Quantifiable identification of flow-limited ventilator dyssynchrony with the deformed lung ventilator model.

BACKGROUND: Ventilator dyssynchrony (VD) can worsen lung injury and is challenging to detect and quantify due to the complex variability in the dyssynchronous breaths. While machine learning (ML) approaches are useful for automating VD detection from the ventilator waveform data, scalable severity quantification and its association with pathogenesis and ventilator mechanics remain challenging. OBJECTIVE: We develop a systematic framework to quantify pathophysiological features observed in ventilator waveform signals such that they can be used to create feature-based severity stratification of VD breaths. METHODS: A mathematical model was developed to represent the pressure and volume waveforms of individual breaths in a feature-based parametric form. Model estimates of respiratory effort strength were used to assess the severity of flow-limited (FL)-VD breaths compared to normal breaths. A total of 93,007 breath waveforms from 13 patients were analyzed. RESULTS: A novel model-defined continuous severity marker was developed and used to estimate breath phenotypes of FL-VD breaths. The phenotypes had a predictive accuracy of over 97% with respect to the previously developed ML-VD identification algorithm. To understand the incidence of FL-VD breaths and their association with the patient state, these phenotypes were further successfully correlated with ventilator-measured parameters and electronic health records. CONCLUSION: This work provides a computational pipeline to identify and quantify the severity of FL-VD breaths and paves the way for a large-scale study of VD causes and effects. This approach has direct application to clinical practice and in meaningful knowledge extraction from the ventilator waveform data.

Endoscopic Submucosal Dissection for Early Esophageal Adenocarcinoma: Low Rates of Metastases in Mucosal Cancers with Poor Differentiation.

BACKGROUND AND AIMS: Endoscopic resection (ER) is accepted as standard treatment for intramucosal esophageal adenocarcinoma (EAC) with well or moderate differentiation. Poor differentiation (PD) is judged as a risk factor for lymph node metastasis (LNM) and surgery is recommended. However, the evidence for this recommendation is weak. Study aim was to analyze the clinical course of patients after ER of EAC with PD. PATIENTS AND METHODS: Patients undergoing endoscopic submucosal dissection for EAC were included from 16 German centers. Inclusion criteria were PD in the resection specimen, R0 resection and endoscopic follow-up. Primary outcome was the metastasis rate during follow-up. Analysis was performed retrospectively in a prospectively collected database. RESULTS: 25 patients with PD as single risk factor (group A) and 15 patients with PD and additional risk factors (submucosal invasion and/or lymphovascular invasion) were included. The metastasis rate was was 1/25 (4.0%; 95%CI 0.4-17.2) in group A and 3/15 (20.0%; 95%CI 6.0-44.4%) in group B, respectively (p=0.293). The rate of EAC-associated deaths was 1/25 (4%; 95%CI 0.4-17.2%) versus 3/15 (20%; 95%CI 6.0-44.4%) in group B (p=0.293) while the overall death rate was 7/25 (28.0%; 95%CI 13.5-47.3%) versus 3/15 (20%; 95%CI 6.0-44.4%) (p=0.715). Median follow-up was 30 months (IQR 15-53). CONCLUSIONS: During long-term follow-up the risk of metastasis is low after ER of mucosal EAC with PD as single risk factor. A conservative approach seems justified in this small patient group. However, the treatment strategy has to be determined on an individualized basis until further prospective data are available.

Experience with a hybrid recruitment approach of patient-facing web portal screening and subsequent phone and medical record review for a neurosurgical intervention trial for chronic ischemic stroke disability (PISCES III).

BACKGROUND: Recruitment of participants is the greatest risk to completion of most clinical trials, with 20-40% of trials failing to reach the targeted enrollment. This is particularly true of trials of central nervous system (CNS) therapies such as intervention for chronic stroke. The PISCES III trial was an invasive trial of stereotactically guided intracerebral injection of CTX0E03, a fetal derived neural stem cell line, in patients with chronic disability due to ischemic stroke. We report on the experience using a novel hybrid recruitment approach of a patient-facing portal to self-identify and perform an initial screen for general trial eligibility (tier 1), followed by phone screening and medical records review (tier 2) prior to a final in-person visit to confirm eligibility and consent. METHODS: Two tiers of screening were established: an initial screen of general eligibility using a patient-facing web portal (tier 1), followed by a more detailed screen that included phone survey and medical record review (tier 2). If potential participants passed the tier 2 screen, they were referred directly to visit 1 at a study site, where final in-person screening and consent were performed. Rates of screening were tracked during the period of trial recruitment and sources of referrals were noted. RESULTS: The approach to screening and recruitment resulted in 6125 tier 1 screens, leading to 1121 referrals to tier 2. The tier 2 screening resulted in 224 medical record requests and identification of 86 qualifying participants for referral to sites. The study attained a viable recruitment rate of 6 enrolled per month prior to being disrupted by COVID 19. CONCLUSIONS: A tiered approach to eligibility screening using a hybrid of web-based portals to self-identify and screen for general eligibility followed by a more detailed phone and medical record review allowed the study to use fewer sites and reduce cost. Despite the difficult and narrow population of patients suffering moderate chronic disability from stroke, this strategy produced a viable recruitment rate for this invasive study of intracranially injected neural stem cells. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03629275.

