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Purpose: Severe asthma poses a significant health burden in those with the disease, therefore a timely diagnosis can ensure patients receive specialist care and appropriate medication management. This study qualitatively explored the patient experience of adult Australians with severe asthma regarding specialist referral, to identify potential opportunities to streamline the process of severe asthma diagnosis and treatment and optimise referral pathways., Patients and Methods: Adults currently being treated with medication for severe asthma were invited to participate in this study. Participants were interviewed and asked to describe initial diagnosis of their asthma or severe asthma, and how they came to be referred to secondary care. Interviews were transcribed verbatim, coded by two members of the research team and thematically analysed., Results: Thirty-two people completed the study; 72% were female. Mean interview length was 33 minutes. The major themes generated were patient-related factors contributing to seeking a severe asthma diagnosis; perceptions of health care provision; diagnosis of severe asthma and the referral journey. Key findings were that both patient and healthcare provider attitudes contributed to participants' willingness to seek or receive a referral, and referral to respiratory specialists was often delayed. Contributing factors included a mismatch between patient expectations and general practice, lack of continuity of primary care, and a lack of patient understanding of the role of the respiratory specialist., Conclusion: Timely severe asthma diagnosis in Australia appears to be hampered by an absence of a clear referral process, lack of general practitioner (GP) knowledge of additional treatment options, underutilisation of pharmacists, and multiple specialists treating patient comorbidities. Directions for future research might include interviewing healthcare providers regarding how well the referral process works for severe asthma patients, and researching the time between referral and when a patient sees the respiratory specialist., Competing Interests: Biljana Cvetkovski reports personal fees from Sanofi, GSK and Viatris, outside the submitted work. Joy W Lee received speaker and travel fees from Sanofi, GSK and Astra Zeneca unrelated to the preparation of this manuscript. Janet Rimmer has honoraria with Sanofi Aventis, Novartis, Mundipharma, BioCSL, Stallergenes. Sinthia Bosnic-Anticevich has received research funding and/or fees for expert lectures and advisory board participation from AstraZeneca, GSK, TEVA Pharmaceuticals, Menarini, Chiesi, Mundipharma, Boehringer Ingelheim, Sanofi, Mylan, J&J, Menarini. Sinthia Bosnic-Anticevich reports grants from AstraZeneca, GSK, Teva, Mylan/Viatris; personal fees from Teva, AstraZeneca, Boehringer Ingelheim, GSK, Sanofi, Mylan/Viatris, Menarini and Chiesi, outside the submitted work. The other authors report no conflicts of interest in this work., (© 2024 Davis et al.)

Importance: The Sentinel System is a key component of the US Food and Drug Administration (FDA) postmarketing safety surveillance commitment and uses clinical health care data to conduct analyses to inform drug labeling and safety communications, FDA advisory committee meetings, and other regulatory decisions. However, observational data are frequently deemed insufficient for reliable evaluation of safety concerns owing to limitations in underlying data or methodology. Advances in large language models (LLMs) provide new opportunities to address some of these limitations. However, careful consideration is necessary for how and where LLMs can be effectively deployed for these purposes., Observations: LLMs may provide new avenues to support signal-identification activities to identify novel adverse event signals from narrative text of electronic health records. These algorithms may be used to support epidemiologic investigations examining the causal relationship between exposure to a medical product and an adverse event through development of probabilistic phenotyping of health outcomes of interest and extraction of information related to important confounding factors. LLMs may perform like traditional natural language processing tools by annotating text with controlled vocabularies with additional tailored training activities. LLMs offer opportunities for enhancing information extraction from adverse event reports, medical literature, and other biomedical knowledge sources. There are several challenges that must be considered when leveraging LLMs for postmarket surveillance. Prompt engineering is needed to ensure that LLM-extracted associations are accurate and specific. LLMs require extensive infrastructure to use, which many health care systems lack, and this can impact diversity, equity, and inclusion, and result in obscuring significant adverse event patterns in some populations. LLMs are known to generate nonfactual statements, which could lead to false positive signals and downstream evaluation activities by the FDA and other entities, incurring substantial cost., Conclusions and Relevance: LLMs represent a novel paradigm that may facilitate generation of information to support medical product postmarket surveillance activities that have not been possible. However, additional work is required to ensure LLMs can be used in a fair and equitable manner, minimize false positive findings, and support the necessary rigor of signal detection needed for regulatory activities.

Racial residential segregation has been deemed a fundamental cause of health inequities. It is a result of historical and contemporary policies such as redlining that have created a geographic separation of races and corresponds with an inequitable distribution of health-promoting resources. Redlining and racial residential segregation may have contributed to racial inequities in COVID-19 vaccine administration in the early stages of public accessibility. We use data from the National Archives (historical redlining), Home Mortgage Disclosure Act (contemporary redlining), American Community Survey from 1940 (historical racial residential segregation) and 2015-2019 (contemporary racial residential segregation), and Washington D.C. government (COVID-19 vaccination administration) to assess the relationships between redlining, racial residential segregation, and COVID-19 vaccine administration during the early stages of vaccine distribution when a tiered system was in place due to limited supply. Pearson correlation was used to assess whether redlining and racial segregation, measured both historically and contemporarily, were correlated with each other in Washington D.C. Subsequently, linear regression was used to assess whether each of these measures associate with COVID-19 vaccine administration. In both historical and contemporary analyses, there was a positive correlation between redlining and racial residential segregation. Further, redlining and racial residential segregation were each positively associated with administration of the novel COVID-19 vaccine. This study highlights the ongoing ways in which redlining and segregation contribute to racial health inequities. Eliminating racial health inequities in American society requires addressing the root causes that affect access to health-promoting resources., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Background and Objective: Most evidence about difficult-to-treat and severe asthma (DTTA) comes from clinical trials and registries. We aimed to identify people with DTTA from a large nationally representative asthma population and describe their characteristics and healthcare utilization compared with people whose asthma was not 'difficult-to-treat'., Methods: We conducted a cross-sectional survey of Australians aged ≥18 years with current asthma from large web-based survey panels. Enrolment was stratified by gender, age-group and state/territory based on national population data for people with asthma. Difficult-to-treat or severe asthma was defined by poor symptom control, exacerbations and/or oral corticosteroid/biologic use despite medium/high-dose inhaled therapy. Outcomes included exacerbations, healthcare utilization, multimorbidity, quality of life and coronavirus disease of 2019 (COVID-19)-related behaviour. Weighted data were analysed using SAS version 9.4., Results: The survey was conducted in February-March 2021. The weighted sample comprised 6048 adults with current asthma (average age 47.3 ± SD 18.1 years, 59.9% female), with 1313 (21.7%) satisfying ≥1 DTTA criteria. Of these, 50.4% had very poorly controlled symptoms (Asthma Control Test ≤15), 36.2% were current smokers, and 85.4% had ≥1 additional chronic condition, most commonly anxiety/depression. More than twice as many participants with DTTA versus non-DTTA had ≥1 urgent general practitioner (GP) visit (61.4% vs. 27.5%, OR 4.8 [4.2-5.5, p < 0.0001]), or ≥1 emergency room visit (41.9% vs. 17.9%, OR 3.8 [3.3-4.4, p < 0.0001]) in the previous 12 months., Conclusion: Our findings emphasize the burden of uncontrolled symptoms, current smoking, multimorbidity and healthcare utilization in people with DTTA in the community, who may be under-represented in registries or clinical trials., (© 2024 The Authors. Respirology published by John Wiley & Sons Australia, Ltd on behalf of Asian Pacific Society of Respirology.)

