Informative missingness: What can we learn from patterns in missing laboratory data in the electronic health record?

BACKGROUND: In electronic health records, patterns of missing laboratory test results could capture patients' course of disease as well as ​​reflect clinician's concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to identify informative patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients. METHODS: We collected and analyzed demographic, diagnosis, and laboratory data for 69,939 patients with positive COVID-19 PCR tests across three countries from 1 January 2020 through 30 September 2021. We analyzed missing laboratory measurements across sites, missingness stratification by demographic variables, temporal trends of missingness, correlations between labs based on missingness indicators over time, and clustering of groups of labs based on their missingness/ordering pattern. RESULTS: With these analyses, we identified mapping issues faced in seven out of 15 sites. We also identified nuances in data collection and variable definition for the various sites. Temporal trend analyses may support the use of laboratory test result missingness patterns in identifying severe COVID-19 patients. Lastly, using missingness patterns, we determined relationships between various labs that reflect clinical behaviors. CONCLUSION: In this work, we use computational approaches to relate missingness patterns to hospital treatment capacity and highlight the heterogeneity of looking at COVID-19 over time and at multiple sites, where there might be different phases, policies, etc. Changes in missingness could suggest a change in a patient's condition, and patterns of missingness among laboratory measurements could potentially identify clinical outcomes. This allows sites to consider missing data as informative to analyses and help researchers identify which sites are better poised to study particular questions.

SurvMaximin: Robust federated approach to transporting survival risk prediction models.

OBJECTIVE: For multi-center heterogeneous Real-World Data (RWD) with time-to-event outcomes and high-dimensional features, we propose the SurvMaximin algorithm to estimate Cox model feature coefficients for a target population by borrowing summary information from a set of health care centers without sharing patient-level information. MATERIALS AND METHODS: For each of the centers from which we want to borrow information to improve the prediction performance for the target population, a penalized Cox model is fitted to estimate feature coefficients for the center. Using estimated feature coefficients and the covariance matrix of the target population, we then obtain a SurvMaximin estimated set of feature coefficients for the target population. The target population can be an entire cohort comprised of all centers, corresponding to federated learning, or a single center, corresponding to transfer learning. RESULTS: Simulation studies and a real-world international electronic health records application study, with 15 participating health care centers across three countries (France, Germany, and the U.S.), show that the proposed SurvMaximin algorithm achieves comparable or higher accuracy compared with the estimator using only the information of the target site and other existing methods. The SurvMaximin estimator is robust to variations in sample sizes and estimated feature coefficients between centers, which amounts to significantly improved estimates for target sites with fewer observations. CONCLUSIONS: The SurvMaximin method is well suited for both federated and transfer learning in the high-dimensional survival analysis setting. SurvMaximin only requires a one-time summary information exchange from participating centers. Estimated regression vectors can be very heterogeneous. SurvMaximin provides robust Cox feature coefficient estimates without outcome information in the target population and is privacy-preserving.

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.

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.].

Spino-femoral muscles affect sagittal alignment and compensatory recruitment: a new look into soft tissues in adult spinal deformity.

OBJECTIVE: To quantify muscle characteristics (volumes and fat infiltration) and identify their relationship to sagittal malalignment and compensatory mechanism recruitment. METHODS: Female adult spinal deformity patients underwent T1-weighted MRI with a 2-point Dixon protocol from the proximal tibia up to the T12 vertebra. 3D reconstructions of 17 muscles, including extensors and flexors of spine, hip and knee, were obtained. Muscle volume standardized by bone volume and percentage of fat infiltration (Pfat) were calculated. Correlations and regressions were performed. RESULTS: A total of 22 patients were included. Significant correlations were observed between sagittal alignment and muscle parameters. Fat infiltration of the hip and knee flexors and extensors correlated with larger C7-S1 SVA. Smaller spinal flexor/extensor volumes correlated with greater PI-LL mismatch (r = - 0.45 and - 0.51). Linear regression identified volume of biceps femoris as only predictor for PT (R2 = 0.34, p = 0.005) and Pfat of gluteus minimus as only predictor for SVA (R2 = 0.45, p = 0.001). Sagittally malaligned patients with larger PT (26.8° vs. 17.2°) had significantly smaller volume and larger Pfat of gluteus medius, gluteus minimus and biceps femoris, but similar values for gluteus maximus, the hip extensor. CONCLUSION: This study is the first to quantify the relationship between degeneration of spino-femoral muscles and sagittal malalignment. This pathoanatomical study identifies the close relationship between gluteal, hamstring muscles and PT, SVA, which deepens our understanding of the underlying etiology that contributes to adult spinal deformity.

