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

Prediction Models for Perioperative Blood Transfusion in Patients Undergoing Gynecologic Surgery: A Systematic Review

This systematic review aimed to evaluate prediction models for perioperative blood transfusion in patients undergoing gynecologic surgery. Given the inherent risks associated with blood transfusion and the critical need for accurate prediction, this study identified and assessed models based on their development, validation, and predictive performance. The review included five studies encompassing various surgical procedures and approaches. Predicting factors commonly used across these models included preoperative hematocrit, race, surgical route, and uterine fibroid characteristics. However, the review highlighted significant variability in the definition of perioperative periods, a lack of standardization in transfusion criteria, and a high risk of bias in most models due to methodological issues, such as a low number of events per variable, inappropriate handling of continuous and categorical predictors, inappropriate handling of missing data, improper methods of predictor selection, inappropriate measurement methods for model performance, and inadequate evaluations of model overfitting and optimism in model performance. Despite some models demonstrating good discrimination and calibration, the overall quality and external validation of these models were limited. Consequently, there is a clear need for more robust and externally validated models to improve clinical decision-making and patient outcomes in gynecologic surgery. Future research should focus on refining these models, incorporating rigorous validation, and adhering to standardized reporting practices.

Characteristics associated with blood transfusion among women undergoing laparoscopic myomectomy: a National Surgical Quality Improvement Program study

BACKGROUND

Uterine fibroids are the most common benign tumors that affect females. A laparoscopic myomectomy is the standard surgical treatment for most women who wish to retain their uterus. The most common complication of a myomectomy is excessive bleeding. However, risk factors for hemorrhage during a laparoscopic myomectomy are not well studied and no risk stratification tool specific for identifying the need for a blood transfusion during a laparoscopic myomectomy currently exists in the literature.

OBJECTIVE

This study aimed to identify risk factors for intraoperative and postoperative blood transfusion during laparoscopic myomectomies and to develop a risk stratification tool to determine the risk for requiring a blood transfusion.

STUDY DESIGN

This was a retrospective cohort study of the American College of Surgeons National Surgical Quality Improvement Program database from 2012 to 2020. Women who underwent a laparoscopic (conventional or robotic) myomectomy were included. Women who received 1 or more blood transfusions within 72 hours after the start time of a laparoscopic myomectomy were compared with those who did not require a blood transfusion. A multivariable analysis was performed to identify risk factors independently associated with the risk for transfusion. Two risk stratification tools to determine the need for a blood transfusion were developed based on the multivariable results, namely (1) based on preoperative factors and (2) based on preoperative and intraoperative factors.

RESULTS

During the study period, 11,498 women underwent a laparoscopic myomectomy. Of these, 331(2.9%) required a transfusion. In a multivariable regression analysis of the preoperative factors, Black or African American and Asian races, Hispanic ethnicity, bleeding disorders, American Society of Anesthesiologists class III or IV classification, and a preoperative hematocrit value ≤35.0% were independently associated with the risk for transfusion. Identified intraoperative factors included specimen weight >250 g or ≥5 intramural myomas and an operation time of ≥197 minutes. A risk stratification tool was developed in which points are assigned based on the identified risk factors. The mean probability of transfusion can be calculated based on the sum of the points.

CONCLUSION

We identified preoperative and intraoperative independent risk factors for a blood transfusion among women who underwent a laparoscopic myomectomy. A risk stratification tool to determine the risk for requiring a blood transfusion was developed based on the identified risk factors. Further studies are needed to validate this tool.

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

OBJECTIVE

The objective of the study was to develop a clinically applicable prediction tool to early seek for postoperative major complications after laparoscopic surgery for benign pathologies.

DESIGN

Retrospective analysis of prospectively collected data was performed.

SETTING

The study was conducted at Tertiary Care University Hospital.

PARTICIPANTS

The participants of this study were reproductive-aged women undergoing laparoscopy for benign conditions.

METHODS

Anamnestic, intraoperative, and postoperative characteristics from January 2019 to December 2021 were retrospectively reviewed. Patients with postoperative complications (reintervention or postoperative bleeding) were matched in a 1:2 ratio with women with same surgical indications without complications. Cases and controls were matched for preoperative hemoglobin, hematocrit, weight, height, body mass index, age, and blood volume. A prediction model was created by inserting multiple independent modifying factors through logistic regression. The receiver operating characteristic (ROC) curve was used to evaluate the predictive accuracy of the model, and the Hosmer-Lemeshow (H-L) test was carried out to evaluate the goodness-of-fit, and a calibration curve was drawn to confirm the predictive performance. A nomogram was depicted to visualize the prediction model.

