A comparison of respiratory oscillometry and spirometry in idiopathic pulmonary fibrosis: performance time, symptom burden and test-retest reliability.

Study question: In large multinational patient surveys, spirometry (which requires repeated, reproducible maximal efforts) can be associated with cough, breathlessness and tiredness, particularly in those with idiopathic pulmonary fibrosis (IPF). Oscillometry is an effort-independent test of airways resistance and reactance. We hypothesised that oscillometry would take less time to perform and would be associated with reduced symptom burden than spirometry. Patients and methods: Spirometry and oscillometry were performed in 66 participants with IPF and repeated 2 weeks later. We compared time taken to perform tests, symptom burden and test-retest reliability with Bland-Altman plots and intraclass correlation coefficients (ICCs). Results: Oscillometry took significantly less time to perform than spirometry (mean -4.5 (99% CI -6.0 to -3.0) min) and was associated with lower symptom burden scores for cough (-1.3, 99% CI -1.7 to -0.8), breathlessness (-1.0, 99% CI -1.4 to -0.5), and tiredness (-0.5, 99% CI -0.9 to -0.2). On Bland-Altman analysis, all measures showed good agreement, with narrow limits of agreement and the mean bias lying close to 0 in all cases. The ICCs for forced expiratory volume in 1 s and forced vital capacity were 0.94 and 0.89, respectively, and ranged between 0.70 and 0.90 for oscillometry measures. Conclusion: Oscillometry is quicker to perform and provokes less symptoms than spirometry in patients with IPF.

Targeted multiplex validation of CSF proteomic biomarkers: implications for differentiation of PCNSL from tumor-free controls and other brain tumors.

Introduction: Primary central nervous system lymphoma (PCNSL) is a rare type of non-Hodgkin's lymphoma that affects brain parenchyma, eyes, cerebrospinal fluid, and spinal cord. Diagnosing PCNSL can be challenging because imaging studies often show similar patterns as other brain tumors, and stereotactic brain lesion biopsy conformation is invasive and not always possible. This study aimed to validate a previous proteomic profiling (PMID: 32610669) of cerebrospinal fluid (CSF) and develop a CSF-based proteomic panel for accurate PCNSL diagnosis and differentiation. Methods: CSF samples were collected from patients of 30 PCNSL, 30 other brain tumors, and 31 tumor-free/benign controls. Liquid chromatography tandem-mass spectrometry targeted proteomics analysis was used to establish CSF-based proteomic panels. Results: Final proteomic panels were selected and optimized to diagnose PCNSL from tumor-free controls or other brain tumor lesions with an area under the curve (AUC) of 0.873 (95%CI: 0.723-0.948) and 0.937 (95%CI: 0.807- 0.985), respectively. Pathways analysis showed diagnosis panel features were significantly enriched in pathways related to extracellular matrices-receptor interaction, focal adhesion, and PI3K-Akt signaling, while prion disease, mineral absorption and HIF-1 signaling were significantly enriched with differentiation panel features. Discussion: This study suggests an accurate clinical test panel for PCNSL diagnosis and differentiation with CSF-based proteomic signatures, which may help overcome the challenges of current diagnostic methods and improve patient outcomes.

Impact of environmental air pollution on respiratory health and function.

Environmental air pollution presents a considerable risk to global respiratory health. If critical levels are exceeded, inhaled pollutants can lead to the development of respiratory dysfunction and provoke exacerbation in those with pre-existing chronic respiratory disease. Over 90% of the global population currently reside in areas where environmental air pollution is considered excessive-with adverse effects ranging from acute airway irritation to complex immunomodulatory alterations. This narrative review provides an up-to-date perspective concerning the impact of environmental air pollution on respiratory health and function and describes the underpinning mechanisms that contribute to the development and progression of chronic respiratory disease.

Comparing performance of primary care clinicians in the interpretation of SPIROmetry with or without Artificial Intelligence Decision support software (SPIRO-AID): a protocol for a randomised controlled trial.

