A Clinically Applicable Prediction Model for the Risk of Transfusion in Women Undergoing Myomectomy

Abstract

We sought to identify the variables independently associated with intra/postoperative blood transfusion at the time of myomectomy. We further hoped to develop an accurate prediction model using preoperative variables to categorize an individual's risk of blood transfusion during myomectomy. Design: Case-control study. Setting: Not applicable to this study, which used the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database. Patients: Women who underwent an open/abdominal or laparoscopic (robotic or conventional) myomectomy between 2014 and 2017 at participating ACS-NSQIP sites. Intervention: The primary dependent variable was occurrence of intra/postoperative bleeding requiring blood transfusion. Patient demographics, clinical characteristics, preoperative comorbidities, intraoperative variables, and additional 30-day postoperative outcomes were compared at the bivariable level. For the prediction-model development, only variables that can be reasonably known before surgery were included. Variables associated with intra/postoperative bleeding were entered into 2 separate multivariable logistic regression models. Validation of our prediction model was performed internally using 250 bootstrapped iterations of 50% subsamples drawn from the overall population of myomectomy cases from the ACS-NSQIP database. Measurements and Main Results: We identified 6387 myomectomies performed during the defined study period. The most common race in our population was black/African American (45.7%), and most of the patients (57.5%) received an open/abdominal route of myomectomy. A total of 623 patients who underwent myomectomy (9.8%) experienced intraoperative/postoperative bleeding with a need for blood transfusion. At the bivariable level, we identified several variables independently associated with the need for blood transfusion at the time of myomectomy. In using only those variables that can be reasonably known before surgery to develop our prediction model, additional multivariable logistic regression elucidated black race, need for preoperative blood transfusion, planned abdominal/open route of surgery, and preoperative hematocrit value as independently associated with blood transfusion. Conclusion:We identified a number of perioperative variables associated with intraoperative or postoperative bleeding requiring blood transfusion at the time of myomectomy. We subsequently created a model that accurately predicts individual bleeding risk from myomectomy, using variables that are reasonably apparent preoperatively. Making this prediction model clinically available to gynecologic surgeons will serve to improve the care of women undergoing myomectomy. Journal of Minimally Invasive Gynecology (2021) 00, 1−9.

Risk of Reintervention or Postoperative Bleeding after Laparoscopy for Benign Gynecological Disease: A Clinical Prediction Model

“…This study showed that a prediction model based on intraoperative blood loss, CRP, and urinary volume 24 h after surgery has a good accuracy to predict complications (reintervention and moderate/high postoperative blood loss) in women undergoing laparoscopic surgery for benign gynecological pathologies. Several authors have tried to define a risk model for gynecological procedures [16][17][18]. Pepin et al [18] described a model for laparoscopic hysterectomy for benign conditions based on race, history of laparotomy, history of laparoscopy, predicted preoperative uterine weight, BMI, and surgeon annual case volume.…”

“…Klebanoff et al [17] formulated a predictive model to estimate the risk of blood transfusion due to intraoperative or postoperative bleeding, showing that ethnicity, surgical approach, and intraoperative blood loss are factors showing a considerable risk for requiring blood transfusion after open or laparoscopic myomectomy. Similarly, Delli Carpini et al [16], analyzing factors associated with complicated myomectomies, emphasized the value of presurgical evaluation in identifying variables that can predict intraoperative blood loss and Hb drop, such as the number of fibroids and International Federation of Gynecology and Obstetrics (FIGO) classification (at preoperative ultrasound assessment), as well as intraoperative factors such as operating time and the intramyometrial injection of diluted epinephrine.…”

Artificial Intelligence and Big Data Technologies in the Construction of Surgical Risk Prediction Model for Patients with Coronary Artery Bypass Grafting

“…Te data acquisition module of the system was connected with the big data integration platform of the hospital. Te data acquisition module collected the business data of risk factors in real time, and then used the data processing module to fnally summarize and save the data to the complication database [20][21][22]. Te patient management interface includes name, gender, treatment type, treatment department, treatment date, and risk assessment results, as shown in Figure 4.…”

How to minimize bleeding in laparoscopic myomectomy

“…The most common complication is myomectomy-associated bleeding. Studies report blood transfusion rates between 4 and 20% [1,3] of patients who underwent myomectomy. Several techniques have been developed to prevent bleeding during open myomectomies: uterine artery temporary ligation, intra-myoma infiltration of vasopressin, intravaginal misoprostol or dinoprostone, the use of pro-fibrin/thrombin agents, or the use of tourniquet around the cervix or infundibulum-pelvic ligaments [4,5].…”