In recent years, equine complex vertebral malformation (ECVM) has been of concern in the equine community, with studies identifying numerous associative morphological variations. Here, we examine the morphological association between C6 and C7 for dependency in ECVM cases, where the partially absent ventral process of C6 transposes on the ventral surface of C7. A C6 ventral process presents two tubercles, one cranial (CrVT) and one caudal (CVT). In this study, the C6 osseous specimens ( n = 85) demonstrated a partial or completely absent CVT (aCVT) graded 1-4 that often extended cranially creating a partially absent cranial ventral tubercle (aCrVT) graded 1-3. In the 85 C6 osseous specimens examined, the corresponding C7s demonstrated either a complete or incomplete transposition of the ventral process from C6 in 44/85, with 30/44 replicating a transverse foramen. A strong statistical dependency existed between C6 grade 4 aCVTs and grades 1-3 aCrVTs and C7 transpositions with replicated transverse foramen. Sidedness was also demonstrated, where a left sided absent C6 associated with transposition on the left ventral surface of C7. This likewise applied to right sidedness and most bilateral cases. These findings might benefit practitioners when radiographing the extent of the ECVM configuration in patients presenting caudal cervical pain.

Background: As the enthusiasm for integrating artificial intelligence (AI) into clinical care grows, so has our understanding of the challenges associated with deploying impactful and sustainable clinical AI models. Complex dataset shifts resulting from evolving clinical environments strain the longevity of AI models as predictive accuracy and associated utility deteriorate over time., Objective: Responsible practice thus necessitates the lifecycle of AI models be extended to include ongoing monitoring and maintenance strategies within health system algorithmovigilance programs. We describe a framework encompassing a 360° continuum of preventive, preemptive, responsive, and reactive approaches to address model monitoring and maintenance from critically different angles., Discussion: We describe the complementary advantages and limitations of these four approaches and highlight the importance of such a coordinated strategy to help ensure the promise of clinical AI is not short-lived., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Maintaining user engagement with mobile health (mHealth) apps can be a challenge. Previously, we developed a conceptual model to optimize patient engagement in mHealth apps by incorporating multiple evidence-based methods, including increasing health literacy, enhancing technical competence, and improving feelings about participation in clinical trials. This viewpoint aims to report on a series of exploratory mini-experiments demonstrating the feasibility of testing our previously published engagement conceptual model. We collected data from 6 participants using an app that showed a series of educational videos and obtained additional data via questionnaires to illustrate and pilot the approach. The videos addressed 3 elements shown to relate to engagement in health care app use: increasing health literacy, enhancing technical competence, and improving positive feelings about participation in clinical trials. We measured changes in participants' knowledge and feelings, collected feedback on the videos and content, made revisions based on this feedback, and conducted participant reassessments. The findings support the feasibility of an iterative approach to creating and refining engagement enhancements in mHealth apps. Systematically identifying the key evidence-based elements intended to be included in an app's design and then systematically testing the implantation of each element separately until a satisfactory level of positive impact is achieved is feasible and should be incorporated into standard app design. While mHealth apps have shown promise, participants are more likely to drop out than to be retained. This viewpoint highlights the potential for mHealth researchers to test and refine mHealth apps using approaches to better engage users., (©Rebecca Monachelli, Sharon Watkins Davis, Allison Barnard, Michelle Longmire, John P Docherty, Ingrid Oakley-Girvan. Originally published in the Interactive Journal of Medical Research (https://www.i-jmr.org/), 26.03.2024.)

Mobile phone applications ("apps") are potentially an effective, low-burden method to collect patient-reported outcomes outside the clinical setting. Using such apps consistently and in a timely way is critical for complete and accurate data capture, but no studies of concurrent reporting by cancer patient-caregiver dyads have been published in the peer-reviewed literature. This study assessed app engagement, defined as adherence, timing, and attrition with two smartphone applications, one for adult cancer patients and one for their informal caregivers. This was a single-arm, pilot study in which adult cancer patients undergoing IV chemotherapy or immunotherapy used the DigiBioMarC app, and their caregivers used the TOGETHERCare app, for approximately one month to report weekly on the patients' symptoms and wellbeing. Using app timestamp metadata, we assessed user adherence, overall and by participant characteristics. Fifty patient-caregiver dyads completed the study. Within the one-month study period, both adult cancer patients and their informal caregivers were highly adherent, with app activity completion at 86% for cancer patients and 84% for caregivers. Caregivers completed 86% of symptom reports, while cancer patients completed 89% of symptom reports. Cancer patients and their caregivers completed most activities within 48 h of availability on the app. These results suggest that the DigiBioMarC and TOGETHERCare apps can be used to collect patient- and caregiver-reported outcomes data during intensive treatment. From our research, we conclude that metadata from mobile apps can be used to inform clinical teams about study participants' engagement and wellbeing outside the clinical setting., (© 2024. The Author(s).)

Several studies have found associations between air pollution and respiratory disease outcomes. However, there is minimal prognostic research exploring whether integrating air quality into clinical prediction models can improve accuracy and utility. In this study, we built models using both logistic regression and random forests to determine the benefits of including air quality data with meteorological and clinical data in prediction of COPD exacerbations requiring medical care. Logistic models were not improved by inclusion of air quality. However, the net benefit curves of random forest models showed greater clinical utility with the addition of air quality data. These models demonstrate a practical and relatively low-cost way to include environmental information into clinical prediction tools to improve the clinical utility of COPD prediction. Findings could be used to provide population level health warnings as well as individual-patient risk assessments., (©2023 AMIA - All rights reserved.)

Introduction: The pitfalls of label leakage, contamination of model input features with outcome information, are well established. Unfortunately, avoiding label leakage in clinical prediction models requires more nuance than the common advice of applying "no time machine rule.", Framework: We provide a framework for contemplating whether and when model features pose leakage concerns by considering the cadence, perspective, and applicability of predictions. To ground these concepts, we use real-world clinical models to highlight examples of appropriate and inappropriate label leakage in practice., Recommendations: Finally, we provide recommendations to support clinical and technical stakeholders as they evaluate the leakage tradeoffs associated with model design, development, and implementation decisions. By providing common language and dimensions to consider when designing models, we hope the clinical prediction community will be better prepared to develop statistically valid and clinically useful machine learning models., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Timely collection of patient-reported outcomes (PROs) decreases emergency department visits and hospitalizations and increases survival. However, little is known about the outcome predictivity of unpaid informal caregivers' reporting using similar clinical outcome assessments., Objective: The aim of this study is to assess whether caregivers and adults with cancer adhered to a planned schedule for electronically collecting patient-reported outcomes (PROs) and if PROs were associated with future clinical events., Methods: We developed 2 iPhone apps to collect PROs, one for patients with cancer and another for caregivers. We enrolled 52 patient-caregiver dyads from Kaiser Permanente Northern California in a nonrandomized study. Participants used the apps independently for 4 weeks. Specific clinical events were obtained from the patients' electronic health records up to 6 months following the study. We used logistic and quasi-Poisson regression analyses to test associations between PROs and clinical events., Results: Participants completed 97% (251/260) of the planned Patient-Reported Outcomes Common Terminology Criteria for Adverse Events (PRO-CTCAE) surveys and 98% (254/260) of the Patient-Reported Outcomes Measurement Information System (PROMIS) surveys. PRO-CTCAE surveys completed by caregivers were associated with patients' hospitalizations or emergency department visits, grade 3-4 treatment-related adverse events, dose reductions (P<.05), and hospice referrals (P=.03). PROMIS surveys completed by caregivers were associated with hospice referrals (P=.02). PRO-CTCAE surveys completed by patients were not associated with any clinical events, but their baseline PROMIS surveys were associated with mortality (P=.03), while their antecedent or final PROMIS surveys were associated with all clinical events examined except for total days of treatment breaks., Conclusions: In this study, caregivers and patients completed PROs using smartphone apps as requested. The association of caregiver PRO-CTCAE surveys with patient clinical events suggests that this is a feasible approach to reducing patient burden in clinical trial data collection and may help provide early information about increasing symptom severity., (©Ingrid Oakley-Girvan, Reem Yunis, Stephanie J Fonda, Michelle Longmire, Tess L Veuthey, Jennifer Shieh, Sara Aghaee, Ai Kubo, Sharon W Davis, Raymond Liu, Elad Neeman. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 21.11.2023.)

