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C-REACTIVE PROTEIN AS POSTOPERATIVE COMPLICATIONS PREDICTOR OF COLORECTAL SURGERIES

Proteína C-reativa como preditor para complicações pós-operatórias em cirurgias colorretais

ABSTRACT

Background:

The use of inflammatory markers in order to accurate the diagnosis, decrease the reoperation rate and enable earlier interventions during the postoperative period of a colorectal surgery is increasingly necessary, with the purpose of reducing morbimortality, nosocomial infections, costs and time of a readmission.

Objective:

To analyze C-reactive protein level on the third postoperative day of an elective colorectal surgery and compare the marks between reoperated and non-reoperated patients and to establish a cutoff value to predict or avoid surgical reoperations.

Methods:

Retrospective study based on the analysis of electronic charts of over 18-year-old patients who underwent an elective colorectal surgery with primary anastomoses during the period from January 2019 to May 2021 by the proctology team of Santa Marcelina Hospital Department of General Surgery with C-reactive protein (CRP) dosage taken on the third postoperative day.

Results:

We assessed 128 patients with a mean age of 59.22 years old and need of reoperation of 20.3% of patients, half of these due to dehiscence of colorectal anastomosis. Comparing CRP rates on the third postoperative day between non-reoperated and reoperated patients, it was noted that in the former group the average was of 153.8±76.2 mg/dL, whereas in reoperated patients it was 198.7±77.4 mg/dL (P<0.0001) and the best CRP cutoff value to predict or investigate reoperation risk was 184.8 mg/L with an accuracy of 68% and negative predictive value of 87.6%.

Conclusion:

CRP levels assessed on the third postoperative day of elective colorectal surgery were higher in patients who were reoperated and the cutoff value for intra-abdominal complication of 184.8mg/L presented a high negative predictive value.

Keywords:
Colorectal surgery; reoperation; C-reactive protein; accuracy; negative predictive value

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