INTRODUCTION: Spirometry is a point-of-care lung function test that helps support the diagnosis and monitoring of chronic lung disease. The quality and interpretation accuracy of spirometry is variable in primary care. This study aims to evaluate whether artificial intelligence (AI) decision support software improves the performance of primary care clinicians in the interpretation of spirometry, against reference standard (expert interpretation). METHODS AND ANALYSIS: A parallel, two-group, statistician-blinded, randomised controlled trial of primary care clinicians in the UK, who refer for, or interpret, spirometry. People with specialist training in respiratory medicine to consultant level were excluded. A minimum target of 228 primary care clinician participants will be randomised with a 1:1 allocation to assess fifty de-identified, real-world patient spirometry sessions through an online platform either with (intervention group) or without (control group) AI decision support software report. Outcomes will cover primary care clinicians' spirometry interpretation performance including measures of technical quality assessment, spirometry pattern recognition and diagnostic prediction, compared with reference standard. Clinicians' self-rated confidence in spirometry interpretation will also be evaluated. The primary outcome is the proportion of the 50 spirometry sessions where the participant's preferred diagnosis matches the reference diagnosis. Unpaired t-tests and analysis of covariance will be used to estimate the difference in primary outcome between intervention and control groups. ETHICS AND DISSEMINATION: This study has been reviewed and given favourable opinion by Health Research Authority Wales (reference: 22/HRA/5023). Results will be submitted for publication in peer-reviewed journals, presented at relevant national and international conferences, disseminated through social media, patient and public routes and directly shared with stakeholders. TRIAL REGISTRATION NUMBER: NCT05933694.

EFFICACY OF INTRAVENOUS IMMUNOGLOBULIN ALONE ON CORONARY ARTERY LESION REDUCTION IN KAWASAKI DISEASE.

Background: Though Aspirin and intravenous immunoglobulin (IVIG) remain the standard treatments for Kawasaki Disease (KD) to minimize coronary artery damage, the duration and dosage of aspirin are inconsistent across hospitals. However, the lack of multi-center randomized trials prevents definitive answers to the impact of high-dose aspirin. Methods: This clinical trial was structured as a prospective, evaluator-blinded, multi-center randomized controlled trial with two parallel arms, aiming to assess the effectiveness of IVIG as a standalone primary therapy of KD in comparison to the combination of IVIG with high-dose aspirin therapy. KD patients were enrolled between September, 2016 and August, 2019. A final cohort of 134 patients were randomly assigned to the standard and test groups with 69 and 65 patients, respectively. The Standard group received IVIG (2 g/kg) along with aspirin (80-100 mg/kg/day) until fever subsided for 48 hours. The test group received IVIG (2 g/kg) alone. Following the initial treatment, both groups received a daily aspirin dose (3-5 mg/kg) for six weeks. The primary outcome measure was the occurrence of coronary artery lesions (CAL) at the 6-8 weeks mark. The secondary outcome is IVIG resistance. Results: The overall rate of CAL in test group decreased from 10.8% at diagnosis to 1.5% and 3.1% at 6 weeks and 6 months, respectively. The CAL rate of standard group declined from 13.0% to 2.9% and 1.4%, with no statistically significant difference (P>0.1) in the frequency of CAL between the two groups. Furthermore, no statistically significant differences were found for treatment (P>0.1) and prevention (P>0.1) effect between the two groups. Conclusions: This marks the first prospective multi-center randomized controlled trial comparing the standard treatment of KD using IVIG plus high-dose aspirin against IVIG alone. Our analysis indicates that addition of high-dose aspirin during initial IVIG treatment is neither statistically significant nor clinically meaningful for CAL reduction. Registration: URL: http://www.clinicaltrials.gov ; identifier: NCT02951234. What is New?: This study represents the first multi-center randomized controlled trial investigating the efficacy of high-dose aspirin or intravenous immunoglobulin (IVIG) during the acute stage of KD. This study assessed the impact of discontinuing high-dose aspirin (80-100 mg/kg/day) on the occurrence of CAL during the acute phase treatment of Kawasaki Disease.No significant differences were observed between high-dose aspirin plus IVIG treatment and IVIG alone treatment in terms of the frequency of abnormal coronary artery abnormalities. Additionally, our analysis revealed no statistically significant differences in either the treatment effect (the number of cases successfully treated) or prevention effect (the prevention of new cases) between these two treatments. What Are the Clinical Implications?: Comparison analysis indicated the non-inferiority between two groups with or without high-dose aspirin.Administering the standard 2 g/kg/day IVIG without high-dose aspirin (80-100 mg/kg/day) during the acute phase therapy for KD does not increase the risk of coronary artery lesions, which are a primary cause of morbidity and mortality in KD patients.Addition of high-dose aspirin during initial IVIG treatment is not statistically significant or clinically meaningful.

