Robotic abdominal resection of tailgut cysts – A technical note with step-by-step description

Tailgut cysts; Retrorectal tumours; Robotic approachQuistes del intestino grueso; Tumores retrorrectales; Enfoque robóticoQuists de l'intestí gruixut; Tumors retrorectals; Enfocament robòticAim Here, we describe a step-by-step standardized technique for tailgut cyst resection using a single-docking robotic approach. Method Each step of the technique is illustrated using a composite collection of four operative patient videos to demonstrate the advantages and feasibility of this technique. The robot platform utilised is Da Vinci Xi. Results Five female patients have undergone this operation in our unit. The size of tumours ranged from 12 to 45 mm. Median operating time was 100 min (range 90–150). Mean blood loss in all the patients was less than 50 ml. There were no major intraoperative complications. One patient had a postoperative presacral collection which required radiological drainage. Length of stay in all patients was one day. Conclusions This technique using a single-docking robotic approach appears safe and feasible. The robotic approach results in improved dexterity and more accurate dissection, better retraction and excellent vision which improves the ease of operating in the pelvis. Therefore, this approach can be replicated for use in a wide variety of patients with tailgut cysts

EASY-APP: An artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis

Acute pancreatitis; Artificial intelligence; Severity predictionPancreatitis aguda; Inteligencia artificial; Predicción de gravedadPancreatitis aguda; Intel·ligència artificial; Predicció de la gravetatBackground Acute pancreatitis (AP) is a potentially severe or even fatal inflammation of the pancreas. Early identification of patients at high risk for developing a severe course of the disease is crucial for preventing organ failure and death. Most of the former predictive scores require many parameters or at least 24 h to predict the severity; therefore, the early therapeutic window is often missed. Methods The early achievable severity index (EASY) is a multicentre, multinational, prospective and observational study (ISRCTN10525246). The predictions were made using machine learning models. We used the scikit-learn, xgboost and catboost Python packages for modelling. We evaluated our models using fourfold cross-validation, and the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), and accuracy metrics were calculated on the union of the test sets of the cross-validation. The most critical factors and their contribution to the prediction were identified using a modern tool of explainable artificial intelligence called SHapley Additive exPlanations (SHAP). Results The prediction model was based on an international cohort of 1184 patients and a validation cohort of 3543 patients. The best performing model was an XGBoost classifier with an average AUC score of 0.81 ± 0.033 and an accuracy of 89.1%, and the model improved with experience. The six most influential features were the respiratory rate, body temperature, abdominal muscular reflex, gender, age and glucose level. Using the XGBoost machine learning algorithm for prediction, the SHAP values for the explanation and the bootstrapping method to estimate confidence, we developed a free and easy-to-use web application in the Streamlit Python-based framework (http://easy-app.org/). Conclusions The EASY prediction score is a practical tool for identifying patients at high risk for severe AP within hours of hospital admission. The web application is available for clinicians and contributes to the improvement of the model.University of Pécs Medical School Research Fund. Grant Number: 300909. National Research, Development and Innovation Office Research Fund. Grant Numbers: K131996, FK131864, K128222, FK12463

Elevated Serum Triglyceride Levels in Acute Pancreatitis: A Parameter to be Measured and Considered Early

Triglicéridos séricos; Pancreatitis agudaTriglicèrids sèrics; Pancreatitis agudaAcute pancreatitis; Serum triglycerideBackground The value of serum triglycerides (TGs) related to complications and the severity of acute pancreatitis (AP) has not been clearly defined. Our study aimed to analyze the association of elevated levels of TG with complications and the severity of AP. Methods The demographic and clinical data of patients with AP were prospectively analyzed. TG levels were measured in the first 24 h of admission. Patients were divided into two groups: one with TG values of<200 mg/dL and another with TG≥200 mg/dL. Data on the outcomes of AP were collected. Results From January 2016 to December 2019, 247 cases were included: 200 with TG<200 mg/dL and 47 with TG≥200 mg/dL. Triglyceride levels≥200 mg/dL were associated with respiratory failure (21.3 vs. 10%, p=0.033), renal failure (23.4 vs. 12%, p=0.044), cardiovascular failure (19.1 vs. 7.5%, p=0.025), organ failure (34 vs. 18.5%, p=0.02), persistent organ failure (27.7 vs. 9.5%, p=0.001), multiple organ failure (19.1 vs. 8%, p=0.031), moderately severe and severe AP (68.1 vs. 40.5%, p=0.001), pancreatic necrosis (63.8 vs. 34%, p<0.001), and admission to the intensive care unit (27.7 vs. 9.5%, p=0.003). In the multivariable analysis, a TG level of≥200 mg/dL was independently associated with respiratory, renal, and cardiovascular failure, organ failure, persistent organ failure, multiple organ failure, pancreatic necrosis, severe pancreatitis, and admission to the intensive care unit (p<0.05). Conclusions In our cohort, TG≥200 mg/dL was related to local and systemic complications. Early determinations of TG levels in AP could help identify patients at risk of complications.Open Access Funding provided by Universitat Autonoma de Barcelona

Study of the neutron-rich region in the vicinity of 208Pb via multinucleon transfer reactions

