Personalising the risk of conversion from laparoscopic to open hysterectomy in benign conditions: development and external validation of risk prediction models

2021 ◽  
Author(s):  
Krupa Madhvani ◽  
Borja M Fernandez‐Felix ◽  
Javier Zamora ◽  
Tyrone Carpenter ◽  
Khalid S Khan
Keyword(s):  
Risk Prediction ◽  
Prediction Models ◽  
External Validation ◽  
Risk Prediction Models

scholarly journals External validation and comparison of four cardiovascular risk prediction models with data from the Australian Diabetes, Obesity and Lifestyle study

2019 ◽  
Vol 210 (4) ◽  
pp. 161-167 ◽  
Author(s):  
Loai Albarqouni ◽  
Jennifer A Doust ◽  
Dianna Magliano ◽  
Elizabeth LM Barr ◽  
Jonathan E Shaw ◽  
...  
Keyword(s):  
Cardiovascular Risk ◽  
Risk Prediction ◽  
Prediction Models ◽  
External Validation ◽  
Risk Prediction Models ◽  
Cardiovascular Risk Prediction

scholarly journals Correction: External validation of risk prediction models for incident colorectal cancer using UK Biobank

2020 ◽  
Vol 122 (10) ◽  
pp. 1572-1575
Author(s):  
J. A. Usher-Smith ◽  
A. Harshfield ◽  
C. L. Saunders ◽  
S. J. Sharp ◽  
J. Emery ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Risk Prediction ◽  
Prediction Models ◽  
External Validation ◽  
Uk Biobank ◽  
Risk Prediction Models

scholarly journals External Validation of International Risk-Prediction Models of IgA Nephropathy in an Asian-Caucasian Cohort

2020 ◽  
Vol 5 (10) ◽  
pp. 1753-1763 ◽  
Author(s):  
Yuemiao Zhang ◽  
Ling Guo ◽  
Zi Wang ◽  
Jinwei Wang ◽  
Lee Er ◽  
...  
Keyword(s):  
Iga Nephropathy ◽  
Risk Prediction ◽  
Prediction Models ◽  
External Validation ◽  
Risk Prediction Models ◽  
Caucasian Cohort

scholarly journals 702 Evaluation of Risk Prediction Models for Postoperative Pulmonary Complications in Adults Undergoing Major Abdominal Surgery: A Systematic Review and External Validation Study in The Respiratory Complications After Abdominal Surgery (RECON) Cohort

2021 ◽  
Vol 108 (Supplement_2) ◽  
Author(s):  
Keyword(s):  
Systematic Review ◽  
Abdominal Surgery ◽  
Risk Prediction ◽  
Prediction Models ◽  
External Validation ◽  
Pulmonary Complications ◽  
Major Abdominal Surgery ◽  
Postoperative Pulmonary Complications ◽  
Risk Prediction Models ◽  
Prediction Tools

Abstract Introduction Postoperative pulmonary complications (PPCs) following major abdominal surgery result in substantial morbidity and mortality, yet stratifying patients for risk-modifying interventions remains challenging. This study aimed to identify and externally validate PPC risk prediction models in an international, prospective cohort. Method A systematic review was conducted to identify risk prediction models for PPC following abdominal surgery. External validation was performed using data from a prospective dataset of adult patients undergoing major abdominal surgery from January to April 2019 in the UK, Ireland, and Australia. The primary outcome was identification of PPC within 30-days (StEP-COMPAC criteria definition). Model discrimination and diagnostic accuracy were compared. Results Six unique risk prediction models were eligible from 2819 records (112 full texts). These were validated across 11,591 patients, with an overall PPC rate of 7.8% (n = 903). The Assess Respiratory Risk in Surgical Patients in Catalonia (ARISCAT) score provided the best discrimination (AUROC: 0.709 (95% CI: 0.692-0.727), yet no risk prediction model demonstrated good discrimination (AUROC >0.7). Conclusions The risk of PPC for patients following major abdominal surgery in the pre-covid era is not well described by existing prediction tools. New prediction tools are required to account for additional variation introduced for patients affected by SARS-CoV-2 infection.

scholarly journals V2 Evaluation of risk prediction models for postoperative pulmonary complications in adults undergoing major abdominal surgery: A systematic review and external validation study of the REspiratory COmplications after abdomiNal surgery (RECON) cohort

BJS Open ◽  
2021 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
◽  
Omar Kouli
Keyword(s):  
Systematic Review ◽  
Abdominal Surgery ◽  
Risk Prediction ◽  
Prediction Models ◽  
External Validation ◽  
Pulmonary Complications ◽  
Major Abdominal Surgery ◽  
Postoperative Pulmonary Complications ◽  
Risk Prediction Models ◽  
Prediction Tools

Abstract Background Postoperative pulmonary complications (PPCs) following major abdominal surgery result in substantial morbidity and mortality, yet stratifying patients for risk-modifying interventions remains challenging. This study aimed to identify and externally validate PPC risk prediction models in an international, prospective cohort. Methods A systematic review was conducted to identify risk prediction models for PPC following abdominal surgery. External validation was performed using data from a prospective dataset of adult patients undergoing major abdominal surgery from January to April 2019 in the UK, Ireland and Australia. The primary outcome was identification of PPC within 30-days (StEP-COMPAC criteria definition). Model discrimination and diagnostic accuracy were compared. Results Six unique risk prediction models were eligible from 2819 records. These were validated across 11,591 patients, with an overall PPC rate of 7.8% (n = 903). The Assess Respiratory Risk in Surgical Patients in Catalonia (ARISCAT) score provided the best discrimination (AUC: 0.709 (95% CI: 0.692-0.727), yet no risk prediction model demonstrated good discrimination (AUC >0.7). Conclusion The risk of PPC for patients following major abdominal surgery in the pre-covid era is not well described by existing prediction tools. New prediction tools are required to account for additional variation introduced for patients affected by SARS-CoV-2 infection.

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