Introduction: Pharmacovigilance programs protect patient health and safety by identifying adverse event signals through postmarketing surveillance of claims data and spontaneous reports. Electronic health records (EHRs) provide new opportunities to address limitations of traditional approaches and promote discovery-oriented pharmacovigilance., Methods: To evaluate the current state of EHR-based medication safety signal identification, we conducted a scoping literature review of studies aimed at identifying safety signals from routinely collected patient-level EHR data. We extracted information on study design, EHR data elements utilized, analytic methods employed, drugs and outcomes evaluated, and key statistical and data analysis choices., Results: We identified 81 eligible studies. Disproportionality methods were the predominant analytic approach, followed by data mining and regression. Variability in study design makes direct comparisons difficult. Studies varied widely in terms of data, confounding adjustment, and statistical considerations., Conclusion: Despite broad interest in utilizing EHRs for safety signal identification, current efforts fail to leverage the full breadth and depth of available data or to rigorously control for confounding. The development of best practices and application of common data models would promote the expansion of EHR-based pharmacovigilance., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

This study examined the anomalous variations of the ventral process of C6 in modern E. ferus caballus. The aim was to provide an incremental grading protocol measuring the absence of the caudal ventral tubercle (CVT) in this ventral process. The findings revealed the most prevalent absent CVT (aCVT) was left unilateral ( n = 35), with bilateral ( n = 29) and right unilateral ( n = 12). Grading was determined in equal increments of absence 1/4, 2/4, 3/4, with 4/4 representing a complete aCVT in 56/76, with a significance of p = 0.0013. This also applied to bilateral specimens. In those C6 osseous specimens displaying a 4/4 grade aCVT, 41/56 had a partial absence of the caudal aspect of the cranial ventral tubercle (CrVT). Here, grading absent CrVTs (aCrVT) followed similarly to aCVTs, though 4/4 was not observed. The significance between 4/4 grade aCVTs and the presentation of an aCrVT was left p = 0.00001 and right p = 0.00018. In bilateral specimens, C6 morphologically resembled C5, implying a homeotic transformation that limited the attachment sites for the cranial and thoracal longus colli muscle. This potentially diminishes function and caudal cervical stability. Therefore, it is recommended that further studies examine the morphological extent of this equine complex vertebral malformation (ECVM) as well as its interrelationships and genetic code/blueprint.

Background: By eliminating the requirement for participants to make frequent visits to research sites, mobile phone applications ("apps") may help to decentralize clinical trials. Apps may also be an effective mechanism for capturing patient-reported outcomes and other endpoints, helping to optimize patient care during and outside of clinical trials., Objectives: We report on the usability of Digital BioMarkers for Clinical Impact (DigiBioMarC™ (DBM)), a novel smartphone-based app used by cancer patients in conjunction with a wearable device (Apple Watch®). DBM is designed to collect patient-reported outcomes and record physical functions., Methods: In a fully decentralized "bring-your-own-device" smartphone study, we enrolled 54 cancer patient and caregiver dyads from Kaiser Permanente Northern California (KPNC) from October 2020 through March 2021. Patients used the app for at least 28 days, completed weekly questionnaires about their symptoms, physical functions, and mood, and performed timed physical tasks. Usability was determined through a subset of the Mobile App Rating Scale (MARS), the full System Usability Scale (SUS), the Net Promoter Score (NPS), and semi-structured interviews., Results: We obtained usability survey data from 50 of 54 patients. Median responses to the selected MARS questions and the mean SUS scores indicated above average usability. The NPS from the semi-structured interviews at the end of the study was 24, indicating a favorable score., Conclusions: Cancer patients reported above average usability for the DBM app. Qualitative analyses indicated that the app was easy to use and helpful. Future work will emphasize implementing further patient recommendations and evaluating the app's clinical efficacy in multiple settings., Competing Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: IOG, SWD, and RY are employed by Medable Inc., which developed the DBM app with funding from the National Institutes of Health through the Small Business Innovation Research program with the National Cancer Institute. SJF is subcontracted to work with Medable to analyze the study data., (© The Author(s) 2023.)

In this study, we examined the ventral process of C6 in extinct and extant Equus (sister taxa to Equus ferus caballus only) with the purpose of describing normal morphology and identifying anomalous variations relevant to recent studies describing a congenital malformation in E. ferus caballus . Overall, 83 specimens from 9 museums and 3 research/educational facilities were examined, totalling 71 extinct specimens from 12 species and 12 extant specimens from 5 species. The lateral view revealed that a large convexity exists in the ventral process between the cranial ventral tubercle (CrVT) and the caudal ventral tubercle (CVT) in the earliest ancestor, Hyracotherium grangeri , from 55 mya, which receded throughout the millennia to become a smaller convexity in E. ferus caballus and the sister taxa. The CrVT is visibly shorter and narrower than the CVT, with a constricted section directly ventral to the transverse process, essentially demarcating the CrVT and CVT. No congenital malformations were evident. As the ventral process of C6 is an integral component for muscle attachment in supporting the head/neck during posture and locomotion, this would indicate that the caudal module in the cervical column might be compromised when a partial or complete absence of the CVT is detected via radiographs in modern E. ferus caballus .

Background: Validating new algorithms, such as methods to disentangle intrinsic treatment risk from risk associated with experiential learning of novel treatments, often requires knowing the ground truth for data characteristics under investigation. Since the ground truth is inaccessible in real world data, simulation studies using synthetic datasets that mimic complex clinical environments are essential. We describe and evaluate a generalizable framework for injecting hierarchical learning effects within a robust data generation process that incorporates the magnitude of intrinsic risk and accounts for known critical elements in clinical data relationships., Methods: We present a multi-step data generating process with customizable options and flexible modules to support a variety of simulation requirements. Synthetic patients with nonlinear and correlated features are assigned to provider and institution case series. The probability of treatment and outcome assignment are associated with patient features based on user definitions. Risk due to experiential learning by providers and/or institutions when novel treatments are introduced is injected at various speeds and magnitudes. To further reflect real-world complexity, users can request missing values and omitted variables. We illustrate an implementation of our method in a case study using MIMIC-III data for reference patient feature distributions., Results: Realized data characteristics in the simulated data reflected specified values. Apparent deviations in treatment effects and feature distributions, though not statistically significant, were most common in small datasets (n < 3000) and attributable to random noise and variability in estimating realized values in small samples. When learning effects were specified, synthetic datasets exhibited changes in the probability of an adverse outcomes as cases accrued for the treatment group impacted by learning and stable probabilities as cases accrued for the treatment group not affected by learning., Conclusions: Our framework extends clinical data simulation techniques beyond generation of patient features to incorporate hierarchical learning effects. This enables the complex simulation studies required to develop and rigorously test algorithms developed to disentangle treatment safety signals from the effects of experiential learning. By supporting such efforts, this work can help identify training opportunities, avoid unwarranted restriction of access to medical advances, and hasten treatment improvements., (© 2023. The Author(s).)

Background and Objective: Breathlessness is prevalent and associated with medical consequences. Obesity is related to breathlessness. However, the magnitude of its contribution has not been clearly documented. This investigation aimed to determine the contribution of obesity to breathlessness by estimating the population attributable fraction (PAF) in a representative sample of Australian adults., Methods: A cross-sectional, nationally representative survey of Australian residents aged ≥18 years was conducted in October 2019. Breathlessness was defined as modified Medical Research Council (mMRC) dyspnoea scale grade ≥2. BMI was calculated from self-reported height and weight. Adjusted relative risks (aRRs) were estimated using a generalized linear model with Poisson distribution, adjusted for age group and/or participant-reported diagnosed illnesses. Adjusted PAFs were estimated using aRR and obesity prevalence in Australian adults., Results: Among those who completed the National Breathlessness Survey, 9769 participants (51.4% female) were included in the analysis; 28.1% of participants were obese. The prevalence of breathlessness was 9.54%. The aRR of obesity for breathlessness was 2.04, adjusted for age. Adjusting for various co-morbid conditions, the aRR was slightly attenuated to around 1.85-1.98. The PAF, adjusted only for age, was 24.6% (95% CI 20.1-29.1) and after further adjustment for co-morbid conditions, the PAF ranged from 21.1% to 23.6%. Obesity accounted for a higher proportion of breathlessness in women than in men., Conclusion: Our results demonstrate that obesity accounts for around a quarter of breathlessness symptoms in Australian adults. This has important implications for health policy in light of the global trend in increasing obesity., (© 2022 The Authors. Respirology published by John Wiley & Sons Australia, Ltd on behalf of Asian Pacific Society of Respirology.)

