Hospital Frailty Risk Score Outperforms Current Risk Stratification Models in Primary Total Hip and Knee Arthroplasty

Hospital frailty risk score predicts postoperative outcomes after endoscopic endonasal resection of non-functioning pituitary adenomas

PURPOSE

Frailty indices are invaluable resources in risk stratification and predicting high-value care outcomes for neurosurgical patients. The Hospital Frailty Risk Score (HFRS) is a recently developed and validated method for evaluating frailty; however, its implementation has yet to be assessed in patients with non-functioning pituitary adenomas undergoing endoscopic endonasal resection. In this study, we aimed to evaluate HFRS's predictive ability for high-value care outcomes, namely postoperative complications, length of stay (LOS), and hospital charges, and to compare it to other traditionally used frailty indices.

METHODS

A retrospective review of electronic medical records from 2017 to 2020. A total of 109 ICD-10 codes corresponding to various frailty-related conditions were used to identify the components of HFRS. These components were then used to calculate the HFRS for each patient, with higher scores indicative of elevated frailty. Standard multivariate logistic regression models were employed to explore the association between HFRS and high-value care outcomes. Model discrimination was assessed using the area under the ROC curves, and the DeLong test was used to compare AUCs.

RESULTS

A total of 172 patients were included, with a mean age of 57.27 ± 12.95 years and an average HFRS score of 3.65 ± 3.27. Among patients, 56% were male, 5.2% experience postoperative complications, 23.3% endured extended LOS, 25.0% incurred high hospital charges. In multivariate regression models, greater HFRS was significantly and independently associated with postoperative complications (OR = 1.51, P < 0.001), extended LOS (OR = 1.17, P = 0.006) and high hospital charges (OR = 1.18, P = 0.004). HFRS had the highest AUC compared to other frailty indices and was the most parsimonious model, with AUC values of 0.82, 0.64, and 0.63 for predicting complications, extended LOS, and higher charges, respectively.

CONCLUSION

Higher HFRS scores are significantly associated with postoperative complications, prolonged LOS, and high hospital charges for patients undergoing pituitary surgery.

Impact of the hospital frailty risk score on outcomes following primary total elbow arthroplasty

BACKGROUND

The Hospital Frailty Risk Score (HFRS) has demonstrated strong correlation with adverse outcomes in various joint replacement surgeries, yet its applicability in total elbow arthroplasty (TEA) remains unexplored. The purpose of this study is to assess the association between HFRS and postoperative complications following elective primary TEA.

METHODS

The Nationwide Readmissions Database was queried to identify patients undergoing primary TEA from 2016-2020. The HFRS was used to compare medical, surgical, and clinical outcomes of frail vs. nonfrail patients. Mean and relative costs, total hospital length of stay, and discharge disposition for frail and nonfrail patients were also compared.

RESULTS

We identified 2049 primary TEA in frail patients and 3693 in nonfrail patients. Frail patients had increased complication rates including acute respiratory failure (13.6% vs. 1.1%; P < .001), urinary tract infections (12.3% vs. 0.0%; P < .001), transfusions (3.9% vs. 1.1%; P < .001), pneumonia (1.1% vs. 0.2%; P < .001), acute respiratory distress syndrome (3.2% vs. 0.6%; P < .001), sepsis (0.7% vs. 0.1%; P < .001), and hardware failure (1.2% vs. 0.1%; P < .001). Frail patients also experienced higher rates of readmission (37% vs. 25%; P < .001) and death (1.7% vs. 0.2%; P < .001), while being less likely to undergo revision (6.5% vs. 17%; P < .001). Frail patients incurred higher health-care costs ($28,497 vs. $23,377; P < .001) and longer length of stay (5.3 days vs. 2.6 days; P < .001), with reduced likelihood of routine hospital stays (36% vs. 71%; P < .001) and increased utilization of short-term hospitalization (P < .001), care facilities (P < .001), and home health-care services (P < .001).

CONCLUSION

HFRS is a validated indicator of frailty and is strongly associated with increased rates of complications in patients undergoing elective primary TEA. These findings should be considered by orthopedic surgeons when assessing surgical candidacy and discussing treatment options in this at-risk patient population.

