Evaluation of the POSSUM scoring system in lung surgery. Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity

Inter-rater agreement in pPOSSUM scores of geriatric trauma patients: a prospective evaluation

PURPOSE

Risk prediction models are widely used in the perioperative setting to identify high-risk patients who may benefit from additional care and to aid clinical decision-making. pPOSSUM is such a prediction model, however, little is known about the inter-rater agreement when scoring subjective parameters. This study assessed the inter-rater agreement between clinicians of different specialties and work-level when scoring 30 clinical case reports of geriatric hip fracture patients with pPOSSUM.

METHODS

Eighteen clinicians of the department of Surgery (three specialists, four residents), Anaesthesiology (four specialists, two residents) and Emergency Medicine (three specialists, two residents) who were familiar with the pPOSSUM scoring system were asked to calculate the scores. The kappa statistic and the statistical method of Fleiss were used to analyse inter-rater agreement.

RESULTS

The response rate was 100%. Among surgeons, Anaesthesiologists and Emergency department doctors (ED), the overall mean kappa values were 0.42, 0.08 and 0.20, respectively. Among surgery, anaesthesiology and ED residents the overall mean kappa values were 0.21, 0.33 and 0.37, respectively. Within the department of Surgery, Anaesthesiology and Emergency Medicine the overall mean kappa values were 0.23, 0.12 and 0.22, respectively. An overall mean kappa value of 0.19 was seen among all specialists. All residents had an overall mean kappa value of 0.21 and all clinicians had an overall mean kappa value of 0.21.

CONCLUSION

The overall inter-rater agreement of clinicians and interdisciplinary agreement when scoring geriatric hip fracture patients with pPOSSUM was low and prone to subjectivity in our study. A higher work-experience level did not lead to better agreement. When pPOSSUM is calculated without clinical assessment by the same clinician, caution is advised to prevent over-reliance on the pPOSSUM risk prediction model.

LEVEL OF EVIDENCE

III.

POSSUM and P-POSSUM Scoring in Hip Fracture Mortalities

INTRODUCTION

Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) and Portsmouth POSSUM (P-POSSUM) are general surgical tools used to efficiently assess mortality and morbidity risk. Data suggest that these tools can be used in hip fracture patients to predict morbidity and mortality; however, it is unclear what score indicates a significant risk on a case-by-case basis. We examined the POSSUM and P-POSSUM scores in a group of hip fracture mortalities in order to assess their accuracy in identification of similar high-risk patients.

MATERIALS AND METHODS

Retrospective analysis of all consecutive mortalities in hip fracture patients at a single tertiary care center over 2 years was performed. Patient medical records were examined for baseline demographics, fracture characteristics, surgical interventions, and cause of death. Twelve physiological and 6 operative variables were used to retrospectively calculate POSSUM and P-POSSUM scores at the time of injury.

RESULTS

Forty-seven hip fracture mortalities were reviewed. Median patient age was 88 years (range: 56-99). Overall, 68.1% (32) underwent surgical intervention. Mean predicted POSSUM morbidity and mortality rates were 73.9% (28%-99%) and 31.1% (5%-83%), respectively. The mean predicted P-POSSUM mortality rate was 26.4% (1%-91%) and 53.2% (25) had a P-POSSUM predicted mortality of >20%. Subgroup analysis demonstrated poor agreement between predicted mortality and observed mortality rate for POSSUM in operative (χ2 = 127.5, P < .00001) and nonoperative cohorts (χ2 = 14.6, P < .00001), in addition to P-POSSUM operative (χ2 = 101.9, P < .00001) and nonoperative (χ2 = 11.9, P < .00001) scoring.

DISCUSSION/CONCLUSION

Hip fracture patients are at significant risk of both morbidity and mortality. A reliable, replicable, and accurate tool to represent the expected risk of such complications could help facilitate clinical decision-making to determine the optimal level of care. Screening tools such as POSSUM and P-POSSUM have limitations in accurately identifying high-risk hip fracture patients.

Interventions to avoid pulmonary complications after lung cancer resection

Surgical resection of lung cancer is the preferred treatment for early-stage disease in medically fit patients. The rates of postoperative pulmonary complications (PPCs) such as pneumonia, empyema and atelectasis are as high as 10% in contemporary series. A review of the literature was performed to identify the best evidence supporting interventions to identify, prevent and treat PPCs. The use of patient risk scores, appropriate choice of antibiotic prophylaxis, intraoperative ventilatory strategies, chest physiotherapy, sputum management and non-invasive ventilatory support were specifically discussed, as was the relevant supporting data. Recommendations to guide best practice and inform future research questions are outlined.

