The Effect of Obesity and Increased Waist Circumference on the Outcome of Laparoscopic Nephrectomy.
Derek Barrry HennesseyE M BoltonA Z ThomasR P ManeckshaT H LynchPublished in: Advances in urology (2017)
Introduction. The prevalence of obesity is increasing worldwide. Obesity can be determined by body mass index (BMI); however waist circumference (WC) is a better measure of central obesity. This study evaluates the outcome of laparoscopic nephrectomy on patients with an abnormal WC. Methods. A WC of >88 cm for women and >102 cm for men was defined as obese. Data collected included age, gender, American Society of Anaesthesiologists (ASA) score, renal function, anaesthetic duration, surgery duration, blood loss, complications, and duration of hospital stay. Results. 144 patients were assessed; 73 (50.7%) of the patients had abnormal WC for their gender. There was no difference between the groups for conversion to open surgery, number of ports used, blood loss, and complications. Abnormal WC was associated with a longer median anaesthetic duration, 233 min, IQR (215-265) versus 204 min, IQR (190-210), p = 0.0022, and operative duration, 178 min, IQR (160-190) versus 137 min, IQR (128-162), p < 0.0001. Patients with an abnormal WC also had a longer inpatient stay, p = 0.0436. Conclusion. Laparoscopic nephrectomy is safe in obese patients. However, obese patients should be informed that their obesity prolongs the anaesthetic duration and duration of the surgery and is associated with a prolonged recovery.
Keyphrases
- body mass index
- obese patients
- weight loss
- weight gain
- robot assisted
- bariatric surgery
- minimally invasive
- metabolic syndrome
- insulin resistance
- type diabetes
- high fat diet induced
- roux en y gastric bypass
- end stage renal disease
- gastric bypass
- ejection fraction
- newly diagnosed
- risk factors
- coronary artery bypass
- chronic kidney disease
- adipose tissue
- mental health
- healthcare
- body weight
- surgical site infection
- emergency department
- polycystic ovary syndrome
- peritoneal dialysis
- coronary artery disease
- acute coronary syndrome
- artificial intelligence
- adverse drug
- deep learning
- machine learning
- editorial comment