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Predictors of anastomotic leak and conduit necrosis after oesophagectomy: Results from the oesophago-gastric anastomosis audit (OGAA)
EA. Griffiths, Oesophago-Gastric Anastomotic Audit (OGAA) Collaborative, Writing Committee, Data Analysis, Steering Committee, National Leads, Site Leads, Collaborators
Jazyk angličtina Země Anglie, Velká Británie
Typ dokumentu časopisecké články, multicentrická studie
- MeSH
- anastomóza chirurgická * MeSH
- chronická obstrukční plicní nemoc MeSH
- ezofagektomie * MeSH
- ezofágus chirurgie patologie MeSH
- hodnocení rizik MeSH
- index tělesné hmotnosti MeSH
- lidé středního věku MeSH
- lidé MeSH
- nádory jícnu * chirurgie patologie MeSH
- nekróza * MeSH
- netěsnost anastomózy * epidemiologie etiologie MeSH
- rizikové faktory MeSH
- ROC křivka MeSH
- senioři MeSH
- žaludek chirurgie patologie MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
BACKGROUND: Both anastomotic leak (AL) and conduit necrosis (CN) after oesophagectomy are associated with high morbidity and mortality. Therefore, the identification of preoperative, modifiable risk factors is desirable. The aim of this study was to generate a risk scoring model for AL and CN after oesophagectomy. METHODS: Patients undergoing curative resection for oesophageal cancer were identified from the international Oesophagogastric Anastomosis Audit (OGAA) from April 2018-December 2018. Definitions for AL and CN were those set out by the Oesophageal Complications Consensus Group. Univariate and multivariate analyses were performed to identify risk factors for both AL and CN. A risk score was then produced for both AL and CN using the derivation set, then internally validated using the validation set. RESULTS: This study included 2247 oesophagectomies across 137 hospitals in 41 countries. The AL rate was 14.2% and CN rate was 2.7%. Preoperative factors that were independent predictors of AL were cardiovascular comorbidity and chronic obstructive pulmonary disease. The risk scoring model showed insufficient predictive ability in internal validation (area under the receiver-operating-characteristic curve [AUROC] = 0.618). Preoperative factors that were independent predictors of CN were: body mass index, Eastern Cooperative Oncology Group performance status, previous myocardial infarction and smoking history. These were converted into a risk-scoring model and internally validated using the validation set with an AUROC of 0.775. CONCLUSION: Despite a large dataset, AL proves difficult to predict using preoperative factors. The risk-scoring model for CN provides an internally validated tool to estimate a patient's risk preoperatively.
Citace poskytuje Crossref.org
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- $a Griffiths, Ewen A $u Department of Upper Gastrointestinal Surgery, Queen Elizabeth Hospital Birmingham, Birmingham, UK. Electronic address: ewen.griffiths@uhb.nhs.uk
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- $a BACKGROUND: Both anastomotic leak (AL) and conduit necrosis (CN) after oesophagectomy are associated with high morbidity and mortality. Therefore, the identification of preoperative, modifiable risk factors is desirable. The aim of this study was to generate a risk scoring model for AL and CN after oesophagectomy. METHODS: Patients undergoing curative resection for oesophageal cancer were identified from the international Oesophagogastric Anastomosis Audit (OGAA) from April 2018-December 2018. Definitions for AL and CN were those set out by the Oesophageal Complications Consensus Group. Univariate and multivariate analyses were performed to identify risk factors for both AL and CN. A risk score was then produced for both AL and CN using the derivation set, then internally validated using the validation set. RESULTS: This study included 2247 oesophagectomies across 137 hospitals in 41 countries. The AL rate was 14.2% and CN rate was 2.7%. Preoperative factors that were independent predictors of AL were cardiovascular comorbidity and chronic obstructive pulmonary disease. The risk scoring model showed insufficient predictive ability in internal validation (area under the receiver-operating-characteristic curve [AUROC] = 0.618). Preoperative factors that were independent predictors of CN were: body mass index, Eastern Cooperative Oncology Group performance status, previous myocardial infarction and smoking history. These were converted into a risk-scoring model and internally validated using the validation set with an AUROC of 0.775. CONCLUSION: Despite a large dataset, AL proves difficult to predict using preoperative factors. The risk-scoring model for CN provides an internally validated tool to estimate a patient's risk preoperatively.
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