Duration of anaesthesia, type of surgery, respiratory co-morbidity, predicted V[O.sub.2]max and smoking predict postoperative pulmonary complications after upper abdominal surgery: an observational study.

Introduction

Pulmonary complications are a leading cause of morbidity and mortality following upper abdominal surgery (Smetana et al 2006). The incidence of postoperative pulmonary complications in this population ranges from 9% to 40%, depending on the criteria used for diagnosis of postoperative pulmonary complications (Brooks-Brunn 1997). As pulmonary complications contribute to prolonged hospital stay and additional health care costs (Thompson et al 2006), numerous strategies have been employed to prevent their development. However, evidence evaluating the efficacy of these interventions is limited. A recent systematic review concluded that only intervention to improve lung volume (such as deep breathing exercises, incentive spirometry, and continuous positive airways pressure) significantly reduces the rate of postoperative pulmonary complications (Lawrence et al 2006). In addition, throughout the world, intervention that improves lung volume forms a major component of prophylactic respiratory physiotherapy (Mackay and Ellis 2002).

Respiratory physiotherapy may be superfluous in patients at low risk of developing pulmonary complications (Pasquina et al 2006). To assist with resource allocation, attempts have been made to predict which individuals will develop pulmonary complications after elective upper abdominal surgery, with high risk patients receiving more intense intervention. A number of studies have investigated risk factors for postoperative pulmonary complications after upper abdominal surgery (Arozullah et al 2001, Barisione et al 1997, Brooks-Brunn 1998, Johnson et al 2007, Kanat et al 2007, McAlister et al 2005, Pereira et al 1999, Serejo et al 2007). Conflicting results have been reported and the research has limitations. In a systematic review, Fisher et al (2002) were unable to identify any valid models for the prediction of postoperative pulmonary complications following nonthoracic surgery. Inconsistent definition of risk factors and outcomes, including the definition of postoperative pulmonary complications and the inclusion of clinically-insignificant respiratory complications, considerably limit the strength of conclusions that can be drawn from previous research. Furthermore, inadequate blinding of observers, small sample size, retrospective data collection, and selection bias are present in a number of early studies (Lawrence et al. 1996). Problems associated with study design, such as insufficient description of the methods of model derivation, mean that early studies cannot be validated. In addition, most studies have not investigated reliability and/or validity in an independent patient cohort, thus limiting their external validity. Some models include pulmonary function as a predictor. However, pulmonary function tests are not routinely conducted on patients prior to abdominal surgery and their usefulness as a predictor of pulmonary risk has therefore been questioned (Kocabas et al 1996; Kroenke et al 1993; Lawrence et al 1996). Finally, few studies have considered the risk of patients undergoing only upper abdominal surgery (Hall et al 1991). As patients undergoing upper abdominal surgery have the greatest incidence of postoperative pulmonary complications, this population may demonstrate different risk factors compared with other populations (Smetana 2006).

The identification of risk factors is further confounded by a lack of standardised, prophylactic, respiratory physiotherapy. As lung expansion strategies may prevent the development of pulmonary complications, standardised prophylactic respiratory intervention may be necessary when examining predictors of postoperative pulmonary complications. To our knowledge, no predictive studies involving patients undergoing upper abdominal surgery have attempted to standardise or record this intervention. Consequently, addressing these methodological concerns will significantly improve the reliability and validity of any model developed to predict the risk of developing postoperative pulmonary complications.

The aim of this study was to identify risk factors associated with the development of pulmonary complications following elective upper abdominal surgery managed with standardised respiratory physiotherapy care in order to formulate a clinical prediction rule that would identify patients who would most benefit from prophylactic respiratory physiotherapy. The specific research question was:

   Can the risk of developing postoperative pulmonary
   complications be predicted after upper abdominal
   surgery?

