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Ann Thorac Surg 1998;66:220-224
© 1998 The Society of Thoracic Surgeons

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Original articles: general thoracic

Predictive respiratory complication quotient predicts pulmonary complications in thoracic surgical patients

^a Department of Anesthesiology and Critical Care Medicine, Memorial Sloan-Kettering Cancer Center, New York, New York, USA

Accepted for publication February 19, 1998.

Address reprint requests to Dr Melendez, Department of Anesthesiology and Critical Care Medicine, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10021
e-mail: (melendej{at}mskcc.org)

	Abstract

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 
Background. This study was designed to develop an accurate preoperative index of prediction of outcome and hospital charges after lung resection with standard available pulmonary tests in a tertiary cancer center.

Methods. Sixty-one consecutive patients undergoing pulmonary resections were evaluated. All patients underwent spirometry, carbon monoxide diffusion capacity, split lung function testing, and room air blood gas analysis at rest and after a 2-minute step climb. The thoracic prospective data base and patient charts were reviewed for length of hospitalization, postoperative length of stay, and complications requiring therapy. Logistic regression analysis of the preoperative data, operation and postoperative outcome was used to develop a new postoperative predictive index: the predictive respiratory complication quotient (PRQ). We describe the design of the equation for the probability of serious pulmonary complications, hospital stay, and hospital charges based on PRQ.

Results. Ten of 12 patients with a PRQ less than 2,200 suffered serious pulmonary complications of pneumonia, respiratory insufficiency, hypoxemia, and death. Forty-nine patients with a PRQ more than 2,200 did not experience any pulmonary complications. Postoperative length of stay and hospital charges correlated with the PRQ.

Conclusions. A construct such as the PRQ may provide a better prediction of outcome than its individual parts. We identified an important underlying relationship between intensive care unit stay, hospital stay and charges, and our index. A PRQ of less than 2,200 was associated with an increased risk of pulmonary complications and mortality.

	Introduction

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 
Prediction of outcomes after thoracic operations offers important benefits. Physicians anticipating those patients most prone to complications can provide special attention aimed at reducing morbidity and mortality. In the present climate, in which resources are becoming scarce and reimbursement follows strict guidelines, an institution equipped with reliable predictive data can begin to make the kinds of cost analysis predictions that will provide accurate financial projections.

Investigators have attempted to predict outcome using spirometry, blood gas analysis, carbon monoxide diffusion capacity, and split lung function testing. Individual parameters have shown some promise at predicting pulmonary complications including death. In 1955, Gaensler and colleagues [1] identified a relationship between spirometric testing and outcome. Boysen and associates [2] expanded the resectability criteria to include patients previously considered too sick to survive thoracotomy by using split lung function tests to estimate predicted postoperative forced expiratory volume in 1 second (ppoFEV₁). However, their measurements of ppoFEV₁ failed to predict pulmonary morbidity. Ferguson and colleagues [3] used logistic regression to demonstrate that predicted postoperative carbon monoxide diffusion capacity percent (ppoDL_co%) was inversely related to the incidence of complications and an important predictor of pulmonary morbidity. Markos and associates [4] provided evidence that a ppoFEV₁ percentage could be useful in estimating complications and outcome. Pierce and colleagues [5] were the first investigators to demonstrate the usefulness of a composite index, the predicted postoperative product (PPP). The PPP, or the algebraic product of the ppoFEV₁ percentage and the ppoDL_co%, incorporated values for ventilation, gas exchange, lung perfusion, and the proportion of the remaining lung into one index. They attributed the predictive power of the PPP to the accurate reflection of ventilation and perfusion abnormalities in the postoperative period.

We have developed an index, based on the methodology of Pierce and colleagues [5], that provides not only a measure of mortality but also one of severe respiratory complications. We constructed the predictive respiratory complication quotient (PRQ) to predict the probability of pulmonary morbidity and mortality in thoracic surgical patients.

