Gynecologic Surgical Procedures, Perioperative Care, Risk Assessment
Conditions
Keywords
Gynecologic oncology surgery, Perioperative complications, Charlson comorbidity index, POSSUM, Mortality
Brief summary
With the global rates of gynecologic cancers on the rise, optimizing perioperative care is imperative. Accurate risk prediction is essential for enhancing patient care, directing preoperative interventions, and facilitating informed decision-making in oncology. This research compares two widely-used risk assessment tools: the Charlson Comorbidity Index (CCI) and the Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM), in predicting perioperative outcomes. The CCI predominantly addresses comorbidities, providing simplicity and broad applicability, while POSSUM incorporates both physiological and operative factors for a more comprehensive risk assessment. Despite their application across various surgical specialties, the specific utility of these tools in onco-gynecologic surgery remains insufficiently explored. The study aims to evaluate the effectiveness of CCI and POSSUM in predicting perioperative complications, with a focus on the incidence of these complications, length of hospital stay, and 30-day mortality. The implementation of these risk tools may enhance multidisciplinary risk management, thus improving patient outcomes in gynecologic oncology surgery.
Detailed description
Onco-gynecologic surgeries, including procedures for ovarian, cervical, uterine, and vulvar cancers, are complex and challenging due to both the technical intricacies of the surgeries and the often compromised health of cancer patients. These procedures carry significant perioperative risks, making optimization of perioperative care critical, especially as global cases of gynecological cancers rise, with millions affected annually. Accurate risk prediction is vital to improve patient outcomes, allowing surgeons and anesthesiologists to tailor preoperative interventions and intraoperative management. These strategies help in identifying high-risk patients, implementing enhanced monitoring, specific anesthetic techniques, or staged surgical approaches to mitigate potential complications. Two prominent risk assessment tools used in surgical practice are the Charlson Comorbidity Index (CCI) and the Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM). The CCI, is a weighted index that considers the number and severity of comorbid conditions to predict mortality risk. Its simplicity and reliance on readily available clinical information have led to its widespread adoption in clinical and research settings. Studies have validated its predictive value across various surgical populations, including oncology patients, although its specific utility in onco-gynecologic surgeries needs further exploration. In contrast, the POSSUM score offers a more comprehensive risk assessment by incorporating both physiological and operative factors. It includes preoperative variables like age and cardiac signs and considers operative factors like procedural complexity and blood loss. This dual approach provides a nuanced prediction of perioperative risk, useful across diverse surgical fields. Despite POSSUM's broad application, its effectiveness specifically in onco-gynecologic surgeries requires additional investigation to fully ascertain its predictive accuracy and utility. Currently, our center conducts preoperative evaluations involving anesthesiologists and gynecologists, yet formal risk assessments using CCI or POSSUM have not been implemented. Incorporating these tools could enhance multidisciplinary risk management, involving anesthetic teams, ward nurses, gynecologic oncologists, and intensivists. By systematically evaluating patient history, these indices can promote effective interdisciplinary communication, significantly improve patient safety, and optimize surgical outcomes. This study aims to compare CCI and POSSUM in predicting perioperative complications, including both anesthetic and surgical complications in onco-gynecologic surgery. Additionally, it seeks to report the incidence of complications, length of hospital stay, and 30-day mortality, providing valuable insights into optimizing patient care in this challenging field.
Interventions
OTHERCCI score
Charlson comorbidity index included age and medical conditions
OTHERPOSSUM score
POSSUM included physical status and laboratory investigation
Sponsors
Mahidol University
Study design
Observational model
CASE_ONLY
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
FEMALE
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Age \> 18 years * Patient underwent elective onco-gynecologic surgery
Exclusion criteria
* Patient required emergency surgery from any indication * Patient chart that not contained primary outcome data eg. absent of the anesthetic record
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Comparison of CCI and POSSUM to predict perioperative complications | from the date of starting surgery to the date of hospital discharge, up to 30 days | To compare the prediction of perioperative anesthetic and surgical morbidity by the Charlson-Comorbidity Index versus POSSUM score in patients undergoing elective onco-gynecological surgery |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Quantity of intraoperative blood loss | Within 24 hours from starting of surgery | Intraoperative blood loss estimated by anesthetic personnel |
| Rate of blood transfusion | Within 24 hours from starting of surgery | Intraoperative rate and amount of packed red cells blood transfusion and/or blood component |
| Rate of vasopressor usage | from the time staring of surgery to the time of finishing surgery, up to 12 hours | Intraoperative rate and amount of vasopressor usage |
| Clavian-Dindo classification of surgical complications | from the date of starting surgery to the date of hospital discharge, up to 30 days | Rate of surgical complications using Clavian-Dindo classification of surgical complications Grade 1 Treatment with simple medication Grade 2 Others medications from grade 1 Grade 3a Surgical intervention under local/regional anesthesia Grade 3b Surgical intervention under general anesthesia Grade 4a Need ICU with single organ dysfunction Grade 4b Need ICU with multiple organ dysfunction Grade 5 Death |
| ICU admission | within 24 hours postoperative | Rate of intensive care unit admission in the postoperative period |
| Intraoperative hypotension | Within 24 hours from starting of surgery | Intraoperative complications related to anesthesia: intraoperative hypotension |
| Myocardial infarction or myocardial injury | from the date of starting surgery to the date of hospital discharge, up to 30 days | Rate of postoperative myocardial infarction and myocardial injury after non-cardiac surgery (MINS)defines as an \>1 fold-elevated cTn (\>99th percentile of the upper reference limit) of presumed ischemic origin (excluding nonischemic etiologies such as pulmonary embolism, stroke, and sepsis) and is associated with adverse short- and long-term outcomes. (from the 2024 AHA/ACC/ACS/ASNC/HRS/SCA/ SCCT/SCMR/SVM Guideline for Perioperative Cardiovascular Management for Noncardiac Surgery: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines) |
| Acute kidney injury | from the date of starting surgery to the date of hospital discharge, up to 30 days | Rate of acute kidney injury which defined follow the KDIGO clinical practice guidelines for acute kidney injury 2020 |
| Postoperative pulmonary complications | from surgery from the date of starting surgery to the date of hospital discharge, up to 30 days | Rate of postoperative pulmonary complications which defined follow the European Perioperative clinical outcome (EPCO) definition for postoperative pulmonary complications |
| Mortality rate | From the day of surgery to 30 days post operation | 30-day mortality |
| Reoperation | within 24 hours postoperative | Rate of reoperation |
Countries
Thailand
Contacts
Primary ContactPatchareya Nivatpumin, M.D.
Backup ContactJitsupa Nithiuthai, M.D.
Outcome results
None listed