1,720,988 research outputs found
Predicting a Prolonged Air Leak After Video-Assisted Thoracic Surgery, Is It Really Possible?
No full text: Validation of predictive risk models for prolonged air leak (PAL) is essential to understand if they can help to reduce its incidence and complications. This study aimed to evaluate both the clinical and statistical performances of 4 existing models. We selected 4 predictive PAL risk models based on their scientific relevance. We referred to these models as Chicago, Bordeaux, Leeds and Pittsburgh model, respectively, according to the affiliation place of the first author. These predicting risk models were retrospectively applied to patients recorded on the second edition of the Italian Video-Assisted Thoracoscopic Surgery Group registry. Predictions for each patient were calculated based on the logistic regression coefficient values provided in the original manuscripts. All models were tested for their overall performance, discrimination, and calibration. We recalibrated the original models with the re-estimation of the model intercept and slope. We used curve decision analysis to describe and compare the clinical effects of the studied risk models. Better statistical metrics characterize the models developed on larger populations (Chicago and Bordeaux models). However, no model has a valid benefit for threshold probability greater than 0.30. The Net benefit of the most performing model (Bordeaux model) at the threshold probability of 0.11 is 23 of 1000 patients, burdened by 333 false positive cases. One of 1000 is the Net benefit at the threshold probability of 0.3. The use of PAL scores based on preoperative predictive factors cannot be currently used in a clinical setting because of a high false positive rate and low positive predictive value
Predicting a Prolonged Air Leak After Video-Assisted Thoracic Surgery, Is It Really Possible?
No full textValidation of predictive risk models for prolonged air leak (PAL) is essential to understand if they can help to reduce its incidence and complications. This study aimed to evaluate both the clinical and statistical performances of 4 existing models. We selected 4 predictive PAL risk models based on their scientific relevance. We referred to these models as Chicago, Bordeaux, Leeds and Pittsburgh model, respectively, according to the affiliation place of the first author. These predicting risk models were retrospectively applied to patients recorded on the second edition of the Italian Video-Assisted Thoracoscopic Surgery Group registry. Predictions for each patient were calculated based on the logistic regression coefficient values provided in the original manuscripts. All models were tested for their overall performance, discrimination, and calibration. We recalibrated the original models with the re-estimation of the model intercept and slope. We used curve decision analysis to describe and compare the clinical effects of the studied risk models. Better statistical metrics characterize the models developed on larger populations (Chicago and Bordeaux models). However, no model has a valid benefit for threshold probability greater than 0.30. The Net benefit of the most performing model (Bordeaux model) at the threshold probability of 0.11 is 23 of 1000 patients, burdened by 333 false positive cases. One of 1000 is the Net benefit at the threshold probability of 0.3. The use of PAL scores based on preoperative predictive factors cannot be currently used in a clinical setting because of a high false positive rate and low positive predictive value
Prolonged air leak after video-assisted thoracic anatomical pulmonary resections: a clinical predicting model based on data from the Italian VATS group registry, a machine learning approach
Full text linkBackground: Prolonged air leak (PAL) is a frequent complication after lung resection surgery and has a high clinical and economic impact. A useful risk predictor model can help recognize those patients who might benefit from additional preventive procedures. Currently, no risk model has sufficient discriminatory capacity to be used in common clinical practice. The aim of this study is to identify predictive risk factors for PAL after video-assisted thoracoscopic surgery (VATS) anatomical resections in the Italian VATS group database and to evaluate their clinical and statistical performance. Methods: We processed data collected in the second edition of the Italian VATS group registry. It includes patients that underwent a thoracoscopic anatomical resection for benign or malignant diseases, between November 2015 and December 2020. We used recursive feature