	Material and methods

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 
After approval from the Institutional Review Board, 61 consecutive patients scheduled to undergo operation for lung cancer between January 1994 and December 1994 and referred to the Department of Pulmonary Medicine for complete preoperative evaluation were studied. All patients underwent spirometry, carbon monoxide diffusion capacity, and split lung function testing. A room air blood gas analysis was done at rest and after a 2-minute step climb to assess exercise capacity, with each step measuring 17.5 cm. Information recorded during the stair climb included number of steps climbed, duration of the climb, and reason for stopping. Observations on pulse, blood pressure, and respiratory rate were obtained before and after the stair climb. The personnel of the pulmonary function laboratory assisted all candidates before and after the test. All tests were ordered by the attending physician as part of the routine preoperative evaluation.

Pulmonary function tests were performed on a Collins GS unit using Collins Plus software (Warren E. Collins, Inc, Braintree, MA). Normal values for spirometry were based on studies reported by Knudson and colleagues [6]. The resting single breath diffusion capacity was determined using the method of Ogilvie and associates and adjusted for hemoglobin [7, 8]. The normal range of DL_co in the pulmonary laboratory was 80 to 100 mL · min^-1 · mm Hg^-1. Testing and exercise arterial blood gases were measured (ABL 520; Radiometer, Copenhagen, Denmark) after a radial artery puncture; the alveolar–arterial oxygen gradient (room air) (A-a PO₂) was calculated using the alveolar gas equation corrected for barometric pressure and age.

All patients had a quantitative lung perfusion scan after intravenous injection of 4 mEq of technetium-99m-labeled microaggregated albumin. Intravenous radiotracer was injected in the supine position and immediately imaged using a large-field-of-view dual-headed gamma camera (Adac Genesys; Adac Lab, Milipitas, CA) in the anterior and posterior projections. This was followed by a variable-dose krypton-81m ventilation scan imaged in the same projections. The quantitative ventilation perfusion scan was read by dividing the hemithorax in thirds in the lateral projection.

The predicted postoperative function was calculated by the equation: . Patients underwent operation if their ppoFEV₁ was more than 800 mL. We excluded from study those patients who underwent chest wall resection. Five surgeons performed all operations. Data were acquired from the pulmonary laboratory data base in conjunction with the prospective thoracic surgical complication data base and verified by chart review. Charts were reviewed for length of hospitalization (LOS) and postoperative LOS. Readmission LOS were added to the initial hospitalization LOS in patients who required a second admission for treatment complication. Surgical and medical complications were considered if they occurred within 60 days of operation. Pulmonary complications were defined as: pneumonia (temperature, >38.5°C, purulent sputum, and chest roentgenographic findings requiring antibiotic therapy), hypoxemia, atelectasis (requiring bronchoscopy), respiratory failure (requiring reintubation and prolonged ventilatory support), and death. Surgical complications were persistent air or chyle leak and reoperation. Medical and cardiac complications included all nonpulmonary and nonsurgical morbidity and mortality. We recalculated the PPP index by substituting (ppoDL_co%)² for ppoDL_co%. Hospital charges were derived from the financial management system of Memorial Sloan-Kettering Cancer Center.

Statistics
Wilcoxon nonparametric tests were performed to compare respiratory functions between patients with and without complications. When applicable, results are expressed as mean ± standard deviation. Relative odds ratio for pulmonary complications was calculated. Stepwise forward logistic regression (p < 0.05) (SPSS 7.5 for Windows; SPSS Inc, Chicago, IL) were used to determine the respiratory parameters for predicting pulmonary, cardiac, surgical, and all complications. The 16 variables tested alone and in combination were age, smoking history, FEV₁, FEV₁ percent predicted, ppoFEV₁ percent predicted, DL_co, DL_co percent predicted, ppoDL_co% predicted, arterial partial pressure of oxygen (PO₂), arterial partial pressure of carbon dioxide (PCO₂), O₂ saturation_rest, O₂ saturation_exercise, O₂ saturation change, A-a PO₂ (room air), A-a PO_2exercise (after exercise), and A-a PO₂ difference. The output was used to construct the equation describing the probability of pulmonary complications. The PRQ was designed to conform to the relative weighted contribution (SPSS Inc) of selected variables where the weight function was 1/X^-Y (only Y = integers were accepted). Receiver operating characteristic curves (MedCalc 4.2 for Windows, Mariakerke, Belgium) were used to select the PRQ cut-off for pulmonary complications. Curve estimation (SPSS Inc) was used to construct the equation depicting the relation between PRQ and postoperative LOS, intensive care unit admissions, and hospital charges.