Method

Design

A prospective cohort observational study was carried out. Consecutive patients undergoing elective upper abdominal surgery were recruited preoperatively from The Royal Melbourne Hospital, Western Hospital, and St. Vincent's Hospital, Melbourne, Australia. Preoperatively, all patients were educated about their surgery and taught deep breathing exercises, forced expiratory manoeuvres, and supported coughing by a physiotherapist. Patients were given verbal and written instructions to complete these lung expansion exercises independently every hour in the postoperative period. Patients were also educated on the importance of early postoperative mobilisation. The preoperative risk factors were recorded by the physiotherapist using a standardised data collection form. Postoperatively, postoperative risk factors were recorded. Postoperative pulmonary complications were assessed daily until discharge by a physiotherapist. On the first day, patients received one session of standardised physiotherapy intervention involving deep breathing exercises, forced expiratory manoeuvres, supported coughing and assisted mobilisation as per preoperative instruction. No further physiotherapy intervention was delivered unless patients were diagnosed with a pulmonary complication, when additional physiotherapy intervention as determined by assessment findings was provided.

Participants

Patients were included if they understood written and spoken English and underwent open upper abdominal surgery, which was defined as 'an incision above or extending above the umbilicus' (Celli 1993). Patients were withdrawn if they required more than 12 hours of mechanical ventilation in intensive care postoperatively or returned for further surgery within the first five postoperative days.

Outcome measures

Predictors were risk factors identified from: previous research, results from a survey of Australian respiratory physiotherapists who identified 16 possible risk factors, a review of the existing literature, and an audit conducted at St Vincent's Hospital, Melbourne, Australia. Only those measures that were routinely collected and easily accessible by clinicians were included. In total, 17 risk factors were investigated and their operational definitions are presented in Table 1. Pre-morbid mobility was ascertained verbally and via the Specific Activity Questionnaire, a self-administered activity questionnaire that provides an estimate of maximal oxygen uptake (Rankin et al 1996). The questionnaire has moderately good predictive ability of functional capacity in cardiac patients with similar characteristics to our participants (eg, sex, age, and body mass index) and was administered as a simple alternative to formal exercise testing that may be considered inappropriate in patients diagnosed with cancer. In the absence of a validated tool for the measurement of functional capacity after abdominal surgery, the Specific Activity Questionnaire provided a simple platform to examine a range of physical activities associated with activities of daily living. Following surgery, duration of anaesthesia and American Society of Anaesthesiologists (ASA) classification were obtained from the anaesthetic report. Details regarding the surgical procedure and incision were collected from the operation report. The method of analgesia and need for intensive care admission were determined from the medical history and assessment of the patient.

Postoperative pulmonary complications were diagnosed according to the criteria listed in Box 1. Daily measures of room air oxyhaemoglobin saturation, maximum oral temperature, auscultation, and the presence of sputum were recorded on a standardised data collection sheet. Chest radiograph, sputum culture, and white cell count were reviewed when ordered by the treating physician and were classified as normal or abnormal according to the radiology and pathology reports respectively. The prescription of antibiotics specific to respiratory infection was identified from medical records. The presence of a postoperative pulmonary complication was documented by the attending physiotherapist and confirmed by the first author.

Box 1. Postoperative pulmonary complication occurred
when four or more of the following criteria were present.

* Chest radiograph report of collapse/consolidation

* Raised maximum oral temperature > 38[degrees]C on more
than one consecutive postoperative day

* Pulse oximetry oxygen saturation (Sp[O.sub.2]) < 90% on
more than one consecutive postoperative day

* Production of yellow or green sputum different to preoperative
assessment

* Presence of infection on sputum culture report

* An otherwise unexplained white cell count greater
than 11 x [10.sup.9]/l or prescription of an antibiotic specific
for respiratory infection

* New abnormal breath sounds on auscultation
different to preoperative assessment

* Physician's diagnosis of postoperative pulmonary
complication

Data analysis

Sample size was determined using an earlier audit of postoperative pulmonary complications in this population. Assuming an incidence of 10%, the probability of miscalculation was 9% (SD 3) for a sample size of 300, which was considered acceptable (Venebles and Ripley 1997).

Chi-square analysis was conducted to identify risk factors for inclusion in the model. Odds ratios and their 95% confidence intervals were calculated for each predictor.