ERS International Congress 2023: highlights from the Allied Respiratory Professionals Assembly.

This article summarises some of the outstanding sessions that were (co)organised by the Allied Respiratory Professionals Assembly during the 2023 European Respiratory Society International Congress. Two sessions from each Assembly group are outlined, covering the following topics: Group 9.01 focuses on respiratory physiology techniques, specifically on predicted values and reference equations, device development and novel applications of cardiopulmonary exercise tests; Group 9.02 presents an overview of the talks given at the mini-symposium on exercise training, physical activity and self-management at home and outlines some of the best abstracts in respiratory physiotherapy; Group 9.03 highlights the nursing role in global respiratory health and presents nursing interventions and outcomes; and Group 9.04 provides an overview of the best abstracts and recent advances in behavioural science and health psychology. This Highlights article provides valuable insight into the latest scientific data and emerging areas affecting the clinical practice of Allied Respiratory Professionals.

Global metabolomics revealed deviations from the metabolic aging clock in colorectal cancer patients.

Background: Markers of aging hold promise in the context of colorectal cancer (CRC) care. Utilizing high-resolution metabolomic profiling, we can unveil distinctive age-related patterns that have the potential to predict early CRC development. Our study aims to unearth a panel of aging markers and delve into the metabolomic alterations associated with aging and CRC. Methods: We assembled a serum cohort comprising 5,649 individuals, consisting of 3,002 healthy volunteers, 715 patients diagnosed with colorectal advanced precancerous lesions (APL), and 1,932 CRC patients, to perform a comprehensive metabolomic analysis. Results: We successfully identified unique age-associated patterns across 42 metabolic pathways. Moreover, we established a metabolic aging clock, comprising 9 key metabolites, using an elastic net regularized regression model that accurately estimates chronological age. Notably, we observed significant chronological disparities among the healthy population, APL patients, and CRC patients. By combining the analysis of circulative carcinoembryonic antigen levels with the categorization of individuals into the "hypo" metabolic aging subgroup, our blood test demonstrates the ability to detect APL and CRC with positive predictive values of 68.4% (64.3%, 72.2%) and 21.4% (17.8%, 25.9%), respectively. Conclusions: This innovative approach utilizing our metabolic aging clock holds significant promise for accurately assessing biological age and enhancing our capacity to detect APL and CRC.

Wnt/ß-catenin signaling activation promotes lipogenesis in the steatotic liver via physical mTOR interaction.