Review of risk assessment tools to predict morbidity and mortality in elderly surgical patients

BACKGROUND

Informed surgical consent requires accurate estimation of risks and benefits. Multiple risk assessment tools are available; however, most are not widely used or are specific to certain interventions. Assessing surgical risk is especially challenging in elderly patients because of their range of comorbidities, level of frailty, or severity of illness and a number of available surgical interventions.

DATA SOURCES

We searched MEDLINE from January 2014 to July 2017 for studies that used risk assessment tools in studies on elderly surgical patients. We then sought the original articles describing each assessment tool and subsequent validation studies.

CONCLUSIONS

We identified risk assessment tools that can improve surgical risk assessment in elderly surgical patients. The majority of the identified tools are not commonly used for pre-operative risk assessment. NSQIP-PMP, mFI and SURPAS are promising tools. Age is commonly used to predict risk, but frailty may be a more appropriate measure.

External validation of the recalibrated thoracic revised cardiac risk index for predicting the risk of major cardiac complications after lung resection

BACKGROUND

The recalibrated thoracic revised cardiac risk index (ThRCRI) has been recently proposed as a specific tool for cardiac risk stratification before lung resection. However, the ThRCRI has never been externally validated in a population other than the one from which it was derived. The objective of this study was to validate the ThRCRI in an external population of candidates having undergone major lung resections to assess its reliability for cardiac risk stratification across different samples.

METHODS

We analyzed 2,621 patients undergoing lobectomy (2,431) or pneumonectomy (190) in a single center from 2000 to 2009. Patients were grouped into four classes of risk (A, B, C, and D) according to the recalibrated ThRCRI. The outcome variable measured was the occurrence of major cardiac complications (cardiac arrest, complete heart block, acute myocardial infarction, pulmonary edema, cardiac death during admission). Incidence of major cardiac events was assessed in the four risk class groupings to assess the discriminative ability of the index score.

RESULTS

The incidence of major cardiac morbidity was 2.2% (59 cases). Patients were grouped into four risk classes according to their recalibrated ThRCRI. Incidence of major cardiac morbidity in risk classes A, B, C, and D were 0.9%, 4.2%, 8%, and 18%, respectively (p<0.0001).

CONCLUSIONS

The recalibrated ThRCRI is a reliable instrument that can be used during preoperative workup to differentiate patients needing further cardiologic testing from those who can proceed without any further cardiac testing.

Recalibration of the revised cardiac risk index in lung resection candidates

BACKGROUND

The revised cardiac risk index (RCRI) has been proposed as a tool for cardiac risk stratification before lung resection. However, the RCRI was originally developed from a generic surgical population including a small group of thoracic patients. The objective of this study was to recalibrate the RCRI in candidates for major lung resections to provide a more specific instrument for cardiac risk stratification.

METHODS

One thousand six hundred ninety-six patients who underwent lobectomy (1,426) or pneumonectomy (270) in two centers between the years of 2000 and 2008 were analyzed. Stepwise logistic regression and bootstrap analyses were used to recalibrate the six variables comprising the RCRI. The outcome variable was occurrence of major cardiac complications (cardiac arrest, complete heart block, acute myocardial infarction, pulmonary edema, or cardiac death during admission). Only those variables with a probability of less than 0.1 in more than 50% of bootstrap samples were retained in the final model and proportionally weighted according to their regression estimates.

RESULTS

The incidence of major cardiac morbidity was 3.3% (57 patients). Four of the six variables present in the RCRI were reliably associated with major cardiac complications: cerebrovascular disease (1.5 points), cardiac ischemia (1.5 points), renal disease (1 point), and pneumonectomy (1.5 points). Patients were grouped into four classes according to their recalibrated RCRI, predicting an incremental risk of cardiac morbidity (p < 0.0001). Compared with the traditional RCRI, the recalibrated score had a higher discrimination (c indexes, 0.72 versus 0.62; p = 0.004).

CONCLUSIONS

The recalibrated RCRI can be reliably used as a first-line screening instrument during cardiologic risk stratification for selecting those patients needing further cardiologic testing from those who can proceed with pulmonary evaluation without any further cardiac tests.