Flow-Limited and Reverse-Triggered Ventilator Dyssynchrony Are Associated With Increased Tidal and Dynamic Transpulmonary Pressure.

OBJECTIVES: Ventilator dyssynchrony may be associated with increased delivered tidal volumes (V t s) and dynamic transpulmonary pressure (ΔP L,dyn ), surrogate markers of lung stress and strain, despite low V t ventilation. However, it is unknown which types of ventilator dyssynchrony are most likely to increase these metrics or if specific ventilation or sedation strategies can mitigate this potential. DESIGN: A prospective cohort analysis to delineate the association between ten types of breaths and delivered V t , ΔP L,dyn , and transpulmonary mechanical energy. SETTING: Patients admitted to the medical ICU. PATIENTS: Over 580,000 breaths from 35 patients with acute respiratory distress syndrome (ARDS) or ARDS risk factors. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patients received continuous esophageal manometry. Ventilator dyssynchrony was identified using a machine learning algorithm. Mixed-effect models predicted V t , ΔP L,dyn , and transpulmonary mechanical energy for each type of ventilator dyssynchrony while controlling for repeated measures. Finally, we described how V t , positive end-expiratory pressure (PEEP), and sedation (Richmond Agitation-Sedation Scale) strategies modify ventilator dyssynchrony's association with these surrogate markers of lung stress and strain. Double-triggered breaths were associated with the most significant increase in V t , ΔP L,dyn , and transpulmonary mechanical energy. However, flow-limited, early reverse-triggered, and early ventilator-terminated breaths were also associated with significant increases in V t , ΔP L,dyn , and energy. The potential of a ventilator dyssynchrony type to increase V t , ΔP L,dyn , or energy clustered similarly. Increasing set V t may be associated with a disproportionate increase in high-volume and high-energy ventilation from double-triggered breaths, but PEEP and sedation do not clinically modify the interaction between ventilator dyssynchrony and surrogate markers of lung stress and strain. CONCLUSIONS: Double-triggered, flow-limited, early reverse-triggered, and early ventilator-terminated breaths are associated with increases in V t , ΔP L,dyn , and energy. As flow-limited breaths are more than twice as common as double-triggered breaths, further work is needed to determine the interaction of ventilator dyssynchrony frequency to cause clinically meaningful changes in patient outcomes.

International Consensus Criteria for Pediatric Sepsis and Septic Shock.

Importance: Sepsis is a leading cause of death among children worldwide. Current pediatric-specific criteria for sepsis were published in 2005 based on expert opinion. In 2016, the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) defined sepsis as life-threatening organ dysfunction caused by a dysregulated host response to infection, but it excluded children. Objective: To update and evaluate criteria for sepsis and septic shock in children. Evidence Review: The Society of Critical Care Medicine (SCCM) convened a task force of 35 pediatric experts in critical care, emergency medicine, infectious diseases, general pediatrics, nursing, public health, and neonatology from 6 continents. Using evidence from an international survey, systematic review and meta-analysis, and a new organ dysfunction score developed based on more than 3 million electronic health record encounters from 10 sites on 4 continents, a modified Delphi consensus process was employed to develop criteria. Findings: Based on survey data, most pediatric clinicians used sepsis to refer to infection with life-threatening organ dysfunction, which differed from prior pediatric sepsis criteria that used systemic inflammatory response syndrome (SIRS) criteria, which have poor predictive properties, and included the redundant term, severe sepsis. The SCCM task force recommends that sepsis in children be identified by a Phoenix Sepsis Score of at least 2 points in children with suspected infection, which indicates potentially life-threatening dysfunction of the respiratory, cardiovascular, coagulation, and/or neurological systems. Children with a Phoenix Sepsis Score of at least 2 points had in-hospital mortality of 7.1% in higher-resource settings and 28.5% in lower-resource settings, more than 8 times that of children with suspected infection not meeting these criteria. Mortality was higher in children who had organ dysfunction in at least 1 of 4-respiratory, cardiovascular, coagulation, and/or neurological-organ systems that was not the primary site of infection. Septic shock was defined as children with sepsis who had cardiovascular dysfunction, indicated by at least 1 cardiovascular point in the Phoenix Sepsis Score, which included severe hypotension for age, blood lactate exceeding 5 mmol/L, or need for vasoactive medication. Children with septic shock had an in-hospital mortality rate of 10.8% and 33.5% in higher- and lower-resource settings, respectively. Conclusions and Relevance: The Phoenix sepsis criteria for sepsis and septic shock in children were derived and validated by the international SCCM Pediatric Sepsis Definition Task Force using a large international database and survey, systematic review and meta-analysis, and modified Delphi consensus approach. A Phoenix Sepsis Score of at least 2 identified potentially life-threatening organ dysfunction in children younger than 18 years with infection, and its use has the potential to improve clinical care, epidemiological assessment, and research in pediatric sepsis and septic shock around the world.

