Disease Trajectory Research Articles

The impact of a primary brain tumor diagnosis on caregivers: Insights from the patients’ perspective

PurposeThe diagnosis of a primary brain tumor (PBT) causes significant distress for the caregiver-patient dyad, warranting increased supportive care intervention. Although researchers have previously assessed caregivers’ perceptions of their own supportive care needs, no study to date has identified how patients perceive the caregiving experience and/or patients’ recommendations for integrating supportive care of caregivers in neuro-oncology. This qualitative study examined caregiver distress as well as caregiver supportive care needs from the patients’ perspective to inform future intervention development.MethodsAdults with PBT (N = 15; Mage = 45; 53% female; 93% White) were divided into four, 90-min focus groups moderated by a clinical neuropsychologist. Patients responded to semi-structured interview questions regarding various supportive care needs throughout the course of disease. Each discussion was transcribed and coded using thematic content analysis and NVivo software. Inter-rater reliability was excellent (MKappa = 0.92, range = 0.85–0.93).ResultsSeven distinct codes related to PBT caregivers emerged and were classified into two broader themes: Caregiver Impact (47% of coded content) and Caregiver Support (53% of coded content). Caregiver Impact refers to patients’ perspective of the practical and emotional demands of caregiving. Under Caregiver Support, patients cited a strong need for increased support of caregivers, including bereavement care, individual psychotherapy, and joint caregiver-patient dyad sessions.ConclusionPatients with PBT expressed profound concerns regarding the demands of caregiving and its impact on the well-being of their loved ones. Findings emphasize the need for comprehensive dyadic support in neuro-oncology throughout the disease trajectory to enhance the overall quality-of-life for both patients and their caregivers.

The mRNA content of plasma extracellular vesicles provides a window into molecular processes in the brain during cerebral malaria.

The impact of cerebral malaria on the transcriptional profiles of cerebral tissues is difficult to study using noninvasive approaches. We isolated plasma extracellular vesicles (EVs) from patients with cerebral malaria and community controls and sequenced their mRNA content. Deconvolution analysis revealed that EVs from cerebral malaria are enriched in transcripts of brain origin. We ordered the patients with cerebral malaria based on their EV-transcriptional profiles from cross-sectionally collected samples and inferred disease trajectory while using healthy community controls as a starting point. We found that neuronal transcripts in plasma EVs decreased with disease trajectory, whereas transcripts from glial, endothelial, and immune cells increased. Disease trajectory correlated positively with severity indicators like death and was associated with increased VEGFA-VEGFR and glutamatergic signaling, as well as platelet and neutrophil activation. These data suggest that brain tissue responses in cerebral malaria can be studied noninvasively using EVs circulating in peripheral blood.

Study of Postacute Sequelae of COVID-19 Using Digital Wearables: Protocol for a Prospective Longitudinal Observational Study.

Postacute sequelae of COVID-19 (PASC) remain understudied in nonhospitalized patients. Digital wearables allow for a continuous collection of physiological parameters such as respiratory rate and oxygen saturation that have been predictive of disease trajectories in hospitalized patients. This protocol outlines the design and procedures of a prospective, longitudinal, observational study of PASC that aims to identify wearables-collected physiological parameters that are associated with PASC in patients with a positive diagnosis. This is a single-arm, prospective, observational study of a cohort of 550 patients, aged 18 to 65 years, male or female, who own a smartphone or a tablet that meets predetermined Bluetooth version and operating system requirements, speak English, and provide documentation of a positive COVID-19 test issued by a health care professional within 5 days before enrollment. The primary end point is long COVID-19, defined as ≥1 symptom at 3 weeks beyond the first symptom onset or positive diagnosis, whichever comes first. The secondary end point is chronic COVID-19, defined as ≥1 symptom at 12 weeks beyond the first symptom onset or positive diagnosis. Participants must be willing and able to consent to participate in the study and adhere to study procedures for 6 months. The first patient was enrolled in October 2021. The estimated year for publishing the study results is 2025. This is a fully decentralized study investigating PASC using wearable devices to collect physiological parameters and patient-reported outcomes. The study will shed light on the duration and symptom manifestation of PASC in nonhospitalized patient subgroups and is an exemplar of the use of wearables as population-level monitoring health tools for communicable diseases. ClinicalTrials.gov NCT04927442; https://clinicaltrials.gov/study/NCT04927442. DERR1-10.2196/57382.

