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Obstetrics & Gynecology 2001;97:721-724
© 2001 by The American College of Obstetricians and Gynecologists
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ORIGINAL RESEARCH

Predictors of Complications and Hospital Stay in Gynecologic Cancer Surgery

MARC M. DEAN, MD, MICHAEL A. FINAN, MD and RICHARD C. KLINE, MD

From the Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Ochsner Clinic and Alton Ochsner Medical Foundation, New Orleans, Louisiana.

Address reprint requests to: Michael A. Finan, MD Ochsner Clinic 1514 Jefferson Highway New Orleans, LA 70121 E-mail: mfinan{at}ochsner.org


   Abstract
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Abstract
Materials and Methods
 Results
 Discussion
 References
 
Objective: To test the hypothesis that comorbid medical conditions can predict length of hospital stay and incidence of postoperative complications.

Methods: We reviewed the medical records of 187 women who had surgery for known or suspected gynecologic malignancies during 1996 and 1997, and 179 were included in the present study. Information on each woman’s comorbid medical conditions, surgical history, surgicopathologic cancer diagnosis, American Society of Anesthesiologists’ classification, surgical procedures, and postoperative complications was collected and analyzed.

Results: Women with two or more comorbid medical conditions had significantly longer mean hospital stays (8.62 days) than those with none or one comorbid medical condition (6.43 days) (P < .001). Women with two or more postoperative complications had significantly longer mean hospital stays (11.88 days) than those with none or one complication (6.02 days) (P < .001). Women with two or more postoperative complications also had significantly more comorbid medical conditions (mean 2.5) than those with none or one complication (mean 1.7) (P < .001). The American Society of Anesthesiologists class also was a significant predictor of postoperative complications and length of hospitalization. Age over 60 years also was associated with statistically significant increase in comorbid medical conditions and significantly longer hospitalizations.

Conclusion: Our findings indicated that certain high-risk patients can be identified before hospital admission based on comorbid medical conditions. Certain risk indices, such as the American Society of Anesthesiologists classification score, also can predict postoperative complications and length of hospital stay. This information can be used to coordinate preoperative and postoperative hospital care and be a reference for certain future disease management systems.

For many years staging systems for gynecologic cancers have been valuable for determining prognoses and survival rates. Each classification system uses many anatomic criteria. An individual’s comorbid medical conditions largely have been ignored among those classification systems. During the past few years, several studies of comorbid medical conditions or symptomatology as indicators of survival and morbidity in prostate cancer,1,2 cervical cancer,3 and breast cancer4,5 have been published. A review by Piccirillo and Feinstein6 suggested that in certain cancers, such as lung, larynx, prostate, and rectal, the tumor-node-metastasis cancer staging system alone is imprecise for prognostic estimates and that symptoms and comorbidities could improve accuracy.

No study to date focused on the relationship between gynecologic oncology surgical patients, comorbid conditions, and influence on postoperative complications, and length of hospital stay. Such a relationship could be valuable for identifying high-risk patients who might need lengthy hospitalizations or tertiary care. Our hypothesis was that comorbid medical conditions can predict length of hospital stay and number of complications. By identifying those patients, gynecologists can coordinate high-risk patients’ hospital care with primary care physicians, rehabilitation services, nursing personnel, and intensive care specialists.

We also were interested in learning whether a preoperative risk index could be used to determine which gynecologic oncology patients were at high risk of postoperative complications and lengthy hospitalizations. We selected the American Society of Anesthesiologists’ classification system because it is a well-established risk assessment tool that has been used since the 1940s to evaluate surgical patients,7–9 is an established part of the operative record, and is always used with patients who have surgery at our hospital. However, the American Society of Anesthesiologists’ classification system mainly focuses on risk of perioperative death and on predicting primary anesthetic death, whereas we wanted to know whether that system can predict postoperative complications and length of hospital stay.


   Materials and Methods
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Abstract
 Materials and Methods
Results
 Discussion
 References
 
The study included all women who had surgery for gynecologic malignancies from January 1, 1996 until December 31, 1997. One hundred eighty-seven women had invasive cancer; and eight were excluded because of incomplete medical records. The medical records of the remaining 179 women were extracted and reviewed. Data were recorded on a specifically designed data form. Admission comorbid medical conditions, surgical histories, and histories of radiation or chemotherapy were recorded, as was age, race, smoking and alcohol usage history, and admission height and weight. For each surgical admission we also recorded surgical procedures done, surgicopathologic diagnosis, American Society of Anesthesiologists classification, length of hospital stay in days, and postoperative complications.

