Global respiratory syncytial virus-associated mortality in young children (RSV GOLD): a retrospective case series

Background Respiratory syncytial virus (RSV) infection is an important cause of pneumonia mortality in young children. However, clinical data for fatal RSV infection are scarce. We aimed to identify clinical and socioeconomic characteristics of children aged younger than 5 years with RSV-related mortality using individual patient data. Methods In this retrospective case series, we developed an online questionnaire to obtain individual patient data for clinical and socioeconomic characteristics of children aged younger than 5 years who died with community-acquired RSV infection between Jan 1, 1995, and Oct 31, 2015, through leading research groups for child pneumonia identified through a comprehensive literature search and existing research networks. For the literature search, we searched PubMed for articles published up to Feb 3, 2015, using the key terms “RSV”, “respiratory syncytial virus”, or “respiratory syncytial viral” combined with “mortality”, “fatality”, “death”, “died”, “deaths”, or “CFR” for articles published in English. We invited researchers and clinicians identified to participate between Nov 1, 2014, and Oct 31, 2015. We calculated descriptive statistics for all variables. Findings We studied 358 children with RSV-related in-hospital death from 23 countries across the world, with data contributed from 31 research groups. 117 (33%) children were from low-income or lower middle-income countries, 77 (22%) were from upper middle-income countries, and 164 (46%) were from high-income countries. 190 (53%) were male. Data for comorbidities were missing for some children in low-income and middle-income countries. Available data showed that comorbidities were present in at least 33 (28%) children from low-income or lower middle-income countries, 36 (47%) from upper middle-income countries, and 114 (70%) from high-income countries. Median age for RSV-related deaths was 5·0 months (IQR 2·3–11·0) in low-income or lower middle-income countries, 4·0 years (2·0–10·0) in upper middle-income countries, and 7·0 years (3·6–16·8) in high-income countries. Interpretation This study is the first large case series of children who died with community-acquired RSV infection. A substantial proportion of children with RSV-related death had comorbidities. Our results show that perinatal immunisation strategies for children aged younger than 6 months could have a substantial impact on RSV-related child mortality in low-income and middle-income countries

Discordant identification of pediatric severe sepsis by research and clinical definitions in the SPROUT international point prevalence study

Introduction: Consensus criteria for pediatric severe sepsis have standardized enrollment for research studies. However, the extent to which critically ill children identified by consensus criteria reflect physician diagnosis of severe sepsis, which underlies external validity for pediatric sepsis research, is not known. We sought to determine the agreement between physician diagnosis and consensus criteria to identify pediatric patients with severe sepsis across a network of international pediatric intensive care units (PICUs). Methods: We conducted a point prevalence study involving 128 PICUs in 26 countries across 6 continents. Over the course of 5 study days, 6925 PICU patients <18 years of age were screened, and 706 with severe sepsis defined either by physician diagnosis or on the basis of 2005 International Pediatric Sepsis Consensus Conference consensus criteria were enrolled. The primary endpoint was agreement of pediatric severe sepsis between physician diagnosis and consensus criteria as measured using Cohen's ?. Secondary endpoints included characteristics and clinical outcomes for patients identified using physician diagnosis versus consensus criteria. Results: Of the 706 patients, 301 (42.6 %) met both definitions. The inter-rater agreement (? ± SE) between physician diagnosis and consensus criteria was 0.57 ± 0.02. Of the 438 patients with a physician's diagnosis of severe sepsis, only 69 % (301 of 438) would have been eligible to participate in a clinical trial of pediatric severe sepsis that enrolled patients based on consensus criteria. Patients with physician-diagnosed severe sepsis who did not meet consensus criteria were younger and had lower severity of illness and lower PICU mortality than those meeting consensus criteria or both definitions. After controlling for age, severity of illness, number of comorbid conditions, and treatment in developed versus resource-limited regions, patients identified with severe sepsis by physician diagnosis alone or by consensus criteria alone did not have PICU mortality significantly different from that of patients identified by both physician diagnosis and consensus criteria. Conclusions: Physician diagnosis of pediatric severe sepsis achieved only moderate agreement with consensus criteria, with physicians diagnosing severe sepsis more broadly. Consequently, the results of a research study based on consensus criteria may have limited generalizability to nearly one-third of PICU patients diagnosed with severe sepsis