Exploring the Influence of Contextual Factors and the Caregiving Process on Caregiver Burden and Quality of Life Outcomes of Heart Failure (HF) Dyads after a Hospital Discharge: A Mixed-Methods Study.

Background: This study explores heart failure (HF) dyadic contextual factors and caregiver burden during acute exacerbation hospitalization and discharge. Methods: It employed a mixed-methods approach, with HF dyads completing questionnaires and semi-structured interviews at a one-week post-discharge outpatient visit. Quantitative tools included the SF-12 Quality of Life, Zarit Burden Interview (ZBI), Bakas Caregiving Outcomes Scale (BCOS), and Self-Care of Heart Failure Index v. 6 (SCHFI). Thematic analysis was conducted on interview data to assess caregiver burden, disease trajectory, comorbidities, caregiving time, and employment status. Results: Twelve HF dyads participated, with caregivers (six female, six male) averaging 65.76 years. The ZBI indicated a low caregiver burden (median score of 15), but qualitative data revealed a higher perceived burden related to social isolation, future fears, and caregiver dependence. Male caregivers reported a lower burden than females. Positive goal congruence was noted in caregiving hours and HF management compliance. HF patients had a 10-year survival prediction of 22.75% per the Charlson Comorbidity Index, with 69% in NYHA class III and an average ejection fraction of 37.7%. Caregivers working full-time and caring for higher NYHA-class patients showed higher ZBI and BCOS scores. Conclusions: The study highlights the need for mixed methods and longitudinal research to understand HF disease trajectory and caregiver burden, emphasizing the importance of including caregivers in HF education and screening for perceived burden to improve outcomes and reduce re-hospitalizations.

Wastewater Surveillance Uncovered the Impacts of the Timing of COVID-19 on the Epidemic Trajectories of Other Respiratory Diseases in Two Northeastern Cities in China

Wastewater Surveillance Uncovered the Impacts of the Timing of COVID-19 on the Epidemic Trajectories of Other Respiratory Diseases in Two Northeastern Cities in China

Identification of factors directly linked to incident chronic obstructive pulmonary disease: A causal graph modeling study.

Beyond exposure to cigarette smoking and aging, the factors that influence lung function decline to incident chronic obstructive pulmonary disease (COPD) remain unclear. Advancements have been made in categorizing COPD into emphysema and airway predominant disease subtypes; however, predicting which healthy individuals will progress to COPD is difficult because they can exhibit profoundly different disease trajectories despite similar initial risk factors. This study aimed to identify clinical, genetic, and radiological features that are directly linked-and subsequently predict-abnormal lung function. We employed graph modeling on 2,643 COPDGene participants (aged 45 to 80 years, 51.25% female, 35.1% African Americans; enrollment 11/2007-4/2011) with smoking history but normal spirometry at study enrollment to identify variables that are directly linked to future lung function abnormalities. We developed logistic regression and random forest predictive models for distinguishing individuals who maintain lung function from those who decline. Of the 131 variables analyzed, 6 were identified as informative to future lung function abnormalities, namely forced expiratory flow in the middle range (FEF25-75%), average lung wall thickness in a 10 mm radius (Pi10), severe emphysema, age, sex, and height. We investigated whether these features predict individuals leaving GOLD 0 status (normal spirometry according to Global Initiative for Obstructive Lung Disease (GOLD) criteria). Linear models, trained with these features, were quite predictive (area under receiver operator characteristic curve or AUROC = 0.75). Random forest predictors performed similarly to logistic regression (AUROC = 0.7), indicating that no significant nonlinear effects were present. The results were externally validated on 150 participants from Specialized Center for Clinically Oriented Research (SCCOR) cohort (aged 45 to 80 years, 52.7% female, 4.7% African Americans; enrollment: 7/2007-12/2012) (AUROC = 0.89). The main limitation of longitudinal studies with 5- and 10-year follow-up is the introduction of mortality bias that disproportionately affects the more severe cases. However, our study focused on spirometrically normal individuals, who have a lower mortality rate. Another limitation is the use of strict criteria to define spirometrically normal individuals, which was unavoidable when studying factors associated with changes in normalized forced expiratory volume in 1 s (FEV1%predicted) or the ratio of FEV1/FVC (forced vital capacity). This study took an agnostic approach to identify which baseline measurements differentiate and predict the early stages of lung function decline in individuals with previous smoking history. Our analysis suggests that emphysema affects obstruction onset, while airway predominant pathology may play a more important role in future FEV1 (%predicted) decline without obstruction, and FEF25-75% may affect both.