Informal caregivers are a critical source of support for cancer patients. However, their perspectives are not routinely collected, despite health impacts related to the burden of caregiving. We created the TOGETHERCare smartphone application (app) to collect observer-reported outcomes regarding the cancer patient's health and caregiver's perceptions of their own mental and physical health, and to provide tips and resources for self-care and patient care. We enrolled 54 caregivers between October 2020 and March 2021 from Kaiser Permanente Northern California (KPNC), an integrated healthcare system. Fifty caregivers used the app for approximately 28 days. Usability and acceptability were assessed using questions from the Mobile App Rating Scale (MARS), the System Usability Scale (SUS), the Net Promoter Score (NPS), and semi-structured interviews. The caregivers' mean age was 54.4 years, 38% were female and 36% were non-White. The SUS total mean score was 83.4 (SD = 14.2), for a percentile rank of 90-95 ("excellent"). Median MARS responses to the functionality questions were also high. The NPS score of 30 at the end of the study indicated that most caregivers would recommend the app. Themes from semi-structured interviews were consistent across the study period and indicated that the app was easy to use and helpful. Caregivers indicated a need for feedback from the app, suggested some changes to the wording of questions, the app's visuals, and timing of notifications. This study demonstrated that caregivers are willing to complete frequent surveys about themselves and their patients. The app is unique because it provides a remote method to collect caregivers' observations about the patient that may be useful for clinical care. To our knowledge, TOGETHERCare is the first mobile app developed specifically to capture adult cancer patient symptoms from the informal caregiver's perspective. Future research will examine whether use of this app can help improve patient outcomes., Competing Interests: IOG, SWD, and RY are employed by Medable Inc., which developed the TOGETHERCare app with funding from the National Institutes of Health. IOG and RY are also Medable stockholders. AI, SJA, MER, and SJF were all paid under subcontracts with Medable, Inc., (Copyright: © 2023 Oakley-Girvan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Up to 14% of patients in the United States undergoing cardiac catheterization each year experience AKI. Consistent use of risk minimization preventive strategies may improve outcomes. We hypothesized that team-based coaching in a Virtual Learning Collaborative (Collaborative) would reduce postprocedural AKI compared with Technical Assistance (Assistance), both with and without Automated Surveillance Reporting (Surveillance)., Methods: The IMPROVE AKI trial was a 2×2 factorial cluster-randomized trial across 20 Veterans Affairs medical centers (VAMCs). Participating VAMCs received Assistance, Assistance with Surveillance, Collaborative, or Collaborative with Surveillance for 18 months to implement AKI prevention strategies. The Assistance and Collaborative approaches promoted hydration and limited NPO and contrast dye dosing. We fit logistic regression models for AKI with site-level random effects accounting for the clustering of patients within medical centers with a prespecified interest in exploring differences across the four intervention arms., Results: Among VAMCs' 4517 patients, 510 experienced AKI (235 AKI events among 1314 patients with preexisting CKD). AKI events in each intervention cluster were 110 (13%) in Assistance, 122 (11%) in Assistance with Surveillance, 190 (13%) in Collaborative, and 88 (8%) in Collaborative with Surveillance. Compared with sites receiving Assistance alone, case-mix-adjusted differences in AKI event proportions were -3% (95% confidence interval [CI], -4 to -3) for Assistance with Surveillance, -3% (95% CI, -3 to -2) for Collaborative, and -5% (95% CI, -6 to -5) for Collaborative with Surveillance. The Collaborative with Surveillance intervention cluster had a substantial 46% reduction in AKI compared with Assistance alone (adjusted odds ratio=0.54; 0.40-0.74)., Conclusions: This implementation trial estimates that the combination of Collaborative with Surveillance reduced the odds of AKI by 46% at VAMCs and is suggestive of a reduction among patients with CKD., Clinical Trial Registry Name and Registration Number: IMPROVE AKI Cluster-Randomized Trial (IMPROVE-AKI), NCT03556293., (Copyright © 2023 by the American Society of Nephrology.)

Understanding the local-scale spatial and temporal variability of ozone formation is crucial for effective mitigation. We combine tropospheric vertical column densities (VCD Trop ) of formaldehyde (HCHO) and nitrogen dioxide (NO 2 ), referred to as HCHO-VCD Trop and NO 2 -VCD Trop , retrieved from airborne remote sensing and the TROPOspheric Monitoring Instrument (TROPOMI) with ground-based measurements to investigate changes in ozone precursors and the inferred chemical production regime on high-ozone days in May-August 2018 over two Northeast urban domains. Over New York City (NYC) and Baltimore/Washington D.C. (BAL/DC), HCHO-VCD Trop increases across the domain, but higher NO 2 -VCD Trop occurs mainly in urban centers on ozone exceedance days (when maximum daily 8 h average (MDA8) ozone exceeds 70 ppb at any monitor in the region). The ratio of HCHO-VCD Trop to NO 2 -VCD Trop , proposed as an indicator of the sensitivity of local surface ozone production rates to its precursors, generally increases on ozone exceedance days, implying a transition toward a more NO x -sensitive ozone production regime that should lead to higher efficacy of NO x controls on the highest ozone days in NYC and BAL/DC. Warmer temperatures and enhanced influence from emissions in the local boundary layer on the high-ozone days are accompanied by slower wind speeds in BAL/DC but stronger, southwesterly winds in NYC.

Rationale, Aims, and Objectives: Chronic pain is a global public health problem that negatively impacts individuals' quality of life and imposes a substantial economic burden on societies. The use of medicinal cannabis (MC) is often considered by patients to help manage chronic pain as an alternative or supplement to more conventional treatments, given enabling legalization in a number of countries. However, healthcare professionals involved in providing guidance for patients related to MC are often doing so in the absence of strong evidence and clinical guidelines. Therefore, it is crucial to understand their perspectives regarding the clinical use and relevance of MC for chronic pain. As little is known about attitudes of HCPs with regard to MC use for chronic pain specifically, the aim of this review was to identify and synthesize the published evidence on this topic., Methods: A systematic search was conducted across six databases: MEDLINE, EMBASE, CINAHL, Scopus, Web of Science, and PubMed from 2001 to March 26, 2021. Three authors independently performed the study selection and data extraction. Thematic analysis was undertaken to identify key themes., Results: A total of 26 studies were included, involving the United States, Israel, Canada, Australia, Ireland, and Norway, and the perspectives of physicians, nurses, and pharmacists. Seven key themes were identified: MC as a treatment option for chronic pain, and perceived indicated uses; willingness to prescribe MC; legal issues; low perceived knowledge and the need for education; comparative safety of MC versus opioids; addiction and abuse; and perceived adverse effects; CONCLUSION: To support best practice in the use of MC for chronic pain, healthcare professionals require education and training, as well as clinical guidelines that provide evidence-based information about efficacy, safety, and appropriate dosage of products for this indication. Until these gaps are addressed, healthcare professionals will be limited in their capacity to make treatment recommendations about MC for people/patients with chronic pain., (© 2022 The Authors. Pain Practice published by Wiley Periodicals LLC on behalf of World Institute of Pain.)

As the implementation of artificial intelligence (AI)-enabled tools is realized across diverse clinical environments, there is a growing understanding of the need for ongoing monitoring and updating of prediction models. Dataset shift-temporal changes in clinical practice, patient populations, and information systems-is now well-documented as a source of deteriorating model accuracy and a challenge to the sustainability of AI-enabled tools in clinical care. While best practices are well-established for training and validating new models, there has been limited work developing best practices for prospective validation and model maintenance. In this paper, we highlight the need for updating clinical prediction models and discuss open questions regarding this critical aspect of the AI modeling lifecycle in three focus areas: model maintenance policies, performance monitoring perspectives, and model updating strategies. With the increasing adoption of AI-enabled tools, the need for such best practices must be addressed and incorporated into new and existing implementations. This commentary aims to encourage conversation and motivate additional research across clinical and data science stakeholders., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2022 Davis, Walsh and Matheny.)