Estimation of spinopelvic muscles' volumes in young asymptomatic subjects: a quantitative analysis.

PURPOSE: Muscles have been proved to be a major component in postural regulation during pathological evolution or aging. Particularly, spinopelvic muscles are recruited for compensatory mechanisms such as pelvic retroversion, or knee flexion. Change in muscles' volume could, therefore, be a marker of greater postural degradation. Yet, it is difficult to interpret spinopelvic muscular degradation as there are few reported values for young asymptomatic adults to compare to. The objective was to provide such reference values on spinopelvic muscles. A model predicting the muscular volume from reduced set of MRI segmented images was investigated. METHODS: A total of 23 asymptomatic subjects younger than 24 years old underwent an MRI acquisition from T12 to the knee. Spinopelvic muscles were segmented to obtain an accurate 3D reconstruction, allowing precise computation of muscle's volume. A model computing the volume of muscular groups from less than six MRI segmented slices was investigated. RESULTS: Baseline values have been reported in tables. For all muscles, invariance was found for the shape factor [ratio of volume over (area times length): SD < 0.04] and volume ratio over total volume (SD < 1.2 %). A model computing the muscular volume from a combination of two to five slices has been evaluated. The five-slices model prediction error (in  % of the real volume from 3D reconstruction) ranged from 6 % (knee flexors and extensors and spine flexors) to 11 % (spine extensors). CONCLUSION: Spinopelvic muscles' values for a reference population have been reported. A new model predicting the muscles' volumes from a reduced set of MRI slices is proposed. While this model still needs to be validated on other populations, the current study appears promising for clinical use to determine, quantitatively, the muscular degradation.

The minimally invasive spinal deformity surgery algorithm: a reproducible rational framework for decision making in minimally invasive spinal deformity surgery.

OBJECT: Minimally invasive surgery (MIS) is an alternative to open deformity surgery for the treatment of patients with adult spinal deformity. However, at this time MIS techniques are not as versatile as open deformity techniques, and MIS techniques have been reported to result in suboptimal sagittal plane correction or pseudarthrosis when used for severe deformities. The minimally invasive spinal deformity surgery (MISDEF) algorithm was created to provide a framework for rational decision making for surgeons who are considering MIS versus open spine surgery. METHODS: A team of experienced spinal deformity surgeons developed the MISDEF algorithm that incorporates a patient's preoperative radiographic parameters and leads to one of 3 general plans ranging from MIS direct or indirect decompression to open deformity surgery with osteotomies. The authors surveyed fellowship-trained spine surgeons experienced with spinal deformity surgery to validate the algorithm using a set of 20 cases to establish interobserver reliability. They then resurveyed the same surgeons 2 months later with the same cases presented in a different sequence to establish intraobserver reliability. Responses were collected and tabulated. Fleiss' analysis was performed using MATLAB software. RESULTS: Over a 3-month period, 11 surgeons completed the surveys. Responses for MISDEF algorithm case review demonstrated an interobserver kappa of 0.58 for the first round of surveys and an interobserver kappa of 0.69 for the second round of surveys, consistent with substantial agreement. In at least 10 cases there was perfect agreement between the reviewing surgeons. The mean intraobserver kappa for the 2 surveys was 0.86 ± 0.15 (± SD) and ranged from 0.62 to 1. CONCLUSIONS: The use of the MISDEF algorithm provides consistent and straightforward guidance for surgeons who are considering either an MIS or an open approach for the treatment of patients with adult spinal deformity. The MISDEF algorithm was found to have substantial inter- and intraobserver agreement. Although further studies are needed, the application of this algorithm could provide a platform for surgeons to achieve the desired goals of surgery.

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.

The impact of a corrective tether on a scoliosis porcine model: a detailed 3D analysis with a 20 weeks follow-up.

