New equations for predicting postoperative risk in patients with hip fracture

O-POSSUM and P-POSSUM as predictors of morbidity and mortality in older patients after hip fracture surgery: a meta-analysis

BACKGROUND

The POSSUM model has been widely used to predict morbidity and mortality after general surgery. Modified versions known as O-POSSUM and P-POSSUM have been used extensively in orthopedic surgery, but their accuracy is unclear. This systematic review evaluated the predictive value of these models in older patients with hip fractures.

METHODS

This study was performed and reported based on the "Preferred reporting items for systematic reviews and meta-analyses" guidelines. PubMed, Cochrane, EMBASE, and Web of Science were comprehensively searched for relevant studies, whose methodological quality was evaluated according to the "Methodological index for non-randomized studies" scale. Revman 5 was used to calculate weighted ratios of observed to expected morbidity or mortality.

RESULTS

The meta-analysis included 10 studies, of which nine (2549 patients) assessed the ability of O-POSSUM to predict postoperative morbidity, nine (3649 patients) assessed the ability of O-POSSUM to predict postoperative mortality, and four (1794 patients) assessed the ability of P-POSSUM to predict postoperative mortality. The corresponding weighted ratios of observed to expected morbidity or mortality were 0.84 (95% CI 0.70-1.00), 0.68 (95% CI 0.49-0.95), and 0.61 (95% CI 0.16-2.38).

CONCLUSIONS

While O-POSSUM shows reasonable accuracy in predicting postoperative morbidity in older patients with hip fractures, both P-POSSUM and O-POSSUM substantially overestimate postoperative mortality. The POSSUM model should be optimized further for this patient population.

Risk scoring models for patients with proximal femur fractures: Qualitative systematic review assessing 30-day mortality and ease of use

BACKGROUND

Hip fractures are a common orthopaedic injury affecting a particularly frail and vulnerable patient cohort. They are at risk of many complications, including prolonged length of stay and mortality. Efforts to identify those at high risk may be beneficial. Over 25 risk prediction models are published for patients with hip fractures.

AIM

The primary aim of this study was to assess the performance of predictor scores in predicting 30-day mortality. The secondary aim was to assess the ease of use of these systems.

METHODS

A qualitative systematic review was performed. A search was conducted on online databases, including PubMed, CINAHL, Clinical Trials.gov, Cochrane, DARE, EMBASE, SCOPUS, and Web of Science.. The terms fragility hip fractures and risk prediction models were utilised while performing the search. These were then expanded using Boolean operators and similar terms. Search results were imported to Covidence. Primary observational studies using one or more hip fracture mortality prediction models and 30-day mortality as an outcome were included. Systematic reviews and studies on specific patient groups defined other medical conditions (e.g. COVID positive or dialysis patients) were excluded.

RESULTS

3,101 studies were screened following duplicate removal. 34 papers were included in the review, in which 23 scoring systems were reported. Six of these were pre-operative and reported in multiple studies. Most demonstrated appropriate fit and fair discrimination. Five of the six pre-operative scoring systems examined, displayed appropriate ease of use, allowing risk calculation at the time of admission.

CONCLUSION

Nottingham Hip Fracture Score remains the most extensive reported scoring system and performs fair overall with AUROCs of 0.64-0.80 and good fit in calibration across all studies. However, new systems utilise many similar predictors. There is a need for the standardisation of publications on scoring systems to allow further systematic review and meta-analyses.

Hip fracture mortality: Predictive models

The preoperative estimation of the risk of mortality after a hip fracture is very useful to plan time of surgery and perioperative care, inform patients and families about the prognosis and allows comparisons between different units. Different models have been developed to stratify mortality risk, but they show heterogeneity in terms of type of population and variables included, monitoring the time and statistical methods used, which makes it difficult to establish comparisons between them. The vast majority of them are awaiting external validation in populations different from those in which they were originally proposed. So far, the Nottingham Hip Fracture Score (NHFS) and the Orthopaedic Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (O-POSSUM) are the most commonly used models. The NHFS is simpler and faster to apply, and by not including intraoperative variables can be used at the time of admission.

Accuracy of the Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity score and the Nottingham risk score in hip fracture patients in Sweden - A prospective observational study

BACKGROUND

Little is known about accuracy of common risk prediction scores in elderly patients suffering from hip fractures. The objective of this study was to investigate accuracy of the Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) score, Portsmouth-POSSUM (P-POSSUM) score and the Nottingham Hip Fracture Score (NHFS) for prediction of mortality and morbidity in this patient group.