Most of the benefit of asthma preventer inhalers is seen with low doses. However, many Australian patients are prescribed doses of inhaled corticosteroids that are higher than necessary to control their asthma. Prescribing unnecessarily high preventer doses increases the patient's risk of adverse effects. They may also increase the patient's out-of-pocket costs. Asthma guidelines recommend considering a step-down in preventer treatment after asthma has been well controlled for two to three months in adults and for six months in children. The step-down process should be individualised for each patient. Preventive therapy should not be stopped completely., Competing Interests: Conflicts of interest: In the last three years, Helen Reddel’s institute has received independent research funding from AstraZeneca, GlaxoSmithKline and Novartis. She or her institute has received honoraria for participation in advisory boards for AstraZeneca, Chiesi, GlaxoSmithKline, Novartis and Sanofi-Genzyme; honoraria from AstraZeneca, Boehringer Ingelheim, Chiesi, GlaxoSmithKline, Sanofi-Genzyme and Teva for independent medical educational presentations; consulting fees from AstraZeneca and Novartis. Helen Reddel is Chair of the Global Initiative for Asthma (GINA) Science Committee, and a member of the Australian Asthma Handbook Guidelines Committee. In the last three years, Gloria Foxley’s institute has received independent research funding from AstraZeneca, GlaxoSmithKline and Novartis. In the last three years, Sharon R Davis’s institute has received independent research funding from AstraZeneca, GlaxoSmithKline and Novartis., ((c) NPS MedicineWise.)

Background: The utility of quality dashboards to inform decision-making and improve clinical outcomes is tightly linked to the accuracy of the information they provide and, in turn, accuracy of underlying prediction models. Despite recognition of the need to update prediction models to maintain accuracy over time, there is limited guidance on updating strategies. We compare predefined and surveillance-based updating strategies applied to a model supporting quality evaluations among US veterans., Methods: We evaluated the performance of a US Department of Veterans Affairs-specific model for postcardiac catheterization acute kidney injury using routinely collected observational data over the 6 years following model development (n=90 295 procedures in 2013-2019). Predicted probabilities were generated from the original model, an annually retrained model, and a surveillance-based approach that monitored performance to inform the timing and method of updates. We evaluated how updating the national model impacted regional quality profiles. We compared observed-to-expected outcome ratios, where values above and below 1 indicated more and fewer adverse outcomes than expected, respectively., Results: The original model overpredicted risk at the national level (observed-to-expected outcome ratio, 0.75 [0.74-0.77]). Annual retraining updated the model 5×; surveillance-based updating retrained once and recalibrated twice. While both strategies improved performance, the surveillance-based approach provided superior calibration (observed-to-expected outcome ratio, 1.01 [0.99-1.03] versus 0.94 [0.92-0.96]). Overprediction by the original model led to optimistic quality assessments, incorrectly indicating most of the US Department of Veterans Affairs' 18 regions observed fewer acute kidney injury events than predicted. Both updating strategies revealed 16 regions performed as expected and 2 regions increasingly underperformed, having more acute kidney injury events than predicted., Conclusions: Miscalibrated clinical prediction models provide inaccurate pictures of performance across clinical units, and degrading calibration further complicates our understanding of quality. Updating strategies tailored to health system needs and capacity should be incorporated into model implementation plans to promote the utility and longevity of quality reporting tools.

Educational practices to reduce negative attitudes toward persons with substance use disorders (SUD) are urgently needed for undergraduate nursing students, but few studies have examined their long term effectiveness. In this pilot, consenting students completed the Drug and Drug Problems Perception Questionnaire (DDPPQ) anonymously online, before and 1 year after integrated curricular content about SUD. Pretest scores were significantly higher than posttest, indicating higher negative attitudes toward persons with SUD before the integrated content. Time main effect was statistically significant. To our knowledge, this is the first report examining long-term effects of an educational intervention with reinforcement in multiple courses over time upon the attitudes of undergraduate nursing students toward persons with SUD.

Purpose: We examined if childhood socioeconomic status (SES) was related to adult leucocyte telomere length (TL) using the data of 361 African American (AA) participants from the GENE-FORECAST Study. We also assessed the mediating role of behavioral and psychosocial factors in the association between childhood SES and adult TL., Methods: Childhood SES was assessed individually by using participant's mother's education and occupation, father's education and occupation, parental home ownership, and family structure. TL was assessed using the quantitative polymerase chain reaction method. Information on potential confounders and mediators were collected. The associations of childhood SES with TL were assessed using multivariable linear regression models. We used path analysis to quantify and test the share of these associations that was statistically explained by each of the mediators (participant's educational attainment, smoking status, physical activity, dietary habit, perceived stress, and depressive symptoms)., Results: Mother's education was associated with longer average TL (β: 0.021; 95% CI: 0.001, 0.04, p=0.038) in confounder adjusted models. Once mediators were introduced in the model, the estimates were reduced and remained marginally significant (β: 0.017; 95% CI: -0.003, 0.038, p=0.061). According to path model, approximately 19% of the effect of mother's education on TL (β: 0.004; 95% CI: -0.001, 0.01, p < 0.10) was mediated through participant's own education level. No significant mediation effect was observed for any other mediators., Conclusions: These data provide evidence that participant's mother's education was positively linked to adult TL in AA population. Participant's own educational level partially explained this association., (© 2021. The Author(s).)

Background: Unfair treatment such as discrimination and racism contribute to depression and perceived stress in African Americans. Although studies have examined how responding to such treatment is associated with ameliorating depressive symptoms and levels of perceived stress, most do not focus on African Americans. The purpose of this study is to assess how talking to others in response to unfair treatment is associated with self-reported depressive symptoms and perceived stress levels in African Americans., Methods: A sample from the 2010-2013 Minority Health Genomics and Translational Research Bio-Repository Database was used and consisted of 376 African American adults aged 30-55 years old residing in the southern region of the United States. Linear regression models were used to assess the association between talking to others following unfair treatment, compared to keeping it to oneself, on self-reported depressive symptoms and perceived stress. The predictor variable was based on the question "If you have been treated unfairly, do you usually talk to people about it or keep it to yourself?"., Results: Talking to someone after being treated unfairly was inversely associated with perceived stress ([Formula: see text]: -3.62, SE: 1.14, p ≤ 0.05) and depressive symptoms ([Formula: see text]: -3.62, SE: 1.14, p ≤ 0.05)., Conclusions: African Americans who talked to others in response to unfair treatment had lower depressive symptoms and perceived stress than those who kept it to themselves. More outreach to African Americans regarding the importance of talk in response to exposure to unfair treatment is needed as a potential coping mechanism., (© 2022. The Author(s).)

Background: Approximately 6.1 million adults in the United States serve as care partners for cancer survivors. Studies have demonstrated that engaging cancer survivors and their care partners through technology-enabled structured symptom collection has several benefits. Given the high utilization of mobile technologies, even among underserved populations and in low resource areas, mobile apps may provide a meaningful access point for all stakeholders for symptom management., Objective: We aimed to develop a mobile app incorporating user preferences to enable cancer survivors' care partners to monitor the survivors' health and to provide care partner resources., Methods: An iterative information gathering process was conducted that included (1) discussions with 138 stakeholders to identify challenges and gaps in survivor home care; (2) semistructured interviews with clinicians (n=3), cancer survivors (n=3), and care partners (n=3) to identify specific needs; and (3) a 28-day feasibility field test with seven care partners., Results: Health professionals noted the importance of identifying early symptoms of adverse events. Survivors requested modules on medication, diet, self-care, reminders, and a version in Spanish. Care partners preferred to focus primarily on the patient's health and not their own. The app was developed incorporating quality-of-life surveys and symptom reporting, as well as resources on home survivor care. Early user testing demonstrated ease of use and app feasibility., Conclusions: TOGETHERCare, a novel mobile app, was developed with user input to track the care partner's health and report on survivor symptoms during home care. The following two clinical benefits emerged: (1) reduced anxiety among care partners who use the app and (2) the potential for identifying survivor symptoms noted by the care partner, which might prevent adverse events., Trial Registration: ClinicalTrials.gov NCT04018677; https://clinicaltrials.gov/ct2/show/NCT04018677., (©Ingrid Oakley-Girvan, Sharon Watkins Davis, Allison Kurian, Lisa G Rosas, Jena Daniels, Oxana Gronskaya Palesh, Rachel J Mesia, Arif H Kamal, Michelle Longmire, Vasu Divi. Originally published in JMIR Formative Research (https://formative.jmir.org), 13.08.2021.)

