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.

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.).

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.

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.

Digital single-operator pancreatoscopy for the treatment of symptomatic pancreatic duct stones: a prospective multicenter cohort trial.

BACKGROUND: Digital single-operator pancreatoscopy (DSOP)-guided lithotripsy is a novel treatment modality for pancreatic endotherapy, with demonstrated technical success in retrospective series of between 88 % and 100 %. The aim of this prospective multicenter trial was to systematically evaluate DSOP in patients with chronic pancreatitis and symptomatic pancreatic duct stones. METHODS: Patients with symptomatic chronic pancreatitis and three or fewer stones ≥ 5mm in the main pancreatic duct (MPD) of the pancreatic head or body were included. The primary end point was complete stone clearance (CSC) in three or fewer treatment sessions with DSOP. Current guidelines recommend extracorporeal shock wave lithotripsy (ESWL) for MPD stones > 5 mm. A performance goal was developed to show that the CSC rate of MPD stones using DSOP was above what has been previously reported for ESWL. Secondary end points were pain relief measured with the Izbicki pain score (IPS), number of interventions, and serious adverse events (SAEs). RESULTS: 40 chronic pancreatitis patients were included. CSC was achieved in 90 % of patients (36/40) on intention-to-treat analysis, after a mean (SD) of 1.36 (0.64) interventions (53 procedures in total). The mean (SD) baseline IPS decreased from 55.3 (46.2) to 10.9 (18.3). Overall pain relief was achieved in 82.4 % (28/34) after 6 months of follow-up, with complete pain relief in 61.8 % (21/34) and partial pain relief in 20.6 % (7/34). SAEs occurred in 12.5 % of patients (5/40), with all treated conservatively. CONCLUSION: DSOP-guided endotherapy is effective and safe for the treatment of symptomatic MPD stones in highly selected patients with chronic pancreatitis. It significantly reduces pain and could be considered as an alternative to standard ERCP techniques for MPD stone treatment in these patients.

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.

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.

Hypothesis-driven modeling of the human lung-ventilator system: A characterization tool for Acute Respiratory Distress Syndrome research.

Mechanical ventilation is an essential tool in the management of Acute Respiratory Distress Syndrome (ARDS), but it exposes patients to the risk of ventilator-induced lung injury (VILI). The human lung-ventilator system (LVS) involves the interaction of complex anatomy with a mechanical apparatus, which limits the ability of process-based models to provide individualized clinical support. This work proposes a hypothesis-driven strategy for LVS modeling in which robust personalization is achieved using a pre-defined parameter basis in a non-physiological model. Model inversion, here via windowed data assimilation, forges observed waveforms into interpretable parameter values that characterize the data rather than quantifying physiological processes. Accurate, model-based inference on human-ventilator data indicates model flexibility and utility over a variety of breath types, including those from dyssynchronous LVSs. Estimated parameters generate static characterizations of the data that are 50%-70% more accurate than breath-wise single-compartment model estimates. They also retain sufficient information to distinguish between the types of breath they represent. However, the fidelity and interpretability of model characterizations are tied to parameter definitions and model resolution. These additional factors must be considered in conjunction with the objectives of specific applications, such as identifying and tracking the development of human VILI.

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.

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.

Over-the-scope-clips versus standard treatment in high-risk patients with acute non-variceal upper gastrointestinal bleeding: a randomised controlled trial (STING-2).

OBJECTIVE: Acute non-variceal upper gastrointestinal bleeding (NVUGIB) is managed by standard endoscopic combination therapy, but a few cases remain difficult and carry a high risk of persistent or recurrent bleeding. The aim of our study was to compare first-line over-the-scope-clips (OTSC) therapy with standard endoscopic treatment in these selected patients. DESIGN: We conducted a prospective, randomised, controlled, multicentre study (NCT03331224). Patients with endoscopic evidence of acute NVUGIB and high risk of rebleeding (defined as complete Rockall Score ≥7) were included. Primary endpoint was clinical success defined as successful endoscopic haemostasis without evidence of recurrent bleeding. RESULTS: 246 patients were screened and 100 patients were finally randomised (mean of 5 cases/centre and year; 70% male, 30% female, mean age 78 years; OTSC group n=48, standard group n=52). All but one case in the standard group were treated with conventional clips. Clinical success was 91.7% (n=44) in the OTSC group compared with 73.1% (n=38) in the ST group (p=0.019), with persistent bleeding occurring in 0 vs 6 in the OTSC versus standard group (p=0.027), all of the latter being successfully managed by rescue therapy with OTSC. Recurrent bleeding was observed in four patients (8.3%) in the OTSC group and in eight patients (15.4%) in the standard group (p=0.362). CONCLUSION: OTSC therapy appears to be superior to standard treatment with clips when used by trained physicians for selected cases of primary therapy of NVUGIB with high risk of rebleeding. Further studies are necessary with regards to patient selection to identify subgroups benefiting most from OTSC haemostasis. TRIAL REGISTRATION NUMBER: NCT03331224.

