Literature DB >> 19758690

Clinical audit in gynecological cancer surgery: development of a risk scoring system to predict adverse events.

Srinivas Kondalsamy-Chennakesavan1, Chantal Bouman, Suzanne De Jong, Karen Sanday, Jim Nicklin, Russell Land, Andreas Obermair.   

Abstract

BACKGROUND: Advanced gynecological surgery undertaken in a specialized gynecologic oncology unit may be associated with significant perioperative morbidity. Validated risk prediction models are available for general surgical specialties but currently not for gynecological cancer surgery.
OBJECTIVE: The objective of this study was to evaluate risk factors for adverse events (AEs) of patients treated for suspected or proven gynecological cancer and to develop a clinical risk score (RS) to predict such AEs.
METHODS: AEs were prospectively recorded and matched with demographical, clinical and histopathological data on 369 patients who had an abdominal or laparoscopic procedure for proven or suspected gynecological cancer at a tertiary gynecological cancer center. Stepwise multiple logistic regression was used to determine the best predictors of AEs. For the risk score (RS), the coefficients from the model were scaled using a factor of 2 and rounded to the nearest integer to derive the risk points. Sum of all the risk points form the RS.
RESULTS: Ninety-five patients (25.8%) had at least one AE. Twenty-nine (7.9%) and 77 (20.9%) patients experienced intra- and postoperative AEs respectively with 11 patients (3.0%) experiencing both. The independent predictors for any AE were complexity of the surgical procedure, elevated SGOT (serum glutamic oxaloacetic transaminase, > or /=35 U/L), higher ASA scores and overweight. The risk score can vary from 0 to 14. The risk for developing any AE is described by the formula 100 / (1 + e((3.697 - (RS /2)))).
CONCLUSION: RS allows for quantification of the risk for AEs. Risk factors are generally not modifiable with the possible exception of obesity.

Entities:  

Mesh:

Year:  2009        PMID: 19758690     DOI: 10.1016/j.ygyno.2009.08.004

Source DB:  PubMed          Journal:  Gynecol Oncol        ISSN: 0090-8258            Impact factor:   5.482


  9 in total

1.  Risk factors for prolonged hospitalization after gynecologic laparoscopic surgery.

Authors:  Behrouz Zand; Michael Frumovitz; Matias F Jofre; Alpa M Nick; Ricardo Dos Reis; Mark F Munsell; Haleh Sangi-Haghpeykar; Charles Levenback; Pamela T Soliman; Kathleen M Schmeler; Pedro T Ramirez
Journal:  Gynecol Oncol       Date:  2012-06-02       Impact factor: 5.482

2.  Comparison of Costs of Radical Cystectomy vs Trimodal Therapy for Patients With Localized Muscle-Invasive Bladder Cancer.

Authors:  Stephen B Williams; Yong Shan; Mohamed D Ray-Zack; Hogan K Hudgins; Usama Jazzar; Douglas S Tyler; Stephen J Freedland; Todd A Swanson; Jacques G Baillargeon; Jim C Hu; Sapna Kaul; Ashish M Kamat; John L Gore; Hemalkumar B Mehta
Journal:  JAMA Surg       Date:  2019-08-21       Impact factor: 14.766

3.  Prediction model for 30-day morbidity after gynecological malignancy surgery.

Authors:  Seung-Hyuk Shim; Sun Joo Lee; Meari Dong; Jung Hwa Suh; Seo Yeon Kim; Ji Hye Lee; Soo-Nyung Kim; Soon-Beom Kang; Jayoun Kim
Journal:  PLoS One       Date:  2017-06-01       Impact factor: 3.240

4.  Fertility-sparing treatment in early endometrial cancer: current state and future strategies.

Authors:  Andreas Obermair; Eva Baxter; Donal J Brennan; Jessica N McAlpine; Jennifer J Muellerer; Frédéric Amant; Mignon D J M van Gent; Robert L Coleman; Shannon N Westin; Melinda S Yates; Camilla Krakstad; Monika Janda
Journal:  Obstet Gynecol Sci       Date:  2020-07-08

5.  Predictors of complications in gynaecological oncological surgery: a prospective multicentre study (UKGOSOC-UK gynaecological oncology surgical outcomes and complications).

Authors:  R Iyer; A Gentry-Maharaj; A Nordin; M Burnell; R Liston; R Manchanda; N Das; R Desai; R Gornall; A Beardmore-Gray; J Nevin; K Hillaby; S Leeson; A Linder; A Lopes; D Meechan; T Mould; S Varkey; A Olaitan; B Rufford; A Ryan; S Shanbhag; A Thackeray; N Wood; K Reynolds; U Menon
Journal:  Br J Cancer       Date:  2014-12-23       Impact factor: 7.640

6.  Application of gene expression programming and neural networks to predict adverse events of radical hysterectomy in cervical cancer patients.

Authors:  Maciej Kusy; Bogdan Obrzut; Jacek Kluska
Journal:  Med Biol Eng Comput       Date:  2013-10-18       Impact factor: 2.602

7.  Prediction of perioperative complications after robotic-assisted radical hysterectomy for cervical cancer using the modified surgical Apgar score.

Authors:  Seon Hee Park; Jung-Yun Lee; Eun Ji Nam; Sunghoon Kim; Sang Wun Kim; Young Tae Kim
Journal:  BMC Cancer       Date:  2018-09-21       Impact factor: 4.430

8.  Can Surgical Apgar Score (SAS) Predict Postoperative Complications in Patients Undergoing Gynecologic Oncological Surgery?

Authors:  Geetu Bhandoria; Jitendra D Mane
Journal:  Indian J Surg Oncol       Date:  2019-11-07

9.  ECOG and BMI as preoperative risk factors for severe postoperative complications in ovarian cancer patients: results of a prospective study (RISC-GYN-trial).

Authors:  Melisa Guelhan Inci; Julia Rasch; Hannah Woopen; Kristina Mueller; Rolf Richter; Jalid Sehouli
Journal:  Arch Gynecol Obstet       Date:  2021-06-24       Impact factor: 2.344

  9 in total

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