.18, 95% CI 1.04-1.33). The incidence of post-acute cardiovascular and pulmonary conditions decreased across time among inpatient cases while the incidence of cardiovascular, digestive, and metabolic conditions increased among outpatient cases. Our study, based on a federated international network, systematically identified robust conditions associated with PASC compared to control groups, underscoring the multifaceted cardiovascular and neurological phenotype profiles of PASC.

International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality.

Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach.

Incidence and risk factors of delirium in post-anaesthesia care unit.

INTRODUCTION: Post-anaesthesia care unit (PACU) delirium is a potentially preventable condition that results in a significant long-term effect. In a multicentre prospective cohort study, we investigate the incidence and risk factors of postoperative delirium in elderly patients undergoing major non-cardiac surgery. METHODS: Patients were consented and recruited from 4 major hospitals in Singapore. Research ethics approval was obtained. Patients older than 65 years undergoing non-cardiac surgery >2 hours were recruited. Baseline perioperative data were collected. Preoperative baseline cognition was obtained. Patients were assessed in the post-anaesthesia care unit for delirium 30-60 minutes after arrival using the Nursing Delirium Screening Scale (Nu-DESC). RESULTS: Ninety-eight patients completed the study. Eleven patients (11.2%) had postoperative delirium. Patients who had PACU delirium were older (74.6±3.2 versus 70.6±4.4 years, P=0.005). Univariate analysis showed those who had PACU delirium are more likely to be ASA 3 (63.6% vs 31.0%, P=0.019), had estimated glomerular filtration rate (eGFR) of >60mL/min/1.73m2 (36.4% vs 10.6%, P=0.013), higher HbA1C value (7.8±1.2 vs 6.6±0.9, P=0.011), raised random blood glucose (10.0±5.0mmol/L vs 6.5±2.4mmol/L, P=0.0066), and moderate-severe depression (18.2% vs 1.1%, P=0.033). They are more likely to stay longer in hospital (median 8 days [range 4-18] vs 4 days [range 2-8], P=0.049). Raised random blood glucose is independently associated with increased PACU delirium on multivariate analysis.

Machine Learning Models Prognosticate Functional Outcomes Better than Clinical Scores in Spontaneous Intracerebral Haemorrhage.

OBJECTIVE: This study aims to develop and compare the use of deep neural networks (DNN) and support vector machines (SVM) to clinical prognostic scores for prognosticating 30-day mortality and 90-day poor functional outcome (PFO) in spontaneous intracerebral haemorrhage (SICH). MATERIALS AND METHODS: We conducted a retrospective cohort study of 297 SICH patients between December 2014 and May 2016. Clinical data was collected from electronic medical records using standardized data collection forms. The machine learning workflow included imputation of missing data, dimensionality reduction, imbalanced-class correction, and evaluation using cross-validation and comparison of accuracy against clinical prognostic scores. RESULTS: 32 (11%) patients had 30-day mortality while 177 (63%) patients had 90-day PFO. For prognosticating 30-day mortality, the class-balanced accuracies for DNN (0.875; 95% CI 0.800-0.950; McNemar's p-value 1.000) and SVM (0.848; 95% CI 0.767-0.930; McNemar's p-value 0.791) were comparable to that of the original ICH score (0.833; 95% CI 0.748-0.918). The c-statistics for DNN (0.895; DeLong's p-value 0.715), and SVM (0.900; DeLong's p-value 0.619), though greater than that of the original ICH score (0.862), were not significantly different. For prognosticating 90-day PFO, the class-balanced accuracies for DNN (0.853; 95% CI 0.772-0.934; McNemar's p-value 0.003) and SVM (0.860; 95% CI 0.781-0.939; McNemar's p-value 0.004) were better than that of the ICH-Grading Scale (0.706; 95% CI 0.600-0.812). The c-statistic for SVM (0.883; DeLong's p-value 0.022) was significantly greater than that of the ICH-Grading Scale (0.778), while the c-statistic for DNN was 0.864 (DeLong's p-value 0.055). CONCLUSION: We showed that the SVM model performs significantly better than clinical prognostic scores in predicting 90-day PFO in SICH.

Authorship Correction: International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study.

[This corrects the article DOI: 10.2196/31400.].

Multinational characterization of neurological phenotypes in patients hospitalized with COVID-19.

Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse multinational populations during early pandemic, we used electronic health records (EHR) from 338 participating hospitals across 6 countries and 3 continents (January-September 2020) for a cross-sectional analysis. We assessed the frequency of International Classification of Disease code of neurological conditions by countries, healthcare systems, time before and after admission for COVID-19 and COVID-19 severity. Among 35,177 hospitalized patients with SARS-CoV-2 infection, there was an increase in the proportion with disorders of consciousness (5.8%, 95% confidence interval [CI] 3.7-7.8%, pFDR < 0.001) and unspecified disorders of the brain (8.1%, 5.7-10.5%, pFDR < 0.001) when compared to the pre-admission proportion. During hospitalization, the relative risk of disorders of consciousness (22%, 19-25%), cerebrovascular diseases (24%, 13-35%), nontraumatic intracranial hemorrhage (34%, 20-50%), encephalitis and/or myelitis (37%, 17-60%) and myopathy (72%, 67-77%) were higher for patients with severe COVID-19 when compared to those who never experienced severe COVID-19. Leveraging a multinational network to capture standardized EHR data, we highlighted the increased prevalence of central and peripheral neurological phenotypes in patients hospitalized with COVID-19, particularly among those with severe disease.

International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study.

