Psychometric Properties of the Automated Insulin Delivery - Benefits and Burdens Scale (AID-BBS) for Adults with Type 1 Diabetes.

OBJECTIVE: To evaluate the psychometric properties of a patient-reported outcome measure, The Automated Insulin Delivery - Benefits and Burdens Scale (AID-BBS), which was designed to assess benefits and burdens of AID use in adults with type 1 diabetes (T1D). The measure was hypothesized to have validity, reliability, and clinical utility for predicting likelihood of continued use of an AID system. RESEARCH DESIGN AND METHODS: 217 adults with T1D (ages 18 to 82 years) who were enrolled in an AID system research trial completed AID-BBS items at study midpoint (6 weeks) and at the end of the trial (13 weeks). Data were collected on pre-post glycemic outcomes. Participants completed other patient-reported psychosocial outcome measures (e.g., emotional well-being, diabetes distress, attitudes toward diabetes technology, diabetes treatment satisfaction) at Week 13. Likelihood of continued device use was assessed with three items at 13 weeks. RESULTS: Exploratory factor analysis supported a one-factor structure for each subscale (15-item benefit and 9-item burden subscale) when evaluated separately. Convergent, discriminant, and predictive validity, internal consistency, and test-retest reliability were supported. Benefit and burden subscales at week 6 predicted usage intention above and beyond device impact on glycemic outcomes, also controlling for baseline glycemic outcomes. CONCLUSION: Findings support the AID-BBS as a psychometrically valid, reliable, and useful instrument for assessing burdens and benefits associated with AID system use in adults with T1D. The measure can be used to help health care providers set realistic expectations and proactively address modifiable burdens.

Myofascial pain - A major player in musculoskeletal pain.

Myofascial pain is a soft tissue pain syndrome with local and referred musculoskeletal pain arising from trigger points. Myofascial pain and myofascial pain syndromes are among some of the most common acute and chronic pain conditions. Myofascial pain can exist independently of other pain generators or can coexist with or is secondary to other acute and chronic painful musculoskeletal conditions. Myofascial pain is most effectively treated with a multimodal treatment plan including injection therapy (known as trigger point injections, physical therapy, postural or ergonomic correction, and treatment of underlying musculoskeletal pain generators. The objectives of this review are to outline the prevalence of myofascial pain, describe the known pathophysiology of myofascial pain and trigger points, discuss the clinical presentation of myofascial pain, and present evidence-based best practices for pharmacologic, non-pharmacologic, and interventional treatments for myofascial pain.

Invasion of spontaneous germinal centers by naive B cells is rapid and persistent.

In autoreactive germinal centers (GC) initiated by a single rogue B cell clone, wild-type B cells expand and give rise to clones that target other autoantigens, known as epitope spreading. The chronic, progressive nature of epitope spreading calls for early interventions to limit autoimmune pathologies, but the kinetics and molecular requirements for wild-type B cell invasion and participation in GC remain largely unknown. With parabiosis and adoptive transfer approaches in a murine model of systemic lupus erythematosus, we demonstrate that wild-type B cells join existing GCs rapidly, clonally expand, persist, and contribute to autoantibody production and diversification. The invasion of autoreactive GCs by wild-type B cells required TLR7, B cell receptor specificity, antigen presentation, and type I interferon signaling. The adoptive transfer model provides a tool for identifying early events in the breaking of B cell tolerance in autoimmunity.

T cell help shapes B cell tolerance.

T cell help is a crucial component of the normal humoral immune response, yet whether it promotes or restrains autoreactive B cell responses remains unclear. Here, we observe that autoreactive germinal centers require T cell help for their formation and persistence. Using retrogenic chimeras transduced with candidate TCRs, we demonstrate that a follicular T cell repertoire restricted to a single autoreactive TCR, but not a foreign antigen-specific TCR, is sufficient to initiate autoreactive germinal centers. Follicular T cell specificity influences the breadth of epitope spreading by regulating wild-type B cell entry into autoreactive germinal centers. These results demonstrate that TCR-dependent T cell help can promote loss of B cell tolerance and that epitope spreading is determined by TCR specificity.

Lupus-associated innate receptors drive extrafollicular evolution of autoreactive B cells.

