Use of C-reactive Protein for the Early Prediction of Anastomotic Leak After Esophagectomy: Systematic Review and Bayesian Meta-analysis
Overview
Affiliations
Background: Early suspicion, diagnosis, and timely treatment of anastomotic leak after esophagectomy is essential. Retrospective studies have investigated the role of C-reactive protein (CRP) as early marker of anastomotic leakage. The aim of this systematic review and meta-analysis was to evaluate the predictive value of CRP after esophageal resection.
Methods: A literature search was conducted to identify all reports including serial postoperative CRP measurements to predict anastomotic leakage after elective open or minimally invasive esophagectomy. Fully Bayesian meta-analysis was carried out using random-effects model for pooling diagnostic accuracy measures along with CRP cut-off values at different postoperative day.
Results: Five studies published between 2012 and 2018 met the inclusion criteria. Overall, 850 patients were included. Ivor-Lewis esophagectomy was the most common surgical procedure (72.3%) and half of the patients had squamous-cell carcinoma (50.4%). The estimated pooled prevalence of anastomotic leak was 11% (95% CI = 8-14%). The serum CRP level on POD3 and POD5 had comparable diagnostic accuracy with a pooled area under the curve of 0.80 (95% CIs 0.77-0.92) and 0.83 (95% CIs 0.61-0.96), respectively. The derived pooled CRP cut-off values were 17.6 mg/dl on POD 3 and 13.2 mg/dl on POD 5; the negative likelihood ratio were 0.35 (95% CIs 0.096-0.62) and 0.195 (95% CIs 0.04-0.52).
Conclusion: After esophagectomy, a CRP value lower than 17.6 mg/dl on POD3 and 13.2 mg/dl on POD5 combined with reassuring clinical and radiological signs may be useful to rule-out leakage. In the context of ERAS protocols, this may help to avoid contrast radiological studies, anticipate oral feeding, accelerate hospital discharge, and reduce costs.
Almutairi F Cureus. 2024; 16(6):e62432.
PMID: 39011204 PMC: 11249052. DOI: 10.7759/cureus.62432.
DellAnna G, Fanti L, Fanizza J, Bara R, Barchi A, Fasulo E J Clin Med. 2024; 13(13).
PMID: 38999371 PMC: 11242239. DOI: 10.3390/jcm13133805.
Bona D, Manara M, Bonitta G, Guerrazzi G, Guraj J, Lombardo F Cancers (Basel). 2024; 16(8).
PMID: 38672550 PMC: 11048031. DOI: 10.3390/cancers16081468.
Complication Prediction after Esophagectomy with Machine Learning.
van de Beld J, Crull D, Mikhal J, Geerdink J, Veldhuis A, Poel M Diagnostics (Basel). 2024; 14(4).
PMID: 38396478 PMC: 10888312. DOI: 10.3390/diagnostics14040439.
Van Daele E, Vanommeslaeghe H, Decostere F, Beckers Perletti L, Beel E, van Nieuwenhove Y J Clin Med. 2024; 13(3).
PMID: 38337519 PMC: 10856250. DOI: 10.3390/jcm13030826.