The multinucleon transfer reaction mechanism was employed to populate isotopes around the doubly- magic 208 Pb nucleus. We used an unstable 94 Rb beam on 208 Pb targets of different thickness. Transfer channels were studied via the fragment-γ and γ-γ coincidences, by using MINIBALL γ spectrometer coupled to a particle detector. Gamma transitions associated to the different Pb isotopes, populated by the neutron transfers, are discussed in terms of excitation energy and spin. Fragment angular distributions were extracted, andcompared with the reaction model

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe

Study of the neutron-rich region in the vicinity of 208Pb via multinucleon transfer reactions

The multinucleon transfer reaction mechanism was employed to populate isotopes around the doubly-magic 208 Pb nucleus. We used an unstable 94 Rb beam on 208 Pb targets of different thickness. Transfer channels were studied via the fragment-γ and γ-γ coincidences, by using MINIBALL γ spectrometer coupled to a particle detector. Gamma transitions associated to the different Pb isotopes, populated by the neutron transfers, are discussed in terms of excitation energy and spin. Fragment angular distributions were extracted, andcompared with the reaction models

EASY-APP: An artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis

BACKGROUND: Acute pancreatitis (AP) is a potentially severe or even fatal inflammation of the pancreas. Early identification of patients at high risk for developing a severe course of the disease is crucial for preventing organ failure and death. Most of the former predictive scores require many parameters or at least 24 h to predict the severity; therefore, the early therapeutic window is often missed. METHODS: The early achievable severity index (EASY) is a multicentre, multinational, prospective and observational study (ISRCTN10525246). The predictions were made using machine learning models. We used the scikit‐learn, xgboost and catboost Python packages for modelling. We evaluated our models using fourfold cross‐validation, and the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), and accuracy metrics were calculated on the union of the test sets of the cross‐validation. The most critical factors and their contribution to the prediction were identified using a modern tool of explainable artificial intelligence called SHapley Additive exPlanations (SHAP). RESULTS: The prediction model was based on an international cohort of 1184 patients and a validation cohort of 3543 patients. The best performing model was an XGBoost classifier with an average AUC score of 0.81 ± 0.033 and an accuracy of 89.1%, and the model improved with experience. The six most influential features were the respiratory rate, body temperature, abdominal muscular reflex, gender, age and glucose level. Using the XGBoost machine learning algorithm for prediction, the SHAP values for the explanation and the bootstrapping method to estimate confidence, we developed a free and easy‐to‐use web application in the Streamlit Python‐based framework (http://easy‐app.org/). CONCLUSIONS: The EASY prediction score is a practical tool for identifying patients at high risk for severe AP within hours of hospital admission. The web application is available for clinicians and contributes to the improvement of the model

Observations of the climate near the surface of Jezero over a half Mars year

International audiencePerseverance landed on Jezero with the most complete suite of environmental sensors ever sent to the surface of another planet. It combines the Mars Environmental Dynamics Analyzer (MEDA), the MastCam-Z and Engineering cameras, SuperCam spectrometers and, finally, the several microphones onboard the Mars 2020 rover. The most recent collection of atmospheric observations at Jezero and their interpretation are building an understanding of what physical processes drive the behavior of the Martian atmosphere near the surface of Jezero. We report on the observed Martian cycles of pressure, temperature, dust opacity with their physical aerosol properties, and the hydrological cycle at Jezero. These cycles have shown different behaviors on time scales from diurnal to seasonal and annual to other locations where we landed before. The differences illustrate the range of environmental processes that one can find near the red planet’s surface. We also report on the observed evolution of the near-surface boundary layer thermodynamics during the day and nighttime regimes

Immunocompromised patients with acute respiratory distress syndrome: Secondary analysis of the LUNG SAFE database

Background: The aim of this study was to describe data on epidemiology, ventilatory management, and outcome of acute respiratory distress syndrome (ARDS) in immunocompromised patients. Methods: We performed a post hoc analysis on the cohort of immunocompromised patients enrolled in the Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE) study. The LUNG SAFE study was an international, prospective study including hypoxemic patients in 459 ICUs from 50 countries across 5 continents. Results: Of 2813 patients with ARDS, 584 (20.8%) were immunocompromised, 38.9% of whom had an unspecified cause. Pneumonia, nonpulmonary sepsis, and noncardiogenic shock were their most common risk factors for ARDS. Hospital mortality was higher in immunocompromised than in immunocompetent patients (52.4% vs 36.2%; p &lt; 0.0001), despite similar severity of ARDS. Decisions regarding limiting life-sustaining measures were significantly more frequent in immunocompromised patients (27.1% vs 18.6%; p &lt; 0.0001). Use of noninvasive ventilation (NIV) as first-line treatment was higher in immunocompromised patients (20.9% vs 15.9%; p = 0.0048), and immunodeficiency remained independently associated with the use of NIV after adjustment for confounders. Forty-eight percent of the patients treated with NIV were intubated, and their mortality was not different from that of the patients invasively ventilated ab initio. Conclusions: Immunosuppression is frequent in patients with ARDS, and infections are the main risk factors for ARDS in these immunocompromised patients. Their management differs from that of immunocompetent patients, particularly the greater use of NIV as first-line ventilation strategy. Compared with immunocompetent subjects, they have higher mortality regardless of ARDS severity as well as a higher frequency of limitation of life-sustaining measures. Nonetheless, nearly half of these patients survive to hospital discharge. Trial registration: ClinicalTrials.gov, NCT02010073. Registered on 12 December 2013