Dataset Information

The applications of machine learning in plastic and reconstructive surgery: protocol of a systematic review.

ABSTRACT: BACKGROUND:Machine learning, a subset of artificial intelligence, is a set of models and methods that can automatically detect patterns in vast amounts of data, extract information and use it to perform various kinds of decision-making under uncertain conditions. This can assist surgeons in clinical decision-making by identifying patient cohorts that will benefit from surgery prior to treatment. The aim of this review is to evaluate the applications of machine learning in plastic and reconstructive surgery. METHODS:A literature review will be undertaken of EMBASE, MEDLINE and CENTRAL (1990 up to September 2019) to identify studies relevant for the review. Studies in which machine learning has been employed in the clinical setting of plastic surgery will be included. Primary outcomes will be the evaluation of the accuracy of machine learning models in predicting a clinical diagnosis and post-surgical outcomes. Secondary outcomes will include a cost analysis of those models. This protocol has been prepared using the Preferred Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines. DISCUSSION:This will be the first systematic review in available literature that summarises the published work on the applications of machine learning in plastic surgery. Our findings will provide the basis of future research in developing artificial intelligence interventions in the specialty. SYSTEMATIC REVIEW REGISTRATION:PROSPERO CRD42019140924.

SUBMITTER: Mantelakis A

PROVIDER: S-EPMC7047352 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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The applications of machine learning in plastic and reconstructive surgery: protocol of a systematic review.

Mantelakis Angelos A Khajuria Ankur A

Systematic reviews 20200228 1

<h4>Background</h4>Machine learning, a subset of artificial intelligence, is a set of models and methods that can automatically detect patterns in vast amounts of data, extract information and use it to perform various kinds of decision-making under uncertain conditions. This can assist surgeons in clinical decision-making by identifying patient cohorts that will benefit from surgery prior to treatment. The aim of this review is to evaluate the applications of machine learning in plastic and rec ...[more]

PMID: 32111260

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Project description:BACKGROUND:After an esophagectomy, the stomach is most commonly used to restore continuity of the upper gastrointestinal tract. These esophago-gastric anastomoses are prone to serious complications such as leakage associated with high morbidity and mortality. Graft perfusion is considered to be an important predictor for anastomotic integrity. Based on the current literature we believe Indocyanine green fluorescence angiography (ICGA) is an easy assessment tool for gastric tube (GT) perfusion, and it might predict anastomotic leakage (AL). AIM:To evaluate feasibility and effectiveness of ICGA in GT perfusion assessment and as a predictor of AL. METHODS:This study was designed according to the PRISMA guidelines and registered in the PROSPERO database. PubMed and EMBASE were independently searched by 2 reviewers for studies presenting data on intraoperative ICGA GT perfusion assessment during esophago-gastric reconstruction after esophagectomy. Relevant outcomes such as feasibility, complications, intraoperative surgical changes based on ICGA findings, quantification attempts, anatomical data and the impact of ICGA on postoperative anastomotic complications, were collected by 2 independent researchers. The quality of the included articles was assessed based on the Methodological Index for Non-Randomized Studies. The 19 included studies presented data on 1192 esophagectomy patients, in 758 patients ICGA was used perioperative to guide esophageal reconstruction. RESULTS:The 19 included studies for qualitative analyses all described ICGA as a safe and easy method to evaluate gastric graft perfusion. AL occurred in 13.8% of the entire cohort, 10% in the ICG guided group and 20.6% in the control group (P < 0.001). When poorly perfused cases are excluded from the analyses, the difference in AL was even larger (AL well-perfused group 6.3% vs control group 20.5%, P < 0.001). The AL rate in the group with an altered surgical plan based on the ICG image was 6.5%, similar to the well perfused group (6.3%) and significantly less than the poorly perfused group (47.8%) (P < 0.001), suggesting that the technique is able to identify and alter a potential bad outcome. CONCLUSION:ICGA is a safe, feasible and promising method for perfusion assessment. The lower AL rate in the well perfused group suggest that a good fluorescent signal predicts a good outcome.

Project description:PurposeThe COVID-19 pandemic has brought unprecedented challenges for oculoplastic surgeons worldwide, in terms of care delivery, medical equipment and at-risk patient management. To date, there are no centralized or compiled international COVID-19 guidelines for oculoplastic surgeons.MethodsWe examined COVID-19 guidelines published by oculoplastic societies worldwide. All countries around the world were initially considered in this study, but only 9 oculoplastic societies met the inclusion criteria: (1) publicly available guidelines displayed on the oculoplastic society's website, or (2) guidelines received from the oculoplastic society after contacting them twice using the contact information on their website.ResultsThe 9 oculoplastic societies examined include: the American Society of Ophthalmic Plastic and Reconstructive Surgery, the British Oculoplastic Surgery Society, the Canadian Society of Oculoplastic Surgery, the European Society of Ophthalmic Plastic and Reconstructive Surgery, la Sociedad Española de Cirugía Plástica Ocular y Orbitaria, la Asociación Colombiana de Cirugía Plastica Ocular, the Asia Pacific Society of Ophthalmic Plastic & Reconstructive Surgery, the Oculoplastics Association of India, and the Philippine Society of Ophthalmic Plastic and Reconstructive Surgery. They all agree that urgent procedures should not be delayed, while non-necessary procedures (including all elective clinic services) should be postponed. When adequate protective equipment is available, oculoplastic surgeons must treat urgent cases. Eight out of 9 societies have provided recommendations on personal protective equipment use in order to prevent the spread of COVID-19 and to adequately protect mucous membranes. Other recommendations provided by certain societies are related to shelter in place measures, hand hygiene and surface disinfection protocols, patient triage, and thyroid eye disease management.ConclusionsAll 9 societies with published recommendations have provided valuable recommendations to their members, regarding urgency of care and infection control solutions (personal protective equipment, hand hygiene, telemedicine, and social isolation).

Dataset Information

The applications of machine learning in plastic and reconstructive surgery: protocol of a systematic review.

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The applications of machine learning in plastic and reconstructive surgery: protocol of a systematic review.

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