Development and Validation of the Phoenix Criteria for Pediatric Sepsis and Septic Shock.

Importance: The Society of Critical Care Medicine Pediatric Sepsis Definition Task Force sought to develop and validate new clinical criteria for pediatric sepsis and septic shock using measures of organ dysfunction through a data-driven approach. Objective: To derive and validate novel criteria for pediatric sepsis and septic shock across differently resourced settings. Design, Setting, and Participants: Multicenter, international, retrospective cohort study in 10 health systems in the US, Colombia, Bangladesh, China, and Kenya, 3 of which were used as external validation sites. Data were collected from emergency and inpatient encounters for children (aged <18 years) from 2010 to 2019: 3 049 699 in the development (including derivation and internal validation) set and 581 317 in the external validation set. Exposure: Stacked regression models to predict mortality in children with suspected infection were derived and validated using the best-performing organ dysfunction subscores from 8 existing scores. The final model was then translated into an integer-based score used to establish binary criteria for sepsis and septic shock. Main Outcomes and Measures: The primary outcome for all analyses was in-hospital mortality. Model- and integer-based score performance measures included the area under the precision recall curve (AUPRC; primary) and area under the receiver operating characteristic curve (AUROC; secondary). For binary criteria, primary performance measures were positive predictive value and sensitivity. Results: Among the 172 984 children with suspected infection in the first 24 hours (development set; 1.2% mortality), a 4-organ-system model performed best. The integer version of that model, the Phoenix Sepsis Score, had AUPRCs of 0.23 to 0.38 (95% CI range, 0.20-0.39) and AUROCs of 0.71 to 0.92 (95% CI range, 0.70-0.92) to predict mortality in the validation sets. Using a Phoenix Sepsis Score of 2 points or higher in children with suspected infection as criteria for sepsis and sepsis plus 1 or more cardiovascular point as criteria for septic shock resulted in a higher positive predictive value and higher or similar sensitivity compared with the 2005 International Pediatric Sepsis Consensus Conference (IPSCC) criteria across differently resourced settings. Conclusions and Relevance: The novel Phoenix sepsis criteria, which were derived and validated using data from higher- and lower-resource settings, had improved performance for the diagnosis of pediatric sepsis and septic shock compared with the existing IPSCC criteria.

Intracranial pressure-flow relationships in traumatic brain injury patients expose gaps in the tenets of models and pressure-oriented management.

Background: The protocols and therapeutic guidance established for treating traumatic brain injuries (TBI) in neurointensive care focus on managing cerebral blood flow (CBF) and brain tissue oxygenation based on pressure signals. The decision support process relies on assumed relationships between cerebral perfusion pressure (CPP) and blood flow, pressure-flow relationships (PFRs), and shares this framework of assumptions with mathematical intracranial hemodynamic models. These foundational assumptions are difficult to verify, and their violation can impact clinical decision-making and model validity. Method: A hypothesis- and model-driven method for verifying and understanding the foundational intracranial hemodynamic PFRs is developed and applied to a novel multi-modality monitoring dataset. Results: Model analysis of joint observations of CPP and CBF validates the standard PFR when autoregulatory processes are impaired as well as unmodelable cases dominated by autoregulation. However, it also identifies a dynamical regime -or behavior pattern- where the PFR assumptions are wrong in a precise, data-inferable way due to negative CPP-CBF coordination over long timescales. This regime is of both clinical and research interest: its dynamics are modelable under modified assumptions while its causal direction and mechanistic pathway remain unclear. Conclusions: Motivated by the understanding of mathematical physiology, the validity of the standard PFR can be assessed a) directly by analyzing pressure reactivity and mean flow indices (PRx and Mx) or b) indirectly through the relationship between CBF and other clinical observables. This approach could potentially help personalize TBI care by considering intracranial pressure and CPP in relation to other data, particularly CBF. The analysis suggests a threshold using clinical indices of autoregulation jointly generalizes independently set indicators to assess CA functionality. These results support the use of increasingly data-rich environments to develop more robust hybrid physiological-machine learning models.