Comorbid medical conditions were defined as those that existed at the time of surgical admission. Any condition that developed during hospitalization after surgery was classified as a postoperative complication and not included as a comorbid medical condition. To keep classification simple, comorbid conditions were not differentiated by severity; each condition was counted as one comorbid condition. For example, a woman’s comorbid conditions included hypertension, type II diabetes, and high cholesterol; another woman’s comorbid condition was history of arthritis. The first woman had three comorbid conditions, and the second only had one. Length of hospital stay was calculated in days, using day of admission as hospital day 1. American Society of Anesthesiologists classifications were taken from the operative record in accordance with guidelines of the American Society of Anesthesiologists.8,9 Postoperative complications were not differentiated by severity; each complication was counted individually.

Statistical analysis was done with SPSS 9.0 (SPSS Inc., Chicago, IL). Categoric variables were analyzed using {chi}2, and means were compared using independent t test or analysis of variance when appropriate. Multivariate logistic regression analysis was used to delineate independent predictors of hospital stay and postoperative complications. P < .05 was considered statistically significant.


   Results
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Abstract
 Materials and Methods
 Results
Discussion
 References
 
Table 1Go shows descriptive data. The median American Society of Anesthesiologists class for the study group was 2 (range 1–4). One hundred ninety-six postoperative complications occurred in the study group (mean 1.09 ± 1.18). The most common were blood transfusion (n = 45, 23.0%), ileus or small bowel obstruction (n = 45, 23.0%), infections (n = 39, 19.9%), and febrile illness that did not require antibiotics (n = 26, 13.3%). Cancer was diagnosed in 179 women. Specific types are listed in Table 1Go. A total of 472 surgical procedures were done on the study population.


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  		Table 1. Clinical Characteristics
 
The mean length of hospital stay was 7.59 ± 4.21 days (Table 2Go). Women who had one or no comorbid medical conditions had a mean length of hospital stay of 6.43 days, whereas those who had two or more had a mean hospital stay of 8.62 days (P < .001). The number of comorbid conditions was also associated with incidence of postoperative complications (Table 3Go). Women who had zero or one postoperative complication had a mean of 1.69 comorbid medical conditions. Women who had two or more postoperative complications had a mean of 2.50 comorbid medical conditions (P < .001).


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  		Table 2. Comorbid Conditions and Duration of Hospitalization
 

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  		Table 3. Postoperative Complications and Comorbid Conditions
 
There was a statistically significant difference in duration of hospitalization for women with two or more postoperative complications (11.88 days) compared with those with zero to one postoperative complication (6.02 days) (P < .001). Duration of hospitalization and number of postoperative complications was greater with higher American Society of Anesthesiologists class. For American Society of Anesthesiologists class 1 women, the mean length of hospitalization was 5.52 days and the mean number of postoperative complications was 0.32. American Society of Anesthesiologists class 4 women had a mean length of hospitalization of 9.80 days and mean number of postoperative complications of 2.00 (P = .013 and P < .001, respectively) (Table 4Go).


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  		Table 4. American Society of Anesthesiologists Class: Hospitalization and Postoperative Complications
 
Age over 60 years was associated with significantly longer hospitalizations (8.18 days) compared with women 60 years and younger (6.92 days) (P = .045) (Table 5Go). Multivariate logistic regression analysis found that age over 60 years (odds ratio [OR] 2.16, 95% confidence interval [CI] 1.18, 3.93) and two or more comorbid medical conditions (OR 3.00, 95% CI 1.63, 5.53) were independent predictors of hospital stay of 7 days or more (P < .001). Having two or more comorbid medical conditions (OR 2.45, 95% CI 1.22, 4.93) also was an independent predictor of having two or more postoperative complications.