Predictors with a value of p < 0.08 were entered into a forward stepwise logistic regression model. Predictors were introduced at various stages of the model development until the model with the greatest area under the receiver operator characteristic (ROC) curve was found. In order to develop a score for the risk of developing postoperative pulmonary complications, the beta-coefficients from the logistic regression analysis were used to determine a weight for each predictor, based on the relative importance of their independent contribution to the development of postoperative pulmonary complications. The ROC curve was examined and a cut-off score to predict pulmonary complications was selected to give the highest sensitivity and specificity. Statistically significant differences were assumed when p < 0.05.

Results

Flow of participants through the study

Two hundred and seventy-three consecutive patients undergoing elective upper abdominal surgery were recruited preoperatively between June 2002 and December 2003 to participate in the study. Five patients did not complete the study (Figure 1). The remaining 268 patients were 58 years old (SD 16). Their mean duration of anaesthesia was 207 minutes (SD 115) and the mean postoperative length of stay was 10.8 days (SD 12.9). Thirty-five participants (13%) developed postoperative pulmonary complications. Table 2 presents the characteristics of participants with and without postoperative pulmonary complications.

Clinical prediction rule

Chi-square analysis for each predictor identified seven that were significantly (p < 0.08) associated with the development of postoperative pulmonary complications (Table 3). These were: anaesthetic greater than 180 minutes, hepatobiliary and upper gastrointestinal surgery, presence of respiratory co-morbidity, current smoking, predicted maximal oxygen uptake as calculated from the Specific Activity Questionnaire, postoperative admission to intensive care, and abnormal preoperative assessment. Intensive care admission criteria were not well defined and varied across the three centres and this variable was therefore excluded from the multivariate analysis.

The remaining six predictors were entered into a forward stepwise logistic regression analysis. Five were identified as independently (p < 0.05) predicting the development of postoperative pulmonary complications and were included in the rule (Box 2). Patients were then scored according to the clinical prediction rule. When their score was tested against the outcome of postoperative pulmonary complication, it demonstrated a highly significant predictive ability (p < 0.001). When evaluating the accuracy of the clinical prediction rule, the area under the ROC curve was calculated to be 0.79, suggesting that the clinical prediction rule was a good predictor of postoperative pulmonary complications (Hosmer and Lemeshow 1989).

In order to generate a cut-off point, ie, a point above which patients would be considered low risk and below which patients would be considered at high risk of pulmonary complications, the ROC curve was examined and the sensitivity and specificity was evaluated for various cutoff values. A cut-off of 2.2 corresponded to a sensitivity of 82% and a specificity of 65%. The odds ratio for the clinical prediction rule was 8.41 (95% CI 3.33 to 21.26, p < 0.001).

[FIGURE 1 OMITTED]

Discussion

This prospective, multi-centre study identified five risk factors associated with the development of postoperative pulmonary complications after upper abdominal surgery and from them derived a clinical rule for predicting the risk of developing complications. All patients received similar prophylactic intervention by a physiotherapist. The five risk factors contained in the model may be assessed in the early postoperative period through a brief patient interview and the completion of a short questionnaire. A risk score can be calculated by entering the values derived from logistic regression analysis into an equation. This score may then be used to determine whether the patient has a high risk of developing postoperative pulmonary complications. Patients identified as high risk may be targeted for intensive prophylactic respiratory intervention, thus ensuring appropriate allocation of physiotherapy resources and limiting the likelihood of clinically significant pulmonary complications.

The risk factors identified in this study both compare and contrast with those reported in a recent systematic review (Smetana et al 2006). Smetana and colleagues concluded that there is strong evidence for the risk factors: advanced age, ASA class 2 or higher, functional dependence, chronic obstructive pulmonary disease, congestive cardiac failure, prolonged surgery, and serum albumin less than 30g/l (Smetana et al 2006). The current study found that respiratory co-morbidity and duration of anaesthetic were significantly associated with an increased risk of developing postoperative pulmonary complications and were therefore included in the clinical prediction rule. Also included was a short questionnaire which provided an estimate of exercise capacity (the Specific Activity Questionnaire, Rankin et al 1996). It is likely that the exercise capacity reflects functional dependence since patients who were functionally dependent would have scored poorly on the Specific Activity Questionnaire. In addition, exercise capacity may reflect other potentially modifiable risks such as obesity, and cardiac and respiratory co-morbidity.