[POSSUM scoring system for predicting mortality in surgical patients]

This study evaluated the use of the POSSUM (Physiological and Operative Severity Score for Enumeration of Mortality and Morbidity) score for predicting mortality in surgical practice. In this study, 416 surgical patients admitted into ICUs for post-surgical care were analyzed. Both predicted and actual mortality rates were compared, according to four risk groups: 0-4%, 5-14%, 15-49%, 50% and over, and the area under the ROC curve of the POSSUM and APACHE II for mortality. The POSSUM and APACHE II scores overestimated the risk of death. The area under the ROC curve of the POSSUM was 0.762, and under APACHE II was 0.737, suggesting the use of POSSUM as an auxiliary tool to predict the risk of death in surgical patients.

Evaluation of POSSUM scoring system in the treatment of osteoporotic fracture of the hip in elder patients

OBJECTIVE

To evaluate the applicability of the modified physiological and operative severity score for enumeration of mortality and morbidity (POSSUM) scoring system in predicting mortality in the patients undergoing hip joint arthroplasty.

METHODS

A total of 295 patients with hip fractures were analyzed using the modified POSSUM surgical scoring system. The mean ages of the patients were 66.59 years in the complicative group, 62.28 years in noncomplicative group, 77.89 years in the death group and 63.25 years in the living group, respectively. The comparisons between the observed and predicted morbidity, between the observed and predicted mortality were made within 30 days after operation.

RESULTS

The average physiological scores and operative severity scores was 18.96+/-4.83 and 13.47+/-2.01 in complicative group, while 15.65+/-3.66 and 11.74+/-2.26 in noncomplicative group (P less than 0.05). The average physiological scores and operative severity scores was 25.56+/-3.78 and 14.22+/-0.67 in death group, while 16.46+/-4.09 and 12.25+/-2.33 in living group (P less than 0.05). Though POSSUM scoring system over-predicted the overall risk of death, its estimate was very close in the high risk groups (larger than 10% ). There was perfect consistence between the observed and the predicted morbidity as calculated by published predictor equation for morbidity, and consistence for mortality in the high risk band.

CONCLUSIONS

Modified POSSUM scoring system may be used to predict the morbidity in patients with hip fracture. Furthermore, POSSUM scoring system overpredicts the overall risk of death, but its estimate is close to the actual data in the high risk band (larger than 10%).

Evaluation of O-POSSUM in predicting in-hospital mortality after resection for oesophageal cancer

Background

The aims of the present study were to validate the Physiological and Operative Severity Score for the enUmeration of Mortality adjusted for oesophagogastric surgery (O-POSSUM).

Methods

Data on patients who underwent potentially curative oesophagectomy in a tertiary referral centre for adenocarcinoma or squamous cell carcinoma of the oesophagus were analysed. The in-hospital mortality predicted by O-POSSUM was compared with the actual value by linear analysis.

Results

Twenty-four (3·6 per cent) of 663 patients died in hospital. The observed : predicted ratio for in-hospital mortality was 0·29. The model had a poor fit (P &lt; 0·001). The area under the receiver–operator characteristic curve was 0·60 (95 per cent confidence interval 0·47 to 0·72); P = 0·113). O-POSSUM score was not related to the severity of complications.

Conclusion

O-POSSUM overpredicted in-hospital mortality threefold and could not identify patients at higher risk of death. O-POSSUM needs substantial modification before it can be used for comparison of treatment outcomes between centres.

Comparison of P-POSSUM and O-POSSUM in predicting mortality after oesophagogastric resections

BACKGROUND

P-POSSUM (Physiological and Operative Severity Score for the enumeration of Mortality and morbidity) predicts mortality and morbidity in general surgical patients providing an adjunct to surgical audit. O-POSSUM was designed specifically to predict mortality and morbidity in patients undergoing oesophagogastric surgery.

AIM

To compare P-POSSUM and O-POSSUM in predicting surgical mortality in patients undergoing elective oesophagogastric cancer resections.

METHODS

Elective oesophagogastric cancer resections in a district general hospital from 1990 to 2002 were scored by P-POSSUM and O-POSSUM methods. Observed mortality rates were compared to predicted mortality rates in six risk groups for each model using the Hosmer-Lemeshow goodness-of-fit test. The power to discriminate between patients who died and those who survived was assessed using the area under the receiver-operator characteristic (ROC) curve.