MRI-Derived Modeling of Disease Progression Patterns in Patients With Temporal Lobe Epilepsy.

Temporal lobe epilepsy (TLE) is assumed to follow a steady course that is similar across patients. To date, phenotypic and temporal diversities of TLE evolution remain unknown. In this study, we aimed at simultaneously characterizing these sources of variability based on cross-sectional data. We studied consecutive patients with TLE referred for evaluation by neurologists to the Montreal Neurological Institute epilepsy clinic, who underwent in-patient video EEG monitoring and multimodal imaging at 3 Tesla, comprising 3D T1 and fluid-attenuated inversion recovery and 2D diffusion-weighted MRI. The cohort included patients with drug-resistant epilepsy and patients with drug-responsive epilepsy. The neuropsychological evaluation included Wechsler Adult Intelligence Scale-III and Leonard tapping task. The control group consisted of participants without TLE recruited through advertisement and who underwent the same MRI acquisition as patients. Based on surface-based analysis of key MRI markers of pathology (gray matter morphology and white matter microstructure), the Subtype and Stage Inference algorithm estimated subtypes and stages of brain pathology to which individual patients were assigned. The number of subtypes was determined by running the algorithm 100 times and estimating mean and SD of disease trajectories and the consistency of patients' assignments based on 1,000 bootstrap samples. Effect of normal aging was subtracted from patients. We examined associations with clinical and cognitive parameters and utility for individualized predictions. We studied 82 patients with TLE (52 female, mean age 35 ± 10 years; 11 drug-responsive) and 41 control participants (23 male, mean age 32 ± 8 years). Among 57 operated, 43/37/20 had Engel-I outcome/hippocampal sclerosis/hippocampal isolated gliosis, respectively. We identified 3 trajectory subtypes: S1 (n = 35), led by ipsilateral hippocampal atrophy and gliosis, followed by white-matter damage; S2 (n = 27), characterized by bilateral neocortical atrophy, followed by ipsilateral hippocampal atrophy and gliosis; and S3 (n = 20), typified by bilateral limbic white-matter damage, followed by bilateral hippocampal gliosis. Patients showed high assignability to their subtypes and stages (>90% bootstrap agreement). S1 had the highest proportions of patients with early disease onset (effect size d = 0.27 vs S2, d = 0.73 vs S3), febrile convulsions (χ2 = 3.70), drug resistance (χ2 = 2.94), a positive MRI (χ2 = 8.42), hippocampal sclerosis (χ2 = 7.57), and Engel-I outcome (χ2 = 1.51), pFDR < 0.05 across all comparisons. S2 and S3 exhibited the intermediate and lowest proportions, respectively. Verbal IQ and digit span were lower in S1 (d = 0.65 and d = 0.50, pFDR < 0.05) and S2 (d = 0.76 and d = 1.09, pFDR < 0.05), compared with S3. We observed progressive decline in sequential motor tapping in S1 and S3 (T = -3.38 and T = -4.94, pFDR = 0.027), compared with S2 (T = 2.14, pFDR = 0.035). S3 showed progressive decline in digit span (T = -5.83, p = 0.021). Supervised classifiers trained on subtype and stage outperformed subtype-only and stage-only models predicting drug response in 73% ± 1.0% (vs 70% ± 1.4% and 63% ± 1.3%) and 76% ± 1.6% for Engel-I outcome (vs 71% ± 0.8% and 72% ± 1.1%), pFDR < 0.05 across all comparisons. Cross-sectional MRI-derived models provide reliable prognostic markers of TLE disease evolution, which follows distinct trajectories, each associated with divergent patterns of hippocampal and whole-brain structural alterations, as well as cognitive and clinical profiles.