In systemic lupus erythematosus, recent findings highlight the extrafollicular (EF) pathway as prominent origin of autoantibody-secreting cells (ASCs). CD21loCD11c+ B cells, associated with aging, infection, and autoimmunity, are contributors to autoreactive EF ASCs but have an obscure developmental trajectory. To study EF kinetics of autoreactive B cell in tissue, we adoptively transferred WT and gene knockout B cell populations into the 564Igi mice - an autoreactive host enriched with autoantigens and T cell help. Time-stamped analyses revealed TLR7 dependence in early escape of peripheral B cell tolerance and establishment of a pre-ASC division program. We propose CD21lo cells as precursors to EF ASCs due to their elevated TLR7 sensitivity and proliferative nature. Blocking receptor function reversed CD21 loss and reduced effector cell generation, portraying CD21 as a differentiation initiator and a possible target for autoreactive B cell suppression. Repertoire analysis further delineated proto-autoreactive B cell selection and receptor evolution toward self-reactivity. This work elucidates receptor and clonal dynamics in EF development of autoreactive B cells, and establishes modular, native systems to probe mechanisms of autoreactivity.

Disparities in Telemedicine Use Among Children Seen in Surgical Clinics During the COVID-19 Pandemic: Experience of One Tertiary Care Freestanding Children's Hospital.

Background: Telemedicine use dramatically increased during the COVID-19 pandemic. However, the effects of telemedicine on pre-existing disparities in pediatric surgical access have not been well described. We describe our center's early experience with telemedicine and disparities in patients' access to outpatient surgical care. Methods: A retrospective study of outpatient visits within all surgical divisions from May to December 2020 was conducted. We assessed the rates of scheduled telemedicine visits during that period, as well as the rate of completing a visit after it has been scheduled. Descriptive and logistic regression analyses were used to test for associations between these rates and patient characteristics. Results: Over the study period, 109,601 visits were scheduled. Telemedicine accounted for 6.1% of all visits with lower cancellation rates than in-person visits (26.9% vs. 34.7%). More scheduled telemedicine encounters were observed for older patients, White, English speakers, those with private insurance, and those living in rural areas. Lower odds of telemedicine visit completion were observed among patients with public insurance (odds ratio [OR] 0.7, 95% confidence interval [CI] 0.64-0.77), Spanish language preference (OR 0.84, 95% CI 0.72-0.97), and those living in rural areas (OR 0.73, 95% CI 0.64-0.84). In contrast, higher odds of telemedicine visit completion were associated with a higher Social Deprivation Index score (OR 1.41, 95% CI 1.27-1.58). Telemedicine visit completion was also associated with increasing community-level income and distance from the hospital. Conclusions: Telemedicine use for outpatient surgical care was generally low during the peak of the pandemic, and certain populations were less likely to utilize it. These findings call for further action to bridge gaps in telemedicine use.

Arthroscopy Association of Canada Position Statement on Opioid Prescription After Arthroscopic Surgery.

Background: Despite the ongoing opioid epidemic, most patients are still prescribed a significant number of opioid medications for pain management after arthroscopic surgery. There is a need for consensus among orthopaedic surgeons and solutions to aid providers in analgesic strategies that reduce the use of opioid pain medications. Purpose: This position statement was developed with a comprehensive systematic review and meta-analysis of exclusively randomized controlled trials (RCTs) to synthesize the best available evidence for managing acute postoperative pain after arthroscopic surgery. Study Design: Position statement. Methods: The Embase, MEDLINE, PubMed, Scopus, and Web of Science databases were searched from inception until August 10, 2022. Keywords included arthroscopy, opioids, analgesia, and pain, and associated variations. We included exclusively RCTs on adult patients to gather the best available evidence for managing acute postoperative pain after arthroscopic surgery. Patient characteristics, pain, and opioid data were extracted, data were analyzed, and trial bias was evaluated. Results: A total of 21 RCTs were identified related to the prescription of opioid-sparing pain medication after arthroscopic surgery. The following recommendations regarding noninvasive, postoperative pain management strategies were made: (1) multimodal oral nonopioid analgesic regimens-including at least 1 of acetaminophen-a nonsteroidal anti-inflammatory drug-can significantly reduce opioid consumption with no change in pain scores; (2) cryotherapy is likely to help with pain management, although the evidence on the optimal method of application (continuous-flow vs ice pack application) is unclear; (3) and (4) limited RCT evidence supports the efficacy of transcutaneous electrical nerve stimulation and relaxation exercises in reducing opioid consumption after arthroscopy; and (5) limited RCT evidence exists against the efficacy of transdermal lidocaine patches in reducing opioid consumption. Conclusion: A range of nonopioid strategies exist that can reduce postarthroscopic procedural opioid consumption with equivalent vocal pain outcomes. Optimal strategies include multimodal analgesia with education and restricted/reduced opioid prescription.