Purpose: The COVID-19 pandemic has had a profound impact on American life. However, the burden of the pandemic has not been distributed equally. The purpose of this study was to investigate whether racial and economic residential segregation were associated with COVID-19 related factors in the nation's capital, Washington D.C., during the first year of the pandemic., Methods: Racial, economic, and racialized economic segregation were assessed using the Index of Concentration at the Extremes measure and data from the 2014-2018 American Community Survey. COVID-19 related factors (i.e., incidence, testing rate, and percent positivity) were assessed using data from the Washington D.C. government. Spearman rank correlation was used to assess the relationship between each segregation measure and each COVID-19 related factor., Results: Washington D.C. neighborhoods with a higher concentration of African Americans, lower income residents, and African Americans with low income had a higher incidence of COVID-19 and greater percent positivity, but lower testing rates compared to their counterparts., Conclusions: There is a geographic mismatch between neighborhoods most vulnerable to COVID-19 and the neighborhoods where the testing resources are being used. More resources should be allocated to the most vulnerable neighborhoods to address the COVID-19 pandemic in an equitable manner., (Copyright © 2021. Published by Elsevier Inc.)

Objective: This pilot aimed to test the engagement, acceptability, and usefulness of a goal-setting smartphone app, Kiss myAsthma, in young people with asthma. Methods: Young people aged 15-24 years old were invited to trial a smartphone app for asthma management. A mixed-methods approach combined quantitative analysis of self-report questionnaires and app usage log data with qualitative thematic analysis of open-ended questions at baseline and six weeks after downloading the app. App log data (pages visited, frequency of use and content of participants interaction, e.g.goals set, symptoms recorded) were analyzed. Results : Nine of 12 participants completed both baseline and six-week questionnaires. Participants reported high satisfaction with app content and usability (median score 5 out of 6 [range 4-6]) and rated the app highly on "feeling confident in my ability to manage my asthma." At six weeks there was a clinically significant change in asthma quality of life (e.g. Emotional Function domain score baseline: 4.7 [2.7-6.3], follow-up: 5.7 [4.7-6.7]; p  = 0.043). Participants logged information about asthma severity, flare-ups and mood and tracked their symptoms with the app's History functionality. Five participants (42%) nominated goals and strategies and 3 participants (25%) entered data in the Inspiration section, a tool to support intrinsic motivation to manage asthma. Qualitative data aligned with quantitative results. Conclusions: This six-week pilot of the Kiss myAsthma app showed its potential to support self-management, quality of life and health behavior change in young people with asthma.

Rabbits are the third most common mammalian pet in the United States. They make good pets because they generally are nonaggressive and are playful, active, and curious. They form strong social bonds, both with rabbits they live with in the household and with the humans who care for them. They have several behaviors derived from their wild counterparts that can cause problems, if not properly allowed for, or be beneficial, such as their proclivity to use a specific site for elimination., Competing Interests: Disclosure The author has nothing to disclose., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Model calibration, critical to the success and safety of clinical prediction models, deteriorates over time in response to the dynamic nature of clinical environments. To support informed, data-driven model updating strategies, we present and evaluate a calibration drift detection system. Methods are developed for maintaining dynamic calibration curves with optimized online stochastic gradient descent and for detecting increasing miscalibration with adaptive sliding windows. These methods are generalizable to support diverse prediction models developed using a variety of learning algorithms and customizable to address the unique needs of clinical use cases. In both simulation and case studies, our system accurately detected calibration drift. When drift is detected, our system further provides actionable alerts by including information on a window of recent data that may be appropriate for model updating. Simulations showed these windows were primarily composed of data accruing after drift onset, supporting the potential utility of the windows for model updating. By promoting model updating as calibration deteriorates rather than on pre-determined schedules, implementations of our drift detection system may minimize interim periods of insufficient model accuracy and focus analytic resources on those models most in need of attention., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Obesity is associated with age-related health conditions and telomere attrition - a marker of cellular aging. Obesity is attributable to adverse modifiable lifestyle factors. Little is known about the mediation effect of lifestyle factors associated with the relationship between obesity and telomere length. Our objective was to examine this association in the US. Pack years smoked, drinking level per day, physical activity (PA) per week and diet based on Healthy Eating Index (HEI) were assessed as mediators associated with the relationship between adiposity measures and leukocyte telomere length (LTL); adiposity measures included body mass index (BMI), % total body fat (TBF) and waist circumference (WC). Separate adjusted linear regressions and mediation analysis were conducted on a total of 4919 respondents aged 20-84 years using cross-sectional 1999-2002 data from the US National Health and Nutrition Examination Survey. Inadequate PA correlated with 1.28% shorter LTL and was a factor accounting for 35% of the relationship between BMI and LTL (β = -0.0128, 95% CI = 0.0259, 0.0004, p = .05). Smoking 30-≥59 pack years correlated with 4% shorter LTL and accounted for 21% of the relationship between %TBF and LTL (β = -0.0386, 95% CI = -0.0742, -0.0030, p = .03). Improvement in diet correlated with 0.11% longer LTL and contributed 25% of the association between %TBF and LTL (β = 0.0011, 95%CI =0.0004, 0.0018, p = .01). Diet correlated with 0.11% longer LTL and correspond to 28% of the relationship between WC and LTL (β = 0.0011, 95%CI = 0.0004, 0.0018, p = .03). Interventions to improve modifiable behaviors may ameliorate cellular aging and aging related health conditions due to obesity among US adults., Competing Interests: Declaration of competing interest The authors have no competing interest to disclose., (Published by Elsevier Inc.)

Objective: Little is known about the relationship between adiposity and telomere length in the United States population. The objective of our research was to examine this relationship in a representative, socioeconomically and sex-specific, diverse racial/ethnic population in the United States., Methods: Body mass index (BMI), % total body fat (TBF) and waist circumference (WC) with leukocyte telomere length (LTL) were examined according to sex-specific race/ethnicity using separate adjusted multivariate linear regressions on a sample of 4,919 respondents aged 20-84 years from the National Health and Nutrition Examination Survey's 1999-2002 data., Results: LTL was shortened .41%, .44%, and .16% in African American (AA) women and was associated with increasing BMI, %TBF, and WC, ( β :-.0041, 95%CI: -.0070, -.0012; P=.007; β :-.0044, 95% CI: -.0081, -.0007; P=.02; β :-.0016, 95%CI: -.0031, -.0001; P=.04, respectively). LTL was shortened .29% in White women and was associated with increasing %TBF ( β :-.0029, 95%CI: -.0048, -.0009; P=.006). There were no associations among AA men, White men or Mexican American men and women., Conclusions: LTL is associated with an obesity phenotype in AA women. Tailored intervention is needed to ameliorate the burden of excess adiposity and subsequent cellular aging., Competing Interests: Competing Interests: None declared., (Copyright © 2020, Ethnicity & Disease, Inc.)