PURPOSE: Non-fusion treatment for adolescent idiopathic scoliosis generates interest due to the potential for growth preservation and mobility. Using an established porcine scoliotic model, this study aims to evaluate the global alignment and the morphology of the spine with and without application of a non-fusion corrective tether. METHODS: At 12 weeks of age, 21 immature Yorkshire pigs had an induction of scoliosis. Once a 50° Cobb angle was obtained; animals were placed into one of the following groups: a scoliosis model group (SM, n = 11) where animals were euthanized, tether release group (TR, n = 5) where the inducing tether was removed, and an anterior correction group (AC, n = 5) where the inducing tether was removed and non-fusion corrective tether was applied. TR and AC were observed for a further 20 weeks and then euthanized. Post-mortem CT scans were used to create 3D spinal reconstructions to obtain global and morphologic parameters. RESULTS: Maximal Cobb angle of the scoliotic deformity was significantly lower for AC (27.9° ± 12.0°) than for the two other groups (TR 52.7° ± 10.0°, SM 48.3° ± 7.6°). AC experienced an increase in kyphosis (24.2° ± 15.9°) compared to TR (7.1° ± 6.4°). Correction in the axial plane was also observed in AC versus TR. Correction of vertebral wedging was found for AC compared to SM and TR in the three apical vertebrae. CONCLUSIONS: 3D realignment of scoliotic curves was observed with application of the corrective tether. The correction was the product of both mechanical action and growth modulation. These findings are encouraging for future development of a non-fusion device for the treatment of immature scoliotic curves.

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.

Sacro-femoral-pubic angle: a coronal parameter to estimate pelvic tilt.

INTRODUCTION: Pelvic tilt is an established measure of position which has been tied to sagittal plane spinal deformity. Increased tilt is noted in the setting of the aging spine and sagittal malalignment syndromes such as flatback (compensatory mechanism). However, the femoral heads are often poorly visualized on sagittal films of scoliosis series in adults, limiting the ability to determine pelvic incidence and tilt. There is a need to establish a coronal plane (better visualization) pelvic parameter which correlates closely with pelvic tilt. METHODS: This is a retrospective review of 71 adult patients (47 females and 24 males) with full-length standing spine radiographs. Visualization of all spinal and pelvic landmarks was available coronally and sagittally (including pelvis and acetabuli). Pelvic tilt was calculated through validated digital analysis software (SpineView(®)). A new parameter, the sacro-femoral-pubic angle (midpoint of S1 endplate to centroid of acetabuli to superior border of the pubic symphysis) was analyzed for correlation (and predictive ability) with sagittal pelvic tilt. RESULTS: The sacro-femoral-pubic angle (SFP angle) was highly correlated to PT, and according to this analysis, pelvic tilt could be estimated by the formula: PT = 75 - (SFP angle). A Pearson's correlation coefficient of 0.74 (p < 0.005) and predictive ability of 76% accuracy was obtained (±7.5°). The correlation and predictive ability was greater for males compared to females (male: r = 0.87 and predictive model = 93%; female: r = 0.67 and predictive model = 67%). CONCLUSION: The pelvic tilt is an essential measure in the context of radiographic evaluation of spinal deformity and malalignment. Given the routinely excellent visibility of coronal films this study established the SFP as a coronal parameter which can reliably estimate pelvic tilt. The high correlation and predictive ability of the SFP angle should prompt further study and clinical application when lateral radiographs do not permit assessment of pelvic parameters.

Explicit and automatic ejection fraction assessment on 2D cardiac ultrasound with a deep learning-based approach.

BACKGROUND: Ejection fraction (EF) is a key parameter for assessing cardiovascular functions in cardiac ultrasound, but its manual assessment is time-consuming and subject to high inter and intra-observer variability. Deep learning-based methods have the potential to perform accurate fully automatic EF predictions but suffer from a lack of explainability and interpretability. This study proposes a fully automatic method to reliably and explicitly evaluate the biplane left ventricular EF on 2D echocardiography following the recommended modified Simpson's rule. METHODS: A deep learning model was trained on apical 4 and 2-chamber echocardiography to segment the left ventricle and locate the mitral valve. Predicted segmentations are then validated with a statistical shape model, which detects potential failures that could impact the EF evaluation. Finally, the end-diastolic and end-systolic frames are identified based on the remaining LV segmentations' areas and EF is estimated on all available cardiac cycles. RESULTS: Our approach was trained on a dataset of 783 patients. Its performances were evaluated on an internal and external dataset of respectively 200 and 450 patients. On the internal dataset, EF assessment achieved a mean absolute error of 6.10% and a bias of 1.56 ± 7.58% using multiple cardiac cycles. The approach evaluated EF with a mean absolute error of 5.39% and a bias of -0.74 ± 7.12% on the external dataset. CONCLUSION: Following the recommended guidelines, we proposed an end-to-end fully automatic approach that achieves state-of-the-art performance in biplane EF evaluation while giving explicit details to clinicians.

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.

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.

Changes in laboratory value improvement and mortality rates over the course of the pandemic: an international retrospective cohort study of hospitalised patients infected with SARS-CoV-2.

