Objective: To assess whether specific patterns of early postoperative complications may predict overall severe morbidity after major surgery, warranting early escalation of care and prevention of failure to rescue.

Summary Of Background Data: It is unclear whether early postoperative complications predict a poor outcome. Detailed knowledge of the chronology and type of early complications after major surgery may alert clinicians when to expect higher risk for subsequent major negative events.

Methods: All 90-day postoperative events following complex pancreas, liver, and rectal surgeries, and liver transplantation were analyzed over a 3-year period in a single tertiary center. Each complication was recorded regarding severity, type (cardiac, infectious, etc), etiology (surgical/medical), and timing of occurrence. The Comprehensive Complication Index (CCI), covering the first 7 postoperative days, was calculated as a measure for early cumulative postoperative morbidity. The statistical analysis (descriptive, sequence pattern analyses, and logistic regression analyses) aimed to detect any combinations of events predicting poor outcome as defined by a cumulative CCI ≥37.1 at 90-days.

Results: The occurrence of ≥2 complications, irrespective of severity, type or etiology, was strongly associated with a severe postoperative course (P < 0.001). Even 2 mild complications (≤ grade II) greatly increased the chance for high morbidity compared to patients with 0 or 1 complication within the first postoperative week (odds ratio 10.2, 95% confidence interval 5.82-17.98). The CCI at postoperative day 7 strongly predicted high 90-day morbidity (odds ratio 3.96 per 10 CCI points, P < 0.001).

Conclusion: Multiple complications of any cause or severity within the first postoperative days represents a "warning-signal" for overall high morbidity by 90 days, which should be used to trigger an escalation of care to prevent failure to rescue and eventually poor outcome.

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Source
http://dx.doi.org/10.1097/SLA.0000000000004254DOI Listing

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