METHODS

This was a prospective single centre observational study on 997 patients suffering out-of-hospital cervical, trochanteric or subtrochanteric fracture of the neck of the femur. Calibration and discrimination was assessed by calculating the ratio of observed to expected events (O:E) and areas under receiver operating characteristics curves (ROC).

RESULTS

The 30-day mortality was 6.2% and complications, as defined by POSSUM, occurred in 41% of the patients. Overall O:E ratios for POSSUM, P-POSSUM and NHFS scores for 30-day mortality were 0.90, 0.98, and 0.79 respectively. The models underestimated mortality in the lower risk bands and overestimated mortality in the higher risk bands. In contrast, POSSUM predicted morbidity well with O:E ratios close to unity in most risk bands. The areas under the ROC curves for the scoring systems was 0.60-0.67.

CONCLUSION

The POSSUM score and NHFS show moderate calibration and poor discrimination in this cohort. The results suggest that mortality and morbidity in hip fracture patients are largely dependent on factors that are not included in these scores.

How to better identify patients at high risk of postoperative complications?

PURPOSE OF REVIEW

Preoperative risk assessment and perioperative factors may help identify patients at increased risk of postoperative complications and allow postoperative management strategies that improve patient outcomes. This review summarizes historical and more recent scoring systems for predicting patients with increased morbidity and mortality in the postoperative period.

RECENT FINDINGS

Most prediction scores predict postoperative mortality with, at best, moderate accuracy. Scores that incorporate surgery-specific and intraoperative covariates may improve the accuracy of traditional scores. Traditional risk factors including increased ASA physical status score, emergent surgery, intraoperative blood loss and hemodynamic instability are consistently associated with increased mortality using most scoring systems.

SUMMARY

Preoperative clinical risk indices and risk calculators estimate surgical risk with moderate accuracy. Surgery-specific risk calculators are helpful in identifying patients at increased risk of 30-day mortality. Particular attention should be paid to intraoperative hemodynamic instability, blood loss, extent of surgical excision and volume of resection.

O-POSSUM score predicts morbidity and mortality in patients undergoing hip fracture surgery

PURPOSE

The aim of this study is to evaluate the O-POSSUM score capacity to predict the morbidity and mortality of patients undergoing hip fracture surgery.

MATERIAL AND METHODS

We retrospectively reviewed the clinical records of patients older than 65years old, operated on for hip fractures between January 2012 and December 2013. Of 229 patients, the mean age was 82.3years and 170 were women. We collected comorbidities, type of surgery, and expected morbidity and mortality O-POSSUM values.

RESULTS

After a minimum follow up of one year, 38 deaths were reported and 77 patients had complications. The expected mortality according to the O-POSSUM was 35 patients and expected morbidity 132.

CONCLUSION

By comparing the observed results with those predicted, the O-POSSUM scale is reliable in predicting mortality and overestimates morbidity.

Modernising Hip Fracture Anaesthesia

Hip fracture carries a 30-day mortality of around 8% in the United Kingdom. This figure has remained relatively unchanged despite modern developments in anaesthetic technique. These range from improvements in perioperative analgesia and mortality scoring systems, changes to intra-operative anaesthetic technique and strategies to reduce the requirement for blood transfusion. In this article, we review the current literature on the perioperative management of patients undergoing hip fracture surgery including some of the current controversies.

Risk scoring models for predicting peri-operative morbidity and mortality in people with fragility hip fractures: Qualitative systematic review

RATIONALE

Accurate peri-operative risk prediction is an essential element of clinical practice. Various risk stratification tools for assessing patients' risk of mortality or morbidity have been developed and applied in clinical practice over the years. This review aims to outline essential characteristics (predictive accuracy, objectivity, clinical utility) of currently available risk scoring tools for hip fracture patients.

METHODS

We searched eight databases; AMED, CINHAL, Clinical Trials.gov, Cochrane, DARE, EMBASE, MEDLINE and Web of Science for all relevant studies published until April 2015. We included published English language observational studies that considered the predictive accuracy of risk stratification tools for patients with fragility hip fracture.

RESULTS

After removal of duplicates, 15,620 studies were screened. Twenty-nine papers met the inclusion criteria, evaluating 25 risk stratification tools. Risk stratification tools considered in more than two studies were; ASA, CCI, E-PASS, NHFS and O-POSSUM. All tools were moderately accurate and validated in multiple studies; however there are some limitations to consider. The E-PASS and O-POSSUM are comprehensive but complex, and require intraoperative data making them a challenge for use on patient bedside. The ASA, CCI and NHFS are simple, easy and inexpensive using routinely available preoperative data. Contrary to the ASA and CCI which has subjective variables in addition to other limitations, the NHFS variables are all objective.

