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Background More than one-third of individuals experience post-acute sequelae of SARS-CoV-2 infection (PASC, which includes long-COVID). The objective is to identify risk factors associated with PASC/long-COVID diagnosis. Methods This was a retrospective case–control study including 31 health systems in the United States from the National COVID Cohort Collaborative (N3C). 8,325 individuals with PASC (defined by the presence of the International Classification of Diseases, version 10 code U09.9 or a long-COVID clinic visit) matched to 41,625 controls within the same health system and COVID index date within ± 45 days of the corresponding case's earliest COVID index date. Measurements of risk factors included demographics, comorbidities, treatment and acute characteristics related to COVID-19. Multivariable logistic regression, random forest, and XGBoost were used to determine the associations between risk factors and PASC. Results Among 8,325 individuals with PASC, the majority were > 50 years of age (56.6%), female (62.8%), and non-Hispanic White (68.6%). In logistic regression, middle-age categories (40 to 69 years; OR ranging from 2.32 to 2.58), female sex (OR 1.4, 95% CI 1.33–1.48), hospitalization associated with COVID-19 (OR 3.8, 95% CI 3.05–4.73), long (8–30 days, OR 1.69, 95% CI 1.31–2.17) or extended hospital stay (30 + days, OR 3.38, 95% CI 2.45–4.67), receipt of mechanical ventilation (OR 1.44, 95% CI 1.18–1.74), and several comorbidities including depression (OR 1.50, 95% CI 1.40–1.60), chronic lung disease (OR 1.63, 95% CI 1.53–1.74), and obesity (OR 1.23, 95% CI 1.16–1.3) were associated with increased likelihood of PASC diagnosis or care at a long-COVID clinic. Characteristics associated with a lower likelihood of PASC diagnosis or care at a long-COVID clinic included younger age (18 to 29 years), male sex, non-Hispanic Black race, and comorbidities such as substance abuse, cardiomyopathy, psychosis, and dementia. More doctors per capita in the county of residence was associated with an increased likelihood of PASC diagnosis or care at a long-COVID clinic. Our findings were consistent in sensitivity analyses using a variety of analytic techniques and approaches to select controls. Conclusions This national study identified important risk factors for PASC diagnosis such as middle age, severe COVID-19 disease, and specific comorbidities. Further clinical and epidemiological research is needed to better understand underlying mechanisms and the potential role of vaccines and therapeutics in altering PASC course.

Data sharing is necessary to maximize the actionable knowledge generated from research data. Data challenges can encourage secondary analyses of datasets. Data challenges in biomedicine often rely on advanced cloud-based computing infrastructure and expensive industry partnerships. Examples include challenges that use Google Cloud virtual machines and the Sage Bionetworks Dream Challenges platform. Such robust infrastructures can be financially prohibitive for investigators without substantial resources. Given the potential to develop scientific and clinical knowledge and the NIH emphasis on data sharing and reuse, there is a need for inexpensive and computationally lightweight methods for data sharing and hosting data challenges. To fill that gap, we developed a workflow that allows for reproducible model training, testing, and evaluation. We leveraged public GitHub repositories, open-source computational languages, and Docker technology. In addition, we conducted a data challenge using the infrastructure we developed. In this manuscript, we report on the infrastructure, workflow, and data challenge results. The infrastructure and workflow are likely to be useful for data challenges and education.

Hypocalcemia is a frequent complication of thyroidectomy. Although typically mild and temporary, it can lead to an increased length of stay, readmission, and in some cases be permanent. Controversy exists as to whether vitamin D deficiency (VDD) contributes to post-thyroidectomy hypocalcemia. This is a retrospective study of 152 patients who underwent thyroidectomy. Patients with or without VDD were compared. Data were analyzed for demographics, operative procedure, calcium levels, and complications of hypocalcemia. There was no difference in the rates of biochemical or symptomatic hypocalcemia or in the need for readmission between the VDD and non-VDD groups. A multivariate analysis controlling for central neck dissection, parathyroid autotransplant, and preoperative diagnosis confirmed no association between VDD and post-thyroidectomy hypocalcemia. Despite VDD being common in patients undergoing thyroidectomy, our results do not suggest that this increases the rate of hypocalcemia. Thus, preoperative evaluation/repletion of VDD is unlikely to reduce post-thyroidectomy hypocalcemia rates.