Antigen presentation by B cells enables epitope spreading across an MHC barrier.

Circumstantial evidence suggests that B cells may instruct T cells to break tolerance. Here, to test this hypothesis, we used a murine model in which a single B cell clone precipitates an autoreactive response resembling systemic lupus erythematosus (SLE). The initiating clone did not need to enter germinal centers to precipitate epitope spreading. Rather, it localized to extrafollicular splenic bridging channels early in the response. Autoantibody produced by the initiating clone was not sufficient to drive the autoreactive response. Subsequent epitope spreading depended on antigen presentation and was compartmentalized by major histocompatibility complex (MHC). B cells carrying two MHC haplotypes could bridge the MHC barrier between B cells that did not share MHC. Thus, B cells directly relay autoreactivity between two separate compartments of MHC-restricted T cells, leading to inclusion of distinct B cell populations in germinal centers. Our findings demonstrate that B cells initiate and propagate the autoimmune response.

Perceptions of Artificial Intelligence-Assisted Care for Children With a Respiratory Complaint.

OBJECTIVES: To evaluate caregiver opinions on the use of artificial intelligence (AI)-assisted medical decision-making for children with a respiratory complaint in the emergency department (ED). METHODS: We surveyed a sample of caregivers of children presenting to a pediatric ED with a respiratory complaint. We assessed caregiver opinions with respect to AI, defined as "specialized computer programs" that "help make decisions about the best way to care for children." We performed multivariable logistic regression to identify factors associated with discomfort with AI-assisted decision-making. RESULTS: Of 279 caregivers who were approached, 254 (91.0%) participated. Most indicated they would want to know if AI was being used for their child's health care (93.5%) and were extremely or somewhat comfortable with the use of AI in deciding the need for blood (87.9%) and viral testing (87.6%), interpreting chest radiography (84.6%), and determining need for hospitalization (78.9%). In multivariable analysis, caregiver age of 30 to 37 years (adjusted odds ratio [aOR] 3.67, 95% confidence interval [CI] 1.43-9.38; relative to 18-29 years) and a diagnosis of bronchospasm (aOR 5.77, 95% CI 1.24-30.28 relative to asthma) were associated with greater discomfort with AI. Caregivers with children being admitted to the hospital (aOR 0.23, 95% CI 0.09-0.50) had less discomfort with AI. CONCLUSIONS: Caregivers were receptive toward the use of AI-assisted decision-making. Some subgroups (caregivers aged 30-37 years with children discharged from the ED) demonstrated greater discomfort with AI. Engaging with these subgroups should be considered when developing AI applications for acute care.

Sepsis Prediction in Hospitalized Children: Model Development and Validation.

BACKGROUND AND OBJECTIVES: Early recognition and treatment of pediatric sepsis remain mainstay approaches to improve outcomes. Although most children with sepsis are diagnosed in the emergency department, some are admitted with unrecognized sepsis or develop sepsis while hospitalized. Our objective was to develop and validate a prediction model of pediatric sepsis to improve recognition in the inpatient setting. METHODS: Patients with sepsis were identified using intention-to-treat criteria. Encounters from 2012 to 2018 were used as a derivation to train a prediction model using variables from an existing model. A 2-tier threshold was determined using a precision-recall curve: an "Alert" tier with high positive predictive value to prompt bedside evaluation and an "Aware" tier with high sensitivity to increase situational awareness. The model was prospectively validated in the electronic health record in silent mode during 2019. RESULTS: A total of 55 980 encounters and 793 (1.4%) episodes of sepsis were used for derivation and prospective validation. The final model consisted of 13 variables with an area under the curve of 0.96 (95% confidence interval 0.95-0.97) in the validation set. The Aware tier had 100% sensitivity and the Alert tier had a positive predictive value of 14% (number needed to alert of 7) in the validation set. CONCLUSIONS: We derived and prospectively validated a 2-tiered prediction model of inpatient pediatric sepsis designed to have a high sensitivity Aware threshold to enable situational awareness and a low number needed to Alert threshold to minimize false alerts. Our model was embedded in our electronic health record and implemented as clinical decision support, which is presented in a companion article.

Sepsis Prediction in Hospitalized Children: Clinical Decision Support Design and Deployment.