Examining emotional and behavioural trajectories in siblings of children with life-limiting conditions

BackgroundHealthy siblings of children with life-limiting conditions often experience emotional and behavioural struggles over the course of the ill child’s condition(s). Resources to support these siblings are limited due to a lack of understanding about their needs. Therefore, this study was designed to characterize the emotional and behavioural trajectories among siblings of children with progressive, life-limiting genetic, metabolic, or neurological conditions over a 12-month observation period.MethodsSeventy siblings were recruited from a large-survey based study (Charting the Territory) that examined the bio-psychosocial health outcomes of parents and siblings. Linear mixed effect models were used to assess the association between siblings’ emotions and behaviour trajectories and selected demographic variables. Siblings’ emotions and behaviour were measured with Child Behaviour Checklist (CBCL).ResultsSiblings’ mean age was 11.2 years at baseline and Internalizing, Externalizing, and Total Behaviour Problems mean scores were within normal ranges across time. However, 7–25% of siblings had scores within the clinical range. Brothers had higher levels of Internalizing Problems than sisters, whereas sisters had higher levels of Externalizing Problems than brothers. When treatment was first sought for the ill child less than a year prior to study participation, siblings had higher levels of Internalizing and Externalizing Problems compared with siblings who participated more than one year after treatment was sought.ConclusionHealthy siblings experience emotional and behavioural problems early in the child’s disease trajectory. Although these problems improve with time, our findings show that brothers and sisters experience different types of challenges. Therefore, timely support for siblings is important as they navigate through the uncertainties and challenges.

Comparison of Histomorphological Indices Between Adult and Pediatric Patients in Response to Induction Therapy.

Renal involvement, known as lupus nephritis (LN), is a common and serious complication of systemic lupus erythematosus (SLE), linked to significant morbidity and mortality. Histomorphological indices, such as the activity index (AI) and chronicity index (CI), are critical in predicting treatment responses and outcomes. This study aims to compare these histomorphological indices between adult and pediatric patients with LN and evaluate their impact on post-induction therapy outcomes. A cross-sectional analysis was conducted at a single nephrology department from 2005 to 2019, including patients with biopsy-confirmed LN. Data on demographic characteristics, histomorphological indices, and clinical outcomes post-induction therapy were collected. Statistical analysis was performed using IBM SPSS Statistics for Windows, Version 20.0 (Released 2011; IBM Corp., Armonk, New York, United States) to identify significant correlations and differences. Pediatric patients exhibited significantly lower AI (p=0.042) and CI scores compared to adults. Lower frequencies of hyaline thrombi (p=0.005) and tubular atrophy (p=0.028) were observed in the pediatric group. Key predictors of a complete response to induction therapy included interstitial inflammation <0.65 and tubular atrophy <0.63. Significant correlations were found between post-induction renal function tests (RFT) and indices such as AI (p=0.035), CI (p<0.001), cellular and fibrocellular crescents (p<0.001), and tubular atrophy (p<0.001). Proteinuria outcomes were significantly associated with CI (p=0.040), interstitial inflammation (p=0.006), and tubular atrophy (p=0.026). The conclusion aligns with the established understanding that pediatric patients with LN often have a different disease trajectory compared to adults. Pediatric patients generally presented with less severe histomorphological damage, contributing to better responses to induction therapy. Detailed histopathological assessments are essential for guiding treatment strategies and improving patient prognosis in both adult and pediatric LN populations.

Breast Cancers That Disseminate to Bone Marrow Acquire Aggressive Phenotypes through CX43-related Tumor-Stroma Tunnels.

