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Published on: March 26, 2018
Preoperative Hyperlactatemia Predicts Mortality in Acute Stanford Type A Dissection: A 16-Year-Period, Single-Center,
Nazan Puluca1,2, Christian König1,2, Gunther Wiesner3
1Department of Cardiovascular Surgery, German Heart Center Munich, Technical University of Munich, 80636 Munich, Germany.
Preoperative lactate levels greater than 3.71 mmol/L strongly predict early mortality in patients undergoing surgery for acute Stanford Type A aortic dissection (ATAAD). Elevated lactate indicates organ malperfusion and is the most significant risk factor for 30-day survival.
Area of Science:
- Cardiovascular Surgery
- Thoracic Surgery
- Intensive Care Medicine
Background:
- Acute Stanford Type A aortic dissection (ATAAD) is a critical surgical emergency.
- Organ malperfusion is a life-threatening complication of ATAAD.
- Lactate levels serve as an indicator of anaerobic glycolysis and organ malperfusion.
Purpose of the Study:
- To evaluate preoperative lactate levels as a surrogate marker for patient outcomes after ATAAD surgery.
- To determine the predictive value of lactate acidosis for mortality in ATAAD patients.
- To analyze the impact of preoperative lactate on short-term and long-term survival.
Main Methods:
- Retrospective analysis of 306 consecutive ATAAD patients from 2000-2016.
- Serum lactate measurements obtained preoperatively.
- Maximal selected rank statistics used to determine lactate cut-point (3.71 mmol/L).
Main Results:
- Patients with lactate > 3.71 mmol/L had significantly higher 30-day mortality (51.5% vs. 18.7%).
- Elevated lactate (> 3.71 mmol/L) was the strongest predictor of 30-day mortality (OR = 7.292).
- This association persisted for overall mortality (HR = 2.772), but age was the only significant factor for long-term survival post-30 days.
Conclusions:
- Preoperative lactate is an accessible surrogate marker for organ malperfusion in ATAAD.
- A preoperative lactate level > 3.71 mmol/L is the strongest predictor of early mortality following ATAAD surgery.
- Lactate levels effectively identify high-risk patients for early adverse outcomes.
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