RESULTS

Thirty-nine complicated procedures were matched with 78 uncomplicated controls. According to the multivariate logistic regression analysis findings, the prediction model was developed using C-reactive protein (CRP), intraoperative blood loss, and 24 h postoperative urinary volume, therefore a nomogram was generated. The area under the ROC curve of the prediction model was 0.879, depicting good accuracy, the sensitivity was 60.00%, while specificity reached 93.59%. The H-L test (χ2 = 4.45, p = 0.931) and the calibration curve indicated a good goodness-of-fit and prediction stability.

LIMITATIONS

The retrospective design, moderate sensitivity, and study population limit the generalization of the findings, requiring additional research.

CONCLUSIONS

This prediction model based on CRP, intraoperative blood loss, and 24 h postoperative urinary volume might be a potentially useful tool for predicting reintervention and postoperative bleeding in patients undergoing planned gynecological laparoscopy.

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

The objective of this work was to predict the risk of mortality rate in patients with coronary artery bypass grafting (CABG) based on the risk prediction model of CABG using artificial intelligence (AI) and big data technologies. The clinical data of 2,364 patients undergoing CABG in our hospital from January 2019 to August 2021 were collected in this work. Based on AI and big data technology, business requirement analysis, system requirement analysis, complication prediction module, big data mining technology, and model building are carried out, respectively; the successful CABG risk prediction system includes case feature analysis service, risk warning service, and case retrieval service. The commonly used precision, recall, and F1-score were adopted to evaluate the quality of the gradient-boosted tree (GBT) model. The analysis proved that the GBT model was the best in terms of precision, F1-score, and area under the receiver operating characteristic curve (ROC). According to the CABG risk prediction model, 1,382 patients had a score of <0, 463 patients had a score of 0 ≤ score ≤ 2, 252 patients had a score of 2 < score ≤ 5, and 267 patients had a score of >5, which were stratified into four groups: A, B, C, and D. The actual number of in-hospital deaths was 25, and the in-hospital mortality rate was 1.05%. The mortality rate predicted by the CABG risk prediction model was 2.67 ± 1.82% (95% confidential interval (CI) (2.87-2.98)), which was higher than the actual value. The CABG risk prediction model showed the credible results only in group B with AUC = 0.763 > 0.7. In group B, 3 patients actually died, the actual mortality rate was 0.33%, and the predicted mortality rate was 0.96 ± 0.78 (95% CI (0.82-0.87)), which overestimated the mortality rate of patients in group B. It successfully constructed a CABG risk prediction model based on the AI and big data technologies, which would overestimate the mortality of patients with intermediate risk, and it is suitable for different types of heart diseases through continuous research and development and innovation, and provides clinical guidance value.

Systematic review highlights high risk of bias of clinical prediction models for blood transfusion in patients undergoing elective surgery

BACKGROUND

Blood transfusion can be a lifesaving intervention after perioperative blood loss. Many prediction models have been developed to identify patients most likely to require blood transfusion during elective surgery, but it is unclear whether any are suitable for clinical practice.

STUDY DESIGN AND SETTING

We conducted a systematic review, searching MEDLINE, Embase, PubMed, The Cochrane Library, Transfusion Evidence Library, Scopus, and Web of Science databases for studies reporting the development or validation of a blood transfusion prediction model in elective surgery patients between January 1, 2000 and June 30, 2021. We extracted study characteristics, discrimination performance (c-statistics) of final models, and data, which we used to perform risk of bias assessment using the Prediction model risk of bias assessment tool (PROBAST).

RESULTS

We reviewed 66 studies (72 developed and 48 externally validated models). Pooled c-statistics of externally validated models ranged from 0.67 to 0.78. Most developed and validated models were at high risk of bias due to handling of predictors, validation methods, and too small sample sizes.

CONCLUSION

Most blood transfusion prediction models are at high risk of bias and suffer from poor reporting and methodological quality, which must be addressed before they can be safely used in clinical practice.

Preoperative Hematocrit Level and Associated Risk of Transfusion for Myomectomy Based on Myoma Burden and Surgical Route

STUDY OBJECTIVE

To determine the association between preoperative hematocrit level and risk of blood transfusion for laparotomic and laparoscopic myomectomy based on myoma burden and surgical route.

DESIGN

A cohort study of prospectively collected data.

SETTING

American College of Surgeons National Surgical Quality Improvement Program participating institutions.

PATIENTS

A total of 26 229 women who underwent a laparotomic or laparoscopic myomectomy from 2010 to 2020.

INTERVENTIONS

The primary outcome assessed was the risk of transfusion based on preoperative hematocrit level. This was evaluated with respect to myoma burden and surgical route.