Box 2. Mean (95% CI) regression coefficients of predictors
and clinical prediction rule from the multivariate analysis,
and accuracy of risk of developing postoperative
pulmonary complications.

Regression coefficients of predictors

Duration of anaesthetic (min) ([[beta].sub.1])
  < 60 = 23.27 (20.40 to 26.13)
  60-119 = 2.05 (-0.15 to 4.24)
  120-179 = 1.95 (-0.02 to 3.92)
  180-239 = 0.21 (-1.22 to 1.65)
  240-299 = 0.18 (-1.30 to 1.65)
  [greater than or equal to] 300 = 0.00

Surgical category ([[beta].sub.2])
  Hepatobiliaric & upper GI = 1.19 (-1.00 to 3.38)
  Colorectal & lower GI = 2.23 (0.01 to 4.44)
  Renal & urological = 2.74 (-0.78 to 6.26)
  Vascular = 20.80 (17.13 to 24.46)
  Other = 0.00
Respiratory co-morbidity ([[beta].sub.3])
  Yes = -0.59 (-6.30 to 5.11)
  No = 0.00
Current Smoker ([[beta].sub.4])
  Yes = -1.00 (-6.59 to 4.59)
  No = 0.00
Predicted V[O.sub.2] max ([[beta].sub.5])
  V[O.sub.2]max < 19.37 ml/kg.min = -0.962 (-6.36 to 4.44)
  V[O.sub.2]max [greater than or equal to] 19.37 ml/kg.min = 0.000

Clinical prediction rule

Score * = 0.49
        + [[beta].sub.1]
        + [[beta].sub.2]
        + [[beta].sub.3]
        + [[beta].sub.4]
        + [[beta].sub.5]

Accuracy of clinical prediction rule

Area under ROC curve = 0.79
OR = 8.41 (95% CI 3.33 to 21.26)

* = score [greater than or equal to] 2.02 is associated with a high
risk of postoperative pulmonary complications

In contrast to the systematic review conducted by Smetana and colleagues (2006), advanced age, ASA status, and cardiac co-morbidity were not found to be significant predictors of pulmonary complications in this current study. This may be explained by differences in the populations studied. The findings of the systematic review were largely influenced by data obtained in the National Surgical Quality Improvement Program, the outcomes of which have been reported in several publications (Arozullah et al 2000, Arozullah et al 2001, Johnson et al 2007, O'Brien et al 2002). Despite a very large sample size, participants were primarily male veterans who underwent a range of surgical procedures including musculoskeletal, lower abdominal, and thoracic surgery. The ASA classification has been identified as a risk factor after abdominal surgery (Hall et al 1996). However, poor inter-observer consistency with the ASA has been demonstrated (Mak et al 2002). This may in part explain why ASA status was not found to be a significant predictor of pulmonary complications in the current study. Age greater than 60 years has been cited as a risk factor for postoperative pulmonary complications in previous literature (Arozullah et al 2000, Arozullah et al 2001, Brooks-Brunn 1997, McAlister et al 2005). Patients who developed a pulmonary complication in the current study tended to be older but this was not statistically significant. This may be because the mean age of patients was below 60 years old. Further research in older patients is needed to determine whether age is a significant risk factor. Cardiac comorbidity has also been identified as a risk factor (Arozullah et al 2000, Lawrence et al 1996). However, in the current study, this broad classification was not associated with the development of postoperative pulmonary complications. A more specific cardiac examination may predict risk better, but may reduce the clinical utility of a prediction rule due to the need for more thorough assessment and preoperative testing. Serum albumin was not considered to be a clinical outcome routinely assessed by physiotherapists so it was not included as a predictor in this study.

Current smoking has been found to predict the risk of pulmonary developing postoperative pulmonary complications (Bluman et al 1998, Brooks-Brunn 1997). In the current study, the odds of smokers developing postoperative pulmonary complications were more than twice that of non-smokers. These findings are supported by a recent systematic review which concluded that short term smoking cessation may reduce risk; however longer periods of cessation may be more effective in preventing pulmonary complications (Theadom and Cropley 2006). Due to the limited number of studies available, further research is needed to determine the effect of smoking on the development of postoperative pulmonary complications.