Background and aims: Wnt/ß-catenin signaling plays an important role in regulating hepatic metabolism. This study is to explore the molecular mechanisms underlying the potential crosstalk between Wnt/ß-catenin and mTOR signaling in hepatic steatosis. Methods: Transgenic mice (overexpress Wnt1 in hepatocytes, Wnt+) mice and wild-type littermates were given high fat diet (HFD) for 12 weeks to induce hepatic steatosis. Mouse hepatocytes cells (AML12) and those transfected to cause constitutive ß-catenin stabilization (S33Y) were treated with oleic acid for lipid accumulation. Results: Wnt+ mice developed more hepatic steatosis in response to HFD. Immunoblot shows a significant increase in the expression of fatty acid synthesis-related genes (SREBP-1 and its downstream targets ACC, AceCS1, and FASN) and a decrease in fatty acid oxidation gene (MCAD) in Wnt+ mice livers under HFD. Wnt+ mice also revealed increased Akt signaling and its downstream target gene mTOR in response to HFD. In vitro, increased lipid accumulation was detected in S33Y cells in response to oleic acid compared to AML12 cells reinforcing the in vivo findings. mTOR inhibition by rapamycin led to a down-regulation of fatty acid synthesis in S33Y cells. In addition, ß-catenin has a physical interaction with mTOR as verified by co-immunoprecipitation in hepatocytes. Conclusions: Taken together, our results demonstrate that ß-catenin stabilization through Wnt signaling serves a central role in lipid metabolism in the steatotic liver through up-regulation of fatty acid synthesis via Akt/mTOR signaling. These findings suggest hepatic Wnt signaling may represent a therapeutic strategy in hepatic steatosis.

Exploring the feasibility of using long-term stored newborn dried blood spots to identify metabolic features for congenital heart disease screening.

Congenital heart disease (CHD) represents a significant contributor to both morbidity and mortality in neonates and children. There's currently no analogous dried blood spot (DBS) screening for CHD immediately after birth. This study was set to assess the feasibility of using DBS to identify reliable metabolite biomarkers with clinical relevance, with the aim to screen and classify CHD utilizing the DBS. We assembled a cohort of DBS datasets from the California Department of Public Health (CDPH) Biobank, encompassing both normal controls and three pre-defined CHD categories. A DBS-based quantitative metabolomics method was developed using liquid chromatography with tandem mass spectrometry (LC-MS/MS). We conducted a correlation analysis comparing the absolute quantitated metabolite concentration in DBS against the CDPH NBS records to verify the reliability of metabolic profiling. For hydrophilic and hydrophobic metabolites, we executed significant pathway and metabolite analyses respectively. Logistic and LightGBM models were established to aid in CHD discrimination and classification. Consistent and reliable quantification of metabolites were demonstrated in DBS samples stored for up to 15 years. We discerned dysregulated metabolic pathways in CHD patients, including deviations in lipid and energy metabolism, as well as oxidative stress pathways. Furthermore, we identified three metabolites and twelve metabolites as potential biomarkers for CHD assessment and subtypes classifying. This study is the first to confirm the feasibility of validating metabolite profiling results using long-term stored DBS samples. Our findings highlight the potential clinical applications of our DBS-based methods for CHD screening and subtype classification.

High-throughput quantitation of amino acids and acylcarnitine in cerebrospinal fluid: identification of PCNSL biomarkers and potential metabolic messengers.

Background: Due to the poor prognosis and rising occurrence, there is a crucial need to improve the diagnosis of Primary Central Nervous System Lymphoma (PCNSL), which is a rare type of non-Hodgkin's lymphoma. This study utilized targeted metabolomics of cerebrospinal fluid (CSF) to identify biomarker panels for the improved diagnosis or differential diagnosis of primary central nervous system lymphoma (PCNSL). Methods: In this study, a cohort of 68 individuals, including patients with primary central nervous system lymphoma (PCNSL), non-malignant disease controls, and patients with other brain tumors, was recruited. Their cerebrospinal fluid samples were analyzed using the Ultra-high performance liquid chromatography - tandem mass spectrometer (UHPLC-MS/MS) technique for targeted metabolomics analysis. Multivariate statistical analysis and logistic regression modeling were employed to identify biomarkers for both diagnosis (Dx) and differential diagnosis (Diff) purposes. The Dx and Diff models were further validated using a separate cohort of 34 subjects through logistic regression modeling. Results: A targeted analysis of 45 metabolites was conducted using UHPLC-MS/MS on cerebrospinal fluid (CSF) samples from a cohort of 68 individuals, including PCNSL patients, non-malignant disease controls, and patients with other brain tumors. Five metabolic features were identified as biomarkers for PCNSL diagnosis, while nine metabolic features were found to be biomarkers for differential diagnosis. Logistic regression modeling was employed to validate the Dx and Diff models using an independent cohort of 34 subjects. The logistic model demonstrated excellent performance, with an AUC of 0.83 for PCNSL vs. non-malignant disease controls and 0.86 for PCNSL vs. other brain tumor patients. Conclusion: Our study has successfully developed two logistic regression models utilizing metabolic markers in cerebrospinal fluid (CSF) for the diagnosis and differential diagnosis of PCNSL. These models provide valuable insights and hold promise for the future development of a non-invasive and reliable diagnostic tool for PCNSL.