RESULTS

313 patients underwent oesophagogastric resections. 32 died within 30 days (10.2%). P-POSSUM predicted 36 deaths (chi2 = 15.19, df = 6, p = 0.019, Hosmer-Lemeshow goodness-of-fit test), giving a standardised mortality ratio (SMR) of 0.89. O-POSSUM predicted 49 deaths (chi2 = 16.51, df = 6, p = 0.011), giving an SMR of 0.65. The area under the ROC curve was 0.68 (95% confidence interval 0.59 to 0.76) for P-POSSUM and 0.61 (95% confidence interval 0.50 to 0.72) for O-POSSUM.

CONCLUSION

Neither model accurately predicted the risk of postoperative death. P-POSSUM provided a better fit to observed results than O-POSSUM, which overpredicted total mortality. P-POSSUM also had superior discriminatory power.

Sistema POSSUM. Un instrumento de medida de la calidad en el paciente quirúrgico

INTRODUCTION

The POSSUM scale (Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity) is a scoring system that is used to predict risk-adjusted mortality and morbidity rates in a wide variety of surgical procedures. In this prospective study, the validity of the POSSUM scale was evaluated in patients undergoing laparotomy in a general surgery department.

PATIENTS AND METHODS

The POSSUM scale was prospectively applied in all patients undergoing elective and emergency laparotomy in the general surgery department of a level II hospital over 8 months. A total of 105 patients were included, of which 24 underwent emergency laparotomy and 81 underwent elective surgery. Predicted mortality and morbidity rates were calculated by using the POSSUM scale. These results were compared with actual outcomes by using Fisher's test.

RESULTS

The mean physiological score was 23.4 points (range: 12-40 points), while the mean surgical score was 11.3 points (range: 6-24 points). Three patients died during the postoperative period and 47 had morbidity. When the observed results for mortality were compared with those predicted by the POSSUM scoring system, no significant differences were observed in the analysis by risk groups, except in the risk group < 20 %, in which the POSSUM scale overestimated mortality. The risk of morbidity was underestimated by the POSSUM scale in the risk group < 20 %.

CONCLUSION

The POSSUM scoring system is a useful predictor of morbidity and mortality in patients undergoing emergency and elective laparotomy.

Postoperative respiratory failure

This analysis differentiates the causes of postoperative respiratory failure. Respiratory failure in thoracic patients is broken down into two distinct groups, aspiration and pneumonia, promoting actions to prevent respiratory failure. The goal is to develop different strategies to avoid postoperative respiratory failure using an active approach (what can be done in the management of patients undergoing lung resection to prevent problems) rather than passive approach (what patient factors caused problems after surgery). Before that analysis, the operative risks after lung resections (lobectomies, pneumonectomies, elderly patients) and esophagectomies are reviewed to understand the data.

Optimization of lung function before pulmonary resection: pulmonologists' perspectives

Many risk factors for morbidity and mortality with lung resection have been identified. Factors such as age, gender, and cancer stage cannot be altered, but lung function can be optimized by treating COPD or asthma with bronchodilators, corticosteroids, or antibiotics (when indicated) and by inspiratory muscle training. Although smoking cessation 2 months in advance of surgery may not be feasible, cessation nevertheless should be encouraged because it may decrease postoperative inflammation and in the long-term may decrease the risk of recurrence. In addition, morbidity and mortality can be minimized by careful patient selection using lung scanning or CT to determine predicted postoperative functions (FEV1% and DLco%) and some form of exercise testing, such as cardiopulmonary exercise testing or simple stair climbing. When the risk of surgery is high, any benefit from possible cure must be weighed against the risk of long-term disability or death. Although much data are available to guide clinicians in these decisions, there still is no one test that provides the answer in individual cases. The art and science of medicine must merge at this point.

Are postoperative complications genetically determined by TNF-β NcoI gene polymorphism?

BACKGROUND

Postoperative infectious complications are the leading causes for postoperative sepsis. In severe sepsis, tumor necrosis factor-beta (TNF-beta) NcoI polymorphism was associated with increased mortality. Therefore, the aim of this study was to determine whether the biallelic NcoI polymorphism within the TNF locus is associated with the development of postoperative complications.