Ultrasound is a well-established modality in equine investigative and diagnostic procedures. Although to date, it has not been utilized in examining the attachments of the equine nuchal ligament lamellae (NLL) onto the cervical vertebrae, for which a noninvasive technique is currently lacking. This study presents a standardized methodology for investigating the equine NLL using ultrasonography, and further evaluates the ultrasound images against postmortem dissection in two nonrelated horses. The ultrasound images in both horses clearly presented the attachment points of the NLL to the dorsal spines of the cervical vertebrae from C2 to C5, whereas no attachment points could be seen from C6 to C7. The ultrasound images were confirmed through close, comparative inspection of the NLL postmortem. Therefore, ultrasound provides a noninvasive alternative to gross anatomic dissections for investigating the NLL attachments in members of the family Equidae. Importantly, this provides an opportunity to examine endangered breeds or isolated populations without the detrimental loss to the gene pool of rare anatomic and or primitive traits., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Early hospital readmission for patients with cirrhosis continues to challenge the healthcare system. Risk stratification may help tailor resources, but existing models were designed using small, single-institution cohorts or had modest performance., Aims: We leveraged a large clinical database from the Department of Veterans Affairs (VA) to design a readmission risk model for patients hospitalized with cirrhosis. Additionally, we analyzed potentially modifiable or unexplored readmission risk factors., Methods: A national VA retrospective cohort of patients with a history of cirrhosis hospitalized for any reason from January 1, 2006, to November 30, 2013, was developed from 123 centers. Using 174 candidate variables within demographics, laboratory results, vital signs, medications, diagnoses and procedures, and healthcare utilization, we built a 47-variable penalized logistic regression model with the outcome of all-cause 30-day readmission. We excluded patients who left against medical advice, transferred to a non-VA facility, or if the hospital length of stay was greater than 30 days. We evaluated calibration and discrimination across variable volume and compared the performance to recalibrated preexisting risk models for readmission., Results: We analyzed 67,749 patients and 179,298 index hospitalizations. The 30-day readmission rate was 23%. Ascites was the most common cirrhosis-related cause of index hospitalization and readmission. The AUC of the model was 0.670 compared to existing models (0.649, 0.566, 0.577). The Brier score of 0.165 showed good calibration., Conclusion: Our model achieved better discrimination and calibration compared to existing models, even after local recalibration. Assessment of calibration by variable parsimony revealed performance improvements for increasing variable inclusion well beyond those detectable for discrimination.

In evolving clinical environments, the accuracy of prediction models deteriorates over time. Guidance on the design of model updating policies is limited, and there is limited exploration of the impact of different policies on future model performance and across different model types. We implemented a new data-driven updating strategy based on a nonparametric testing procedure and compared this strategy to two baseline approaches in which models are never updated or fully refit annually. The test-based strategy generally recommended intermittent recalibration and delivered more highly calibrated predictions than either of the baseline strategies. The test-based strategy highlighted differences in the updating requirements between logistic regression, L1-regularized logistic regression, random forest, and neural network models, both in terms of the extent and timing of updates. These findings underscore the potential improvements in using a data-driven maintenance approach over "one-size fits all" to sustain more stable and accurate model performance over time., (©2019 AMIA - All rights reserved.)

Background: Growing evidence suggests that leptin is critical for glycemic control. Impaired leptin signaling may also contribute to low adiponectin expression in obese individuals. We assessed the association of leptin and adiponectin with incident type 2 diabetes (T2D), their interactions with sex and obesity status, and mediation by insulin resistance., Methods: We included study participants from the Jackson Heart Study, a prospective cohort of adult African Americans in Jackson, Mississippi, that were free of T2D at the baseline Exam 1. Incident T2D was defined as new cases at Exam 2 or Exam 3. We created separate Cox regression models (hazard ratios per log-transformed ng/mL of leptin and adiponectin) with and without insulin resistance, HOMA-IR. Mediation by insulin resistance was analyzed. Several interactions were assessed, including by sex, HbA1c, and obesity., Results: Among our 3363 participants (mean age 53 years, 63% women), 584 developed incident T2D. Leptin was directly associated with incident T2D when modeled without HOMA-IR (HR = 1.29, 95% CI = 1.05-1.58). This direct association between leptin and T2D was significant among men (HR = 1.33, 95% CI = 1.05-1.69), but nonsignificant among women (HR = 1.24, 95% CI = 0.94-1.64); statistical interaction with sex was nonsignificant (p = 0.65). The associations in all participants and in men were nullified by HOMA-IR (HR = 0.99, 95% CI = 0.80-1.22; HR = 1.00, 95% CI = 0.78-1.28, respectively), indicating mediation through insulin resistance (proportion mediated: 1.04), and were not observed in abdominally obese participants. Adiponectin was inversely associated with T2D even after adjustment for HOMA-IR in women (HR = 0.68, 95% CI = 0.55-0.84), but not in men (HR = 0.80, 95% CI = 0.62-1.04). The inverse association was present only among abdominally obese participants, and persisted after adjustment for HOMA-IR., Conclusions: Among African Americans in the Jackson Heart Study the association of leptin with incident type 2 diabetes was mediated by insulin resistance. This association was present only among abdominally non-obese participants. Differences by sex appeared: men showed a significant association mediated by insulin resistance. Among abdominally obese participants, adiponectin was inversely associated with incident T2D even after adjustment for HOMA-IR. Our results should inform future clinical trials that aim to reduce the burden of type 2 diabetes through the modification of serum levels of leptin and adiponectin.

Purpose: To examine the longitudinal effects of a history of neonatal abstinence syndrome (NAS) on language development over the first 10 years of life., Design and Methods: This study used a retrospective, longitudinal design. The data were analyzed using generalized linear mixed models (GLMM) to examine the effects of NAS on language delay over time while controlling for demographic, prenatal, and household factors., Results: There was a significant difference in the pattern of language delays over time between the NAS and non-NAS groups. At the age of 5 (est: -1.788, p < .001), children with a history of NAS had a decreased log odds of developing language delays than those without NAS. Conversely, compared with age 1, at the age of 10 (est: 1.098 p < .001), children with a history of NAS had an increased log odds of developing language delays than those without NAS., Conclusions: Children with a history of NAS had significantly different rates of language delays over time. Children with a history of NAS had significantly higher rates of language delays at 10 years than children without NAS., Practice Implications: There is a need to increase developmental surveillance, along with referrals for specialized services, for children with a history of NAS through middle childhood., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest., (Copyright © 2019 Elsevier Inc. All rights reserved.)

For over 200 years, equine anatomic literature has chiefly portrayed the attachment points of the nuchal ligament lamellae (NLL) from the second to the seventh cervical vertebrae (C2-C7). However, recent studies have shown that the modern domestic horse, Equus caballus, primarily exhibits the attachments points from C2-C5. Here we present the rare finding of a complete NLL attached from C2-C7 in one Australian Stock Horse (ASH) and discuss the potential implications of these findings. Previously, this trait has only been confirmed among close descendants of Equus ferus ferus; namely the primitive Dutch Konik and Bosnian Mountain Horse. The examination of the NLL attachment points in 55 unrelated horses of mixed breeds revealed that 52 horses had attachments from C2-C5; 1 horse (Welsh Cob) had attachments from C2-C6; and only 2 horses (ASH and Dutch Konik) presented with a complete NLL attached from C2-C7. In light of earlier findings that suggest this loss of NLL attachment at C6 and C7 occurred after domestication, a possible explanation for this finding in 1 ASH is that it is a remnant trait from the founder population of Waler horses that contributed to the early development of the ASH breed. The reported rare occurrence of a complete NLL (C2-C7) in a modern domesticated equine (ASH) suggests that there may be other individuals expressing this unique trait, providing opportunity for its preservation., (Copyright © 2019 Elsevier Inc. All rights reserved.)

The Yonaguni pony is a rare breed of pony that has remained isolated on the westernmost island of Japan and may well retain normal morphological traits currently lost in most domestic horses (Equus caballus), such as the attachment of the nuchal ligament lamellae (NLL) from C2-C7. Recent research has found that NLL attachments are no longer present at C6 and C7 in most modern domesticated horses. This study investigated the attachments of the NLL in three Yonaguni ponies; 2 were examined in situ(deceased), and 1 was examined in vivo via ultrasound. The aim was to verify the attachments and compare the morphology to that in equids from previous studies. The in situ (2/2) and in vivo (1/1) findings revealed that the NLL was attached from C2-C7 in the Yonaguni ponies., (©2020 The Japanese Society of Equine Science.)

