scholarly journals Correction to: Surgeon experience with dynamic intraligamentary stabilization does not influence risk of failure

2018 ◽  
Vol 27 (1) ◽  
pp. 335-335
Author(s):  
Philipp Henle ◽  
Kathrin S. Bieri ◽  
Janosch Haeberli ◽  
Nele Arnout ◽  
Jan Victor ◽  
...  
2018 ◽  
Vol 26 (10) ◽  
pp. 2978-2985 ◽  
Author(s):  
Philipp Henle ◽  
Kathrin S. Bieri ◽  
Janosch Haeberli ◽  
Nele Arnout ◽  
Jan Victor ◽  
...  

2004 ◽  
Vol 171 (4S) ◽  
pp. 336-336
Author(s):  
Allison Frisella ◽  
Caroline D Ames ◽  
David Lieber ◽  
Ramakrishna Venkatesh ◽  
Peter G. Schulam ◽  
...  

2012 ◽  
Author(s):  
Peter Ayton ◽  
Eugenio Alberdi ◽  
Lorenzo Strigini ◽  
David Wright
Keyword(s):  

2019 ◽  
Author(s):  
Aoife Garrahy ◽  
Zarina Brady ◽  
Mark Sherlock ◽  
Christopher J Thompson ◽  
Amar Agha ◽  
...  

2012 ◽  
Vol 30 (1) ◽  
pp. 119-127
Author(s):  
Henryk Tomaszek ◽  
Ryszard Kaleta ◽  
Mariusz Zieja

The paper is an attempt to describe the forecast on the risk of damages resulting from failures to the means of transport. It has been assumed that the product of the probability of failure (fault) occurrence and measures of effects thereof are to be used to estimate the risk. The below presented dependences that describe the risk of damages have been based on the failure rate. With the available literature as the basis, a preliminary description of the probability of a failure (fault) and the level of losses has been proposed. The paper gives dependences on short- and long-range risk forecasts. To determine the relationship for the probability of a failure (fault), the failure rate has been used.


2020 ◽  
Vol 32 (2) ◽  
pp. 207-220 ◽  
Author(s):  
Darryl Lau ◽  
Vedat Deviren ◽  
Christopher P. Ames

OBJECTIVEPosterior-based thoracolumbar 3-column osteotomy (3CO) is a formidable surgical procedure. Surgeon experience and case volume are known factors that influence surgical complication rates, but these factors have not been studied well in cases of adult spinal deformity (ASD). This study examines how surgeon experience affects perioperative complications and operative measures following thoracolumbar 3CO in ASD.METHODSA retrospective study was performed of a consecutive cohort of thoracolumbar ASD patients who underwent 3CO performed by the senior authors from 2006 to 2018. Multivariate analysis was used to assess whether experience (years of experience and/or number of procedures) is associated with perioperative complications, operative duration, and blood loss.RESULTSA total of 362 patients underwent 66 vertebral column resections (VCRs) and 296 pedicle subtraction osteotomies (PSOs). The overall complication rate was 29.4%, and the surgical complication rate was 8.0%. The rate of postoperative neurological deficits was 6.2%. There was a trend toward lower overall complication rates with greater operative years of experience (from 44.4% to 28.0%) (p = 0.115). Years of operative experience was associated with a significantly lower rate of neurological deficits (p = 0.027); the incidence dropped from 22.2% to 4.0%. The mean operative time was 310.7 minutes overall. Both increased years of experience and higher case numbers were significantly associated with shorter operative times (p < 0.001 and p = 0.001, respectively). Only operative years of experience was independently associated with operative times (p < 0.001): 358.3 minutes from 2006 to 2008 to 275.5 minutes in 2018 (82.8 minutes shorter). Over time, there was less deviation and more consistency in operative times, despite the implementation of various interventions to promote fusion and prevent construct failure: utilization of multiple-rod constructs (standard, satellite, and nested rods), bone morphogenetic protein, vertebroplasty, and ligament augmentation. Of note, the use of tranexamic acid did not significantly lower blood loss.CONCLUSIONSSurgeon years of experience, rather than number of 3COs performed, was a significant factor in mitigating neurological complications and improving quality measures following thoracolumbar 3CO for ASD. The 3- to 5-year experience mark was when the senior surgeon overcame a learning curve and was able to minimize neurological complication rates. There was a continuous decrease in operative time as the surgeon’s experience increased; this was in concurrence with the implementation of additional preventative surgical interventions. Ongoing practice changes should be implemented and can be done safely, but it is imperative to self-assess the risks and benefits of those practice changes.