Whilst it has been established that upper abdominal surgery is associated with an increased risk of pulmonary morbidity (Smetana et al 2006), few studies have investigated the incidence of postoperative pulmonary complications according to type of abdominal surgery. In the current study, patients who underwent hepatobiliary and upper gastrointestinal surgery were twice as likely to develop complications than those from any other surgical category. This may be because hepatobiliary and upper gastrointestinal problems can be associated with other problems that increase the risk of pulmonary complications such as diaphragmatic dysfunction (Dureuil et al 1986).

Admission to intensive care was found to be a significant predictor of developing pulmonary complications. However, this factor was not included in the clinical prediction rule because of inconsistencies in admission criteria between the three sites. Patients who are considered to be at a high risk of postoperative morbidity are electively admitted to the intensive care unit for monitoring and prophylactic intervention. Such patients are not expected to follow a routine postoperative course. The clinical prediction rule developed in the current study aims to determine whether a patient is at risk of developing postoperative pulmonary complications and whether intensive postoperative respiratory intervention is indicated. Patients in the intensive care unit are already considered to have a high risk of developing complications and intensive prophylactic respiratory intervention is therefore warranted for these patients.

This study has developed a new clinical rule for predicting the risk of developing postoperative pulmonary complications that addresses the methodological flaws of previous studies and has good clinical utility. However, there are limitations to the research. Investigating the inter-rater reliability of the rule when used by novice and experienced physiotherapists may highlight its value as a learning aid in novice and student physiotherapists. To ensure consistency with the predictive accuracy reported in this study, validation of the clinical prediction rule in an independent sample of upper abdominal surgery patients is required prior to implementation in the clinical setting. Difficulties with recruitment of patients over an 18 month period in three different tertiary hospitals limited the sample size. Even though the sample size was reasonable according to power calculations, a larger sample size would allow examination of a large number of potential risk factors and avoid the risk of 'over-fitting' the model to the data.

This was a multi-centre study which provides good external validity. In addition, the study was prospective and did not suffer from issues related to retrospective data collection, such as missing data and inconsistent definitions of variables. A further strength of this study is that the clinical prediction rule has been developed specifically for use in the upper abdominal surgery population. Deriving a clinical prediction rule using 'weighted' predictors may be a more sensitive method of predicting risk than using arbitrarily assigned scores to factors thought to contribute to the development of pulmonary complications. Comparison of this rule with others used after abdominal surgery is recommended to further investigate its validity and clinical utility. A reliable and valid clinical rule for predicting the risk of developing pulmonary complications should allow the prioritisation of respiratory care to patients who are most likely to benefit. Level 1 evidence supports the use of respiratory prophylaxis after abdominal surgery (Lawrence et al 2006). Consequently, adoption of the rule into routine clinical practice should be considered following validation in an independent population.

Ethics: The Human Research Ethics Committee of The Royal Melbourne Hospital (Melbourne Health) and the Human Research Ethics Committee of St Vincent's Hospital Melbourne Hospital (Melbourne Health) approved this study. Written informed consent was obtained from all participants before data collection began.

Competing interests: None declared.

Support: St. Vincent's Hospital; Melbourne Research Grant; Melbourne Early Career Researcher Grants Scheme; The University of Melbourne 

Acknowledgements: The authors thank the physiotherapy departments from St. Vincent's Hospital, The Royal Melbourne Hospital, and The Western Hospital for their assistance with staff and patient recruitment. We would also like to thank Associate Professor Ian Gordon, from the University of Melbourne, for his assistance with statistical analysis.

References

Arozullah AM, Daley J, Henderson WG, Khuri SF (2000) Multifactorial risk index for predicting postoperative respiratory failure in men after noncardiac surgery. Annals of Surgery 232: 242-253.

Arozullah AM, Khuri SF, Henderson WG, Daley J (2001) Development and validation of a multifactorial risk index for predicting postoperative pneumonia after major noncardiac surgery. Annals of Internal Medicine 135: 847-857.

Barisione G, Rovida S, Gazzaniga GM, Fontana L (1997) Upper abdominal surgery: does a lung function test exist to predict early severe postoperative respiratory complications? European Respiratory Journal 10: 1301-1308.