Prospective randomized controlled trial comparing a novel and dedicated device with conventional endoscopic techniques for the treatment of buried bumper syndrome (with video).

BACKGROUND AND AIMS: Buried bumper syndrome (BBS) is a rare adverse event of PEG tubes. This study compared the newly developed Flamingo device (Fujifilm Medwork GmbH, Höchstadt, Germany) with conventional endoscopic techniques for BBS treatment. METHODS: This prospective, randomized controlled trial compared the Flamingo set (study group) with other endoscopic techniques (control group) for BBS treatment in 6 German hospitals. The primary endpoint was procedure time. Further outcome parameters were technical success, adverse event rate, and number and cost of devices used in each group. RESULTS: Thirty-six patients (18 in each group; mean age, 73 years; 12 women) were included in this study between March 2018 and December 2022. Median time since placement of the feeding tube was 30 months. The bumper was located in the gastric corpus in 27 patients, and the internal bumper was completely overgrown in 31 patients. The duration of the removal procedure was 17 minutes (range, 3-72) in the study group compared with 38 minutes (range, 12-111) in the control group (P = .046). The primary technical success rate was 77.8% in the study group and 55.6% in the control group (P = .157), whereas the overall technical success rate was 100% compared with 83.3% (P = .070). Adverse events occurred in 4 patients (11.1%). CONCLUSIONS: Endoscopic removal of the buried bumper using the Flamingo device was significantly faster than that with other endoscopic techniques and showed a higher technical success rate. This device may become the endoscopic treatment of choice for BBS. (Clinical trial registration number: NCT03186066.).

The Development, Optimization, and Validation of Four Different Machine Learning Algorithms to Identify Ventilator Dyssynchrony.

Invasive mechanical ventilation can worsen lung injury. Ventilator dyssynchrony (VD) may propagate ventilator-induced lung injury (VILI) and is challenging to detect and systematically monitor because each patient takes approximately 25,000 breaths a day yet some types of VD are rare, accounting for less than 1% of all breaths. Therefore, we sought to develop and validate accurate machine learning (ML) algorithms to detect multiple types of VD by leveraging esophageal pressure waveform data to quantify patient effort with airway pressure, flow, and volume data generated during mechanical ventilation, building a computational pipeline to facilitate the study of VD. Materials and Methods: We collected ventilator waveform and esophageal pressure data from 30 patients admitted to the ICU. Esophageal pressure allows the measurement of transpulmonary pressure and patient effort. Waveform data were cleaned, features considered essential to VD detection were calculated, and a set of 10,000 breaths were manually labeled. Four ML algorithms were trained to classify each type of VD: logistic regression, support vector classification, random forest, and XGBoost. Results: We trained ML models to detect different families and seven types of VD with high sensitivity (>90% and >80%, respectively). Three types of VD remained difficult for ML to classify because of their rarity and lack of sample size. XGBoost classified breaths with increased specificity compared to other ML algorithms. Discussion: We developed ML models to detect multiple types of VD accurately. The ability to accurately detect multiple VD types addresses one of the significant limitations in understanding the role of VD in affecting patient outcomes. Conclusion: ML models identify multiple types of VD by utilizing esophageal pressure data and airway pressure, flow, and volume waveforms. The development of such computational pipelines will facilitate the identification of VD in a scalable fashion, allowing for the systematic study of VD and its impact on patient outcomes.

ß-cell intrinsic dynamics rather than gap junction structure dictates subpopulations in the islet functional network.

Diabetes is caused by the inability of electrically coupled, functionally heterogeneous ß-cells within the pancreatic islet to provide adequate insulin secretion. Functional networks have been used to represent synchronized oscillatory [Ca2+] dynamics and to study ß-cell subpopulations, which play an important role in driving islet function. The mechanism by which highly synchronized ß-cell subpopulations drive islet function is unclear. We used experimental and computational techniques to investigate the relationship between functional networks, structural (gap junction) networks, and intrinsic ß-cell dynamics in slow and fast oscillating islets. Highly synchronized subpopulations in the functional network were differentiated by intrinsic dynamics, including metabolic activity and KATP channel conductance, more than structural coupling. Consistent with this, intrinsic dynamics were more predictive of high synchronization in the islet functional network as compared to high levels of structural coupling. Finally, dysfunction of gap junctions, which can occur in diabetes, caused decreases in the efficiency and clustering of the functional network. These results indicate that intrinsic dynamics rather than structure drive connections in the functional network and highly synchronized subpopulations, but gap junctions are still essential for overall network efficiency. These findings deepen our interpretation of functional networks and the formation of functional subpopulations in dynamic tissues such as the islet.