Understanding of SARS-CoV-2 infection in US children has been limited by the lack of large, multicenter studies with granular data. To examine the characteristics, changes over time, outcomes, and severity risk factors of children with SARS-CoV-2 within the National COVID Cohort Collaborative (N3C). A prospective cohort study of encounters with end dates before September 24, 2021, was conducted at 56 N3C facilities throughout the US. Participants included children younger than 19 years at initial SARS-CoV-2 testing. Case incidence and severity over time, demographic and comorbidity severity risk factors, vital sign and laboratory trajectories, clinical outcomes, and acute COVID-19 vs multisystem inflammatory syndrome in children (MIS-C), and Delta vs pre-Delta variant differences for children with SARS-CoV-2. A total of 1 068 410 children were tested for SARS-CoV-2 and 167 262 test results (15.6%) were positive (82 882 [49.6%] girls; median age, 11.9 [IQR, 6.0-16.1] years). Among the 10 245 children (6.1%) who were hospitalized, 1423 (13.9%) met the criteria for severe disease: mechanical ventilation (796 [7.8%]), vasopressor-inotropic support (868 [8.5%]), extracorporeal membrane oxygenation (42 [0.4%]), or death (131 [1.3%]). Male sex (odds ratio [OR], 1.37; 95% CI, 1.21-1.56), Black/African American race (OR, 1.25; 95% CI, 1.06-1.47), obesity (OR, 1.19; 95% CI, 1.01-1.41), and several pediatric complex chronic condition (PCCC) subcategories were associated with higher severity disease. Vital signs and many laboratory test values from the day of admission were predictive of peak disease severity. Variables associated with increased odds for MIS-C vs acute COVID-19 included male sex (OR, 1.59; 95% CI, 1.33-1.90), Black/African American race (OR, 1.44; 95% CI, 1.17-1.77), younger than 12 years (OR, 1.81; 95% CI, 1.51-2.18), obesity (OR, 1.76; 95% CI, 1.40-2.22), and not having a pediatric complex chronic condition (OR, 0.72; 95% CI, 0.65-0.80). The children with MIS-C had a more inflammatory laboratory profile and severe clinical phenotype, with higher rates of invasive ventilation (117 of 707 [16.5%] vs 514 of 8241 [6.2%]; P < .001) and need for vasoactive-inotropic support (191 of 707 [27.0%] vs 426 of 8241 [5.2%]; P < .001) compared with those who had acute COVID-19. Comparing children during the Delta vs pre-Delta eras, there was no significant change in hospitalization rate (1738 [6.0%] vs 8507 [6.2%]; P = .18) and lower odds for severe disease (179 [10.3%] vs 1242 [14.6%]) (decreased by a factor of 0.67; 95% CI, 0.57-0.79; P < .001). In this cohort study of US children with SARS-CoV-2, there were observed differences in demographic characteristics, preexisting comorbidities, and initial vital sign and laboratory values between severity subgroups. Taken together, these results suggest that early identification of children likely to progress to severe disease could be achieved using readily available data elements from the day of admission. Further work is needed to translate this knowledge into improved outcomes.

This diagnostic study assesses the ability of a pediatric blood pressure percentile tool to accelerate identification of children with hypertension and hypotension by clinicians and researchers.

Background Epigenetic clocks have been used to indicate differences in biological states between individuals of same chronological age. However, so far, only few studies have examined epigenetic aging in newborns—especially regarding different gestational or perinatal tissues. In this study, we investigated which birth- and pregnancy-related variables are most important in predicting gestational epigenetic age acceleration or deceleration (i.e., the deviation between gestational epigenetic age estimated from the DNA methylome and chronological gestational age) in chorionic villus, placenta and cord blood tissues from two independent study cohorts (ITU, n = 639 and PREDO, n = 966). We further characterized the correspondence of epigenetic age deviations between these tissues. Results Among the most predictive factors of epigenetic age deviations in single tissues were child sex, birth length, maternal smoking during pregnancy, maternal mental disorders until childbirth, delivery mode and parity. However, the specific factors related to epigenetic age deviation and the direction of association differed across tissues. In individuals with samples available from more than one tissue, relative epigenetic age deviations were not correlated across tissues. Conclusion Gestational epigenetic age acceleration or deceleration was not related to more favorable or unfavorable factors in one direction in the investigated tissues, and the relative epigenetic age differed between tissues of the same person. This indicates that epigenetic age deviations associate with distinct, tissue specific, factors during the gestational and perinatal period. Our findings suggest that the epigenetic age of the newborn should be seen as a characteristic of a specific tissue, and less as a general characteristic of the child itself.

Abstract PurposeDistinguishing between acute and chronic vertebral compression fractures typically requires advanced imaging techniques such as magnetic resonance imaging (MRI). Recognizing specific radiographic findings associated with fracture acuity may improve the accuracy of radiographic assessment.MethodsPatients with compression fractures that had both radiographic and MRI studies of the lumbar spine within a 30-day time frame were retrospectively reviewed. MRI studies were used to determine compression fracture acuity. Radiographs were interpreted by a separate group of radiologists blinded to the MRI results. Radiographic findings of endplate osteophyte, subendplate density, subendplate cleft, and subendplate cyst were recorded as was the overall impression of fracture acuity.ResultsSensitivity and specificity for radiographic reporting of acute fracture were 0.52 (95% CI: 0.42, 0.61) and 0.95 (95% CI: 0.93, 0.97) respectively. For chronic fractures, the sensitivity and specificity were 0.52 (95% CI: 0.41, 0.63) and 0.94 (95% CI: 0.92, 0.96).The radiographic presence of a subendplate cleft increased the odds of a fracture being acute by a factor of 1.75 (95% CI: 1.09, 2.81; P = 0.0202). The radiographic presence of subendplate density increased the odds of a fracture being acute by a factor of 1.78 (95% CI: 1.21, 2.63; P = 0.0037). The presence of an endplate osteophyte or subendplate cyst was not significantly associated with fracture acuity.ConclusionRadiographs are relatively insensitive in distinguishing between acute and chronic lumbar compression fractures but the presence of a subendplate cleft or subendplate density increases the likelihood that a given fracture is acute.