Bluman LG, Mosca L, Newman N, Simon DG (1998) Preoperative smoking habits and postoperative pulmonary complications. Chest 113: 883-889.

Brooks-Brunn J (1997) Predictors of postoperative pulmonary complications following abdominal surgery. Chest 111: 564-571.

Brooks-Brunn J (1998) Validation of a predictive model for postoperative pulmonary complications. Heart and Lung 27: 151-158.

Celli BR (1993) Perioperative respiratory care of the patient undergoing upper abdominal surgery. Clinics in Chest Medicine 14: 253-261.

Dripps RD, Lamont A, Eckenhoff JE (1961) The role of anaesthesia in surgical mortality. Journal of the American Medical Association 178: 261-266.

Dureuil B, Viires N, Cantineau JP, Aubier M, Desmonts JM (1986) Diaphragmatic contractility after upper abdominal surgery. Journal of Applied Physiology 61: 1775-1780.

Fisher BW, Majumdar SR, McAlister FA (2002) Predicting pulmonary complications after nonthoracic surgery: a systematic review of blinded studies. American Journal of Medicine 112: 219-25.

Hall JC, Tarala RA, Hall JL (1996) Respiratory insufficiency after abdominal surgery. Respirology 1: 133-138.

Hosmer DW, Lemeshow S (1989) Applied Logistic Regression. New York: Wiley.

Johnson RG, Arozullah AM, Neumayer L, Henderson WG, Hosokawa P, Khuri SF (2007) Multivariable predictors of postoperative respiratory failure after general and vascular surgery: results from the patient safety in surgery study. Journal of the American College of Surgeons 204: 1188- 1198.

Kanat F, Golcuk A, Teke T, Golcuk M (2007) Risk factors for postoperative pulmonary complications in upper abdominal surgery. Australian and New Zealand Journal of Surgery 77: 135-141.

Kocabas A, Kara K, Ozgur G, Sonmez H, Burgut R (1996) Value of preoperative spirometry to predict postoperative pulmonary complications. Respiratory Medicine 90: 25-33.

Kroenke K, Lawrence VA, Theroux JF, Tuley MR, Hilsenbeck S (1993) Postoperative complications after thoracic and major abdominal surgery in patients with and without obstructive lung disease. Chest 104: 1445-1451.

Kuczmarski RJ, Flegal KM (2000) Criteria for definition of overweight in transition: background and recommendations for the United States. American Journal of Clinical Nutrition 72: 1074-1081.

Lawrence VA, Cornell JE, Smetana GW (2006) Strategies to reduce postoperative pulmonary complications after noncardiothoracic surgery: systematic review for the American College of Physicians. Annals of Internal Medicine 144: 596-608.

Lawrence VA, Dhanda R, Hilsenbeck SG, Page CP (1996) Risk of pulmonary complications after elective abdominal surgery. Chest 110: 744-750.

Mackay MR, Ellis E (2002) Physiotherapy outcomes and staffing resources in open abdominal surgery patients. Physiotherapy Theory and Practice 18: 75-93.

Mak PH, Campbell RC, Irwin MG (2002) The ASA physical status: inter-observer consistency. Anaesthesia and Intensive Care 30: 633-640.

McAlister FA, Bertsch K, Man J, Bradley J, Jacka M (2005) Incidence of and risk factors for pulmonary complications after nonthoracic surgery. American Journal of Respiratory and Critical Care Medicine 171: 514-517.

O'Brien MM, Gonzales R, Shroyer AL, Grunwald GK, Daley J, Henderson WG et al (2002) Modest serum creatinine elevation affects adverse outcome after general surgery. Kidney International 62: 585-592.

Pasquina P, Tramer MR, Granier J, Walder B (2006) Respiratory physiotherapy to prevent pulmonary complications after abdominal surgery. Chest 130: 1887-1889.

Pereira ED, Fernandes AL, da Silva Ancao M, de Arauja Pereres C, Atallah AN, Faresin SM (1999) Prospective assessment of the risk of postoperative pulmonary complications in patients submitted to upper abdominal surgery. Sao Paulo Medical Journal 117:151-60.

Rankin SL, Briffa TG, Morton AR, Hung J (1996) A specific activity questionnaire to measure the functional capacity of cardiac patients. American Journal of Cardiology 77: 1220-1223.