	Results

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 
Sixty-one preoperative studies and operations were performed in 61 patients. The mean age was 64.9 ± 11.1 years. Thirty-four men and 27 women underwent 20 pneumonectomies and 41 lobectomies. There were 49 non–small cell carcinomas divided into stage I (24 patients), stage II (17), stage III (6), and stage IV (2 patients). There were also 2 neuroendocrine tumors, 2 mesotheliomas, 1 goblet cell carcinoma, 1 metastatic colon carcinoma, and 6 benign tumors. The results of the Wilcoxon rank test on preoperative data are shown in Table 1. Thirty-five complications of all types occurred in 27 patients. Ten pulmonary complications occurred. The probability of pulmonary complications () is described by the equation: ; p = 0.02, where the weight constant (Y) for ppoFEV₁% was 1, for ppoDl_co percent was 2 and for A-a PO₂ was -1, thus, .

View larger version (23K): [in this window] [in a new window]   Fig 1. Plot of probability of severe pulmonary complication versus predictive respiratory complication quotient.

The mean postoperative LOS was 6.4 ± 1.4 days for patients without complications with a mean hospital stay of 8.8 ± 1.8 days. The mean postoperative LOS was 23.3 ± 18.3 days for patients with pulmonary complications with a mean hospital stay of 27.8 ± 20.2 days, including two deaths. The relationship between PRQ and postoperative LOS is shown in Figure 2. The postoperative LOS is described by the equation: ; p = 0.009. Five of 10 patients with pulmonary complications required admission to the intensive care unit. Other complications were successfully treated on the surgical floors. Patients without pulmonary complications did not require intensive care unit care. The average stay in the intensive care unit was 19 days with a range of 4 to 46 days. The probability of intensive care unit admission (ß) is described by the equation: ; p = 0.05. The mean hospital charges were $77,387.00 ± 11,114.00 or 291% higher in patients with than in patients without pulmonary complications (p = 0.011).

View larger version (25K): [in this window] [in a new window]   Fig 2. Plot of predictive respiratory complication quotient versus postoperative length of stay.

	Comment

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

The PRQ appears to provide a very accurate prediction of serious pulmonary complications after thoracic operation for cancer. This index not only incorporates the ppoFEV₁ percent and the ppoDL_co%, but adds a variable, the A-a PO₂. The PRQ also weighs the relative contributions of each of the three variables. Our data showed that ppoDL_co% was the most important contributor in the model, therefore the square adjustment. Previous studies seem to agree that ppoDL_co% is an important factor in postthoracic surgical patients developing pulmonary complications [3–5]. Excluding possibly exercise testing, investigators found DL_co variables to provide the best single prediction of outcome when compared with other pulmonary laboratory parameters. Recalculating the data by Pierce and colleagues [5] by substituting (ppoDL_co%)² for ppoDL_co% results in a construct that improves the PPP predictive power for respiratory failure and mortality. The ppoFEV₁ is considered by many researchers to be an important variable in predicting outcome; a value of 800 mL is commonly quoted as the margin of resectability [9]. Markos and colleagues [4] demonstrated that a ppoFEV₁ percentage more than 40% was associated with no postoperative deaths, whereas a value less than 40% was associated with 50% mortality. The ppoFEV₁ percentage was superior to the ppoFEV₁ at predicting complications, hence its inclusion in the index. The A-a PO₂ was the measure of oxygenation that showed statistically significant predictive value; it was inversely related to outcome. There is no precedent for using A-a PO₂ in the prediction of outcome. However, there is some evidence to suggest that a patient with hypoxemia, not attributable to right-to-left intrapulmonary shunting caused by areas of resectable postobstructive atelectasis and pneumonia is more likely to do worse after thoracic operation [4, 10].