Altered expression of the L-arginine/nitric oxide pathway in ovarian cancer: metabolic biomarkers and biological implications.

MOTIVATION: Ovarian cancer (OC) is a highly lethal gynecological malignancy. Extensive research has shown that OC cells undergo significant metabolic alterations during tumorigenesis. In this study, we aim to leverage these metabolic changes as potential biomarkers for assessing ovarian cancer. METHODS: A functional module-based approach was utilized to identify key gene expression pathways that distinguish different stages of ovarian cancer (OC) within a tissue biopsy cohort. This cohort consisted of control samples (n = 79), stage I/II samples (n = 280), and stage III/IV samples (n = 1016). To further explore these altered molecular pathways, minimal spanning tree (MST) analysis was applied, leading to the formulation of metabolic biomarker hypotheses for OC liquid biopsy. To validate, a multiple reaction monitoring (MRM) based quantitative LCMS/MS method was developed. This method allowed for the precise quantification of targeted metabolite biomarkers using an OC blood cohort comprising control samples (n = 464), benign samples (n = 3), and OC samples (n = 13). RESULTS: Eleven functional modules were identified as significant differentiators (false discovery rate, FDR < 0.05) between normal and early-stage, or early-stage and late-stage ovarian cancer (OC) tumor tissues. MST analysis revealed that the metabolic L-arginine/nitric oxide (L-ARG/NO) pathway was reprogrammed, and the modules related to "DNA replication" and "DNA repair and recombination" served as anchor modules connecting the other nine modules. Based on this analysis, symmetric dimethylarginine (SDMA) and arginine were proposed as potential liquid biopsy biomarkers for OC assessment. Our quantitative LCMS/MS analysis on our OC blood cohort provided direct evidence supporting the use of the SDMA-to-arginine ratio as a liquid biopsy panel to distinguish between normal and OC samples, with an area under the ROC curve (AUC) of 98.3%. CONCLUSION: Our comprehensive analysis of tissue genomics and blood quantitative LC/MSMS metabolic data shed light on the metabolic reprogramming underlying OC pathophysiology. These findings offer new insights into the potential diagnostic utility of the SDMA-to-arginine ratio for OC assessment. Further validation studies using adequately powered OC cohorts are warranted to fully establish the clinical effectiveness of this diagnostic test.

The association of cardiorespiratory fitness with spirometric small airway obstruction.

Spirometric small airway obstruction is associated with impaired ventilatory response to exercise independently of FEV1/FVC ratio https://bit.ly/3pre4sk.

European Respiratory Society/American Thoracic Society technical statement: standardisation of the measurement of lung volumes, 2023 update.

This document updates the 2005 European Respiratory Society (ERS) and American Thoracic Society (ATS) technical standard for the measurement of lung volumes. The 2005 document integrated the recommendations of an ATS/ERS task force with those from an earlier National Heart, Lung, and Blood Institute workshop that led to the publication of background papers between 1995 and 1999 and a consensus workshop report with more in-depth descriptions and discussion. Advancements in hardware and software, new research and emerging approaches have necessitated an update to the 2005 technical standard to guide laboratory directors, physiologists, operators, pulmonologists and manufacturers. Key updates include standardisation of linked spirometry, new equipment quality control and validation recommendations, generalisation of the multiple breath washout concept beyond nitrogen, a new acceptability and grading system with addition of example tracings, and a brief review of imaging and other new techniques to measure lung volumes. Future directions and key research questions are also noted.