Home Telehealth Uptake and Continued Use Among Heart Failure and Chronic Obstructive Pulmonary Disease Patients: a Systematic Review

Background Home telehealth has the potential to benefit heart failure (HF) and chronic obstructive pulmonary disease (COPD) patients, however large-scale deployment is yet to be achieved. Purpose The aim of this review was to assess levels of uptake of home telehealth by patients with HF and COPD and the factors that determine whether patients do or do not accept and continue to use telehealth. Methods This research performs a narrative synthesis of the results from included studies. Results Thirty-seven studies met the inclusion criteria. Studies that reported rates of refusal and/or withdrawal found that almost one third of patients who were offered telehealth refused and one fifth of participants who did accept later abandoned telehealth. Seven barriers to, and nine facilitators of, home telehealth use were identified. Conclusions Research reports need to provide more details regarding telehealth refusal and abandonment, in order to understand the reasons why patients decide not to use telehealth

Estimated impact of maternal vaccination on global paediatric influenza-related in-hospital mortality: A retrospective case series

BACKGROUND: Influenza virus infection is an important cause of under-five mortality. Maternal vaccination protects children younger than 3 months of age from influenza infection. However, it is unknown to what extent paediatric influenza-related mortality may be prevented by a maternal vaccine since global age-stratified mortality data are lacking. METHODS: We invited clinicians and researchers to share clinical and demographic characteristics from children younger than 5 years who died with laboratory-confirmed influenza infection between January 1, 1995 and March 31, 2020. We evaluated the potential impact of maternal vaccination by estimating the number of children younger than 3 months with in-hospital influenza-related death using published global mortality estimates. FINDINGS: We included 314 children from 31 countries. Comorbidities were present in 166 (53%) children and 41 (13%) children were born prematurely. Median age at death was 8·6 (IQR 4·5-16·6), 11·5 (IQR 4·3-24·0), and 15·5 (IQR 7·4-27·0) months for children from low- and lower-middle-income countries (LMICs), upper-middle-income countries (UMICs), and high-income countries (HICs), respectively. The proportion of children younger than 3 months at time of death was 17% in LMICs, 12% in UMICs, and 7% in HICs. We estimated that 3339 annual influenza-related in-hospital deaths occur in the first 3 months of life globally. INTERPRETATION: In our study, less than 20% of children is younger than 3 months at time of influenza-related death. Although maternal influenza vaccination may impact maternal and infant influenza disease burden, additional immunisation strategies are needed to prevent global influenza-related childhood mortality. The missing data, global coverage, and data quality in this study should be taken into consideration for further interpretation of the results. FUNDING: Bill & Melinda Gates Foundation

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Image1_Signatures of illness in children requiring unplanned intubation in the pediatric intensive care unit: A retrospective cohort machine-learning study.tiff

Acute respiratory failure requiring the initiation of invasive mechanical ventilation remains commonplace in the pediatric intensive care unit (PICU). Early recognition of patients at risk for respiratory failure may provide clinicians with the opportunity to intervene and potentially improve outcomes. Through the development of a random forest model to identify patients at risk for requiring unplanned intubation, we tested the hypothesis that subtle signatures of illness are present in physiological and biochemical time series of PICU patients in the early stages of respiratory decompensation. We included 116 unplanned intubation events as recorded in the National Emergency Airway Registry for Children in 92 PICU admissions over a 29-month period at our institution. We observed that children have a physiologic signature of illness preceding unplanned intubation in the PICU. Generally, it comprises younger age, and abnormalities in electrolyte, hematologic and vital sign parameters. Additionally, given the heterogeneity of the PICU patient population, we found differences in the presentation among the major patient groups – medical, cardiac surgical, and non-cardiac surgical. At four hours prior to the event, our random forest model demonstrated an area under the receiver operating characteristic curve of 0.766 (0.738 for medical, 0.755 for cardiac surgical, and 0.797 for non-cardiac surgical patients). The multivariable statistical models that captured the physiological and biochemical dynamics leading up to the event of urgent unplanned intubation in a PICU can be repurposed for bedside risk prediction.</p

Image3_Signatures of illness in children requiring unplanned intubation in the pediatric intensive care unit: A retrospective cohort machine-learning study.jpg

