Validation of the peak bilirubin criterion for outcome after partial hepatectomy

Understanding conditional cumulative incidence of complications following liver resection to optimize hospital stay

BACKGROUND

After liver resection, the in-hospital observation periods associated with minimal risks for complications and unplanned readmission remains unclear. This study aimed to assess changes in risks of complications over time.

METHODS

Surgical complexity of liver resection was stratified into grades I (low complexity), II (intermediate), and III (high). The cumulative incidence rate and risk factors for complication ≥ Clavien-Dindo grade II (defined as treatment-requiring complications) were assessed.

RESULTS

Of 581 patients, grade I, II, and III resections were performed in 81 (13.9%), 119 (20.5%), and 381 patients (65.6%). Complexity grades (I vs. III, hazard ratio [HR] 0.45, P = 0.007; II vs. III, HR 0.60, P = 0.011) and background liver status (HR 1.76, P = 0.004) were risk factors for treatment-requiring complications. The cumulative incidence rate of treatment-requiring complications was higher after grade III resection than grade I resection (38.1% vs. 16.1%, P < 0.001) or grade II resection (38.1% vs. 25.2%, P = 0.019). Without cirrhosis/chronic hepatitis, the cumulative incidence rate of treatment-requiring complications decreased to less than 10% on postoperative day (POD) 3 after grade I resection, POD 5 after grade II resection, and POD 10 after grade III resection.

CONCLUSION

Conditional complication risk analysis stratified by surgical complexity may be useful for optimizing in-hospital observation.

Quantitative magnetic resonance imaging predicts individual future liver performance after liver resection for cancer

The risk of poor post-operative outcome and the benefits of surgical resection as a curative therapy require careful assessment by the clinical care team for patients with primary and secondary liver cancer. Advances in surgical techniques have improved patient outcomes but identifying which individual patients are at greatest risk of poor post-operative liver performance remains a challenge. Here we report results from a multicentre observational clinical trial (ClinicalTrials.gov NCT03213314) which aimed to inform personalised pre-operative risk assessment in liver cancer surgery by evaluating liver health using quantitative multiparametric magnetic resonance imaging (MRI). We combined estimation of future liver remnant (FLR) volume with corrected T1 (cT1) of the liver parenchyma as a representation of liver health in 143 patients prior to treatment. Patients with an elevated preoperative liver cT1, indicative of fibroinflammation, had a longer post-operative hospital stay compared to those with a cT1 within the normal range (6.5 vs 5 days; p = 0.0053). A composite score combining FLR and cT1 predicted poor liver performance in the 5 days immediately following surgery (AUROC = 0.78). Furthermore, this composite score correlated with the regenerative performance of the liver in the 3 months following resection. This study highlights the utility of quantitative MRI for identifying patients at increased risk of poor post-operative liver performance and a longer stay in hospital. This approach has the potential to inform the assessment of individualised patient risk as part of the clinical decision-making process for liver cancer surgery.