Impact of endobiliary radiofrequency ablation on biliary drainage in patients with malignant biliary strictures treated with uncovered self-expandable metal stents: a randomized controlled multicenter trial.

BACKGROUND AND AIMS: Endobiliary radiofrequency ablation (RFA), usually combined with endoscopic stent insertion, is a simple procedure with the potential to improve stent patency and patient survival for malignant biliary obstruction. We conducted this randomized multicenter trial to evaluate the impact of RFA on stent patency. METHODS: Eighty-six patients with malignant biliary obstruction and nonresectable tumors (pancreatic carcinoma, cholangiocarcinoma, or metastases) were included and randomly assigned to receive a self-expandable metal stent (SEMS) only (n = 44) or RFA followed by SEMS insertion (RFA+SEMS, n = 42). The primary outcome measure was stent patency after 3 and 6 months; secondary outcome measures were patient survival and early adverse events within 30 days. RESULTS: Technical success rates for RFA and stent insertion were 100% and 98.8%, respectively. Stent patency after 3 and 6 months did not differ significantly between groups (RFA+SEMS group, 73.1% and 33.3%, respectively; SEMS-only group, 81.8% and 52.4%, respectively; P = .6). Similarly, the addition of RFA did not impact overall survival (hazard ratio, .72; P = .389 for RFA+SEMS). The adverse event rate in the RFA+SEMS group was 10.5% compared with 2.3% in the SEMS-only group, without a statistically significant difference (P = .18). CONCLUSIONS: RFA as an addition to SEMS implantation had no positive impact on patency rate or survival. (Clinical trial registration number: DRKS00018993.).

Correction: Personalized glucose forecasting for type 2 diabetes using data assimilation.

[This corrects the article DOI: 10.1371/journal.pcbi.1005232.].

Esophageal stenting for benign and malignant disease: European Society of Gastrointestinal Endoscopy (ESGE) Guideline - Update 2021.

MALIGNANT DISEASE: 1: ESGE recommends placement of partially or fully covered self-expandable metal stents (SEMSs) for palliation of malignant dysphagia over laser therapy, photodynamic therapy, and esophageal bypass.Strong recommendation, high quality evidence. 2 : ESGE recommends brachytherapy as a valid alternative, alone or in addition to stenting, in esophageal cancer patients with malignant dysphagia and expected longer life expectancy.Strong recommendation, high quality evidence. 3: ESGE recommends esophageal SEMS placement for sealing malignant tracheoesophageal or bronchoesophageal fistulas. Strong recommendation, low quality evidence. 4 : ESGE does not recommend SEMS placement as a bridge to surgery or before preoperative chemoradiotherapy because it is associated with a high incidence of adverse events. Other options such as feeding tube placement are preferable. Strong recommendation, low quality evidence. BENIGN DISEASE: 5: ESGE recommends against the use of SEMSs as first-line therapy for the management of benign esophageal strictures because of the potential for adverse events, the availability of alternative therapies, and their cost. Strong recommendation, low quality evidence. 6: ESGE suggests consideration of temporary placement of self-expandable stents for refractory benign esophageal strictures. Weak recommendation, moderate quality evidence. 7: ESGE suggests that fully covered SEMSs be preferred over partially covered SEMSs for the treatment of refractory benign esophageal strictures because of their very low risk of embedment and ease of removability. Weak recommendation, low quality evidence. 8: ESGE recommends the stent-in-stent technique to remove partially covered SEMSs that are embedded in the esophageal wall. Strong recommendation, low quality evidence. 9: ESGE recommends that temporary stent placement can be considered for the treatment of leaks, fistulas, and perforations. No specific type of stent can be recommended, and the duration of stenting should be individualized. Strong recommendation, low quality of evidence. 10 : ESGE recommends considering placement of a fully covered large-diameter SEMS for the treatment of esophageal variceal bleeding refractory to medical, endoscopic, and/or radiological therapy, or as initial therapy for patients with massive bleeding. Strong recommendation, moderate quality evidence.