Acute respiratory failure requiring the initiation of invasive mechanical ventilation remains commonplace in the pediatric intensive care unit (PICU). Early recognition of patients at risk for respiratory failure may provide clinicians with the opportunity to intervene and potentially improve outcomes. Through the development of a random forest model to identify patients at risk for requiring unplanned intubation, we tested the hypothesis that subtle signatures of illness are present in physiological and biochemical time series of PICU patients in the early stages of respiratory decompensation. We included 116 unplanned intubation events as recorded in the National Emergency Airway Registry for Children in 92 PICU admissions over a 29-month period at our institution. We observed that children have a physiologic signature of illness preceding unplanned intubation in the PICU. Generally, it comprises younger age, and abnormalities in electrolyte, hematologic and vital sign parameters. Additionally, given the heterogeneity of the PICU patient population, we found differences in the presentation among the major patient groups – medical, cardiac surgical, and non-cardiac surgical. At four hours prior to the event, our random forest model demonstrated an area under the receiver operating characteristic curve of 0.766 (0.738 for medical, 0.755 for cardiac surgical, and 0.797 for non-cardiac surgical patients). The multivariable statistical models that captured the physiological and biochemical dynamics leading up to the event of urgent unplanned intubation in a PICU can be repurposed for bedside risk prediction.</p

Image2_Signatures of illness in children requiring unplanned intubation in the pediatric intensive care unit: A retrospective cohort machine-learning study.pdf

Acute respiratory failure requiring the initiation of invasive mechanical ventilation remains commonplace in the pediatric intensive care unit (PICU). Early recognition of patients at risk for respiratory failure may provide clinicians with the opportunity to intervene and potentially improve outcomes. Through the development of a random forest model to identify patients at risk for requiring unplanned intubation, we tested the hypothesis that subtle signatures of illness are present in physiological and biochemical time series of PICU patients in the early stages of respiratory decompensation. We included 116 unplanned intubation events as recorded in the National Emergency Airway Registry for Children in 92 PICU admissions over a 29-month period at our institution. We observed that children have a physiologic signature of illness preceding unplanned intubation in the PICU. Generally, it comprises younger age, and abnormalities in electrolyte, hematologic and vital sign parameters. Additionally, given the heterogeneity of the PICU patient population, we found differences in the presentation among the major patient groups – medical, cardiac surgical, and non-cardiac surgical. At four hours prior to the event, our random forest model demonstrated an area under the receiver operating characteristic curve of 0.766 (0.738 for medical, 0.755 for cardiac surgical, and 0.797 for non-cardiac surgical patients). The multivariable statistical models that captured the physiological and biochemical dynamics leading up to the event of urgent unplanned intubation in a PICU can be repurposed for bedside risk prediction.</p

Patterns of Organ Dysfunction in Critically Ill Children Based on PODIUM Criteria

OBJECTIVES: The goal of this study was to determine the incidence, prognostic performance, and generalizability of the Pediatric Organ Dysfunction Information Update Mandate (PODIUM) organ dysfunction criteria using electronic health record (EHR) data. Additionally, we sought to compare the performance of the PODIUM criteria with the organ dysfunction criteria proposed by the 2005 International Pediatric Sepsis Consensus Conference (IPSCC). METHODS: Retrospective observational cohort study of critically ill children at 2 medical centers in the United States between 2010 and 2018. We assessed prevalence of organ dysfunction based on the PODIUM and IPSCC criteria for each 24-hour period from admission to 28 days. We studied the prognostic performance of the criteria to discriminate in-hospital mortality. RESULTS: Overall, 22 427 PICU admissions met inclusion criteria, and in-hospital mortality was 2.3%. The cumulative incidence of each PODIUM organ dysfunction ranged from 15% to 30%, with an in-hospital mortality of 6% to 10% for most organ systems. The number of concurrent PODIUM organ dysfunctions demonstrated good-to-excellent discrimination for in-hospital mortality (area under the curve 0.87-0.93 for day 1 through 28) and compared favorably to the IPSCC criteria (area under the curve 0.84-0.92, P < .001 to P = .06). CONCLUSIONS: We present the first evaluation of the PODIUM organ dysfunction criteria in 2 EHR databases. The use of the PODIUM organ dysfunction criteria appears promising for epidemiologic and clinical research studies using EHR data. More studies are needed to evaluate the PODIUM criteria that are not routinely collected in structured format in EHR databases