Differential effects of two-hit models of acute and ventilator-induced lung injury on lung structure, function, and inflammation.

Acute respiratory distress syndrome (ARDS) and acute lung injury have a diverse spectrum of causative factors including sepsis, aspiration of gastric contents, and near drowning. Clinical management of severe lung injury typically includes mechanical ventilation to maintain gas exchange which can lead to ventilator-induced lung injury (VILI). The cause of respiratory failure is acknowledged to affect the degree of lung inflammation, changes in lung structure, and the mechanical function of the injured lung. However, these differential effects of injury and the role of etiology in the structure-function relationship are not fully understood. To address this knowledge gap we caused lung injury with intratracheal hydrochloric acid (HCL) or endotoxin (LPS) 2 days prior to ventilation or with an injurious lavage (LAV) immediately prior to ventilation. These injury groups were then ventilated with high inspiratory pressures and positive end expiratory pressure (PEEP) = 0 cmH2O to cause VILI and model the clinical course of ARDS followed by supportive ventilation. The effects of injury were quantified using invasive lung function measurements recorded during PEEP ladders where the end-expiratory pressure was increased from 0 to 15 cm H2O and decreased back to 0 cmH2O in steps of 3 cmH2O. Design-based stereology was used to quantify the parenchymal structure of lungs air-inflated to 2, 5, and 10 cmH2O. Pro-inflammatory gene expression was measured with real-time quantitative polymerase chain reaction and alveolocapillary leak was estimated by measuring bronchoalveolar lavage protein content. The LAV group had small, stiff lungs that were recruitable at higher pressures, but did not demonstrate substantial inflammation. The LPS group showed septal swelling and high pro-inflammatory gene expression that was exacerbated by VILI. Despite widespread alveolar collapse, elastance in LPS was only modestly elevated above healthy mice (CTL) and there was no evidence of recruitability. The HCL group showed increased elastance and some recruitability, although to a lesser degree than LAV. Pro-inflammatory gene expression was elevated, but less than LPS, and the airspace dimensions were reduced. Taken together, those data highlight how different modes of injury, in combination with a 2nd hit of VILI, yield markedly different effects.

Interpretable physiological forecasting in the ICU using constrained data assimilation and electronic health record data.

OBJECTIVE: Prediction of physiological mechanics are important in medical practice because interventions are guided by predicted impacts of interventions. But prediction is difficult in medicine because medicine is complex and difficult to understand from data alone, and the data are sparse relative to the complexity of the generating processes. Computational methods can increase prediction accuracy, but prediction with clinical data is difficult because the data are sparse, noisy and nonstationary. This paper focuses on predicting physiological processes given sparse, non-stationary, electronic health record data in the intensive care unit using data assimilation (DA), a broad collection of methods that pair mechanistic models with inference methods. METHODS: A methodological pipeline embedding a glucose-insulin model into a new DA framework, the constrained ensemble Kalman filter (CEnKF) to forecast blood glucose was developed. The data include tube-fed patients whose nutrition, blood glucose, administered insulins and medications were extracted by hand due to their complexity and to ensure accuracy. The model was estimated using an individual's data as if they arrived in real-time, and the estimated model was run forward producing a forecast. Both constrained and unconstrained ensemble Kalman filters were estimated to compare the impact of constraints. Constraint boundaries, model parameter sets estimated, and data used to estimate the models were varied to investigate their influence on forecasting accuracy. Forecasting accuracy was evaluated according to mean squared error between the model-forecasted glucose and the measurements and by comparing distributions of measured glucose and forecast ensemble means. RESULTS: The novel CEnKF produced substantial gains in robustness and accuracy while minimizing the data requirements compared to the unconstrained ensemble Kalman filters. Administered insulin and tube-nutrition were important for accurate forecasting, but including glucose in IV medication delivery did not increase forecast accuracy. Model flexibility, controlled by constraint boundaries and estimated parameters, did influence forecasting accuracy. CONCLUSION: Accurate and robust physiological forecasting with sparse clinical data is possible with DA. Introducing constrained inference, particularly on unmeasured states and parameters, reduced forecast error and data requirements. The results are not particularly sensitive to model flexibility such as constraint boundaries, but over or under constraining increased forecasting errors.

A simple modeling framework for prediction in the human glucose-insulin system.