elimination (RFE), using a backward selection process, to find the optimal combination of predictors. The study population was randomly split based on the outcome into a derivation (80%) and an internal validation cohort (20%). Discrimination of the model was measured using the area under the curve, or C-statistic. Calibration was displayed using a calibration plot and was measured using Emax and Eavg, the maximum and the average difference in predicted versus loess calibrated probabilities. Results: A cohort of 6,236 patients was eligible for the study after application of the exclusion criteria. Five-day PAL rate in this patient cohort was 11.3%. For the construction of our predictive model, we used both preoperative and intraoperative variables, with a total of 320 variables. The presence of variables with missing values greater than 5% led to 120 remaining predictors. RFE algorithm recommended 8 features for the model that are relevant in predicting the target variable. Conclusions: We confirmed significant prognostic risk factors for the prediction of PAL: decreased DLCO/VA ratio, longer duration of surgery, male sex, the need for adhesiolysis, COPD, and right side. We identified middle lobe resections and ground glass opacity as protective factors. After internal validation, a C statistic of 0.63 was revealed, which is too low to generate a reliable score in clinical practice
EARLY AND MID-TERM OUTCOMES OF EVAR WITH AN ULTRA LOW-PROFILE ENDOGRAFT FROM THE TRIVENETO INCRAFT REGISTRY
No full textTo evaluate early and mid-term outcomes of Incraft (Cordis Corporation, Bridgewater, NJ) ultra-low-profile endograft analysing data from the Triveneto Incraft Registry (TIR)
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Can a standardised Ventilation Mechanical Test for quantitative intraoperative air leak grading reduce the length of hospital stay after video-assisted thoracoscopic surgery lobectomy?
No full textEarly outcomes of the Conformable endograft in severe neck angulation from the Triveneto Conformable Registry
No full textObjective: The study reports retrospective evaluation of early outcomes from a multicentric experience with the Excluder conformable endograft with active control system (CEXC Device) in the treatment of abdominal aortic aneurysms. Its design allows more flexibility, given by proximal unconnected stent rows and a bending wire within the delivery catheter enables control of proximal angulation. This study specifically focuses on the severe neck angulation (SNA) subgroup (≥60°). Methods: All patients treated with CEXC Device in nine vascular surgery centers of Triveneto area (Northeast Italy) between January 2019 and July 2022 were enrolled prospectively and analyzed retrospectively. Demographic and aortic anatomical characteristics were evaluated. Endovascular aneurysm repair in SNA were selected for analysis. Major investigated outcomes were technical success, endoleaks, morbidity, mortality, and reinterventions at 30 days and during follow-up. Endograft migration and postoperative aortic neck angulation changes were also analyzed. Results: A total of 129 patients were enrolled. An infrarenal angle of ≥60° was observed in 56 patients (43%) (SNA group) and their data analyzed. The mean patient age was 78.9 ± 5.9 years and median abdominal aortic aneurysm diameter 59 mm (range, 45-94 mm). Median aortic infrarenal neck length, angulation and diameter were 22 mm (range, 13-58 mm), 77° (range, 60°-150°), and 22.0 ± 3.5 mm respectively. Analysis revealed a technical success rate of 100% and perioperative major complication rate of 1.7%. Intraoperative and perioperative morbidity and mortality rates were 3.5% (one buttock claudication and one inguinal surgical cutdown) and 0%, respectively. No perioperative type I endoleaks were observed. The median follow-up was 13 months (range, 1-40 months). Five patients died during follow-up from aneurysm-unrelated causes. Two reinterventions occurred (3.5%): one conversion for a type IA endoleak and one sac embolization for a type II endoleak. Aneurysm sac shrinkage was observed in 15 patients (26%) and aneurysm stability in 35 patients (62%), respectively. Estimated freedom from reinterventions at 24 months was 92%. Aortic neck median postoperative angulation was 75° (range, 45°-139°). Conclusions: The Triveneto Conformable Registry shows good early results of the CEXC device in severely angulated aortic infrarenal necks. These data need confirmation on longer follow-up and a wider cohort of patients to further increase endovascular aneurysm repair eligibility in SNA
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