The Impact of Body Mass Index on Shortterm Surgical Outcomes After Laparoscopic Hepatectomy

A Retrospective Study

Xin Yu; Hong Yu; Xiangming Fang


BMC Anesthesiol. 2016;16(29) 

In This Article


Patients and Data Collection

In this retrospective study, 554 consecutive patients who underwent LH between 1998 and 2013 at Sir Run Run Shaw Hospital were identified from patients database, three patients died during the postoperative period were excluded.

According to the WHO's definition of obesity for the Asia-Pacific region,[8] 551 Patients were segregated into four groups by BMI: underweight <18.5 kg/m2 (Group1); normal weight 18.5–23.9 kg/m2 (Group 2); overweight 24–27.9 kg/m2 (Group 3); obese ≥28 kg/m2 (Group 4).

BMI was calculated according to a standardized definition as weight in kilograms divided by height in meters squared. BMI was recorded the day before the surgery.

Data collection included standard demographic information (age, gender, height, and weight), American Society of Anesthesiologists (ASA) score, prior abdominal surgery, diabetes, conversion, operation duration, blood loss, transfusion (Hemoglobin < 7 g/dl as the indication), type of disease, type of resection, pathology, complications (those that occurred at any time during the postoperative hospital stay), postoperative length of stay (LOS), and severity of complication which were categorized according to the Clavien-Dindo classification system.[9] In the analysis, grades 1 and 2 were considered as minor complications, whereas grades 3–5 were considered as major complications. And only the highest ranked complication was chosen for the final analysis.

Liver resection cases were categorized according to Couinaud's classification as follows:[10] (1) Left hepatectomy for resection of segments II–IV; (2) Right hemihepatectomy for resection of segments V–VIII; (3) Left lateral hepatectomy for resection of segments II and III; (4) Segmentectomy for resection of a single segment; (5) Local hepatectomy for resection of less than a single segment. (6) Caudate for resection of segment I.

Surgical Procedure

The indication of laparoscopic treatment for liver disease was made during a multidisciplinary conference, which included hepatobiliary surgeons, radiologists, as well as patient's preference.

The procedure was performed with the patient in the supine and 30° anti-Trendelenburg position under carbon dioxide pneumoperitoneum, the abdominal pressure was maintained between 12 and 15 mmHg. For a right hemihepatectomy, the patient would be positioned in the 45°right side cushion with the table turned to its left side.

A 10-mm trocar was positioned above the umbilicus for insertion of optical device and the linear stapler. A 12-mm port was positioned on the crossing of left midcalvicular line and costal margin for surgical aspirator or harmonic scissors. Other two 5-mm ports were inserted in the left upper abdominal quadrant according to the lesion location, allowing the assistant aspirate, irrigate or hang the live for a better exposure.

Instead of total hepatic vascular occlusion, regional occlusion of liver left/right inflow and outflow was used to reduce bleeding and minimize the ischemia reperfusion injury.[11] The pringle maneuver was used only when there was bleeding.

Liver parenchymal transection and small vascular disconnection were almost performed with multifunctional electric knife LPMOD (laparoscopic multiple operation dissector) which can scrape the hepatic parenchyma, separate and dissect vessels and bile ducts of liver section, and allow suction of blood and smoke to provide a clear view.[12] The operation was considered to convert if there was an unsatisfactory visualization, an uncontrolled bleeding, difficult manipulation, or unclear tumor edge.

Statistical Analysis

Data are presented as the mean ± SD for normal distribution, and the median with an interquartile range for non-normally distributed parameters. Continuous data normally distributed were compared using the two-side Student's t-test. Continuous data non-normally distributed were compared using the Kruskal-Wallis test. Comparisons between groups for categorical variables were performed using the ANOVA analysis with Fisher's exact test, as appropriate. To identify variables that were independent predictors of conversion rate and complications, only factors associated with conversion rate and complications in the univariate analysis with significant difference entered into a logistic regression analysis. 95 % confident interval (CI) and odd ratios (OR) were calculated. Significance was defined as p < 0.05. All statistic analyses were made with SPSS Version18.