Development of a Urine Metabolomics Biomarker-Based Prediction Model for Preeclampsia during Early Pregnancy.

Preeclampsia (PE) is a condition that poses a significant risk of maternal mortality and multiple organ failure during pregnancy. Early prediction of PE can enable timely surveillance and interventions, such as low-dose aspirin administration. In this study, conducted at Stanford Health Care, we examined a cohort of 60 pregnant women and collected 478 urine samples between gestational weeks 8 and 20 for comprehensive metabolomic profiling. By employing liquid chromatography mass spectrometry (LCMS/MS), we identified the structures of seven out of 26 metabolomics biomarkers detected. Utilizing the XGBoost algorithm, we developed a predictive model based on these seven metabolomics biomarkers to identify individuals at risk of developing PE. The performance of the model was evaluated using 10-fold cross-validation, yielding an area under the receiver operating characteristic curve of 0.856. Our findings suggest that measuring urinary metabolomics biomarkers offers a noninvasive approach to assess the risk of PE prior to its onset.

ERS International Congress 2022: highlights from the Allied Respiratory Professionals Assembly.

In this article, we provide a brief overview of some of the outstanding sessions that were (co)organised by the Allied Respiratory Professionals Assembly during the 2022 European Respiratory Society International Congress, which was held in a hybrid format. Early Career Members from Assembly 9 summarised the content of the sessions, with the support of the Officers from the four Assembly groups: Respiratory Function Technologists and Scientists (Group 9.01); Physiotherapists (Group 9.02); Nurses (Group 9.03); and Psychologists and Behavioural Scientists (Group 9.04). The sessions covered the following topics: recent advances in cardiopulmonary exercise and challenge testing; the role and new trends in physiotherapy, exercise and physical activity promotion interventions in chronic respiratory diseases; development of the international curriculum for respiratory nurses and nursing aspects in disease management; and treatment adherence, e-health interventions and post-coronavirus disease 2019 challenges. This Highlights article targets delegates who attended the Congress sessions, as well as those who were unable to attend, and provides valuable insight into the latest scientific data and emerging areas affecting the clinical practice of Allied Respiratory Professionals.

Prognostic role of minute ventilation/carbon dioxide production slope for perioperative morbidity and long-term survival in resectable patients with nonsmall-cell lung cancer: a prospective study using propensity score overlap weighting.

BACKGROUND: The role of minute ventilation/carbon dioxide production ( / CO 2 ) slope, a ventilation efficiency marker, in predicting short-term and long-term health outcomes for patients with nonsmall-cell lung cancer (NSCLC) undergoing lung resection has not been well investigated. MATERIAL AND METHODS: This prospective cohort study consecutively enrolled NSCLC patients who underwent a presurgical cardiopulmonary exercise test from November 2014 to December 2019. The association of / CO 2 slope with relapse-free survival (RFS), overall survival (OS), and perioperative mortality was evaluated using the Cox proportional hazards and logistic models. Covariates were adjusted using propensity score overlap weighting. The optimal cut-off point of the E/ CO 2 slope was estimated using the receiver operating characteristics curve. Internal validation was completed through bootstrap resampling. RESULTS: A cohort of 895 patients [median age (interquartile range), 59 (13) years; 62.5% male] was followed for a median of 40 (range, 1-85) months. Throughout the study, there were 247 relapses or deaths and 156 perioperative complications. The incidence rates per 1000 person-years for relapses or deaths were 108.8 and 79.6 among patients with high and low E/ CO 2 slopes, respectively [weighted incidence rate difference per 1000 person-years, 29.21 (95% CI, 7.30-51.12)]. A E/ CO 2 slope of greater than or equal to 31 was associated with shorter RFS [hazard ratio for relapse or death, 1.38 (95% CI, 1.02-1.88), P =0.04] and poorer OS [hazard ratio for death, 1.69 (1.15-2.48), P =0.02] compared to a lower / CO 2 slope. A high E/ CO 2 slope increased the risk of perioperative morbidity compared with a low E/ CO 2 slope [odds ratio, 2.32 (1.54-3.49), P <0.001]. CONCLUSIONS: In patients with operable NSCLC, a high E/ CO 2 slope was significantly associated with elevated risks of poorer RFS, OS, and perioperative morbidity.