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  		Table 5. Patient Age: Hospitalization and Comorbid Conditions
 

   Discussion
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Abstract
 Materials and Methods
 Results
 Discussion
References
 
We found that the number of comorbid medical conditions can predict length of hospitalization and frequency of postoperative complications. It was not surprising that women with more comorbid medical conditions had longer hospitalizations. There was a difference between having no or only one comorbid condition and having two or more comorbid conditions. That same relationship also was found in the postoperative complication rate. As expected, women with two or more postoperative complications had significantly longer hospitalizations than those with zero or one postoperative complication. Among 48 women with two or more postoperative complications, the only independent predictors of longer hospitalization were age over 60 years and more preexisting comorbid medical conditions. We decided to use the number of comorbid conditions because it was simple and easily assessed. It has universal application and can be readily understood by insurance companies and review personnel.

The American Society of Anesthesiologists classification system also was a good predictor of length of hospitalization and incidence of postoperative complications. Other studies evaluated its usefulness for predicting outcomes such as perioperative death10 or anesthetic death,7,11 with mixed results. That classification system, as an indicator of hospitalization and complications, gives surgeons another preoperative risk assessment tool that is easy to understand and use, and indicates that preoperative risk indices can predict who is at high risk for surgical complications and lengthy hospitalizations. In further research we should design a system to rate gynecologic oncology surgical patients at admission, similar to scoring systems such as the Acute Physiology and Chronic Health Evaluation II,12 which were created to evaluate patients on admission to intensive care units.

Our finding of greater length of hospitalization and higher incidence of comorbid medical conditions for women over age 60 years agreed with results of previous studies.13 Physicians who practice in community hospitals or rural areas also can use this system to evaluate patients and decide on determination for consultation or referral. Solid data on certain high-risk surgical patients and lengths of hospitalizations also can be used in certain disease management systems being created by insurance companies and other health care providers.


   Footnotes
 
PII S0029-7844(00)01198-4

Received April 28, 2000. Received in revised form November 27, 2000. Accepted December 7, 2000.


   References
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Abstract
 Materials and Methods
 Results
 Discussion
 References
 
1. Albertsen PC, Fryback DG, Storer BE, Kolon TF, Fine J. The impact of co-morbidity on life expectancy among men with localized prostate cancer. J Urol 1996;156:127–32.[Medline]

2. Fowler JE Jr, Terrell FL, Renfroe DL. Co-morbidities and survival of men with localized prostate cancer treated with surgery or radiation therapy. J Urol 1996;156:1714–8.[Medline]

3. Peipert JF, Wells CK, Schwartz PE, Feinstein AR. Prognostic value of clinical variables in invasive cervical cancer. Obstet Gynecol 1994;84:746–51.[Abstract/Free Full Text]

4. Satariano WA, Ragland DR. The effect of comorbidity on 3-year survival of women with primary breast cancer. Ann Intern Med 1994;120:104–10.[Abstract/Free Full Text]

5. West DW, Satariano WA, Ragland DR, Hiatt RA. Comorbidity and breast cancer survival: A comparison between black and white women. Ann Epidemiol 1996;6:413–9.[Medline]

6. Piccirillo JF, Feinstein AR. Clinical symptoms and comorbidity: Significance for the prognostic classification of cancer. Cancer 1996;77:834–42.[Medline]

7. Dripps RD, Lamont A, Eckenhoff JE. The role of anesthesia in surgical mortality. JAMA 1961;178:261–66.

8. Owens WD, Felts JA, Spitznagel EL Jr. ASA physical status classifications: A study of consistency of ratings. Anesthesiology 1978;49:239–43.[Medline]

9. Saklad M. Grading of patients for surgical procedures. Anesthesia 1941;2:281–84.

10. Farrow SC, Fowkes FGR, Lunn JN, Robertson IB, Samuel P. Epidemiology in anaesthesia. II: Factors affecting mortality in hospital. Br J Anaesth 1982;54:811–7.[Abstract/Free Full Text]

11. Goldstein A Jr, Keats AS. The risk of anesthesia. Anesthesiology 1970;33:130–43.[Medline]

12. Van Le L, Fakhry S, Walton LA, Moore DH, Fowler WC, Rutledge R. Use of the APACHE II scoring system to determine mortality of gynecologic oncology patients in the intensive care unit. Obstet Gynecol 1995;85:53–5.[Abstract]

13. Yancik R, Havlik RJ, Wesley MN, Ries L, Lovy S, Rossi WK, et al. Cancer and comorbidity in older patients: A descriptive profile. Ann Epidemiol 1996;6:399–412.[Medline]




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