Forecasting blood glucose (BG) levels with routinely collected data is useful for glycemic management. BG dynamics are nonlinear, complex, and nonstationary, which can be represented by nonlinear models. However, the sparsity of routinely collected data creates parameter identifiability issues when high-fidelity complex models are used, thereby resulting in inaccurate forecasts. One can use models with reduced physiological fidelity for robust and accurate parameter estimation and forecasting with sparse data. For this purpose, we approximate the nonlinear dynamics of BG regulation by a linear stochastic differential equation: we develop a linear stochastic model, which can be specialized to different settings: type 2 diabetes mellitus (T2DM) and intensive care unit (ICU), with different choices of appropriate model functions. The model includes deterministic terms quantifying glucose removal from the bloodstream through the glycemic regulation system and representing the effect of nutrition and externally delivered insulin. The stochastic term encapsulates the BG oscillations. The model output is in the form of an expected value accompanied by a band around this value. The model parameters are estimated patient-specifically, leading to personalized models. The forecasts consist of values for BG mean and variation, quantifying possible high and low BG levels. Such predictions have potential use for glycemic management as part of control systems. We present experimental results on parameter estimation and forecasting in T2DM and ICU settings. We compare the model's predictive capability with two different nonlinear models built for T2DM and ICU contexts to have a sense of the level of prediction achieved by this model.

Who needs what (features) when? Personalizing engagement with data-driven self-management to improve health equity.

OBJECTIVES: To examine the feasibility of promoting engagement with data-driven self-management of health among individuals from minoritized medically underserved communities by tailoring the design of self-management interventions to individuals' type of motivation and regulation in accordance with the Self-Determination Theory. METHODS: Fifty-three individuals with type 2 diabetes from an impoverished minority community were randomly assigned to four different versions of an mHealth app for data-driven self-management with the focus on nutrition, Platano; each version was tailored to a specific type of motivation and regulation within the SDT self-determination continuum. These versions included financial rewards (external regulation), feedback from expert registered dietitians (RDF, introjected regulation), self-assessment of attainment of one's nutritional goals (SA, identified regulation), and personalized meal-time nutrition decision support with post-meal blood glucose forecasts (FORC, integrated regulation). We used qualitative interviews to examine interaction between participants' experiences with the app and their motivation type (internal-external). RESULTS: As hypothesized, we found a clear interaction between the type of motivation and Platano features that users responded to and benefited from. For example, those with more internal motivation reported more positive experience with SA and FORC than those with more external motivation. However, we also found that Platano features that aimed to specifically address the needs of individuals with external regulation did not create the desired experience. We attribute this to a mismatch in emphasis on informational versus emotional support, particularly evident in RDF. In addition, we found that for participants recruited from an economically disadvantaged community, internal factors, such as motivation and regulation, interacted with external factors, most notably with limited health literacy and limited access to resources. CONCLUSIONS: The study suggests feasibility of using SDT to tailor design of mHealth interventions for promoting data-driven self-management to individuals' motivation and regulation. However, further research is needed to better align design solutions with different levels of self-determination continuum, to incorporate stronger emphasis on emotional support for individuals with external regulation, and to address unique needs and challenges of underserved communities, with particular attention to limited health literacy and access to resources.

Reduced model for female endocrine dynamics: Validation and functional variations.

A normally functioning menstrual cycle requires significant crosstalk between hormones originating in ovarian and brain tissues. Reproductive hormone dysregulation may cause abnormal function and sometimes infertility. The inherent complexity in this endocrine system is a challenge to identifying mechanisms of cycle disruption, particularly given the large number of unknown parameters in existing mathematical models. We develop a new endocrine model to limit model complexity and use simulated distributions of unknown parameters for model analysis. By employing a comprehensive model evaluation, we identify a collection of mechanisms that differentiate normal and abnormal phenotypes. We also discover an intermediate phenotype-displaying relatively normal hormone levels and cycle dynamics-that is grouped statistically with the irregular phenotype. Results provide insight into how clinical symptoms associated with ovulatory disruption may not be detected through hormone measurements alone.

Endoscopic papillectomy for ampullary lesions in patients with familial adenomatous polyposis compared with sporadic lesions: a propensity score-matched cohort.