OBJECTIVE: To assess changes in international mortality rates and laboratory recovery rates during hospitalisation for patients hospitalised with SARS-CoV-2 between the first wave (1 March to 30 June 2020) and the second wave (1 July 2020 to 31 January 2021) of the COVID-19 pandemic. DESIGN, SETTING AND PARTICIPANTS: This is a retrospective cohort study of 83 178 hospitalised patients admitted between 7 days before or 14 days after PCR-confirmed SARS-CoV-2 infection within the Consortium for Clinical Characterization of COVID-19 by Electronic Health Record, an international multihealthcare system collaborative of 288 hospitals in the USA and Europe. The laboratory recovery rates and mortality rates over time were compared between the two waves of the pandemic. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was all-cause mortality rate within 28 days after hospitalisation stratified by predicted low, medium and high mortality risk at baseline. The secondary outcome was the average rate of change in laboratory values during the first week of hospitalisation. RESULTS: Baseline Charlson Comorbidity Index and laboratory values at admission were not significantly different between the first and second waves. The improvement in laboratory values over time was faster in the second wave compared with the first. The average C reactive protein rate of change was -4.72 mg/dL vs -4.14 mg/dL per day (p=0.05). The mortality rates within each risk category significantly decreased over time, with the most substantial decrease in the high-risk group (42.3% in March-April 2020 vs 30.8% in November 2020 to January 2021, p<0.001) and a moderate decrease in the intermediate-risk group (21.5% in March-April 2020 vs 14.3% in November 2020 to January 2021, p<0.001). CONCLUSIONS: Admission profiles of patients hospitalised with SARS-CoV-2 infection did not differ greatly between the first and second waves of the pandemic, but there were notable differences in laboratory improvement rates during hospitalisation. Mortality risks among patients with similar risk profiles decreased over the course of the pandemic. The improvement in laboratory values and mortality risk was consistent across multiple countries.

Delayed Gadolinium Leakage in Ocular Structures: A Potential Marker for Age- and Vascular Risk Factor-Related Small Vessel Disease?

BACKGROUND: Gadolinium leakage in ocular structures (GLOS) was recently observed in fluid-attenuated inversion recovery (FLAIR) images obtained the day after an initial gadolinium injection in stroke patients. The specificity of GLOS to stroke and its mechanisms remain unclear. OBJECTIVE: We investigated the factors associated with GLOS in a cohort of patients presenting with acute neurological deficits. MATERIALS AND METHODS: This retrospective study included consecutive patients admitted to our stroke unit for acute neurological deficit between July 2017 and August 2018 who underwent baseline brain magnetic resonance imaging with the injection of a macrocyclic gadolinium agent and another scan without injection within 72 hours. The patients were separated into a stroke group and a stroke mimic group based on diffusion-weighted images. Gadolinium leakage in ocular structures was defined as a bright signal in the vitreous in follow-up FLAIR compared with baseline FLAIR (pregadolinium). Clinical data were collected together with imaging features from the baseline scans, including the volume of the infarct and of hypoperfusion if applicable, white matter hyperintensities, the number of lacunes, and the number of microbleeds, which were combined to yield a small vessel disease (SVD) score. We compared the prevalence of GLOS in both groups using the χ2 test. In the entire cohort, univariate and multivariate regression models were used to test the associations between GLOS and the collected data. RESULTS: Among the 467 patients included in the study, GLOS was observed in similar proportions in the stroke group (32.2%, 136/422) and the stroke mimic group (28.9%, 13/45; mean difference, 3.3%; 95% confidence interval, -10.9 to 17.6; P = 0.65). In univariate analysis, GLOS was associated with older age, increased prevalence of vascular risk factors, brain imaging features of SVD (white matter hyperintensities, lacunes, microbleeds), as well as with impairment of renal function and increased dose of gadolinium. No associations were found with factors related to stroke, such as its volume, acute treatment, or rate of recanalization. Multivariate analyses showed that aging (P < 0.001), diabetes (P = 0.010), severe renal failure (P = 0.004), and increased dose of gadolinium (P < 0.001) were independent contributors to GLOS. CONCLUSIONS: Gadolinium leakage in ocular structures, which occurs more commonly at higher concentrations of gadolinium, is not specific to stroke and may represent increased permeability of the blood-retinal barrier associated with age- and vascular risk factor-related SVD.

Pre-operative peripheral intravenous cannula insertion failure at the first attempt in adults: Development of the VENSCORE predictive scale and identification of risk factors.

