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Eur J Cardiothorac Surg 2001;19:924-928
© 2001 Elsevier Science NL
a Department of Thoracic Surgery, University Of Ancona, Ancona, Italy
b Department of Epidemiology, Biostatistics and Medical Information Technology, University Of Ancona, Ancona, Italy
Received 26 September 2000; received in revised form 17 January 2001; accepted 15 March 2001.
Corresponding author. Via St. Margherita 23, Ancona 60129, Italy. Tel.: +39-071-34738; fax: +39-071-883911
e-mail: alexit_2000{at}yahoo.com
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Abstract |
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 Top Abstract 1. Introduction2. Materials and methods3. Results4. DiscussionReferences |
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Key Words: Scoring system • Audit • Morbidity • Thoracic surgery
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1. Introduction |
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TopAbstract1. Introduction2. Materials and methods3. Results4. DiscussionReferences |
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Morbidity rate is frequently used as an outcome variable in surgical audit. However, if not adjusted for the physiological state of the patient and the type of operation performed, it may yield misleading information.
To obviate this methodological problem, POSSUM was validated in a general surgery population [1] and, then, applied for audit purposes in general and vascular surgery [2–5].
The aim of the present study was to assess the performance of our thoracic surgery unit over two successive periods of activity using POSSUM as an instrument of audit.
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2. Materials and methods |
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TopAbstract1. Introduction2. Materials and methods3. Results4. DiscussionReferences |
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The operations performed included the following: 419 pulmonary resections (wedge resection, segmentectomy, lobectomy, pneumonectomy), 65 video-assisted thoracic surgery (VATS) procedures (including 38 bullectomies), 18 transthoracic esophagectomies, 30 thymectomies, 56 mediastinoscopies or anterior mediastinotomies, nine pleural decortications, 47 chest tube thoracostomies, five mediastinal tumor resections, seven diaphragmatic hernia repairs, 15 rib resections, 14 chest wall resections, 69 thoracotomies (for biopsy or explorative), and 57 other procedures. For malignant diseases, 585 operations were performed, and 216 for benign lesions.
The median age of the patients was 62 (25th–75th percentiles, 52–69) with a prevalence of males (75.4%) over females (604 vs. 197).
All of the surgical candidates underwent respiratory and cardiovascular functional evaluation to assess operability. The same medical staff administered the perioperative treatment and the same surgical team performed the operative procedures over the time of the study.
Postoperative complications were considered as those occurring within 30 days of the operation or during a longer period if the patient was still in the hospital. They included respiratory failure requiring mechanical ventilation for more than 48 h, pneumonia, atelectasis requiring bronchoscopy, bronchopleural fistula, prolonged air leak (more than 7 days), adult respiratory distress syndrome (ARDS), hemothorax requiring re-operation, chylothorax, large pleural effusion, pulmonary edema, pulmonary embolism, myocardial infarction, arrhythmia requiring medical therapy, metabolic complications (i.e. renal failure), fever higher than 38°C for more than 4 consecutive days, re-operation.
We included only those complications that added complexity to the management of the patients and prolonged the hospital stay. Furthermore, we considered the occurrence of any of the aforementioned complications as a single outcome measure. This was done according to the work of the originators of POSSUM [1] and also because most of the work done with complications at the present time does not weigh complications [6].
POSSUM was prospectively calculated for each patient according to Copeland et al. [1]. The physiological score (PS) is a 12-factor, four-grade score, including age, cardiac status, pulse rate, systolic blood pressure, respiratory status, Glascow coma score, serum concentrations of urea, potassium, and sodium, hemoglobin concentration, white cell count, and electrocardiogram findings.
The six-factor, four-grade operative severity score (OSS) correct for the type of operation, number of procedures, total blood loss, peritoneal contamination, presence and extent of malignancy, and degree of urgency of operation was used.
In order to adapt the system to the thoracic surgery setting, the ‘peritoneal soiling’ factor was replaced by the ‘pleural soiling’ factor. Moreover, all of the pulmonary resections were considered as major surgery (four points in the OSS), except for wedge resection and segmentectomy (two points) or if they were associated with other procedures (i.e. extrapleural pneumonectomy, associated resection of mediastinal organs or tissues, associated chest wall resection etc.). In the latter case, they were considered as ‘major+’ surgery (eight points).
Other surgical procedures were scored as follows: esophagectomy (eight points); thymectomy, thyroidectomy, mediastinal tumor resection, pleural decortication, chest wall resection with prosthetic reconstruction (four points); VATS procedures, explorative thoracotomy, chest wall resection without prosthetic reconstruction, diaphragmatic hernia repair, anti-reflux procedures (two points); rib resection, chest tube thoracostomy, mediastinoscopy or anterior mediastinotomy, simple thoracoscopy (one point).
2.1. Statistical analysis
The first step of the analysis was conceived to estimate the capability of POSSUM to predict postoperative complications in the thoracic surgery setting.
The logistic regression model [7] was used to estimate the risk of postoperative morbidity as dependent on the PS and the OSS of POSSUM. The dependent variable (predicted variable) of the logistic regression model was the postoperative outcome (regular or complicated).
Since the use of the same population, either in the estimation of the parameters or in the assessment of the discriminant capability, may lead to a bias in the evaluation of the effective predictive ability, 400 patients (sample 1) were randomly extracted from the complete database of 801 observations. The logistic analysis was applied to sample 1 and the estimated parameters were then used to calculate the probabilities of postoperative complications in the remaining 401 cases (sample 2).