Estrogen receptor-positive (ER+) breast cancer commonly disseminates to bone marrow, where interactions with mesenchymal stromal cells (MSCs) shape disease trajectory. We modeled these interactions with tumor-MSC co-cultures and used an integrated transcriptome-proteome-network-analyses workflow to identify a comprehensive catalog of contact-induced changes. Conditioned media from MSCs failed to recapitulate genes and proteins, some borrowed and others tumor-intrinsic, induced in cancer cells by direct contact. Protein-protein interaction networks revealed the rich connectome between 'borrowed' and 'intrinsic' components. Bioinformatics prioritized one of the 'borrowed' components, CCDC88A /GIV, a multi-modular metastasis-related protein that has recently been implicated in driving a hallmark of cancer, growth signaling autonomy. MSCs transferred GIV protein to ER+ breast cancer cells (that lack GIV) through tunnelling nanotubes via connexin (Cx)43-facilitated intercellular transport. Reinstating GIV alone in GIV-negative breast cancer cells reproduced ∼20% of both the 'borrowed' and the 'intrinsic' gene induction patterns from contact co-cultures; conferred resistance to anti-estrogen drugs; and enhanced tumor dissemination. Findings provide a multiomic insight into MSC→tumor cell intercellular transport and validate how transport of one such candidate, GIV, from the haves (MSCs) to have-nots (ER+ breast cancer) orchestrates aggressive disease states.

2245 Disease trajectories and medical expenditures of older long-term care residents in China: prospective observational study

Abstract Introduction Global ageing and an increasing disability population impose huge health and economic burdens on societies, and understanding the impact of disability on mortality and medical expenditures among the elderly is vital. Methods This study was based on the government-led long-term care insurance program initiated in July 2017 and followed up to June 2021. Diagnosis and hospitalisation costs were extracted from electronic medical records and medical insurance system. The networks of the disease trajectories were established by combining disease pairs with overlapping diseases. Medical expenditures relating to exact disease were calculated and compared between age groups. Results The 30,003 participants had a mean age of 79.6 ± 11.1 years, with 57.0% females. After a mean follow-up time of 21 ± 16 months, 17,428 (58.1%) death were observed. Diseases with the highest HRs included septic shock (HR 3.59, 95% CI, 3.36–3.84), respiratory failure (HR 3.19, 95% CI, 3.05–3.34), sepsis (HR 2.98, 95% CI, 2.80–3.18), malnutrition (HR 2.38, 95% CI, 2.27–2.48), and decubitus ulcer (HR 2.27, 95% CI, 2.14–2.41). The disease trajectories were initially related to hypertension and diabetes mellitus, while mortality was associated with malnutrition, infectious diseases, and organic failure. In subgroup analysis, participants with older age, those living in nursing institutions, and males had more complex disease trajectories. The medical costs gradually decreased with increasing age, and there was a rapid increasing trend before death for the decedents. Among the diseases of top 30 frequent hospitalisation visits, intracerebral haemorrhage, sepsis, and respiratory failure ranked as the top three total medical costs. Conclusions The study shows that malnutrition and infection-related diseases contribute to death in older disabled and the latter account for part of the highest medical cost, calling for comprehensive strategies for infection prevention and treatment.

Multisystem health comorbidity networks of metabolic dysfunction-associated steatotic liver disease

The global burden of metabolic dysfunction-associated steatotic liver disease (MASLD) is growing, but its subsequent health consequences have not been thoroughly examined. A phenome-wide association study was conducted to map the associations of MASLD with 948 unique clinical outcomes among 361,021 Europeans in the UK Biobank. Disease trajectory and comorbidity analyses were applied to visualize the sequential patterns of multiple comorbidities related to the occurrence of MASLD. The associations jointly verified by observational and polygenic phenome-wide analyses were further replicated by two-sample Mendelian randomization analysis using data from the FinnGen study and international consortia. The observational and polygenic phenome-wide association study revealed the associations of MASLD with 96 intrahepatic and extrahepatic diseases, including circulatory, metabolic, genitourinary, neurological, gastrointestinal, and hematologic diseases. Sequential patterns of MASLD-related extrahepatic comorbidities were primarily found in circulatory, metabolic, and inflammatory diseases. Mendelian randomization analyses supported the causal associations between MASLD and the risk of several intrahepatic disorders, metabolic diseases, cardio-cerebrovascular disease, and ascites but found no associations with neurological diseases. This study elucidated multisystem comorbidities and health consequences of MASLD, contributing to the development of combination interventions targeting distinct pathways for health promotion among patients with MASLD. X.L. was funded by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001) and the National Nature Science Foundation of China (82204019) and Y.D. was funded by the Key Project of Traditional Chinese Medicine Science and Technology Plan of Zhejiang Province (GZY-ZJ-KJ-24077) and the National Natural Science Foundation of China (82001673 and 82272860).