The PRQ uses the rationale that the margin of resectability be based on an algebraic combination of multiple variables. As Pierce and colleagues [5] explained, there is an advantage to this kind of algorithm: a patient may undergo operation despite one poor individual measurement as long as another measurement is well above the minimum. For example, if a patient has a ppoFEV₁ percentage and a ppoDL_co% of 50%, and a PO₂ more than 50 mm Hg with a corresponding A-a PO₂ of less than 57, the PRQ is close but above the resectability margin of 2,200 identified by receiver operating characteristic curves. Such a patient should be capable of tolerating the planned procedure.

We failed to corroborate the significance of a number of factors described by other investigators as predictors of outcome (see Table 1) [4, 9, 11–17]. The ability to successfully exercise has been used to assess the cardiopulmonary risk of thoracotomy. Studies have also used exercise testing with cycle ergometry to assess surgical risk. Most, but not all, exercise testing studies have shown that they can be used to assess the operative risk for cardiopulmonary complications [4, 18]. Markos and colleagues [4] used staged bicycle ergometry to show the significance of exercise desaturation in predicting outcome. Rao and associates [11] used stair climbing to show similar results. Although we used stair climbing, we were unable to show any relationship between exercise desaturation and outcome. Some investigators believe a PCO₂ more than 45 mm Hg is a predictor of poor outcome after lung resection, whereas others believe that PCO₂ plays no role [14–17]. The PCO₂ did not have any importance in the prediction of outcome in our patients. There was no difference in the PCO₂ between the pulmonary complication group and the noncomplication group. In addition, there were 7 patients with a PCO₂ more than 45 mm Hg and a PRQ more than 2,200 who experienced no complications. Kearney and coworkers [9] showed smoking history to be a predictor of outcome. We were unable to describe any relation between smoking history and complications. The significance of advanced age as a predictor of complications is controversial [15]. We had 29 patients who were older than 65 years; 5 patients experienced pulmonary complications, and another 12 experienced other types of complications. In total, 17 of the 27 patients experiencing complications were older than 65 years. Advanced age was a marginally important parameter in the prediction of all complications (p = 0.06). Pierce and coworkers [5] reported a difference in the relation of the PPP and operation to the accuracy of the prediction; the predictive power of the PPP was better for lobectomies than for pneumonectomies. Our results do not corroborate this finding. In addition, our population did not experience a higher incidence of complications in pneumonectomy patients. Although sample size may play a part in our findings, we believe that postoperative pulmonary complications are better associated with the remaining lung function than with the nature of the operation. The PRQ with its various weighted variables better corrects for the operation bias.

There was a statistically significant increase in the postoperative LOS between patients with and without pulmonary complications. Pulmonary complications studied resulted in prolongation of postoperative LOS in hospital as well as the requirement for intensive care unit care. This outcome clearly has a financial impact, underscoring the importance of the PRQ. Patients with pulmonary complications spent an average of 9.5 days in the intensive care unit. This was associated with a threefold increase in the mean charge for hospitalization. Clearly, it is of great importance that we identify patients who are likely to incur such high expenses. The task was accomplished thanks to the application of well-defined criteria for complications. Similar analysis may be possibly performed for other complications aiding hospitals in identifying potential sources of increased expenditures. A PRQ of less than 2,200 is associated with an increased risk of pulmonary complications and mortality.

Although this study lacks prospective validation, we believe our results have significant legitimacy. Predicting postoperative outcome is a very complex process partly the result of vaguely defined complications. It is of utmost importance that precise definitions for complications are used when examining outcomes, so that useful comparisons can be made between studies. Many reviews have even attempted to correlate nonpulmonary complications with preoperative pulmonary parameters making the process of understanding outcome almost impossible to sort.

In conclusion, the PRQ can predict outcome after lung resection better than other well-studied parameters. We describe the design of the equations for the probability of serious pulmonary complications, postoperative LOS, and probability of admission to the intensive care unit based on the PRQ. Hospital expenditures were correlated to the PRQ. We believe that our hypothesis deserves serious consideration and prospective corroboration.