The aforementioned predicted probabilities were then used to plot the receiver operating characteristic (ROC) curve along with the 95% confidence intervals (95% CI) according to the methodology proposed by Metz et al. [8]. The area under the curve represents the probability of concordance between the predicted and observed morbidities. An area of one means perfect agreement, whereas an area of or under 0.5 represents prediction no better than chance. The model fit was measured with Hosmer–Lemeshow statistics [7].
In the second part of the analysis, we used POSSUM as an instrument of audit: we divided the complete data set of patients into two groups according to the period of operation: group 1, from 1992 through 1994; and group 2, from 1995 through 1997; we then applied the previously validated logistic regression parameters to calculate the probability of complication for each of the two periods.
The proportions of observed and POSSUM-predicted morbidity were compared within each group by means of the z-test for a comparison of a proportion with an expected value.
All the analyses were performed by using the SAS system package (SAS Institute, Inc., Cary, NC) and a level of 5% was chosen to assess statistical significance.
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3. Results |
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TopAbstract1. Introduction2. Materials and methods3. Results4. DiscussionReferences |
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The complications, in order of frequency, were: prolonged air leak (74), arrhythmia (41), fever (31), respiratory failure (27), re-operation (20), hemothorax (17), bronchopleural fistula (14), pneumonia (11), atelectasis (ten), pulmonary edema (seven), myocardial infarction (five), pleural effusion (four), ARDS (four), pulmonary embolism (three), chylothorax (two).
We had 20 re-operations (two deaths: 10% mortality) caused by hemothorax (nine cases), bronchopleural fistula (seven cases), chylothorax (two cases), prolonged air leak (one case), and sternotomy dehiscence (one case). Fifteen out of 20 re-operations were performed after a prior lung resection.
The characteristics of the complicated patients compared with those without complications are shown in Table 1. The former were older, had higher values of POSSUM PS and OSS, and were more often male.
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The characteristics of two groups of patients undergoing thoracic procedures in two successive periods of activity at our institution (group 1: 1992 through 1994; group 2: 1995 through 1997) are shown in Table 3.
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4. Discussion |
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TopAbstract1. Introduction2. Materials and methods3. Results4. DiscussionReferences |
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Postoperative morbidity rate was chosen as a dependent variable to evaluate the surgical outcome. When used as an outcome measure, complication rate has three inherent problems. First, the definition of a complication may be complex and subjective. Second, there may be variations in the recording of complications. Finally, the postoperative morbidity rate may be greatly influenced by the severity of the operation performed and by the physiological conditions of the patients.
In a prospective internal audit, such as the one designed in the present analysis, the list of complications taken into account is selected at the beginning of the study and the criteria of inclusion of the patients into each of these complications is constant throughout the duration of the study.
Moreover, being a prospective study performed at a single institution over a relatively short period of time, no variation in the recording of complications should have occurred.
To obviate the third problem, a factor of correction needs to be introduced. For this purpose, POSSUM was originally validated in general surgery [1] to adjust the crude rate of morbidity and mortality for the type and severity of operation and for the physiological state of the surgical candidate. However, POSSUM was never validated in settings other than general surgery [1].
In a previous study, we showed that POSSUM was a significant predictor of postoperative complications in a group of patients undergoing lung resection [9]. This result prompted us to investigate whether POSSUM may be reliably applied to the whole thoracic surgery case-mix. Thus, all the patients submitted to thoracic procedures at our institute from 1992 through 1997 were included in the present study.
The validation process was primary in the present analysis and warranted the use of POSSUM as an instrument of internal comparison between two successive periods of activity (1992 through 1994 vs. 1995 through 1997).
A statistically significant difference was noted between observed and POSSUM-predicted complications in the first period, whereas no difference was evident in the more recent period.
The present study showed an improved performance of our unit in the last period of activity, which would not have been detected if only observed morbidity rates were analyzed. Moreover, a worse-than-expected outcome, like the one in the first period of our analysis, may reveal an unsuspected clinical mismanagement, which can eventually be identified and corrected.
When the analysis was restricted to patients with a high risk of developing complications, such as those identified by a high POSSUM-predicted probability, there was a greater proportion of uncomplicated patients in the second period of activity. This revealed an improved management of these more complex cases, which may be explained by a learning curve effect or by the introduction of successful changes in the perioperative treatment.
Finally, POSSUM allows the inclusion of the single ‘surgical success’ cases as a matter of discussion and as an indicator of the quality of surgical care.
Patients in a high-risk group in whom no complications were observed may be carefully studied in order to disclose possible successful factors of their perioperative treatment, which may be generalized to future patients.
We think that in an well-organized managed care system, a reliable instrument of surgical audit is appropriate in the comparative analysis of costs and results, and for a more accurate allocation of resources. We showed that POSSUM can be reliably used as a tool of internal audit in a thoracic surgery institution. However, the results of the present work reflect the activity of a low volume thoracic surgery unit and need independent confirmation from other centers. Moreover, the applicability of this scoring system as an instrument to compare the performance of different thoracic surgery units, as was done in general surgery [2–5], should be warranted by future investigations.
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References |
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TopAbstract1. Introduction2. Materials and methods3. Results4. DiscussionReferences |
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