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- Arnelo, Urban, et al.
(författare)
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Intraoperative pancreatoscopy can improve the detection of skip lesions during surgery for intraductal papillary mucinous neoplasia : a pilot study
- 2023
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Ingår i: Pancreatology (Print). - : Elsevier. - 1424-3903 .- 1424-3911. ; 23:6, s. 704-711
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: Intraoperative pancreatoscopy is a promising procedure that might guide surgical resection for suspected main duct (MD) and mixed type (MT) intraductal papillary mucinous neoplasms (IPMNs). The aim of the present study was to assess the diagnostic yield and clinical impact of intraoperative pancreatoscopy in patients operated on for MD and MT-IPMNs.Methods: This is a retrospective cohort study. Patients undergoing surgery for suspected MD or MT-IPMN underwent intraoperative pancreatoscopy and frozen section analysis. In all patients who required extended resection due to pancreatoscopic findings, we compared the final histology with the results of the intraoperative frozen section analysis.Results: In total, 46 patients, 48% females, mean age (range) 67 years (45–82 years) underwent intraoperative pancreatoscopy. No mortality or procedure related complications were observed. Pancreatoscopy changed the operative course in 30 patients (65%), leading to extended resections in 20 patients (43%) and to parenchyma sparing procedures in 10 patients (22%). Analyzing the group of patients who underwent extended resections, 7 (35%) displayed lesions that needed further surgical treatment (six high grade dysplasia and one with G1 pancreatic neuroendocrine tumor) and among those 7, just 1 (14%) would have been detected exclusively with histological frozen section analysis of the transection margin. The combination of both pancreatoscopy and frozen section analysis lead to 86% sensitivity and 92% specificity for the detection of pathological tissue in the remnant pancreas.Conclusion: Intraoperative pancreatoscopy is a safe and feasible procedure and might allow the detection of skip lesions during surgery for suspect MD-involving IPMNs.
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- Belov, Vladimir, et al.
(författare)
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Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures
- 2024
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Ingår i: Scientific Reports. - : NATURE PORTFOLIO. - 2045-2322. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.
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- Creignou, Maria, et al.
(författare)
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Early transfusion patterns improve the Molecular International Prognostic Scoring System (IPSS-M) prediction in myelodysplastic syndromes
- 2024
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Ingår i: Journal of Internal Medicine. - : WILEY. - 0954-6820 .- 1365-2796.
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Tidskriftsartikel (refereegranskat)abstract
- Background The Molecular International Prognostic Scoring System (IPSS-M) is the new gold standard for diagnostic outcome prediction in patients with myelodysplastic syndromes (MDS). This study was designed to assess the additive prognostic impact of dynamic transfusion parameters during early follow-up. Methods We retrieved complete transfusion data from 677 adult Swedish MDS patients included in the IPSS-M cohort. Time-dependent erythrocyte transfusion dependency (E-TD) was added to IPSS-M features and analyzed regarding overall survival and leukemic transformation (acute myeloid leukemia). A multistate Markov model was applied to assess the prognostic value of early changes in transfusion patterns. Results Specific clinical and genetic features were predicted for diagnostic and time-dependent transfusion patterns. Importantly, transfusion state both at diagnosis and within the first year strongly predicts outcomes in both lower (LR) and higher-risk (HR) MDSs. In multivariable analysis, 8-month landmark E-TD predicted shorter survival independently of IPSS-M (p < 0.001). A predictive model based on IPSS-M and 8-month landmark E-TD performed significantly better than a model including only IPSS-M. Similar trends were observed in an independent validation cohort (n = 218). Early transfusion patterns impacted both future transfusion requirements and outcomes in a multistate Markov model. Conclusion The transfusion requirement is a robust and available clinical parameter incorporating the effects of first-line management. In MDS, it provides dynamic risk information independently of diagnostic IPSS-M and, in particular, clinical guidance to LR MDS patients eligible for potentially curative therapeutic intervention.
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