Serejo LG, da Silva-Junior FP, Bastos JP, de Bruin GS, Mota RM, de Bruin PF (2007) Risk factors for pulmonary complications after emergency abdominal surgery. Respiratory Medicine 101: 808-813.

Smetana GW, Lawrence VA, Cornell JE (2006) Preoperative pulmonary risk stratification for noncardiothoracic surgery: Systematic review for the American College of Physicians. Annals of Internal Medicine 144: 581-595.

Theadom A, Cropley M (2006) Effects of preoperative smoking cessation on the incidence and risk of intraoperative and postoperative complications in adult smokers: a systematic review. Tobacco Control 15: 325-358.

Thompson DA, Makary MA, Dorman T, Pronovost PJ (2006) Clinical and economic outcomes of hospital acquired pneumonia in intra-abdominal surgery patients. Annals of Surgery 243: 547-552.

Venebles WN, Ripley BD (1997) Modern applied statistics with S-plus (2nd ed). New York: Springer.

Rebecca L Scholes (1,2), Laura Browning (2), Ewa M Sztendur (3) and Linda Denehy (2)

(1) Monash University, (2) The University of Melbourne, (3) Victoria University Australia

Correspondence: Dr Rebecca Scholes, Department of Physiotherapy, Faculty of Medicine, Nursing and Health Sciences, Monash University, Australia. Email: [e-mail]

Table 1. Operational definition of predictors.

Predictor                   Definition

Gender                      Male or Female

Age                         Age in years

Surgical category           1. Hepatobiliary and upper gastrointestinal
                            2. Colorectal and lower gastrointestinal
                            3. Renal and Urology
                            4. Vascular
                            5. Other

Incision                    Defined according to site and type
Co-morbidity--cardiac       Documented history of cardiac disease
Co-morbidity--cancer        Documented history of cancer
Co-morbidity--respiratory   Documented history of chronic respiratory
Smoker                        disease
                            1. Non-smoker--never smoked
                            2. Ex-smoker--ceased smoking [greater than
                               or equal to] 8 weeks preoperatively
                            3. Current smoker- currently smokes

Body Mass Index (BMI)       Calculated as weight in kilograms/height
Obesity                       in [metres.sup.2]
Pre-morbid mobility         BMI > 30kg/[m.sup.2]
                            Self reported as:
                              1. Mobilise < 100 m
                              2. Mobilise [less than or equal to] 900 m
                              3. Mobilise [greater than or equal to]
                                 1 km
                              4. Mobilise [greater than or equal to]
                                 5 km
                              5. Mobilise [greater than or equal to]
                                 10 km

Predicted [VO.sub.2]max     [VO.sub.2]max calculated according to the
American Society of         Specific Activity Questionnaire (Rankin et
Anesthesiologists           al 1996) Documented by anaesthetist
physical status             preoperatively as:
                              1. Healthy patient
                              2. Patient with mild to moderate
                                 systemic disease
                              3. Patient with severe systemic disease
                                 that limits activity, but is not
                                 incapacitating
                              4. Patient with an incapacitating
                                 systemic disease that is a constant
                                 threat to life
                              5. Moribund patient who is not expected
                                 to survive 24 hours with or without
                                 operation

Anaesthesia duration        Time in minutes
Type of postoperative       1. Epidural
analgesia                   2. Morphine infusion
                            3. Patient-controlled analgesia
                            4. Patient-controlled epidural analgesia
                            5. Other

Intensive care              Length of postoperative stay in intensive
                            care unit in days

Presence of preoperative    History of acute upper or lower respiratory
chest infection             tract infection requiring medication in the
                            past 14 days [+ or -] presence of purulent
                            sputum

Abnormal preoperative       Abnormal auscultation, cough, thoracic
respiratory assessment      expansion, or preoperative oxygen
                            saturation levels

[VO.sub.2]max = maximal oxygen uptake

Table 2. Characteristics of patients with and
without postoperative pulmonary complications.

