early outcome
Recently Published Documents


TOTAL DOCUMENTS

726
(FIVE YEARS 122)

H-INDEX

56
(FIVE YEARS 3)

2021 ◽  
Vol 11 (12) ◽  
pp. 1377
Author(s):  
Pedro Berjano ◽  
Francesco Langella ◽  
Luca Ventriglia ◽  
Domenico Compagnone ◽  
Paolo Barletta ◽  
...  

The study aims to create a preoperative model from baseline demographic and health-related quality of life scores (HRQOL) to predict a good to excellent early clinical outcome using a machine learning (ML) approach. A single spine surgery center retrospective review of prospectively collected data from January 2016 to December 2020 from the institutional registry (SpineREG) was performed. The inclusion criteria were age ≥ 18 years, both sexes, lumbar arthrodesis procedure, a complete follow up assessment (Oswestry Disability Index—ODI, SF-36 and COMI back) and the capability to read and understand the Italian language. A delta of improvement of the ODI higher than 12.7/100 was considered a “good early outcome”. A combined target model of ODI (Δ ≥ 12.7/100), SF-36 PCS (Δ ≥ 6/100) and COMI back (Δ ≥ 2.2/10) was considered an “excellent early outcome”. The performance of the ML models was evaluated in terms of sensitivity, i.e., True Positive Rate (TPR), specificity, i.e., True Negative Rate (TNR), accuracy and area under the receiver operating characteristic curve (AUC ROC). A total of 1243 patients were included in this study. The model for predicting ODI at 6 months’ follow up showed a good balance between sensitivity (74.3%) and specificity (79.4%), while providing a good accuracy (75.8%) with ROC AUC = 0.842. The combined target model showed a sensitivity of 74.2% and specificity of 71.8%, with an accuracy of 72.8%, and an ROC AUC = 0.808. The results of our study suggest that a machine learning approach showed high performance in predicting early good to excellent clinical results.


2021 ◽  
Vol 429 ◽  
pp. 119704
Author(s):  
Po-Lin Chen ◽  
Yeng-Fung Liaw ◽  
Nien-Chen Liao ◽  
Jin-An Huang

2021 ◽  
Author(s):  
Francesco Langella ◽  
Luca Ventriglia ◽  
Domenico Compagnone ◽  
Paolo Barletta ◽  
David Huber ◽  
...  

AbstractAimsTo create, using a machine learning (ML) approach, a preoperative model from baseline demographic and health-related quality of life scores (HRQOL) to predict a good to excellent early clinical outcome.Patients and MethodsA single spine surgery center retrospective review of prospectively collected data from January 2016 to December 2020 from the institutional registry (SpineREG) was performed. The inclusion criteria were age ≥ 18 years, both sexes, lumbar arthrodesis procedure, a complete follow up assessment (ODI, SF-36 and COMI back) and the capability to read and understand the Italian language. A delta of improvement of the ODI higher than 12.7/100 was considered a “good early outcome”. A combined target model of ODI (Δ ≥ 12.7/100), SF-36 PCS (Δ ≥ 6/100) and COMI back (Δ ≥ 2.2/10) was considered an “excellent early outcome”. The performance of the ML models was evaluated in terms of sensitivity, i.e., True Positive Rate (TPR), specificity, i.e., True Negative Rate (TNR), accuracy and area under the receiver operating characteristic curve (AUC ROC).ResultsA total of 1243 patients were included in this study. The model for predicting ODI at 6 months follow up showed a good balance between sensitivity (74.3%) and specificity (79.4%), while providing a good accuracy (75.8%) with ROC AUC = 0.842. The combined target model showed a sensitivity of 74.2% and specificity of 71.8%, with an accuracy of 72.8%, and a ROC AUC = 0.808.ConclusionThe results of our study suggest that a machine learning approach showed high performance in predicting early good to excellent clinical results.


2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Yong-Hai Zhou ◽  
Xin-Ru Han ◽  
Fang-Qing Xia ◽  
Neha-Devi Poonit ◽  
Li Liu

Eye ◽  
2021 ◽  
Author(s):  
Neeru Amrita Vallabh ◽  
Fiona Mason ◽  
Jonathan T. S. Yu ◽  
Kenneth Yau ◽  
Cecilia H. Fenerty ◽  
...  

2021 ◽  
Author(s):  
Lina Ya’qoub ◽  
Marvin Eng

We will review transcatheter mitral valve replacement (TMVR) and discuss this evolving cutting edge procedure in terms of types (valve in valve, valve in ring and valve in mitral annular calcification MAC), clinical indications, pre-procedural planning and value of pre-procedural imaging including computed tomography role, technical challenges encountered in these procedures, potential complications for each type of TMVR, and potential strategies to mitigate and avoid such complications, We will review the currently available devices dedicated for mitral valve replacement, with a summary of their preliminary data and early outcome results. We will also discuss knowledge gaps and ideas for future research.


2021 ◽  
pp. 55-59
Author(s):  
Rajkumar Verma ◽  
Satyendra Kumar ◽  
Vipin Mishra ◽  
Narendra Kumar

INTRODUCTION : Fissure-in-Ano is one of the common and most painful anorectal conditions encountered in surgical practice. Inspite of several conservative treatment options, surgical treatment in the form of Lateral Internal Spincterotomy (LIS) remains the gold standard of treatment for anal ssure. However we compare Laser lateral internal sphincterotomy with Open lateral internal Sphincterotomy for better postoperative pain relief and lesser hospital stay. AIM: Early outcome of laser lateral internal Sphincterotomy versus open lateral internal sphincterotomy in the treatment of anal ssures. MATERIALS AND METHODS: The study was conducted on 50 cases of Laser lateral internal sphincterotomy compare with 50 cases of Open lateral internal sphincterotomy in Maharani Laxmi Bai Medical College, Jhansi between January 2020 to July 2021. RESULTS:In our study in Group A 6% were in 16-20 years, 52% in 21-30 years, 20% in 31-40 years, 20% in 41-50 years and 2% 51-60% years and Group B 2% in 16-20 years, 34% in 21-30 years, 32% in 31-40 years, 18% 41-50%, 10% in 51-60 and 4% in >60. Group A mean postoperative VAS pain score in 6 hours 5.12±0,328, 12 hours 4.32±0.768, 24 hours 3.74±0.777, 36 hours 2.76±1.379 and 48 hours 2.3±1.418. In Group B mean postoperative VAS pain score in 6 hours 5.2±0.452, 12 hours 2.7±1.741, 24 hours 1.76±1.451, 36 hours 0.58±0.971 and 48 hours 0.28±0.671. Group A 44% presented with Perianal swelling, 42% Prutis Ani and 40% atus incontinence. In Group B 6% presented with amount of blood loss 6%, 18% Perianal swelling, 6% infection, 18% atus incontinence. The mean postoperative pain score was signicantly less in Group B at 12 to 48 hours. Group A mean hospital stay was 5.02±1.237 days and in Group B 2.02±0.141 days. It was signicantly less in Group B. CONCLUSION: Laser lateral Internal Spincterotomy is better than open Lateral Internal Spincterotomy with respect to less postoperative pain and lesser hospital stay and also less postoperative complications in the treatment of anal ssure.


Sign in / Sign up

Export Citation Format

Share Document