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Is postoperative decrease of serum albumin an early predictor of complications after major abdominal surgery? A prospective cohort study in a European centre.

BMJ Open 2017 April 9
OBJECTIVE: To test postoperative serum albumin drop (ΔAlb) as a marker of surgical stress response and early predictor of clinical outcomes.

DESIGN: Prospective cohort study (NCT02356484). Albumin was prospectively measured in 138 patients undergoing major abdominal surgery. Blood samples were collected before surgery and on postoperative days 0, 1 2 and 3. ΔAlb was compared to the modified estimation of physiologic ability and surgical stress (mE-PASS) score and correlated to the performances of C reactive protein (CRP), procalcitonin (PCT) and lactate (LCT). Postoperative outcomes were postoperative complications according to Clavien classification and Comprehensive Complication Index (CCI), and length of hospital stay (LoS).

SETTING: Department of abdominal surgery in a European tertiary centre.

PARTICIPANTS: Adult patients undergoing elective major abdominal surgery, with anticipated duration ≥2 hours. Patients on immunosuppressive or antibiotic treatments before surgery were excluded.

RESULTS: The level of serum albumin rapidly dropped after surgery. ΔAlb correlated to the mE-PASS score (r=0.275, p=0.01) and to CRP increase (r=0.536, p<0.001). ΔAlb also correlated to overall complications (r=0.485, p<0.001), CCI (r=0.383, p<0.001) and LoS (r=0.468, p<0.001). A ΔAlb ≥10 g/L yielded a sensitivity of 77.1% and a specificity of 67.2% (AUC: 78.3%) to predict complications. Patients with ΔAlb ≥10 g/L on POD 1 showed a threefold increased risk of overall postoperative complications.

CONCLUSIONS: Early postoperative decrease of serum albumin correlated with the extent of surgery, its metabolic response and with adverse outcomes such as complications and length of stay. A decreased concentration of serum albumin ≥10 g/L on POD 1 was associated with a threefold increased risk of overall postoperative complications and may thus be used to identify patients at risk.

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