BACKGROUND: Familial adenomatous polyposis (FAP) is a rare inherited syndrome that predisposes the patient to cancer. Treatment of FAP-related ampullary lesions is challenging and the role of endoscopic papillectomy has not been elucidated. We retrospectively analyzed the outcomes of endoscopic papillectomy in matched cohorts of FAP-related and sporadic ampullary lesions (SALs). METHODS: This retrospective multicenter study included 1422 endoscopic papillectomy procedures. Propensity score matching including age, sex, comorbidity, histologic subtype, and size was performed. Main outcomes were complete resection (R0), technical success, complications, and recurrence. RESULTS: Propensity score matching identified 202 patients (101 FAP, 101 SAL) with comparable baseline characteristics. FAP patients were mainly asymptomatic (79.2 % [95 %CI 71.2-87.3] vs. 46.5 % [95 %CI 36.6-56.4]); P < 0.001). The initial R0 rate was significantly lower in FAP patients (63.4 % [95 %CI 53.8-72.9] vs. 83.2 % [95 %CI 75.8-90.6]; P = 0.001). After repeated interventions (mean 1.30 per patient), R0 was comparable (FAP 93.1 % [95 %CI 88.0-98.1] vs. SAL 97.0 % [95 %CI 93.7-100]; P = 0.19). Adverse events occurred in 28.7 %. Pancreatitis and bleeding were the most common adverse events in both groups. Severe adverse events were rare (3.5 %). Overall, 21 FAP patients (20.8 % [95 %CI 12.7-28.8]) and 16 SAL patients (15.8 % [95 %CI 8.6-23.1]; P = 0.36) had recurrence. Recurrences occurred later in FAP patients (25 [95 %CI 18.3-31.7] vs. 2 [95 %CI CI 0.06-3.9] months). CONCLUSIONS: Endoscopic papillectomy was safe and effective in FAP-related ampullary lesions. Criteria for endoscopic resection of ampullary lesions can be extended to FAP patients. FAP patients have a lifetime risk of relapse even after complete resection, and require long-time surveillance.

Outcomes of rescue procedures in the management of locally recurrent ampullary tumors: A Pancreas 2000/EPC study.

BACKGROUND: Ampullary lesions are rare and can be locally treated either with endoscopic papillectomy or transduodenal surgical ampullectomy. Management of local recurrence after a first-line treatment has been poorly studied. METHODS: Patients with a local recurrence of an ampullary lesion initially treated with endoscopic papillectomy or transduodenal surgical ampullectomy were retrospectively included from a multi-institutional database (58 centers) between 2005 and 2018. RESULTS: A total of 103 patients were included, 21 (20.4%) treated with redo endoscopic papillectomy, 14 (13.6%) with transduodenal surgical ampullectomy, and 68 (66%) with pancreaticoduodenectomy. Redo endoscopic papillectomy had low morbidity with 4.8% (n = 1) severe to fatal complications and a R0 rate of 81% (n = 17). Transduodenal surgical ampullectomy and pancreaticoduodenectomy after a first procedure had a higher morbidity with Clavien III and more complications, respectively, 28.6% (n = 4) and 25% (n = 17); R0 resection rates were 85.7% (n = 12) and 92.6% (n = 63), both without statistically significant difference compared to endoscopic papillectomy (P = .1 and 0.2). Pancreaticoduodenectomy had 4.4% (n = 2) mortality. No deaths were registered after transduodenal surgical ampullectomy or endoscopic papillectomy. Recurrences treated with pancreaticoduodenectomy were more likely to be adenocarcinomas (79.4%, n = 54 vs 21.4%, n = 3 for transduodenal surgical ampullectomy and 4.8%, n = 1 for endoscopic papillectomy, P < .0001). Three-year overall survival and disease-free survival were comparable. CONCLUSION: Endoscopy is appropriate for noninvasive recurrences, with resection rate and survival outcomes comparable to surgery. Surgery applies more to invasive recurrences, with transduodenal surgical ampullectomy rather for carcinoma in situ and early cancers and pancreaticoduodenectomy for more advanced tumors.

A Phase II Study of Nab-Paclitaxel and Gemcitabine as First-Line Therapy in Patients with Cholangiocarcinoma Ineligible for Cisplatin-Based Chemotherapy (NACHO).

INTRODUCTION: Gemcitabine and cisplatin is the standard first-line systemic treatment in patients with advanced cholangiocarcinoma (CCA). However, a substantial number of patients do not qualify for cisplatin due to comorbidities or poor performance status. The phase II pilot study NACHO evaluated the efficacy of nab-paclitaxel (125 mg/m2) and gemcitabine (1000 mg/m2) given on days 1, 8, and 15 every 4 weeks as first-line therapy in patients with advanced CCA ineligible for cisplatin-based chemotherapy. METHODS: Patients with any comorbidity precluding cisplatin therapy, such as renal impairment, impaired hearing, increased risk or history for thromboembolic events, intolerance of extensive hydration, or significant cardiovascular disease were eligible. Primary endpoint was overall response rate (ORR) per RECIST 1.1. Secondary endpoints were progression-free survival (PFS), overall survival (OS), safety, and patient reported outcome. RESULTS: From December 2016 to July 2017, 10 patients were prospectively enrolled and treated. The ORR with nab-paclitaxel/gemcitabine was 50%, the disease control rate (DCR) was 90%. Median PFS was 5.7 months (95% CI: 5.3-6.1), and median OS was 7.8 months (95% CI: 5.4-10.2). In total, 13 SAEs were documented without any new safety signals. There were 14 grade 3-4 treatment-related adverse events (TRAEs) in 10 patients of the ITT population. Exploratory subgroup analyses including known prognostic markers were performed. CONCLUSIONS: The NACHO trial supports safety and efficacy of nab-paclitaxel and gemcitabine in patients with advanced CCA ineligible for cisplatin-based therapy and should be further evaluated in a larger prospective trial.