Enabling personalized decision support with patient-generated data and attributable components.

Decision-making related to health is complex. Machine learning (ML) and patient generated data can identify patterns and insights at the individual level, where human cognition falls short, but not all ML-generated information is of equal utility for making health-related decisions. We develop and apply attributable components analysis (ACA), a method inspired by optimal transport theory, to type 2 diabetes self-monitoring data to identify patterns of association between nutrition and blood glucose control. In comparison with linear regression, we found that ACA offers a number of characteristics that make it promising for use in decision support applications. For example, ACA was able to identify non-linear relationships, was more robust to outliers, and offered broader and more expressive uncertainty estimates. In addition, our results highlight a tradeoff between model accuracy and interpretability, and we discuss implications for ML-driven decision support systems.

Delay-induced uncertainty for a paradigmatic glucose-insulin model.

Medical practice in the intensive care unit is based on the assumption that physiological systems such as the human glucose-insulin system are predictable. We demonstrate that delay within the glucose-insulin system can induce sustained temporal chaos, rendering the system unpredictable. Specifically, we exhibit such chaos for the ultradian glucose-insulin model. This well-validated, finite-dimensional model represents feedback delay as a three-stage filter. Using the theory of rank one maps from smooth dynamical systems, we precisely explain the nature of the resulting delay-induced uncertainty (DIU). We develop a framework one may use to diagnose DIU in a general oscillatory dynamical system. For infinite-dimensional delay systems, no analog of the theory of rank one maps exists. Nevertheless, we show that the geometric principles encoded in our DIU framework apply to such systems by exhibiting sustained temporal chaos for a linear shear flow. Our results are potentially broadly applicable because delay is ubiquitous throughout mathematical physiology.

Use of over-the-scope clips in the colon in clinical practice: results from a German administrative database.

BACKGROUND : The efficacy and safety of over-the-scope (OTS) clips in the colon is limited. This study aimed to evaluate OTS clip use in the colon in routine colonoscopy. METHODS: Using administrative data from a large health insurance company, patients with OTS clip placement during colonoscopy were identified and analyzed by specific administrative codes. Indication for OTS clipping was analyzed, and follow-up was evaluated for surgical and repeat endoscopic interventions. RESULTS: In 505 patients, indications for OTS clips were iatrogenic perforations (n = 80; Group A), polypectomy (n = 315; Group B), colonic bleeding (n = 51; Group C), and various underlying diseases (n = 59; Group D). In 11 Group A patients (13.8 %), surgical interventions occurred, mostly within 24 hours after clipping (n = 9), predominantly overstitching (n = 8). OTS clipping during polypectomy (Group B) was for complications (e. g. bleeding in 27 %) or was applied prophylactically. Only five patients required early surgery, three of whom had colorectal cancer. In four Group C patients (7.8 %), surgical resections were performed (persistent bleeding n = 1, colorectal cancer n = 2), while six patients underwent early repeat colonoscopy for recurrent bleeding. During further follow-up (days 11-30), 17 patients underwent resection for colonic neoplasms (n = 12) or persistent bleeding (n = 4), but only one case could be directly traced back to local OTS clip complication. CONCLUSION: Colonic OTS clipping appears safe and effective in selected indications and complications in clinical routine but must be anatomically and technically feasible, avoiding overuse.

Development and validation of early warning score system: A systematic literature review.