	Acknowledgments

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 
We thank Drs Manjit S. Bains, Michael E. Burt, Robert J. Ginsberg, Patricia M. McCormack, and Valerie W. Rusch for their invaluable assistance. We also thank all the technicians of the pulmonary function laboratory. We give special thanks to Dr Vittoria Arslan and Patricia Tietjen for their invaluable comments.

	References

Top Abstract Introduction Material and methods Results Comment Acknowledgments References

 

1. Gaensler E.A., Cugell D.W., Lindgren I., et al. The role of pulmonary insufficiency in mortality and invalidism following surgery for pulmonary tuberculosis. J Thorac Surg 1955;29:163-188.
2. Boysen P.G., Block A.J., Olsen G.N., et al. Prospective evaluation for pneumonectomy using ^99mtechnetium quantitative perfusion lung scan. Chest 1977;72:422-425.[Abstract/Free Full Text]
3. Ferguson M.K., Reeder L.B., Mick R. Optimizing selection of patients for major lung resection. J Thorac Cardiovasc Surg 1993;109:275-281.
4. Markos J., Mullen B.P., Hillman D.R., et al. Preoperative assessment as a predictor of mortality and morbidity after lung resection. Am Rev Respir Dis 1989;139:902-910.[Medline]
5. Pierce R.J., Copland J.M., Sharpe K., et al. Preoperative risk evaluation for lung cancer resection: predicted postoperative product as a predictor of surgical mortality. Am J Respir Crit Care Med 1994;150:947-955.[Abstract]
6. Knudson R., Lebowitz M., Holberg C. Changes in the normal maximal expiratory flow-volume curve with growth and aging. Am Rev Respir Dis 1983;127:725-734.[Medline]
7. Ogilvie C., Foster R., Blakemore W. A standardized breath holding technique for the clinical measurement of the diffusing capacity of the lung for carbon monoxide. J Clin Invest 1957;36:1-17.
8. Bates D., Macklem P., Christie R. An introduction to the integrated study of the lung. In: Bates D., Macklem P., Christie R., eds. Respiratory function in disease. Philadelphia: Saunders, 1971:93-94.
9. Kearney D.J., Lee T.H., Reilly J.J., et al. Assessment of operative risk in patients undergoing lung resection. The importance of predicted pulmonary function. Chest 1994;105:753-759.[Abstract/Free Full Text]
10. Tisi G.M. Preoperative evaluation of pulmonary function: validity, indications, and benefits. Am Rev Resp Dis 1979;119:293-310.[Medline]
11. Rao V., Todd T.R.J., Kuus A., Buth K.J., Pearson F.G. Exercise oximetry versus spirometry in the assessment of risk prior to lung resection. Ann Thorac Surg 1995;60:603-609.[Abstract/Free Full Text]
12. Olsen G.N., Bolton J.W.R., Weiman D.S., et al. Stair climbing as an exercise test to predict the postoperative complications of lung resection. Two years’ experience. Chest 1991;99:587-590.[Abstract/Free Full Text]
13. Holden D.A., Rice T.W., Stelmach K., et al. Exercise testing, 6-min walk, and stair climb in the evaluation of patients at high risk for pulmonary resection. Chest 1992;102:1774-1779.[Abstract/Free Full Text]
14. Epstein S.K., Faling L.J., Daly B.D.T., et al. Predicting complications after pulmonary resection. Preoperative exercise testing vs a multifactorial cardiopulmonary risk index. Chest 1993;104:694-700.[Abstract/Free Full Text]
15. Harpole D.H., Liptay M.J., DeCamp M.M., et al. Prospective analysis of pneumonectomy: risk factors for major morbidity and cardiac dysrrythmias. Ann Thorac Surg 1996;61:977-982.[Abstract/Free Full Text]
16. Stein M., Koota G.M., Simon M., et al. Pulmonary evaluation of surgical patients. JAMA 1962;181:765-770.
17. Mohr D.N., Jett J.R. Preoperative evaluation of pulmonary risk factors. J Gen Int Med 1988;3:277-287.[Medline]
18. Epstein S., Faling J., Daly B., Celli B. Inability to perform bicycle ergometry predicts increased morbidity and mortality after lung resection. Chest 1995;107:311-316.[Abstract/Free Full Text]

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