Disease progression in chronic heart failure is linear: Insights from multistate modelling.

Understanding the pattern of disease progression in chronic heart failure (HF) may inform patient care and healthcare system design. We used a four-state Markov model to describe the disease trajectory of patients with HF. Consecutive patients (n = 4918) were enrolled (median age 75 [67-81] years, 61.3% men, 44% with HF and reduced ejection fraction). We generated a model by observing events during the first 2 years of follow-up. The model yielded surprisingly accurate predictions of how a population with HF will behave during subsequent years. As examples, the predicted transition probability from hospitalization to death was 0.11; the observed probabilities were 0.13, 0.14, and 0.16 at 3, 4, and 5 years, respectively. Similarly, the predicted transition intensity for rehospitalization was 0.35; the observed probabilities were 0.38, 0.34, and 0.35 at 3, 4, and 5 years, respectively. A multivariable model including covariates thought to influence outcome did not improve accuracy. Predicted average life expectancy was approximately 10 years for the unadjusted model and 13 years for the multivariable model, consistent with the observed mortality of 41% at 5 years. A multistate Markov chain model for patients with chronic HF suggests that the proportion of patients transitioning each year from a given state to another remains constant. This finding suggests that the course of HF at a population level is more linear than is commonly supposed and predictable based on current patient status.

Care of the Patient Nearing the End of Life in the Neurointensive Care Unit.

Neurologically critically ill patients present with unique disease trajectories, prognostic uncertainties, and challenges to end-of-life (EOL) care. Acute brain injuries place these patients at risk for underrecognized symptoms and unmet EOL management needs, which can negatively affect their quality of care and lead to complicated grief in surviving loved ones. To care for patients nearing the EOL in the neurointensive care unit, health care clinicians must consider neuroanatomic localization, barriers to symptom assessment and management, unique aspects of the dying process, and EOL management needs. We aim to define current best practices, barriers, and future directions for EOL care of the neurologically critically ill patient.

Supporting distress behaviours in people with dementia in the community

The outward signs of distress can take many forms, including agitation, aggression, apathy, anxiety and depression and is experienced by most people with dementia at some point during the disease trajectory. Supporting people with dementia who experience distress can pose a significant challenge to community nurses who may lack the time, knowledge and skills to manage distress effectively. This article discusses distress in dementia, including the interplay between stress and distress, examines the various forms of distress and its causes. The article also presents two fictionalised case studies, drawn from the authors’ clinical experience, demonstrating evidence-based approaches community nurses can use in their practice to support people with dementia who experience distress.

ABCDE assessment for palliative care truth-telling dilemmas: a case study.

In Indonesia, the diagnosis of a serious illness is often mediated through the patient's family, reflecting the cultural importance of family involvement in the patient's care and collective decision-making. To use a case study to show the difficulty that healthcare professionals face telling the patient the truth about their condition in Indonesia. The Kagawa-Singer and Blackhall ABCDE framework was used during truth-telling dilemmas to assess patients' and families' attitudes (A), beliefs (B), contexts (C), decision-making styles (D) and environments (E). Studies have shown that family involvement in health-related communications can alleviate the stress associated with the disclosure of a serious illness. Palliative care nurses must acknowledge the importance of family in the patient's cultural context, by involving them in the disclosure of a diagnosis and disease trajectory by integrating every element of the ABCDE model in palliative care.

Standardizing visual display of gastrointestinal pathology results for improved clinical interpretation.