METHODS

One hundred sixty patients were included in this prospective observation study. Patients undergoing major gastrointestinal surgery, such as esophagectomy, gastrectomy, Whipple operation, major liver resection, or colon resection were included. Patients were monitored during the clinical course, and postoperative complications, divided into severe and minor complications, were documented. The NcoI restriction fragment length polymorphism of the TNF-beta gene was determined by polymerase chain reaction; gene expression as well as complications were correlated.

RESULTS

The patients' genotype distribution and demographic characteristics were comparable within the different groups of operations. Patients with the heterozygous genotype TNF-beta1/beta2 had a 1.6-fold higher relative risk for developing complications. If patients with the homozygous genotype TNF-beta2 developed a complication, they had a 1.5-fold higher relative risk for severe complications. Furthermore, the mortality of patients with postoperative sepsis who were homozygous for the genotype TNF-beta2 was significantly elevated.

CONCLUSIONS

The TNF-beta NcoI polymorphism influences the development of postoperative complications. While the genotype TNF-beta1/beta2 has a higher risk for developing complications in general, the TNF-beta2/beta2 genotype is associated with more severe complications and mortality from sepsis.

Risk-adjusted surgical audit with the POSSUM scoring system in a developing country. Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity

BACKGROUND

The Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) is an objective and appropriate scoring system for risk-adjusted comparative general surgical audit. This score was devised in the UK and has been used widely, but application of POSSUM to centres outside the UK has been limited, especially in developing countries. This prospective study validated its application in a surgical practice with a different population and level of resources.

METHODS

All general surgical patients who were operated on under regional or general anaesthesia as inpatients over a 4-month period at Sarawak General Hospital in 1999 were entered into the study. All data (12 physiological and six operative factors) were analysed for mortality only with the POSSUM equation and the modified Portsmouth POSSUM (P-POSSUM) equation. Comparisons were made between predicted and observed mortality rates according to four groups of risk: 0-4, 5-14, 15-49 and 50 per cent or more using the 'linear' method of analysis.

RESULTS

There were 605 patients who satisfied the criteria for the study. Some 56.7 per cent of patients were in the lowest risk group. The POSSUM predictor equation significantly overestimated the mortality in this group, by a factor of 9.3. The overall observed mortality rate was 6.1 per cent and, again, the POSSUM predictor equation overestimated it at 10.5 per cent (P < 0.01). In contrast, the observed and predicted mortality rates for all risk groups, including the predicted overall mortality rate of 4.8 per cent, were comparable when the P-POSSUM predictor equation was used.

CONCLUSION

The POSSUM scoring system with the modified P-POSSUM predictor equation for mortality was applicable in Malaysia, a developing country, for risk-adjusted surgical audit. This scoring system may serve as a useful comparative audit tool for surgical practice in many geographical locations.

Operative mortality rates among surgeons: comparison of POSSUM and p-POSSUM scoring systems in gastrointestinal surgery

PURPOSE

The original Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity and the more recent Portsmouth predictor equation for mortality scoring systems were developed to provide risk-adjusted mortality rates in general surgery. The aim of this study was to compare crude and risk-adjusted operative mortality rates among four surgeons using the above scoring systems and assess their applicability for patients scored retrospectively.

METHODS

A total of 505 consecutive patients undergoing major gastrointestinal surgery were analyzed; 65 percent underwent colorectal, 27.5 percent underwent upper gastrointestinal, and 7.5 percent underwent small-bowel surgery. The observed:predicted mortality ratios using the Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity and Portsmouth predictor equation for mortality scoring systems were calculated for each surgeon.

RESULTS

The actual overall operative mortality rate was 11.1 percent (elective was 3.9 percent, and emergency was 25.1 percent). The Portsmouth predictor equation for mortality equation predicted a mortality rate of 11.3 percent (P = 0.51). However, the Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity scoring system was found to overpredict death by a factor of two: 21.5 percent (P < 0.001). Mortality rates among the four surgeons varied from 7.6 to 14.7 percent but depended on the proportion of elective vs. emergency surgery. The observed:predicted ratio for Portsmouth predictor equation for mortality was close to unity (0.905-1.067) for all surgeons, but it was 0.45 to 0.56 for Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity.

CONCLUSION

The Portsmouth predictor equation for mortality equation seems to be a more accurate predictor of mortality in gastrointestinal surgery. It would seem to provide the best choice for analyzing operative mortality rates for individual surgeons, taking into account variation in case mix and fitness of patients even when scored retrospectively. This has important implications for the future assessment of surgeons' clinical standards and the assessment of quality of surgical care.