CONCLUSION

In the search for a simple and inexpensive, easy to calculate, objective and accurate tool, the NHFS may be the most appropriate of the currently available scores for hip fracture patients. However more studies need to be undertaken before it becomes a national hip fracture risk stratification or audit tool of choice.

Predicting 30-day mortality following hip fracture surgery: evaluation of six risk prediction models

INTRODUCTION

While predictors for mortality after hip fracture surgery have been widely studied, research regarding risk prediction models is limited. Risk models can predict mortality for individual patients, provide insight in prognosis, and be valuable in surgical audits. Existing models have not been validated independently. The purpose of this study is to evaluate the performance of existing risk models for predicting 30-day mortality following hip fracture surgery.

PATIENTS AND METHODS

In this retrospective study, all consecutive hip fracture patients admitted between 2004 and 2010 were included. Predicted mortality was calculated for individual patients and compared to the observed outcome. The discriminative performance of the models was assessed using the area under the receiver operating characteristic curve (AUC). Calibration was analysed with the Hosmer-Lemeshow goodness-of-fit test.

RESULTS

A literature search yielded six risk prediction models: the Charlson Comorbidity Index (CCI), Orthopaedic Physiologic and Operative Severity Score for the enUmeration of Mortality and Morbidity (O-POSSUM), Estimation of Physiologic Ability and Surgical Stress (E-PASS), a risk model by Jiang et al., the Nottingham Hip Fracture Score (NHFS), and a model by Holt et al. The latter three models were specifically designed for the hip fracture population. All models except the O-POSSUM achieved an AUC greater than 0.70, demonstrating acceptable discriminative power. The score by Jiang et al. performed best with an AUC of 0.78, this was however not significantly different from the NHFS (0.77) or the model by Holt et al. (0.76). When applying the Hosmer-Lemeshow goodness-of-fit test, the model by Holt et al., the NHFS and the model by Jiang et al. showed a significant lack of fit (p<0.05). The CCI, O-POSSUM and E-PASS did not demonstrate lack of calibration.

DISCUSSION

None of the existing models yielded excellent discrimination (AUC>0.80). The best discrimination was demonstrated by the models designed for the hip fracture population, however, they had a lack of fit. The NHFS shows most promising results, with reasonable discrimination and extensive validation in earlier studies. Additional research is needed to examine recalibration and to determine the best risk model for predicting early mortality following hip fracture surgery.

Intensive care monitoring after total joint replacement

Patient safety is a critical issue in elective total joint replacement surgery. Identifying risk factors that might predict complications and intensive care unit (ICU) admission proves instrumental in reducing morbidity and mortality. The institution's experience with risk stratification and pre-operative ICU triage has resulted in a reduction in unplanned ICU admissions and post-operative complications after total hip replacement. The application of the prediction tools to total knee replacement has proven less robust so far. This work also reviews areas for future research in patient safety and cost containment.

Predictive value of E-PASS and POSSUM systems for postoperative risk assessment of spinal surgery

Object

The Estimation of Physiological Ability and Surgical Stress (E-PASS) and Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) systems are surgical risk scoring systems that take into account both the patient's preoperative condition and intraoperative variables. While they predict postoperative morbidity and mortality rates for several types of surgery, spinal surgeries are currently not included. The authors assessed the usefulness of E-PASS and POSSUM algorithms and compared the predictive ability of both systems in patients with spinal disorders considered for surgery.

Methods

The E-PASS system includes a preoperative risk score, a surgical stress score, and a comprehensive risk score that is determined by both the preoperative risk score and surgical stress score. The POSSUM system is composed of a physiological score and an operative severity score; its total score is based on both the physiological score and operative severity score. The authors calculated the E-PASS and POSSUM scores for 601 consecutive patients who had undergone spinal surgery and investigated the relationship between the individual scores of both systems and the incidence of postoperative complications. They also assessed the correctness of the predicted morbidity rate of both systems.

Results

Postoperative complications developed in 64 patients (10.6%); there were no in-hospital deaths. All EPASS scores (p ≤ 0.001) and the operative severity score and total score of the POSSUM (p < 0.03) were significantly higher in patients with postoperative complications than in those without postoperative complications. The morbidity rates correlated linearly and significantly with all E-PASS scores (p ≤ 0.001); their coefficients (preoperative risk score, ρ = 0.179; surgical stress score, ρ = 0.131; and comprehensive risk score, ρ = 0.198) were higher than those for the POSSUM scores (physiological score, ρ = 0.059; operative severity score, ρ = 0.111; and total score, ρ = 0.091). The area under the receiver operating characteristic curve for the predicted morbidity rate was 0.668 for the E-PASS and 0.588 for the POSSUM system.