MEASUREMENTS AND MAIN RESULTS

There were 26 229 women who underwent a myomectomy during the study interval, 2345 women (9%) of whom required a blood transfusion. Compared with patients who did not require transfusion, those who did had lower median preoperative hematocrit levels (34.7 vs 38.2). Patients were stratified by surgical approach (laparotomic vs laparoscopic) and myoma burden (1-4 myomas/weight ≤250 g or ≥5 myomas/weight >250 g) using Current Procedural Terminology codes (58140, 58146, 58545, 58546). In all categories, there was an inverse relationship between blood transfusion and preoperative hematocrit level with increasing risk depending on preoperative hematocrit range. The odds ratios comparing hematocrit level of 29% with 39% were 6.16 (95% confidence interval [CI], 5.15-7.36), 4.92 (95% CI, 4.19-5.78), 4.85 (95% CI, 3.72-6.33), and 5.2 (95% CI, 3.63-7.43) for patients with laparotomic (1-4 myomas/≤250 g, ≥5 myomas/>250 g) and laparoscopic myomectomy (1-4 myomas/≤250 g, 5 myomas/>250 g), respectively.

CONCLUSION

Incremental increases in hematocrit result in a significantly decreased risk of blood transfusion at the time of myomectomy.

Safety of Same-Day Discharge Versus Hospital Admission in Minimally Invasive Myomectomy

STUDY OBJECTIVE

To compare postoperative complication rates between same-day discharge patients and patients admitted to hospital after minimally invasive myomectomy, stratified by patient demographics and perioperative variables including myoma burden.

DESIGN

Retrospective cohort study. Setting Hospitals participating in the National Surgical Quality Improvement Program database from January 2015 to December 2019.

PATIENTS

Female patients aged ≥18 years undergoing minimally invasive myomectomy.

INTERVENTIONS

Patients were categorized into either the same-day discharge or admitted patient cohort. Univariate comparisons of demographics, perioperative variables, and 30-day postoperative complications were performed. Multivariate logistic regression was used to 1) identify demographic and perioperative factors associated with admission, and 2) compare postoperative complication rates of same-day discharge patients with those of admitted patients while adjusting for demographic and perioperative factors.

MEASUREMENTS AND MAIN RESULTS

Eight thousand one hundred patients were recruited during the study period. The overall rate of same-day discharge was 57.2% in 2015 and 65.0% in 2019. The same-day discharge rate was 64.6% for patients with a smaller myoma burden (1-4 fibroids and ≤250 grams, Current Procedural Terminology 58545) and 56.8% for larger myoma burden (≥5 fibroids or >250 grams, Current Procedural Terminology 58546). Age, race, American Society of Anesthesiologists classification III or IV, preoperative hematocrit <36%, hypertension, diabetes, bleeding disorder, and increasing operative time were associated with admission to hospital. After adjusting for these variables, composite postoperative complication rates were similar between admitted patients and patients who were discharged the same day regardless of myoma burden (adjusted OR [aOR], 0.66; 95% confidence interval [CI] 0.18-2.47 for low myoma burden and aOR, 0.91; 95% CI 0.18-4.63 for high myoma burden). Admitted patients with both low (aOR, 9.1; 95% CI 2.27-37.04) and high (aOR, 8.24; 95% CI 1.59-42.49) myoma burdens were significantly more likely to receive a blood transfusion compared to same-day discharge patients.

CONCLUSION

Same-day discharge after minimally invasive myomectomy, regardless of myoma burden, is associated with low complication rates. Our findings may aid in shared decision making on discharge planning.

How to minimize bleeding in laparoscopic myomectomy

PURPOSE OF REVIEW

Laparoscopic myomectomy is a common surgical procedure for symptomatic myomas. However, bleeding control during surgery may pose a challenge. Therefore, the aim of this study was to review recent evidence regarding interventions to control bleeding during laparoscopic myomectomy.

RECENT FINDINGS

The use of vasopressin resulted in less blood loss compared to placebo. Barbed sutures reduced blood loss compared to conventional sutures. Intravenous infusion of tranexamic acid (TXA) in the intraoperative period of large myomectomies showed no significant difference compared to placebo. Uterine artery occlusion (UAO) and emergency uterine artery embolization were reported to be feasible and may reduce and treat bleeding before conversion to laparotomy.

SUMMARY

Several methods can control bleeding during laparoscopic myomectomy. Vasopressin and barbed sutures resulted in decreased blood loss, and TXA did not have an impact on bleeding control. The use of UAO and emergency embolization techniques can contribute to the control of bleeding; however, further studies are needed to prove the efficacy of these and other agents.