scholarly journals Comment on: Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

2020 ◽  
Vol 107 (7) ◽  
pp. e205-e205
Author(s):  
P. Mentula ◽  
H. Sammalkorpi ◽  
A. Leppäniemi
Keyword(s):  
Risk Prediction ◽  
Prediction Models ◽  
Risk Prediction Models ◽  
Suspected Appendicitis

scholarly journals P8 A single centre evaluation of risk prediction models and imaging modalities in acute appendicitis

BJS Open ◽  
2021 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
James Ashcroft ◽  
Aminder A Singh ◽  
Siobhan Rooney ◽  
John Bennett ◽  
Richard Justin Davies ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Prediction ◽  
Prediction Models ◽  
Ct Imaging ◽  
Low Risk ◽  
Imaging Modalities ◽  
Risk Prediction Models ◽  
Suspected Appendicitis ◽  
High Risk Women ◽  
Low Risk Women

Abstract Objective Patients with suspected appendicitis remain a diagnostic challenge. This study aims to validate risk prediction models and to investigate diagnostic accuracy of ultrasonography (US) and computed tomography (CT) in adults undergoing an appendicectomy. Materials and Methods A retrospective case review of patients aged 16-45 undergoing an appendicectomy between January 2019 to January 2020 at a tertiary referral centre was performed. Primary outcomes were the accuracy of a high-risk appendicitis risk score and US and CT imaging modalities when compared to histological reports following appendicectomy. Results A total of 206 patients (107/205, 51.9% women) were included. Removal of histologically normal appendix was equally likely in men and women (13.1 versus 11.2%, relative risk 1.17, 95% c.i. 0.56 to 2.44; P =0.67). A high-risk appendicitis score correctly identified 84.0% (79/94) of cases in men and 85.9% (67/78) of cases in women. US was reported as equivocal in 85.7% (18/21) of low-risk women and 59.0% (23/39) of high-risk women. CT in low-risk women resulted in 25.0% (2/8) equivocal results whilst correctly diagnosing (5/6) or excluding (1/2) appendicitis in 75.0% of the total cohort (6/8). In high-risk women CT resulted in 3.8% (1/26) equivocal results whilst correctly detecting (22/23) or excluding (1/3) appendicitis in 88.5% of total high-risk patients (23/26). Conclusions This study suggests that risk prediction models may be useful in both women and men to identify appendicitis. US imaging gave high rates of equivocal results and should not be relied upon for the diagnosis of appendicitis but may be useful to exclude other differential diagnoses. CT imaging is a highly accurate diagnostic tool and could be considered in those at low-risk where clinical suspicion remains to reduce negative appendicectomy rates.

scholarly journals Rare Germline Pathogenic Variants Identified by Multigene Panel Testing and the Risk of Aggressive Prostate Cancer

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1495
Author(s):  
Tú Nguyen-Dumont ◽  
James G. Dowty ◽  
Robert J. MacInnis ◽  
Jason A. Steen ◽  
Moeen Riaz ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Prediction ◽  
Prediction Models ◽  
Risk Prediction Models ◽  
Aggressive Prostate Cancer ◽  
Panel Testing ◽  
Pathogenic Variants ◽  
Increased Risk ◽  
Predisposition Genes ◽  
Rare Genetic Variants

While gene panel sequencing is becoming widely used for cancer risk prediction, its clinical utility with respect to predicting aggressive prostate cancer (PrCa) is limited by our current understanding of the genetic risk factors associated with predisposition to this potentially lethal disease phenotype. This study included 837 men diagnosed with aggressive PrCa and 7261 controls (unaffected men and men who did not meet criteria for aggressive PrCa). Rare germline pathogenic variants (including likely pathogenic variants) were identified by targeted sequencing of 26 known or putative cancer predisposition genes. We found that 85 (10%) men with aggressive PrCa and 265 (4%) controls carried a pathogenic variant (p < 0.0001). Aggressive PrCa odds ratios (ORs) were estimated using unconditional logistic regression. Increased risk of aggressive PrCa (OR (95% confidence interval)) was identified for pathogenic variants in BRCA2 (5.8 (2.7–12.4)), BRCA1 (5.5 (1.8–16.6)), and ATM (3.8 (1.6–9.1)). Our study provides further evidence that rare germline pathogenic variants in these genes are associated with increased risk of this aggressive, clinically relevant subset of PrCa. These rare genetic variants could be incorporated into risk prediction models to improve their precision to identify men at highest risk of aggressive prostate cancer and be used to identify men with newly diagnosed prostate cancer who require urgent treatment.

scholarly journals Risk Prediction of Barrett’s Esophagus in a Taiwanese Health Examination Center Based on Regression Models

2021 ◽  
Vol 18 (10) ◽  
pp. 5332
Author(s):  
Po-Hsiang Lin ◽  
Jer-Guang Hsieh ◽  
Hsien-Chung Yu ◽  
Jyh-Horng Jeng ◽  
Chiao-Lin Hsu ◽  
...  
Keyword(s):  
Barrett’S Esophagus ◽  
Risk Prediction ◽  
Barrett's Esophagus ◽  
Gastrointestinal Endoscopy ◽  
Prediction Models ◽  
Upper Gastrointestinal Endoscopy ◽  
Health Examination ◽  
Endoscopic Screening ◽  
Risk Prediction Models ◽  
Upper Gastrointestinal

Determining the target population for the screening of Barrett’s esophagus (BE), a precancerous condition of esophageal adenocarcinoma, remains a challenge in Asia. The aim of our study was to develop risk prediction models for BE using logistic regression (LR) and artificial neural network (ANN) methods. Their predictive performances were compared. We retrospectively analyzed 9646 adults aged ≥20 years undergoing upper gastrointestinal endoscopy at a health examinations center in Taiwan. Evaluated by using 10-fold cross-validation, both models exhibited good discriminative power, with comparable area under curve (AUC) for the LR and ANN models (Both AUC were 0.702). Our risk prediction models for BE were developed from individuals with or without clinical indications of upper gastrointestinal endoscopy. The models have the potential to serve as a practical tool for identifying high-risk individuals of BE among the general population for endoscopic screening.

scholarly journals Evaluating risk prediction models for adults with heart failure: A systematic literature review

PLoS ONE ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. e0224135 ◽  
Author(s):  
Gian Luca Di Tanna ◽  
Heidi Wirtz ◽  
Karen L. Burrows ◽  
Gary Globe
Keyword(s):  
Heart Failure ◽  
Literature Review ◽  
Risk Prediction ◽  
Systematic Literature Review ◽  
Prediction Models ◽  
Risk Prediction Models
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