Conclusions

As E-PASS predicted morbidity more correctly than POSSUM, it is useful for estimating the postoperative risk of patients considered for spinal surgery.

Validity of E-PASS System for Postoperative Morbidity of Spinal Surgery

STUDY DESIGN

A single-center retrospective cohort study.

OBJECTIVE

To evaluate the ability of the Estimation of Physiologic Ability and Surgical Stress (E-PASS) system to predict postoperative risk in patients scheduled for spinal surgery.

SUMMARY OF BACKGROUND DATA

The E-PASS system is a surgical audit to predict postoperative morbidity and mortality in general surgery. It is currently not applied in patients with spinal disorders.

METHODS

The E-PASS system is comprised of a preoperative risk score (PRS), a surgical stress score (SSS), and a comprehensive risk score (CRS). The latter reflects both the PRS and SSS. We calculated the E-PASS scores for 275 consecutive patients who underwent spinal surgery and evaluated the relationship between the incidence of postoperative complications and each score of the E-PASS system and their ability to predict postoperative morbidity.

RESULTS

Postoperative complications developed in 31 patients (11.3%). All E-PASS scores were significantly higher in patients with postoperative complications and they were linearly correlated with the overall incidence of postoperative complications. In particular, PRS was correlated with complications at nonsurgical sites and SSS with surgical site complications. The area under the receiver operating characteristic curve (AUC) for PRS and SSS was higher in patients with complications at nonsurgical and surgical sites, respectively. The AUC for CRS exhibited good predictive power for both types of complication.

CONCLUSIONS

The E-PASS system correctly predicted morbidity. The predictive ability of CRS was good for overall morbidity. The E-PASS system is useful for the accurate prediction of the risk for in-hospital morbidity in individual patients scheduled for spinal surgery.

Comparison of the POSSUM score and P-POSSUM score in patients with femoral neck fracture

PURPOSE

The ageing of the population in developed countries has led to an increased number of patients with hip fractures all over the world. POSSUM and P-POSSUM scores predict morbidity and mortality of patients who will be undergoing a surgical treatment. The aim of this study was to evaluate accuracy of these two scores in hip-fractured patients.

MATERIALS AND METHODS

Between January and December 2012, in our department 144 patients were hospitalised for femoral neck fractures according to the grade III or IV of Garden's classification treated with total hip arthroplasty or endoprosthesis. POSSUM scores and P-POSSUM scores were calculated for each patient with complete clinical data. We then calculated the observed and the expected ratio.

RESULTS

134 patients were eligible: 110 females and 24 males. The mean age for women was 79 years, and the mean age for men was 84 years. We observed 13 deaths and 66 complications. The POSSUM scores predicted 16 deaths and 60 complications, while P-POSSUM scores predicted 6 deaths. The O/E ratio for POSSUM mortality was 0.81 and for P-POSSUM was 2.17, while POSSUM morbidity was 1.1.

CONCLUSION

In our study, we have shown that on the one hand, the POSSUM score predicted accurately both the mortality and morbidity in patients undergoing surgery for the femoral neck fracture, while on the other hand, the P-POSSUM score underestimated them. For this reason, we believe that the POSSUM is indeed a good audit tool, which can accurately predict both mortality and morbidity in a cohort of patients.

Evaluation of a Modified POSSUM Scoring System for Predicting the Morbidity in Patients Undergoing Lumbar Surgery

For most spine surgeons, operative intervention is common for the treatment of lumbar disc herniation, lumbar stenosis, lumbar fracture or lumbar spondylolisthesis. However, with the increase in lumbar surgery, the complication rate increases accordingly. Whereas the Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) scoring system has been widely used to predict morbidity in various surgical fields, the application of this system in lumbar surgery has not been reported. From January 2008 to January 2010, we recruited 158 patients (85 males and 73 females) with operation for lumbar disc herniation, lumbar stenosis, lumbar fracture, or lumbar spondylolisthesis. All patients were analyzed to compare the morbidity by a modified POSSUM scoring system. According to the modified POSSUM, the expected morbidity was 51 cases (32.3 %), whereas the observed mortality was 42 cases (26.6 %). The overall observed-to-expected ratio was 0.82, and the chi-squared test indicated no statistically significant difference between the expected and observed morbidities (χ (2) = 1.23, P = 0.27), suggesting that the modified POSSUM can accurately estimate the outcome. The modified POSSUM scoring system we developed is a useful tool for predicting and evaluating morbidity in lumbar surgery. Further studies are required to investigate whether this scoring system can predict mortality.