BACKGROUND: Following development and validation of a sepsis prediction model described in a companion article, we aimed to use quality improvement and safety methodology to guide the design and deployment of clinical decision support (CDS) tools and clinician workflows to improve pediatric sepsis recognition in the inpatient setting. METHODS: CDS tools and sepsis huddle workflows were created to implement an electronic health record-based sepsis prediction model. These were proactively analyzed and refined using simulation and safety science principles before implementation and were introduced across inpatient units during 2020-2021. Huddle compliance, alerts per non-ICU patient days, and days between sepsis-attributable emergent transfers were monitored. Rapid Plan-Do-Study-Act (PDSA) cycles based on user feedback and weekly metric data informed improvement throughout implementation. RESULTS: There were 264 sepsis alerts on 173 patients with an 89% bedside huddle completion rate and 10 alerts per 1000 non-ICU patient days per month. There was no special cause variation in the metric days between sepsis-attributable emergent transfers. CONCLUSIONS: An automated electronic health record-based sepsis prediction model, CDS tools, and sepsis huddle workflows were implemented on inpatient units with a relatively low rate of interruptive alerts and high compliance with bedside huddles. Use of CDS best practices, simulation, safety tools, and quality improvement principles led to high utilization of the sepsis screening process.

Seafloor warm water temperature anomalies impact benthic macrofauna communities of a high-Arctic cold-water fjord.

Amid the alarming atmospheric and oceanic warming rates taking place in the Arctic, western fjords around the Svalbard archipelago are experiencing an increased frequency of warm water intrusions in recent decades, causing ecological shifts in their ecosystems. However, hardly anything is known about their potential impacts on the until recently considered stable and colder northern fjords. We analyzed macrobenthic fauna from four locations in Rijpfjorden (a high-Arctic fjord in the north of Svalbard) along its axis, sampled intermittently in the years 2003, 2007, 2010, 2013 and 2017. After a strong seafloor warm water temperature anomaly (SfWWTA) in 2006, the abundance of individuals and species richness dropped significantly across the entire fjord in 2007, together with diversity declines at the outer parts (reflected in Shannon index drops) and increases in beta diversity between inner and outer parts of the fjord. After a period of three years with stable water temperatures and higher sea-ice cover, communities recovered through recolonization processes by 2010, leading to homogenization in community composition across the fjord and less beta diversity. For the last two periods (2010-2013 and 2013-2017), beta diversity between the inner and outer parts gradually increased again, and both the inner and outer sites started to re-assemble in different directions. A few taxa began to dominate the fjord from 2010 onwards at the outer parts, translating into evenness and diversity drops. The inner basin, however, although experiencing strong shifts in abundances, was partially protected by a fjordic sill from impacts of these temperature anomalies and remained comparatively more stable regarding community diversity after the disturbance event. Our results indicate that although shifts in abundances were behind important spatio-temporal community fluctuations, beta diversity variations were also driven by the occurrence-based macrofauna data, suggesting an important role of rare taxa. This is the first multidecadal time series of soft-bottom macrobenthic communities for a high-Arctic fjord, indicating that potential periodic marine heatwaves might drive shifts in community structure, either through direct effects from thermal stress on the communities or through changes in environmental regimes led by temperature fluctuations (i.e. sea ice cover and glacial runoff, which could lead to shifts in primary production and food supply to the benthos). Although high-Arctic macrobenthic communities might be resilient to some extent, sustained warm water anomalies could lead to permanent changes in cold-water fjordic benthic systems.

A narrative review of the mechanisms and consequences of intermittent hypoxia and the role of advanced analytic techniques in pediatric autonomic disorders.

Disorders of autonomic functions are typically characterized by disturbances in multiple organ systems. These disturbances are often comorbidities of common and rare diseases, such as epilepsy, sleep apnea, Rett syndrome, congenital heart disease or mitochondrial diseases. Characteristic of many autonomic disorders is the association with intermittent hypoxia and oxidative stress, which can cause or exaggerate a variety of other autonomic dysfunctions, making the treatment and management of these syndromes very complex. In this review we discuss the cellular mechanisms by which intermittent hypoxia can trigger a cascade of molecular, cellular and network events that result in the dysregulation of multiple organ systems. We also describe the importance of computational approaches, artificial intelligence and the analysis of big data to better characterize and recognize the interconnectedness of the various autonomic and non-autonomic symptoms. These techniques can lead to a better understanding of the progression of autonomic disorders, ultimately resulting in better care and management.

Spatial enrichment of the type 1 interferon signature in the brain of a neuropsychiatric lupus murine model.