BACKGROUND: Many countries have experienced 2 predominant waves of COVID-19-related hospitalizations. Comparing the clinical trajectories of patients hospitalized in separate waves of the pandemic enables further understanding of the evolving epidemiology, pathophysiology, and health care dynamics of the COVID-19 pandemic. OBJECTIVE: In this retrospective cohort study, we analyzed electronic health record (EHR) data from patients with SARS-CoV-2 infections hospitalized in participating health care systems representing 315 hospitals across 6 countries. We compared hospitalization rates, severe COVID-19 risk, and mean laboratory values between patients hospitalized during the first and second waves of the pandemic. METHODS: Using a federated approach, each participating health care system extracted patient-level clinical data on their first and second wave cohorts and submitted aggregated data to the central site. Data quality control steps were adopted at the central site to correct for implausible values and harmonize units. Statistical analyses were performed by computing individual health care system effect sizes and synthesizing these using random effect meta-analyses to account for heterogeneity. We focused the laboratory analysis on C-reactive protein (CRP), ferritin, fibrinogen, procalcitonin, D-dimer, and creatinine based on their reported associations with severe COVID-19. RESULTS: Data were available for 79,613 patients, of which 32,467 were hospitalized in the first wave and 47,146 in the second wave. The prevalence of male patients and patients aged 50 to 69 years decreased significantly between the first and second waves. Patients hospitalized in the second wave had a 9.9% reduction in the risk of severe COVID-19 compared to patients hospitalized in the first wave (95% CI 8.5%-11.3%). Demographic subgroup analyses indicated that patients aged 26 to 49 years and 50 to 69 years; male and female patients; and black patients had significantly lower risk for severe disease in the second wave than in the first wave. At admission, the mean values of CRP were significantly lower in the second wave than in the first wave. On the seventh hospital day, the mean values of CRP, ferritin, fibrinogen, and procalcitonin were significantly lower in the second wave than in the first wave. In general, countries exhibited variable changes in laboratory testing rates from the first to the second wave. At admission, there was a significantly higher testing rate for D-dimer in France, Germany, and Spain. CONCLUSIONS: Patients hospitalized in the second wave were at significantly lower risk for severe COVID-19. This corresponded to mean laboratory values in the second wave that were more likely to be in typical physiological ranges on the seventh hospital day compared to the first wave. Our federated approach demonstrated the feasibility and power of harmonizing heterogeneous EHR data from multiple international health care systems to rapidly conduct large-scale studies to characterize how COVID-19 clinical trajectories evolve.

Multinational Prevalence of Neurological Phenotypes in Patients Hospitalized with COVID-19.

OBJECTIVE: Neurological complications can worsen outcomes in COVID-19. We defined the prevalence of a wide range of neurological conditions among patients hospitalized with COVID-19 in geographically diverse multinational populations. METHODS: Using electronic health record (EHR) data from 348 participating hospitals across 6 countries and 3 continents between January and September 2020, we performed a cross-sectional study of hospitalized adult and pediatric patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test, both with and without severe COVID-19. We assessed the frequency of each disease category and 3-character International Classification of Disease (ICD) code of neurological diseases by countries, sites, time before and after admission for COVID-19, and COVID-19 severity. RESULTS: Among the 35,177 hospitalized patients with SARS-CoV-2 infection, there was increased prevalence of disorders of consciousness (5.8%, 95% confidence interval [CI]: 3.7%-7.8%, p FDR <.001) and unspecified disorders of the brain (8.1%, 95%CI: 5.7%-10.5%, p FDR <.001), compared to pre-admission prevalence. During hospitalization, patients who experienced severe COVID-19 status had 22% (95%CI: 19%-25%) increase in the relative risk (RR) of disorders of consciousness, 24% (95%CI: 13%-35%) increase in other cerebrovascular diseases, 34% (95%CI: 20%-50%) increase in nontraumatic intracranial hemorrhage, 37% (95%CI: 17%-60%) increase in encephalitis and/or myelitis, and 72% (95%CI: 67%-77%) increase in myopathy compared to those who never experienced severe disease. INTERPRETATION: Using an international network and common EHR data elements, we highlight an increase in the prevalence of central and peripheral neurological phenotypes in patients hospitalized with SARS-CoV-2 infection, particularly among those with severe disease.

Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data.

OBJECTIVE: The Consortium for Clinical Characterization of COVID-19 by EHR (4CE) is an international collaboration addressing coronavirus disease 2019 (COVID-19) with federated analyses of electronic health record (EHR) data. We sought to develop and validate a computable phenotype for COVID-19 severity. MATERIALS AND METHODS: Twelve 4CE sites participated. First, we developed an EHR-based severity phenotype consisting of 6 code classes, and we validated it on patient hospitalization data from the 12 4CE clinical sites against the outcomes of intensive care unit (ICU) admission and/or death. We also piloted an alternative machine learning approach and compared selected predictors of severity with the 4CE phenotype at 1 site. RESULTS: The full 4CE severity phenotype had pooled sensitivity of 0.73 and specificity 0.83 for the combined outcome of ICU admission and/or death. The sensitivity of individual code categories for acuity had high variability-up to 0.65 across sites. At one pilot site, the expert-derived phenotype had mean area under the curve of 0.903 (95% confidence interval, 0.886-0.921), compared with an area under the curve of 0.956 (95% confidence interval, 0.952-0.959) for the machine learning approach. Billing codes were poor proxies of ICU admission, with as low as 49% precision and recall compared with chart review. DISCUSSION: We developed a severity phenotype using 6 code classes that proved resilient to coding variability across international institutions. In contrast, machine learning approaches may overfit hospital-specific orders. Manual chart review revealed discrepancies even in the gold-standard outcomes, possibly owing to heterogeneous pandemic conditions. CONCLUSIONS: We developed an EHR-based severity phenotype for COVID-19 in hospitalized patients and validated it at 12 international sites.