Fecal Keratin 8 Is a Noninvasive and Specific Marker for Intestinal Injury in Necrotizing Enterocolitis.

Specific biomarkers of intestinal injury associated with necrotizing enterocolitis (NEC) are needed to diagnose and monitor intestinal mucosal injury and recovery. This study aims to develop and test a modified enzyme-linked immunosorbent assay (ELISA) protocol to detect the total keratin 8 (K8) in the stool of newborns with NEC and investigate the clinical value of fecal K8 as a marker of intestinal injury specifically associated with NEC. We collected fecal samples from five newborns with NEC and five gestational age-matched premature neonates without NEC at the Lucile Packard Children's Hospital Stanford and Washington University School of Medicine, respectively. Fecal K8 levels were measured using a modified ELISA protocol and Western blot, and fecal calprotectin was measured using a commercial ELISA kit. Clinical data, including gestational age, birth weight, Bell stage for NEC, feeding strategies, total white blood cell (WBC) count, and other pertinent clinical variables, were collected and analyzed. Fecal K8 levels were significantly higher in the pre-NEC group (1-2 days before diagnosis of NEC) and NEC group than those in the non-NEC group (p = 0.013, p = 0.041). Moreover, fecal K8 was relatively higher at the onset of NEC and declined after the resolution of the disease (p = 0.019). Results with similar trends to fecal K8 were also seen in fecal calprotectin (p = 0.046), but not seen in total WBC count (p = 0.182). In conclusion, a modified ELISA protocol for the total K8 protein was successfully developed for the detection of fecal K8 in the clinical setting of premature newborns with NEC. Fecal K8 is noted to be significantly increased in premature newborns with NEC and may, therefore, serve as a noninvasive and specific marker for intestinal epithelial injury associated with NEC.

Data-driven longitudinal characterization of neonatal health and morbidity.

Although prematurity is the single largest cause of death in children under 5 years of age, the current definition of prematurity, based on gestational age, lacks the precision needed for guiding care decisions. Here, we propose a longitudinal risk assessment for adverse neonatal outcomes in newborns based on a deep learning model that uses electronic health records (EHRs) to predict a wide range of outcomes over a period starting shortly before conception and ending months after birth. By linking the EHRs of the Lucile Packard Children's Hospital and the Stanford Healthcare Adult Hospital, we developed a cohort of 22,104 mother-newborn dyads delivered between 2014 and 2018. Maternal and newborn EHRs were extracted and used to train a multi-input multitask deep learning model, featuring a long short-term memory neural network, to predict 24 different neonatal outcomes. An additional cohort of 10,250 mother-newborn dyads delivered at the same Stanford Hospitals from 2019 to September 2020 was used to validate the model. Areas under the receiver operating characteristic curve at delivery exceeded 0.9 for 10 of the 24 neonatal outcomes considered and were between 0.8 and 0.9 for 7 additional outcomes. Moreover, comprehensive association analysis identified multiple known associations between various maternal and neonatal features and specific neonatal outcomes. This study used linked EHRs from more than 30,000 mother-newborn dyads and would serve as a resource for the investigation and prediction of neonatal outcomes. An interactive website is available for independent investigators to leverage this unique dataset: https://maternal-child-health-associations.shinyapps.io/shiny_app/.