STUDY OBJECTIVE: Our objective was to develop a clinical scale (the VENSCORE) to predict pre-operative peripheral intravenous cannula (PIVC) insertion failure at the first attempt in adults. DESIGN: This was a prospective multicenter cohort study that included internal validation with bootstrapping. SETTING: The operating rooms of 14 hospitals in southern France from June 2016 to June 2018. PATIENTS: Consecutive adult patients aged 18 years or older were recruited upon arrival to the operating room, regardless of American Society of Anaesthesiology (ASA) physical status. INTERVENTIONS: PIVC insertion on arrival to the OR. MEASUREMENTS: PIVC insertion failure at the first attempt was the outcome of interest. Data collected included the number of PIVC insertion attempts and potential predictors of the risk of failure (including pre-operative patient characteristics and data relative to the procedure). Uni- and multivariable logistic analyses were performed. Based on these results, the VENSCORE scale was developed to predict the risk of failure of the first PIVC insertion. MAIN RESULTS: In total, 3394 patients were included, and 27 were excluded because of protocol violations. The PIVC insertion failure rate at the first attempt was 20.3%. Based on multivariable analysis, a history of difficult PIVC insertions, high-risk surgery, poor vein visibility, and moderate to poor vein palpability were identified as risk factors for insertion failure at the first attempt. The area under the curve of the predictive model was 0.82 (95% confidence interval: 0.80-0.84). A VENSCORE value of 0 points was associated with a failure rate of 7%, versus 97% for a score of 6. CONCLUSIONS: The four-item VENSCORE scale could be useful for prospectively identifying adults at risk of first PIVC insertion attempt failure.

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.

International Analysis of Electronic Health Records of Children and Youth Hospitalized With COVID-19 Infection in 6 Countries.

Importance: Additional sources of pediatric epidemiological and clinical data are needed to efficiently study COVID-19 in children and youth and inform infection prevention and clinical treatment of pediatric patients. Objective: To describe international hospitalization trends and key epidemiological and clinical features of children and youth with COVID-19. Design, Setting, and Participants: This retrospective cohort study included pediatric patients hospitalized between February 2 and October 10, 2020. Patient-level electronic health record (EHR) data were collected across 27 hospitals in France, Germany, Spain, Singapore, the UK, and the US. Patients younger than 21 years who tested positive for COVID-19 and were hospitalized at an institution participating in the Consortium for Clinical Characterization of COVID-19 by EHR were included in the study. Main Outcomes and Measures: Patient characteristics, clinical features, and medication use. Results: There were 347 males (52%; 95% CI, 48.5-55.3) and 324 females (48%; 95% CI, 44.4-51.3) in this study's cohort. There was a bimodal age distribution, with the greatest proportion of patients in the 0- to 2-year (199 patients [30%]) and 12- to 17-year (170 patients [25%]) age range. Trends in hospitalizations for 671 children and youth found discrete surges with variable timing across 6 countries. Data from this cohort mirrored national-level pediatric hospitalization trends for most countries with available data, with peaks in hospitalizations during the initial spring surge occurring within 23 days in the national-level and 4CE data. A total of 27 364 laboratory values for 16 laboratory tests were analyzed, with mean values indicating elevations in markers of inflammation (C-reactive protein, 83 mg/L; 95% CI, 53-112 mg/L; ferritin, 417 ng/mL; 95% CI, 228-607 ng/mL; and procalcitonin, 1.45 ng/mL; 95% CI, 0.13-2.77 ng/mL). Abnormalities in coagulation were also evident (D-dimer, 0.78 ug/mL; 95% CI, 0.35-1.21 ug/mL; and fibrinogen, 477 mg/dL; 95% CI, 385-569 mg/dL). Cardiac troponin, when checked (n = 59), was elevated (0.032 ng/mL; 95% CI, 0.000-0.080 ng/mL). Common complications included cardiac arrhythmias (15.0%; 95% CI, 8.1%-21.7%), viral pneumonia (13.3%; 95% CI, 6.5%-20.1%), and respiratory failure (10.5%; 95% CI, 5.8%-15.3%). Few children were treated with COVID-19-directed medications. Conclusions and Relevance: This study of EHRs of children and youth hospitalized for COVID-19 in 6 countries demonstrated variability in hospitalization trends across countries and identified common complications and laboratory abnormalities in children and youth with COVID-19 infection. Large-scale informatics-based approaches to integrate and analyze data across health care systems complement methods of disease surveillance and advance understanding of epidemiological and clinical features associated with COVID-19 in children and youth.