Pathology is an essential component of disease diagnosis and management in pediatric gastroenterology. Pathology reports have not been standardized in some areas of pediatric gastrointestinal pathology and pathology reporting varies. Development of electronic medical record (EMR) pathology synoptic report templates (PSRT) enables pathology data collection in a specific format and can help standardize pathology reporting. We developed, implemented, and evaluated EMR PSRTs for eosinophilic esophagitis (EoE) and inflammatory bowel disease (IBD). PSRTs were developed by a multidisciplinary team of pediatric experts of allergy, gastroenterology, and pathology for both EoE and IBD based on available literature and validated scales. Likert surveys (range 1 low acceptance to 5 high acceptance) based on the Technology Acceptance Model assessed user acceptance of the developed PSRTs. The use of PSRTs was monitored via control charts. Overall, evaluation questionnaires achieved >80% response rates. Clinicians and pathologists reported moderate-to-high levels of Perceived Usefulness (median (interquartile range) for EoE PSRT: clinicians 4.0 (4.0, 5.0) and pathologists 3.5 (3.5, 4.0); and IBD PSRT: clinicians 4.0 (3.0, 4.0) and pathologists 4.0 (4.0, 5.0)) and Perceived Ease of Use (EoE PSRT: clinicians 4.5 (4.0, 5.0) and pathologists 4.0 (4.0, 4.0); and IBD PSRT: clinicians 4.0 (4.0, 5.0) and pathologists 4.0 (4.0, 5.0)) of the developed PSRTs. Control charts demonstrated 100% utilization by 2-5 months from launch. We demonstrate successful implementation of synoptic reporting for both pediatric EoE and IBD pathology. EMR synoptic reporting provides standardization of pathology reporting and improved methods of pathology data presentation, which could potentially optimize provider efficiency, clinician interpretation of pathology results and disease trajectory, patient care, and clinician satisfaction.

Occupational Disease in New York State: The Political Economic Context.

In 1987 Landrigan and Markowitz co-authored a report entitled "Occupational Disease in New York State." They found that death and illness from occupational disease were common and that the costs of exposure to hazardous conditions warranted public funding for new occupational health infrastructure in New York State. A recent confirmatory report recognized a wider spectrum of contemporary hazards and emphasized how public health problems connect to work. These reports provide factual snapshots at 2 points in time, but they do not explain nor analyze the changing conditions they describe. Including macro-contexts such as globalization, financialization, and neoliberalism, this article demonstrates several unique occupational safety and health implications by clarifying key themes related to the state's role, especially regulation and healthcare delivery systems. Conclusions directly tie the trajectory of occupational disease to workers' collective ability to confront and roll back neoliberalism while pushing occupational disease out of its medical/science silo.

Artificial intelligence and headache.

In this narrative review, we introduce key artificial intelligence (AI) and machine learning (ML) concepts, aimed at headache clinicians and researchers. Thereafter, we thoroughly review the use of AI in headache, based on a comprehensive literature search across PubMed, Embase and IEEExplore. Finally, we discuss limitations, as well as ethical and political perspectives. We identified six main research topics. First, natural language processing can be used to effectively extract and systematize unstructured headache research data, such as from electronic health records. Second, the most common application of ML is for classification of headache disorders, typically based on clinical record data, or neuroimaging data, with accuracies ranging from around 60% to well over 90%. Third, ML is used for prediction of headache disease trajectories. Fourth, ML shows promise in forecasting of headaches using self-reported data such as triggers and premonitory symptoms, data from wearable sensors and external data. Fifth and sixth, ML can be used for prediction of treatment responses and inference of treatment effects, respectively, aiming to optimize and individualize headache management. The potential uses of AI and ML in headache are broad, but, at present, many studies suffer from poor reporting and lack out-of-sample evaluation, and most models are not validated in a clinical setting.

Nordic inflammatory bowel disease treatment strategy trial: protocol for the NORDTREAT randomised controlled biomarker-strategy trial

IntroductionThe absence of reliable prognostic markers poses a challenge to the management of inflammatory bowel disease (IBD). Patients with aggressive disease may not receive sufficient treatment with conventional ‘step-up’ therapy,...