Sernbo score predicts survival after intracapsular hip fracture in the elderly

INTRODUCTION

The Sernbo score uses four factors (age, social situation, mobility and mental state) to divide patients into a high-risk and a low-risk group. This study sought to assess the use of the Sernbo score in predicting mortality after an intracapsular hip fracture.

METHODS

A total of 259 patients with displaced intracapsular hip fractures were included in the study. Data from prospectively generated databases provided 22 descriptive variables for each patient. These included operative management, blood tests and co-mobidities. Multivariate analysis was used to identify significant predictors of mortality.

RESULTS

The mean patient age was 85 years and the mean follow-up duration was 1.5 years. The one-year survival rate was 92% (± 0.03) in the low-risk group and 65% (± 0.046) in the high-risk group. Four variables predicted mortality: Sernbo score >15 (p=0.0023), blood creatinine (p=0.0026), ASA (American Society of Anaesthesiologists) grade >3 (p=0.0038) and non-operative treatment (p=0.0377). Receiver operating characteristic curve analysis showed the Sernbo score as the only predictor of 30-day mortality (area under curve 0.71 [0.65-0.76]). The score had a sensitivity of 92% and a specificity of 51% for prediction of death at 30 days.

CONCLUSIONS

The Sernbo score identifies patients at high risk of death in the 30 days following injury. This very simple score could be used to direct extra early multidisciplinary input to high-risk patients on admission with an intracapsular hip fracture.

Unplanned admission to the intensive care unit after total hip arthroplasty

Triage to the intensive care unit (ICU) after elective total hip arthroplasty proves a complex medical and resource decision point. A total of 1259 consecutive total hip arthroplasties were reviewed; 89 patients experienced unplanned ICU admissions. Significant risk factors for ICU admission in univariate analysis were age greater than 75 years, revision surgery, obstructive sleep apnea, creatinine clearance less than 60 mL/min, prior myocardial infarction, American Society of Anesthesiologist class 3 or greater, use of vasopressors intraoperatively, and body mass index greater than 35 kg/m(2). With multiple regression, age greater than 75 years (odds ratio [OR], 2.6 [1.2-5.6]), revision surgery (OR, 5.8 [3.0-11.4]), creatinine clearance less than 60 mL/min (OR, 6.5 [2.5-16.3]), prior myocardial infarction (OR, 7.2 [2.0-25.4]), and body mass index greater than 35 kg/m(2) (OR, 2.9 [1.4-6.2]) were predictive of unplanned ICU admission. With 1 risk factor, the risk of ICU admission was 40%, 2 (75%), 3 (93.5%), 4 (98.5%), and 5 (>99%). A prospective study of these risk factors is needed to establish a threshold for planned ICU admission.

The 1-year mortality of patients treated in a hip fracture program for elders

Comanagement of geriatric hip fracture patients with standardized protocols has been shown to improve short-term outcomes after surgery. A standardized, patient-centered, comanaged Hip Fracture Program for Elders is examined for 1-year mortality. Patients ≥60 years of age who were treated in the Hip Fracture Program for Elders were comanaged by orthopaedic surgeons and geriatricians. Data including age, place of origin, procedure, length of stay, 1-year mortality, Charlson score, and activities of daily living (ADLs) were retrospectively collected. A total of 758 patients ≥60 years of age with hip fractures between April 15, 2005, and March 1, 2009, were included. Their data were analyzed, and the Social Security Death Index and the hospital data system were searched for mortality data. Seventy-eight percent were female, with a mean age of 84.8 years. The mean Charlson score was 3. Fifty percent were admitted from an institutional setting. The overall 1-year mortality was 21.2%. Age (odds ratio [OR] = 1.03, 95% confidence interval [CI] = 1.00-1.05; P = .02), male gender (OR = 1.55, 95% CI = 1.01-2.36; P = .04), low Parker mobility score (OR = 2.94, 95% CI = 1.31-6.57; P = .01), and a Charlson score of 4 or greater (OR = 2.15, 95% CI = 1.30-3.55; P = .002) were predictive of 1-year mortality. ADL dependence was a borderline predictor, as was medium Parker mobility score. Prefracture residence and moderate comorbidity (Charlson score of 2-3) were not independently predictive of mortality at 1 year after adjusting for other characteristics. A comprehensive comanaged hip fracture program for elders not only improves the short-term outcomes but also demonstrates a low 1-year mortality rate, particularly in patients from nursing facilities.