OBJECTIVES: This review aims to: 1) evaluate the quality of model reporting, 2) provide an overview of methodology for developing and validating Early Warning Score Systems (EWSs) for adult patients in acute care settings, and 3) highlight the strengths and limitations of the methodologies, as well as identify future directions for EWS derivation and validation studies. METHODOLOGY: A systematic search was conducted in PubMed, Cochrane Library, and CINAHL. Only peer reviewed articles and clinical guidelines regarding developing and validating EWSs for adult patients in acute care settings were included. 615 articles were extracted and reviewed by five of the authors. Selected studies were evaluated based on the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist. The studies were analyzed according to their study design, predictor selection, outcome measurement, methodology of modeling, and validation strategy. RESULTS: A total of 29 articles were included in the final analysis. Twenty-six articles reported on the development and validation of a new EWS, while three reported on validation and model modification. Only eight studies met more than 75% of the items in the TRIPOD checklist. Three major techniques were utilized among the studies to inform their predictive algorithms: 1) clinical-consensus models (n = 6), 2) regression models (n = 15), and 3) tree models (n = 5). The number of predictors included in the EWSs varied from 3 to 72 with a median of seven. Twenty-eight models included vital signs, while 11 included lab data. Pulse oximetry, mental status, and other variables extracted from electronic health records (EHRs) were among other frequently used predictors. In-hospital mortality, unplanned transfer to the intensive care unit (ICU), and cardiac arrest were commonly used clinical outcomes. Twenty-eight studies conducted a form of model validation either within the study or against other widely-used EWSs. Only three studies validated their model using an external database separate from the derived database. CONCLUSION: This literature review demonstrates that the characteristics of the cohort, predictors, and outcome selection, as well as the metrics for model validation, vary greatly across EWS studies. There is no consensus on the optimal strategy for developing such algorithms since data-driven models with acceptable predictive accuracy are often site-specific. A standardized checklist for clinical prediction model reporting exists, but few studies have included reporting aligned with it in their publications. Data-driven models are subjected to biases in the use of EHR data, thus it is particularly important to provide detailed study protocols and acknowledge, leverage, or reduce potential biases of the data used for EWS development to improve transparency and generalizability.

A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism.

BACKGROUND: Semisupervised and unsupervised anomaly detection methods have been widely used in various applications to detect anomalous objects from a given data set. Specifically, these methods are popular in the medical domain because of their suitability for applications where there is a lack of a sufficient data set for the other classes. Infection incidence often brings prolonged hyperglycemia and frequent insulin injections in people with type 1 diabetes, which are significant anomalies. Despite these potentials, there have been very few studies that focused on detecting infection incidences in individuals with type 1 diabetes using a dedicated personalized health model. OBJECTIVE: This study aims to develop a personalized health model that can automatically detect the incidence of infection in people with type 1 diabetes using blood glucose levels and insulin-to-carbohydrate ratio as input variables. The model is expected to detect deviations from the norm because of infection incidences considering elevated blood glucose levels coupled with unusual changes in the insulin-to-carbohydrate ratio. METHODS: Three groups of one-class classifiers were trained on target data sets (regular days) and tested on a data set containing both the target and the nontarget (infection days). For comparison, two unsupervised models were also tested. The data set consists of high-precision self-recorded data collected from three real subjects with type 1 diabetes incorporating blood glucose, insulin, diet, and events of infection. The models were evaluated on two groups of data: raw and filtered data and compared based on their performance, computational time, and number of samples required. RESULTS: The one-class classifiers achieved excellent performance. In comparison, the unsupervised models suffered from performance degradation mainly because of the atypical nature of the data. Among the one-class classifiers, the boundary and domain-based method produced a better description of the data. Regarding the computational time, nearest neighbor, support vector data description, and self-organizing map took considerable training time, which typically increased as the sample size increased, and only local outlier factor and connectivity-based outlier factor took considerable testing time. CONCLUSIONS: We demonstrated the applicability of one-class classifiers and unsupervised models for the detection of infection incidence in people with type 1 diabetes. In this patient group, detecting infection can provide an opportunity to devise tailored services and also to detect potential public health threats. The proposed approaches achieved excellent performance; in particular, the boundary and domain-based method performed better. Among the respective groups, particular models such as one-class support vector machine, K-nearest neighbor, and K-means achieved excellent performance in all the sample sizes and infection cases. Overall, we foresee that the results could encourage researchers to examine beyond the presented features into other additional features of the self-recorded data, for example, continuous glucose monitoring features and physical activity data, on a large scale.