Among systemic lupus erythematosus (SLE) patients, neuropsychiatric symptoms are highly prevalent, being observed in up to 80% of adult and 95% of pediatric patients. Type 1 interferons, particularly interferon alpha (IFNα), have been implicated in the pathogenesis of SLE and its associated neuropsychiatric symptoms (NPSLE). However, it remains unclear how type 1 interferon signaling in the central nervous system (CNS) might result in neuropsychiatric sequelae. In this study, we validate an NPSLE mouse model and find an elevated peripheral type 1 interferon signature alongside clinically relevant NPSLE symptoms such as anxiety and fatigue. Unbiased single-nucleus sequencing of the hindbrain and hippocampus revealed that interferon-stimulated genes (ISGs) were among the most highly upregulated genes in both regions and that gene pathways involved in cellular interaction and neuronal development were generally repressed among astrocytes, oligodendrocytes, and neurons. Using image-based spatial transcriptomics, we found that the type 1 interferon signature is enriched as spatially distinct patches within the brain parenchyma of these mice. Our results suggest that type 1 interferon in the CNS may play an important mechanistic role in mediating NPSLE behavioral phenotypes by repressing general cellular communication pathways, and that type 1 interferon signaling modulators are a potential therapeutic option for NPSLE.

Complex subsets but redundant clonality after B cells egress from spontaneous germinal centers.

Affinity matured self-reactive antibodies are found in autoimmune diseases like systemic lupus erythematous. Here, we used fate-mapping reporter mice and single-cell transcriptomics coupled to antibody repertoire analysis to characterize the post-germinal center (GC) B cell compartment in a new mouse model of autoimmunity. Antibody-secreting cells (ASCs) and memory B cells (MemBs) from spontaneous GCs grouped into multiple subclusters. ASCs matured into two terminal clusters, with distinct secretion, antibody repertoire and metabolic profiles. MemBs contained FCRL5+ and CD23+ subsets, with different in vivo localization in the spleen. GC-derived FCRL5+ MemBs share transcriptomic and repertoire properties with atypical B cells found in aging and infection and localize to the marginal zone, suggesting a similar contribution to recall responses. While transcriptomically diverse, ASC and MemB subsets maintained an underlying clonal redundancy. Therefore, self-reactive clones could escape subset-targeting therapy by perpetuation of self-reactivity in distinct subsets.

[WITHDRAWN] Spatial enrichment of the type 1 interferon signature in the brain of a neuropsychiatric lupus murine model.

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Ventilatory and Orthostatic Challenges Reveal Biomarkers for Neurocognition in Children and Young Adults With Congenital Central Hypoventilation Syndrome.

BACKGROUND: Children and young adults with congenital central hypoventilation syndrome (CCHS) are at risk of cognitive deficits. They experience autonomic dysfunction and chemoreceptor insensitivity measured during ventilatory and orthostatic challenges, but relationships between these features are undefined. RESEARCH QUESTION: Can a biomarker be identified from physiologic responses to ventilatory and orthostatic challenges that is related to neurocognitive outcomes in CCHS? STUDY DESIGN AND METHODS: This retrospective study included 25 children and young adults with CCHS tested over an inpatient stay. Relationships between physiologic measurements during hypercarbic and hypoxic ventilatory challenges, hypoxic ventilatory challenges, and orthostatic challenges and neurocognitive outcomes (by Wechsler intelligence indexes) were examined. Independent variable inclusion was determined by significant associations in Pearson's analyses. Multivariate linear regressions were used to assess relationships between measured physiologic responses to challenges and neurocognitive scores. RESULTS: Significant relationships were identified between areas of fluid intelligence and measures of oxygen saturation (SpO2) and heart rate (HR) during challenges. Specifically, perceptual reasoning was related to HR (adjusted regression [ß] coefficient, -0.68; 95% CI, 1.24 to -0.12; P = .02) during orthostasis. Working memory was related to change in HR (ß, -1.33; 95% CI, -2.61 to -0.05; P = .042) during the hypoxic ventilatory challenge. Processing speed was related to HR (ß, -1.19; 95% CI, -1.93 to -0.46; P = .003) during orthostasis, to baseline SpO2 (hypercarbic and hypoxic ß, 8.57 [95% CI, 1.63-15.51]; hypoxic ß, 8.37 [95% CI, 3.65-13.11]; P = .002 for both) during the ventilatory challenges, and to intrachallenge SpO2 (ß, 5.89; 95% CI, 0.71-11.07; P = .028) during the hypoxic ventilatory challenge. INTERPRETATION: In children and young adults with CCHS, SpO2 and HR-or change in HR-at rest and as a response to hypoxia and orthostasis are related to cognitive outcomes in domains of known risk, particularly fluid reasoning. These findings can guide additional research on the usefulness of these as biomarkers in understanding the impact of daily physical stressors on neurodevelopment in this high-risk group.