Introduction and hypothesisPatient safety data including rates of obstetric anal sphincter injury (OASI) are often derived from hospital discharge codes. With the transition to electronic medical records (EMRs), we hypothesized that electronic provider-entered delivery data would more accurately document obstetric perineal injury than traditional billing/diagnostic codes.MethodsWe evaluated the accuracy of perineal laceration diagnoses after singleton vaginal deliveries during one calendar year at an American tertiary academic medical center. We reviewed the entire hospital chart to determine the most likely laceration diagnosis and compared that expert review diagnosis (ExpRD) with documentation in the EMR delivery summary (EDS) and ICD-9 diagnostic codes (IDCs).ResultsWe retrospectively selected 354 total delivery records. OASI complicated 56 of those. 303 records (86%) were coded identically by the EDS and IDCs. Diagnoses from the IDCs and the EDS were mostly correct compared with ExpRD (sensitivity = 96%, specificity = 100%). There was no systematic over- or under-diagnosis of OASI for either the EDS (p = 0.070) or the IDCs (p = 0.447). When considering all laceration types the EDS was correct for 21 (5.9%) lacerations that were incorrect according to the IDCs. Overall, the EDS was more accurate (p < 0.05) owing to errors in IDC minor laceration diagnoses.ConclusionsElectronic medical record delivery summary data and EMR-derived diagnostic codes similarly characterize OASI. The EDS does not improve OASI reporting, but may be more accurate when considering all perineal lacerations. This assumes that providers have correctly identified and categorized the lacerations that they record in the EMR.

Objectives The publication of the Phoenix criteria for pediatric sepsis and septic shock initiates a new era in clinical care and research of pediatric sepsis. Tools to consistently and accurately apply the Phoenix criteria to electronic health records (EHRs) is one part of building a robust and internally consistent body of research across multiple research groups and datasets. Materials and Methods We developed the phoenix R package and Python module to provide researchers with intuitive and simple functions to apply the Phoenix criteria to EHR data. Results The phoenix R package and Python module enable researchers to apply the Phoenix criteria to EHR datasets and derive the relevant indicators, total scores, and sub-scores. Discussion The transition to the Phoenix criteria marks a major change in the conceptual definition of pediatric sepsis. Applicable across differentially resourced settings, the Phoenix criteria should help improve clinical care and research. Conclusion The phoenix R package and Python model are freely available on CRAN, PyPi, and GitHub. These tools enable the consistent and accurate application of the Phoenix criteria to EHR datasets. Lay Summary The Phoenix criteria for pediatric sepsis and septic shock mark the beginning of a new era for clinical care and research of pediatric sepsis. The new criteria represent a conceptual shift in defining sepsis, moving away from an inflammatory based criteria to life-threatening organ dysfunction based criteria. As these new diagnostic criteria move to the bedside and research areas, the need to consistently and accurately apply the Phoenix criteria to electronic health records (EHR) data is necessary to build a robust and internally consistent body of research. We developed the phoenix R package and Python module. These 2 freely available tools, along with example SQL queries, provide pediatric sepsis researchers the means to apply the Phoenix criteria to EHR data without needing to implement the criteria themselves. The use of phoenix will reduce sources of error in research and provide a common implementation for multiple research groups, across multiple data formats, and multiple programming paradigms.

ABSTRACT Context Chronic stress is a risk factor for preterm birth; however, objective measures of stress in pregnancy are limited. Maternal stress biomarkers may fill this gap. Steroid hormones and neurosteroids such as allopregnanolone (ALLO) play important roles in stress physiology and pregnancy maintenance and therefore may be promising for preterm birth prediction. Objective We evaluated maternal serum ALLO, progesterone, cortisol, cortisone, pregnanolone, and epipregnanolone twice in gestation to evaluate associations with preterm birth. Methods We performed a nested case-control study using biobanked fasting serum samples from the Healthy Start prebirth cohort. We included healthy women with a singleton pregnancy and matched preterm cases with term controls (1:1; N = 27 per group). We used a new HPLC-tandem mass spectrometry assay to quantify ALLO and five related steroids. We used ANOVA, Fisher exact, χ2, t test, and linear and logistic regression as statistical tests. Results Maternal serum ALLO did not associate with preterm birth nor differ between groups. Mean cortisol levels were significantly higher in the preterm group early in pregnancy (13w0d-18w0d; P < 0.05) and higher early pregnancy cortisol associated with increased odds of preterm birth (at 13w0d; odds ratio, 1.007; 95% CI, 1.0002-1.014). Progesterone, cortisone, pregnanolone, and epipregnanolone did not associate with preterm birth. Conclusion The findings from our pilot study suggest potential utility of cortisol as a maternal serum biomarker for preterm birth risk assessment in early pregnancy. Further evaluation using larger cohorts and additional gestational timepoints for ALLO and the other analytes may be informative.