FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4328112977> ?p ?o ?g. }

• W4328112977 endingPage "105" @default.
• W4328112977 startingPage "95" @default.
• W4328112977 abstract "Atrioventricular block requiring permanent pacemaker (PPM) implantation is an important complication of transcatheter aortic valve replacement (TAVR). Application of machine learning could potentially be used to predict pre-procedural risk for PPM.To apply machine learning to be used to predict pre-procedural risk for PPM.A retrospective study of 1200 patients who underwent TAVR (January 2014-December 2017) was performed. 964 patients without prior PPM were included for a 30-d analysis and 657 patients without PPM requirement through 30 d were included for a 1-year analysis. After the exclusion of variables with near-zero variance or ≥ 50% missing data, 167 variables were included in the random forest gradient boosting algorithm (GBM) optimized using 5-fold cross-validations repeated 10 times. The receiver operator curve (ROC) for the GBM model and PPM risk score models were calculated to predict the risk of PPM at 30 d and 1 year.Of 964 patients included in the 30-d analysis without prior PPM, 19.6% required PPM post-TAVR. The mean age of patients was 80.9 ± 8.7 years. 42.1 % were female. Of 657 patients included in the 1-year analysis, the mean age of the patients was 80.7 ± 8.2. Of those, 42.6% of patients were female and 26.7% required PPM at 1-year post-TAVR. The area under ROC to predict 30-d and 1-year risk of PPM for the GBM model (0.66 and 0.72) was superior to that of the PPM risk score (0.55 and 0.54) with a P value < 0.001.The GBM model has good discrimination and calibration in identifying patients at high risk of PPM post-TAVR." @default.
• W4328112977 created "2023-03-22" @default.
• W4328112977 creator A5001752698 @default.
• W4328112977 creator A5001962925 @default.
• W4328112977 creator A5016178572 @default.
• W4328112977 creator A5018761121 @default.
• W4328112977 creator A5020379926 @default.
• W4328112977 creator A5041696948 @default.
• W4328112977 creator A5043133312 @default.
• W4328112977 creator A5044601513 @default.
• W4328112977 creator A5051102742 @default.
• W4328112977 creator A5061056186 @default.
• W4328112977 creator A5062970790 @default.
• W4328112977 creator A5065201284 @default.
• W4328112977 creator A5067501968 @default.
• W4328112977 creator A5083719814 @default.
• W4328112977 creator A5085110064 @default.
• W4328112977 creator A5086188803 @default.
• W4328112977 creator A5086493260 @default.
• W4328112977 creator A5086970664 @default.
• W4328112977 creator A5090079035 @default.
• W4328112977 date "2023-03-26" @default.
• W4328112977 modified "2023-09-27" @default.
• W4328112977 title "Prediction of permanent pacemaker implantation after transcatheter aortic valve replacement: The role of machine learning" @default.
• W4328112977 cites W107933927 @default.
• W4328112977 cites W132511837 @default.
• W4328112977 cites W1853851516 @default.
• W4328112977 cites W1866120224 @default.
• W4328112977 cites W1893332563 @default.
• W4328112977 cites W196650475 @default.
• W4328112977 cites W1982135373 @default.
• W4328112977 cites W2004967032 @default.
• W4328112977 cites W2009071367 @default.
• W4328112977 cites W2015186417 @default.
• W4328112977 cites W2021944894 @default.
• W4328112977 cites W2036505339 @default.
• W4328112977 cites W2072681305 @default.
• W4328112977 cites W2094914614 @default.
• W4328112977 cites W2098813733 @default.
• W4328112977 cites W2144132400 @default.
• W4328112977 cites W2149277991 @default.
• W4328112977 cites W2149609916 @default.
• W4328112977 cites W2169299179 @default.
• W4328112977 cites W2173551257 @default.
• W4328112977 cites W2177870565 @default.
• W4328112977 cites W2188390004 @default.
• W4328112977 cites W2254946724 @default.
• W4328112977 cites W2293244739 @default.
• W4328112977 cites W2308734203 @default.
• W4328112977 cites W2320982379 @default.
• W4328112977 cites W2324073140 @default.
• W4328112977 cites W2399783176 @default.
• W4328112977 cites W2408866005 @default.
• W4328112977 cites W2472486038 @default.
• W4328112977 cites W2551157276 @default.
• W4328112977 cites W2557004725 @default.
• W4328112977 cites W258896770 @default.
• W4328112977 cites W2605849388 @default.
• W4328112977 cites W2606654769 @default.
• W4328112977 cites W2611968684 @default.
• W4328112977 cites W2617110182 @default.
• W4328112977 cites W2784094750 @default.
• W4328112977 cites W2800686558 @default.
• W4328112977 cites W2911964244 @default.
• W4328112977 cites W2921388585 @default.
• W4328112977 cites W2986202787 @default.
• W4328112977 doi "https://doi.org/10.4330/wjc.v15.i3.95" @default.
• W4328112977 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37033682" @default.
• W4328112977 hasPublicationYear "2023" @default.
• W4328112977 type Work @default.
• W4328112977 citedByCount "1" @default.
• W4328112977 countsByYear W43281129772023 @default.
• W4328112977 crossrefType "journal-article" @default.
• W4328112977 hasAuthorship W4328112977A5001752698 @default.
• W4328112977 hasAuthorship W4328112977A5001962925 @default.
• W4328112977 hasAuthorship W4328112977A5016178572 @default.
• W4328112977 hasAuthorship W4328112977A5018761121 @default.
• W4328112977 hasAuthorship W4328112977A5020379926 @default.
• W4328112977 hasAuthorship W4328112977A5041696948 @default.
• W4328112977 hasAuthorship W4328112977A5043133312 @default.
• W4328112977 hasAuthorship W4328112977A5044601513 @default.
• W4328112977 hasAuthorship W4328112977A5051102742 @default.
• W4328112977 hasAuthorship W4328112977A5061056186 @default.
• W4328112977 hasAuthorship W4328112977A5062970790 @default.
• W4328112977 hasAuthorship W4328112977A5065201284 @default.
• W4328112977 hasAuthorship W4328112977A5067501968 @default.
• W4328112977 hasAuthorship W4328112977A5083719814 @default.
• W4328112977 hasAuthorship W4328112977A5085110064 @default.
• W4328112977 hasAuthorship W4328112977A5086188803 @default.
• W4328112977 hasAuthorship W4328112977A5086493260 @default.
• W4328112977 hasAuthorship W4328112977A5086970664 @default.
• W4328112977 hasAuthorship W4328112977A5090079035 @default.
• W4328112977 hasBestOaLocation W43281129771 @default.
• W4328112977 hasConcept C126322002 @default.
• W4328112977 hasConcept C164705383 @default.
• W4328112977 hasConcept C167135981 @default.
• W4328112977 hasConcept C2778557577 @default.
• W4328112977 hasConcept C2780007028 @default.

• next