Association of Youth Suicides and County-Level Mental Health Professional Shortage Areas in the US.

Importance: Suicide is the second leading cause of death among US adolescents. Workforce shortages of mental health professionals in the US are widespread, but the association between mental health workforce shortages and youth suicides is not well understood. Objective: To assess the association between youth suicide rates and mental health professional workforce shortages at the county level, adjusting for county demographic and socioeconomic characteristics. Design, Setting, and Participants: This retrospective cross-sectional study included all US counties and used data of all US youlth suicides from January 2015, through December 31, 2016. Data were analyzed from July 1, 2021, through December 20, 2021. Exposures: County health-professional shortage area designation for mental health, assigned by the US Health Resources and Services Administration based on mental health professionals relative to the population, level of need for mental health services, and service availability in contiguous areas. Designated shortage areas receive a score from 0 to 25, with higher scores indicating greater workforce shortages. Main Outcomes and Measures: Suicides by youth aged 5 to 19 years from 2015 to 2016 were identified from the US Centers for Disease Control and Prevention's Compressed Mortality File. A multivariable negative binomial regression model was used to analyze the association between youth suicide rates and mental health workforce shortage designation, adjusting for the presence of a children's mental health hospital and county-level markers of health insurance coverage, education, unemployment, income, poverty, urbanicity, racial and ethnic composition, and year. Similar models were performed for the subgroups of (1) firearm suicides and (2) counties assigned a numeric shortage score. Results: During the study period, there were 5034 youth suicides (72.8% male and 68.2% non-Hispanic White) with an annual suicide rate of 3.99 per 100 000 youths. Of 3133 US counties, 2117 (67.6%) were designated as mental health workforce shortage areas. After adjusting for county characteristics, mental health workforce shortage designation was associated with an increased youth suicide rate (adjusted incidence rate ratio [aIRR], 1.16; 95% CI, 1.07-1.26) and an increased youth firearm suicide rate (aIRR, 1.27; 95% CI, 1.13-1.42). For counties with an assigned numeric workforce shortage score, the adjusted youth suicide rate increased 4% for every 1-point increase in the score (aIRR, 1.04; 95% CI, 1.02-1.06). Conclusions and Relevance: In this cross-sectional study, US county mental health professional workforce shortages were associated with increased youth suicide rates. These findings may inform suicide prevention efforts.

Novel approaches to capturing and using continuous cardiorespiratory physiological data in hospitalized children.

Continuous cardiorespiratory physiological monitoring is a cornerstone of care in hospitalized children. The data generated by monitoring devices coupled with machine learning could transform the way we provide care. This scoping review summarizes existing evidence on novel approaches to continuous cardiorespiratory monitoring in hospitalized children. We aimed to identify opportunities for the development of monitoring technology and the use of machine learning to analyze continuous physiological data to improve the outcomes of hospitalized children. We included original research articles published on or after January 1, 2001, involving novel approaches to collect and use continuous cardiorespiratory physiological data in hospitalized children. OVID Medline, PubMed, and Embase databases were searched. We screened 2909 articles and performed full-text extraction of 105 articles. We identified 58 articles describing novel devices or approaches, which were generally small and single-center. In addition, we identified 47 articles that described the use of continuous physiological data in prediction models, but only 7 integrated multidimensional data (e.g., demographics, laboratory results). We identified three areas for development: (1) further validation of promising novel devices; (2) more studies of models integrating multidimensional data with continuous cardiorespiratory data; and (3) further dissemination, implementation, and validation of prediction models using continuous cardiorespiratory data. IMPACT: We performed a comprehensive scoping review of novel approaches to capture and use continuous cardiorespiratory physiological data for monitoring, diagnosis, providing care, and predicting events in hospitalized infants and children, from novel devices to machine learning-based prediction models. We identified three key areas for future development: (1) further validation of promising novel devices; (2) more studies of models integrating multidimensional data with continuous cardiorespiratory data; and (3) further dissemination, implementation, and validation of prediction models using cardiorespiratory data.