Clinical Outcome and Treatment Sequences of Patients with Advanced Pancreatic Cancer Treated with Contemporary Chemotherapy Protocols.

INTRODUCTION: Systemic therapy is firmly established in patients with advanced or metastatic pancreatic ductal adenocarcinoma (PDAC). Clinical efficacy is still modest and options are limited. Combination therapy protocols such as FOLFIRINOX and gemcitabine/nab-paclitaxel (Gem/NP) define standard-of-care. Patients may receive a sequence of both regimens as first- and second-line palliative treatment. However, there is no guidance regarding a preferred order. METHODS: This is a retrospective analysis of clinical characteristics, treatment trajectories, and outcomes of patients with advanced PDAC treated at the West German Cancer Center Essen from 2014 to 2020 to inform treatment decisions with respect to predictive factors, impact of chemotherapy regimen sequence, and maintenance treatment. RESULTS: We identified 170 patients with available follow-up. Of those, 160 (94.1%) patients received palliative CTX for primary metastatic, locally advanced, or recurrent PDAC. Median progression-free survival (PFS) upon first palliative chemotherapy was 4.1 (3.1-5.9) months. First-line FOLFIRINOX was associated with superior PFS (median 6.3 months) and OS (9.7 months, HR 0.7, p = 0.03) as compared to Gem/NP or other regimens (PFS 3.0, OS 6.9 months). However, OS benefit of first-line FOLFIRINOX was lost in patients who received at least two treatment lines (median OS 12.1 vs. 13.1 months, p = 0.43). A landmark analysis of patients with clinical benefit (defined as CR/PR/SD for at least 20 weeks) upon first-line therapy revealed improved OS (HR 0.53, p = 0.02) for patients receiving continued deescalated maintenance therapy. Second-line regimens resulted in similar PFS (overall log-rank p = 0.92, median PFS upon second-line therapy 2.3 [1.8-2.9], per-regimen median between 1.8 and 3.9 months). A previously established systemic inflammation score proved to be strongly prognostic and allowed identification of a patient subgroup with dismal prognosis (OS 2.9 vs. 11.4 months, HR 5.23, p < 0.001), independent of other prognostic factors and with no relevant interaction with the choice of first-line regimen. CONCLUSION: In this real-world population of PDAC patients treated with contemporary combination chemotherapies, a positive impact of first-line FOLFIRINOX was only observed when no second or further line treatment was administered. Intensity-reduced maintenance therapy may lead to superior survival.

Deep learning-based assessment of body composition and liver tumour burden for survival modelling in advanced colorectal cancer.

BACKGROUND: Personalized therapy planning remains a significant challenge in advanced colorectal cancer care, despite extensive research on prognostic and predictive markers. A strong correlation of sarcopenia or overall body composition and survival has been described. Here, we explore whether automated assessment of body composition and liver metastases from standard of care CT images can add to clinical parameters in personalized survival risk prognostication. METHODS: We retrospectively analysed clinical imaging data from 85 patients (50.6% female, mean age 58.9 SD 12.2 years) with colorectal cancer and synchronous liver metastases. Pretrained deep learning models were used to assess body composition and liver metastasis geometry from abdominal CT images before the initiation of systemic treatment. Abdominal muscle-to-bone ratio (MBR) was calculated by dividing abdominal muscle volume by abdominal bone volume. MBR was compared with body mass index (BMI), abdominal muscle volume, and abdominal muscle volume divided by height squared. Differences in overall survival based on body composition and liver metastasis parameters were compared using Kaplan-Meier survival curves. Results were correlated with clinical and biomarker data to develop a machine learning model for survival risk prognostication. RESULTS: The MBR, unlike abdominal muscle volume or BMI, was significantly associated with overall survival (HR 0.39, 95% CI: 0.19-0.80, P = 0.009). The MBR (P = 0.022), liver metastasis surface area (P = 0.01) and primary tumour sidedness (P = 0.007) were independently associated with overall survival in multivariate analysis. Body composition parameters did not correlate with KRAS mutational status or primary tumour sidedness. A prediction model based on MBR, liver metastasis surface area and primary tumour sidedness achieved a concordance index of 0.69. CONCLUSIONS: Automated segmentation enables to extract prognostic parameters from routine imaging data for personalized survival modelling in advanced colorectal cancer patients.