Objective: Clinical prediction models require updating as performance deteriorates over time. We developed a testing procedure to select updating methods that minimizes overfitting, incorporates uncertainty associated with updating sample sizes, and is applicable to both parametric and nonparametric models., Materials and Methods: We describe a procedure to select an updating method for dichotomous outcome models by balancing simplicity against accuracy. We illustrate the test's properties on simulated scenarios of population shift and 2 models based on Department of Veterans Affairs inpatient admissions., Results: In simulations, the test generally recommended no update under no population shift, no update or modest recalibration under case mix shifts, intercept correction under changing outcome rates, and refitting under shifted predictor-outcome associations. The recommended updates provided superior or similar calibration to that achieved with more complex updating. In the case study, however, small update sets lead the test to recommend simpler updates than may have been ideal based on subsequent performance., Discussion: Our test's recommendations highlighted the benefits of simple updating as opposed to systematic refitting in response to performance drift. The complexity of recommended updating methods reflected sample size and magnitude of performance drift, as anticipated. The case study highlights the conservative nature of our test., Conclusions: This new test supports data-driven updating of models developed with both biostatistical and machine learning approaches, promoting the transportability and maintenance of a wide array of clinical prediction models and, in turn, a variety of applications relying on modern prediction tools., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: Cirrhotic patients are at high hospitalisation risk with subsequent high mortality. Current risk prediction models have varied performances with methodological room for improvement. We used current analytical techniques using automatically extractable variables from the electronic health record (EHR) to develop and validate a posthospitalisation mortality risk score for cirrhotic patients and compared performance with the model for end-stage liver disease (MELD), model for end-stage liver disease with sodium (MELD-Na), and the CLIF Consortium Acute Decompensation (CLIF-C AD) models., Design: We analysed a retrospective cohort of 73 976 patients comprising 247 650 hospitalisations between 2006 and 2013 at any of 123 Department of Veterans Affairs hospitals. Using 45 predictor variables, we built a time-dependent Cox proportional hazards model with all-cause mortality as the outcome. We compared performance to the three extant models and reported discrimination and calibration using bootstrapping. Furthermore, we analysed differential utility using the net reclassification index (NRI)., Results: The C-statistic for the final model was 0.863, representing a significant improvement over the MELD, MELD-Na, and the CLIF-C AD, which had C-statistics of 0.655, 0.675, and 0.679, respectively. Multiple risk factors were significant in our model, including variables reflecting disease severity and haemodynamic compromise. The NRI showed a 24% improvement in predicting survival of low-risk patients and a 30% improvement in predicting death of high-risk patients., Conclusion: We developed a more accurate mortality risk prediction score using variables automatically extractable from an EHR that may be used to risk stratify patients with cirrhosis for targeted postdischarge management., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Socioeconomically disadvantaged neighborhoods have been associated with poor health outcomes. Little is known about the biological mechanism by which deprived neighborhood conditions exert negative influences on health. Data from the 1999-2002 National Health and Nutrition Examination Surveys (NHANES) were used to assess the relationship between neighborhood deprivation index (NDI) and log-transformed leukocyte telomere length (LTL) via multilevel modeling to control for census tract level clustering. Models were constructed using tertiles of NDI (ref = low NDI). NDI was calculated using census tract level socioeconomic indicators from the 2000 U.S. Census. The sample (n = 5,106 adults) was 49.8% female and consisted of 82.9% non-Hispanic whites, 9.4% non-Hispanic blacks, and 7.6% Mexican Americans. Mean age was 45.8 years. Residents of neighborhoods with high NDI were younger, non-white, had lower educational attainment, and had a lower poverty to income ratio (all p  < 0.0001). Neighborhood deprivation was inversely associated with LTL among individuals living in neighborhoods with medium NDI (β = -0.043, SE = 0.012, p  = 0.0005) and high NDI (β = -0.039, SE = 0.013, p  = 0.003). Among men, both medium (β = -0.042, SE = 0.015, p  = 0.006) and high (β = -0.047, SE = 0.015, p  = 0.001) NDI were associated with shorter LTL. Among women, only medium NDI (β = -0.020, SE = 0.016, p  = 0.009) was associated with shorter LTL. After controlling for individual characteristics, including individual-level socioeconomic status, increasing neighborhood socioeconomic deprivation is associated with shorter LTL among a nationally representative sample of US adults. This suggests that telomere shortening may be a mechanism through which neighborhood deprivation results in poor health outcomes.

Opioid use during pregnancy is on the rise in the United States. Neonatal abstinence syndrome (NAS), also known as newborn drug withdrawal, is a public health epidemic. Between 2004 and 2014, Tennessee experienced a fivefold increase in NAS hospitalizations, from 1.5 to 8.0 per 1,000 live births. Soaring increases in the number of newborns with NAS nationwide have caught the attention of many federal and state lawmakers, especially given the unknown burdens associated with medical and social services needed by those affected over time. Tennessee opioid-related regulations and laws enacted between 2000 and 2018 were systematically reviewed and analyzed to identify each law's purpose; effects on families and individuals; pros and cons in terms of social, practical, and legal factors; and implications for nursing practice. Our findings were that Tennessee's laws are intended to decrease the number of opioids prescribed, ensure access to continued prenatal care and substance abuse management for mothers with substance use disorders, and reduce the ease of obtaining opioids. We also found that Tennessee lawmakers have enacted laws and regulations aimed at decreasing the abuse of opioids, but not reducing the incidence of NAS. As new laws are considered, it is critical that health care providers and lawmakers work together to ensure that the developed and enacted laws strike a balance between safely managing the care of both pregnant women and their newborns without producing negative outcomes.

The 55-million-year history of equine phylogeny has been well-documented from the skeletal record; however, this is less true for the soft tissue structures that are now vestigial in modern horse. A recent study reported that two ligamentous structures resembling functional interosseous muscle II and IV were evident in Dutch Konik horses. The current study investigates this finding and compares it to members of the genus Equus to identify either a breed anomaly or functional primitive trait. Distal limbs ( n = 574) were dissected from four species of Equus ; E. caballus , E. asinus , E. przewalskii and E. quagga boehmi . E. caballus is represented by 18 breeds of horse, including the primitive Dutch Konik'. The interosseous muscle II and IV were evident in all four species, but only two breeds of E. caballus expressed this trait-the Dutch Konik and Bosnian Mountain Horse. These two breeds were the only close descendants of the extinct Equus ferus ferus (Tarpan) represented in this study. In conclusion, the interosseous muscle II and IV originated from the distal nodule of metacarpal II and IV, respectively, and inserted into the corresponding branches of interosseous muscle III proximal to the sesamoids. This suggests a functional role in medial and lateral joint stability and a primitive trait in modern equids.

Objective: To explore influences on patients' purchase and use of asthma preventer medicines and the perceived acceptability of financial incentives via reduced patient co-payments., Methods: Semi-structured telephone or face-to-face interviews were conducted with adults and carers of children with asthma. Interviews were recorded, transcribed verbatim and coded. Data were analysed using thematic analysis via grounded theory., Results: Twenty-four adults and 20 carers for children aged 3-17 years with asthma were interviewed. For medicines choice, most participants did not consider themselves the primary decision-maker; cost of medicines was an issue for some, but effectiveness was described as more important. For adherence, cost, side-effects, perceived benefit and patient behaviours were important., Conclusions: Patient barriers to adherence with asthma preventer medicines including cost are ongoing. Healthcare professionals need to encourage empathic discussion with patients about cost issues. Implications for public health: Asthma patients and carers could benefit from greater involvement and respect within shared decision-making. Healthcare professionals should be aware that cost may be a barrier for patient adherence, and provided with information about the relative costs of guideline-recommended asthma medicines. Patients and healthcare professionals need education around the efficacy of ICS-alone treatment and the rationale behind co-payments, for initiatives around quality use of medicines to succeed., (© 2019 The Authors.)