Characteristic                                    Participants

                                               PPC           No PPC
                                            (n = 35)       (n = 233)

Gender ratio, n male (%)                     21 (60)        128 (55)
Age (yr), mean (SD)                        61.4 (12.3)    57.4 (16.9)
Cardiac co-morbidity, n (%)                  13 (37)        73 (31)
Respiratory co-morbidity, n (%)              13 (37)        52 (22)
Cancer co-morbidity, n (%)                   24 (69)        138 (59)
Current smoker, n (%)                        13 (37)        51 (22)
Obese, n (%)                                 9 (26)         46 (20)
Body mass index (kg/[m.sup.2]),
  mean (SD)                                25.7 (5.1)      26.6 (5.6)
Predicted [VO.sub.2] max from SAQ
  (ml/kg/min), mean (SD)                   18.5 (6.2)      19.7 (7.7)
Preoperative chest infection, n (%)          4 (11)          19 (8)
Abnormal preoperative assessment, n (%)      19 (54)        90 (39)
Pre-morbid mobility [greater than or
  equal to] 1 km, n (%)                      26 (74)        192 (82)
ASA status, n (%)
  1                                           2 (6)         29 (12)
  2                                          16 (46)        99 (42)
  3                                          14 (40)        72 (31)
  4                                           2 (6)          8 (3)
Missing data                                  1 (3)         25 (11)
Duration of anaesthesia (min) (SD)        280.3 (178.0)   196.2 (98.3)
Incision type--laparotomy, n (%)             27 (77)        176 (76)
Surgical category, n (%)
  Hepatobiliary and upper GI                 16 (46)        63 (27)
  Colorectal and lower GI                    14 (40)        121 (52)
  Renal and urology                           1 (3)         32 (14)
  Vascular                                    0 (0)          6 (3)
  Other                                      4 (11)          11 (5)
Type of analgesia, n (%)
  Epidural                                   24 (69)        134 (58)
  Morphine infusion                           1 (3)          12 (5)
  PCA                                         0 (0)         1 (0.4)
  PCEA                                       10 (29)        73 (31)
  Other                                       0 (0)          8 (3)
Postoperative ICU admission, n (%)           17 (49)        36 (15)
Length of post-op hospital stay
  (days), mean (SD)                        22.5 (28.0)     9.0 (7.4)

ASA = American Society of Anesthesiologists, GI =
gastrointestinal, ICU: Intensive care unit, PCA = Patient
controlled analgesia, PCEA = Patient controlled epidural
analgesia, PPC = Postoperative pulmonary complication, SAQ =
Specific Activity Questionnaire.

Table 3. Odds ratio (95% CI) of developing postoperative
pulmonary complications for each predictor and their statistical
significance (p value) from the Chi-square analysis.

Predictor                               Odds ratio        Significance

Anaesthetic category > 180 min     4.32 (1.73 to 10.80)     < 0.001
Hepatobiliary and upper
  GI surgery                       2.27 (1.10 to 4.69)      < 0.001
Current smoker                     2.11 (0.99 to 4.48)        0.05
Respiratory co-morbidity           2.08 (0.97 to 4.36)        0.06
Predicted [VO.sub.2] max
  < 19.37 ml/kg.min                2.03 (0.95 to 4.32)        0.06
Postoperative admission to ICU     5.17 (2.44 to 10.96)     < 0.001
Abnormal preoperative assessment   1.89 (0.92 to 3.86)        0.08
Age > 60 yr                        1.77 (0.85 to 3.67)        0.12
Premorbid mobility [greater than
  or equal to] 1 km                0.59 (0.26 to 1.35)        0.21
Cancer co-morbidity                1.50 (0.70 to 3.21)        0.29
Obese                              1.37 (0.60 to 3.12)        0.45
Cardiac co-morbidity               1.30 (0.62 to 2.71)        0.49
Preoperative chest infection       1.45 (0.46 to 4.55)        0.52
Gender                             1.23 (0.60 to 2.54)        0.57
ASA status > 2                     1.43 (0.69 to 2.96)        0.65
Postoperative epidural analgesia   1.48 (0.69 to 3.16)        0.71
Laparotomy incision                1.09 (0.47 to 2.54)        0.84

ASA = American Society of Anesthesiologists, ICU = Intensive care
unit, [VO.sub.2]max = maximal oxygen uptake, GI = gastrointestinal