2001 ◽  
Vol 1 (4) ◽  
pp. 177-184
Author(s):  
B.I. Dvorak ◽  
J.W. Schauble

Environmental engineers are frequently faced with uncertainty in making design decisions because the true value of many process parameters is unknown. In this study, the design of countercurrent air stripping towers was modeled using fuzzy numbers, taking into account uncertainties in mass transfer and Henry's constant. It was found that, in addition to cost, the risk of failure is an important design consideration for stripping tower design. A significant over-design is both cost-effective and results in less risk of design failure. The air-to-water ratio that yielded the least risk of failure switched from low to high as the removal efficiency of the tower increased. An important result is that at lower removal efficiencies, tower design and operation is most sensitive to uncertainties in mass transfer and at higher removal efficiencies, tower design and operation is most sensitive to uncertainties in Henry's constant . The implication is that low air-to-water ratios are best when the regulatory target removal efficiency is low and/or when the uncertainty in the value of the contaminant's Henry's constant is larger than the uncertainty in the mass transfer coefficient value. Otherwise a high air-to-water ratio results in the least risk of process failure.


Author(s):  
Jin K. Kim ◽  
Mitchell Shiff ◽  
Michael E. Chua ◽  
Fadi Zu’bi ◽  
Jessica M. Ming ◽  
...  

2021 ◽  
Vol 42 (Supplement_1) ◽  
pp. S193-S193
Author(s):  
Samantha Huang ◽  
Justin Dang ◽  
Clifford C Sheckter ◽  
Haig A Yenikomshian ◽  
Justin Gillenwater

Abstract Introduction Current methods of burn evaluation and treatment are subjective and dependent on surgeon experience, with high rates of inter-rater variability leading to inaccurate diagnoses and treatment. Machine learning (ML) and automated methods are being used to develop more objective and accurate methods for burn diagnosis and triage. Defined as a subfield of artificial intelligence that applies algorithms capable of knowledge acquisition, machine learning draws patterns from data, which it can then apply to clinically relevant tasks. This technology has the potential to improve burn management by quantitating diagnoses, improving diagnostic accuracy, and increasing access to burn care. The aim of this systematic review is to summarize the literature regarding machine learning and automated methods for burn wound evaluation and treatment. Methods A systematic review of articles available on PubMed and MEDLINE (OVID) was performed. Keywords used in the search process included burns, machine learning, deep learning, burn classification technology, and mobile applications. Reviews, case reports, and opinion papers were excluded. Data were extracted on study design, study objectives, study models, devices used to capture data, machine learning, or automated software used, expertise level and number of evaluators, and ML accuracy of burn wound evaluation. Results The search identified 592 unique titles. After screening, 35 relevant articles were identified for systematic review. Nine studies used machine learning and automated software to estimate percent total body surface area (%TBSA) burned, 4 calculated fluid requirements, 18 estimated burn depth, 5 estimated need for surgery, 6 predicted mortality, and 2 evaluated scarring in burn patients. Devices used to estimate %TBSA burned showed an accuracy comparable to or better than traditional methods. Burn depth estimation sensitivities resulted in unweighted means &gt;81%, which increased to &gt;83% with equal weighting applied. Mortality prediction sensitivity had an unweighted mean of 96.75%, which increased to 99.35% with equal weighting. Conclusions Machine learning and automated technology are promising tools that provide objective and accurate measures of evaluating burn wounds. Existing methods address the key steps in burn care management; however, existing data reporting on their robustness remain in the early stages. Further resources should be dedicated to leveraging this technology to improve outcomes in burn care.


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