Influence of parkinson's disease on complications and revisions in total hip and knee arthroplasty: insights from a matched pair analysis

PURPOSE

The outcome of elective total joint arthroplasty (TJA) in patients with Parkinson's disease (PD) is controversial due to the concomitant risk profile. This study investigated postoperative complications and revision rates following total hip (THA) and knee arthroplasty (TKA) in patients with PD.

METHODS

Ninety-six patients with PD undergoing THA or TKA were matched 1:1 with non-PD patients using propensity score matching for age, sex and comorbidity (Charlson Comorbidity index, CCI). Rates of revisions, medical and surgical complications were compared. Univariate and multivariate regression analyses were calculated.

RESULTS

PD patients exhibited higher rates of revision-surgeries within 90 days (13.5% vs. 5.2%; p = 0.048), medical complications (68.8% vs. 43.8%; p < 0.001) and surgical complications (40.6% vs. 21.9%; p = 0.005). Multivariate regression analysis confirmed PD as a significant risk factor for complications and long-term revision-surgeries.

CONCLUSION

PD increases the risk of adverse outcomes following THA and TKA. Improvements in pre-operative planning and post-operative care are critical to the improvement of outcomes in this vulnerable population.

A high hospital frailty risk score indicates an increased risk for complications following surgical treatment of proximal humerus fractures

BACKGROUND

Approximately 70 % of proximal humerus fractures (PHF) occur after the age of 60. High complication rates have been described in correlation with the treatment of PHF. Major risk factors for the outcome might be frailty, mobility and comorbidities of patients at the time of hospital admission. The aim of this study was to create risk adjusted quality indicators for surgical treatment of proximal humerus fractures based on German claims data and to evaluate the impact of the Hospital Frailty Risk Score (HFRS) on risk adjustment.

METHODS

Retrospective claims data (2015-2021) were used to create risk adjusted quality indicators for eight outcomes by clustered multivariable logistic regression. The comparison of different risk adjustment model performances was done by ROC-AUC and Standardized Mortality/Morbidity Ratios.

RESULTS

In total, N = 34,912 patients (median age 75 years, 80.3 % female) were included. The most common surgical procedure was open reduction and internal fixation with plate osteosynthesis with 39.7 %, followed by reverse shoulder arthroplasty with 25.3 %. The most influential risk factor for all outcomes was a high HFRS with an Odds Ratio of 2.0 (95 %-Confidence Interval 1.8-2.3) for any secondary surgery (365 days) up to an Odds Ratio of 17.6 (95 %-Confidence Interval 14.9-20.8) for general complications during the index stay.

CONCLUSION

Comparative quality reporting for the surgical treatment of PHF appears feasible with the developed models for risk adjustment using claims data. Preoperative evaluation of HFRS in PHF can contribute to risk assessment, and individual patient management. It therefore enables personalized treatment decisions.

Impact of Frailty on COVID-19 Hospitalizations: Results from the California State Inpatient Database

OBJECTIVES

Frail patients are at greater risk of experiencing adverse clinical outcomes in any critical illness due to decreased physiologic reserves, greater susceptibility to the adverse effects of treatment, and greater needs for intensive care. In this study, we sought to assess the prevalence of frailty and associated adverse in-hospital outcomes among coronavirus disease 2019 (COVID-19) hospitalizations using the 2020 California State Inpatient Database (SID).

METHODS

For this study, we conducted a retrospective analysis of data from all COVID-19 hospital patients aged 18 years and older. We identified hospitalizations that were at high risk of frailty using the Hospital Frailty Risk Score. The primary outcome of our study was in-hospital mortality, and the secondary outcomes were prolonged length of stay, vasopressor use, mechanical ventilation, and intensive care unit admission.

RESULTS

The prevalence of frailty was 44.3% among COVID-19 hospitalizations. Using propensity score matching analysis, we found that the odds of mortality (odds ratio [OR] 4.54, 95% confidence interval [CI] 4.28-4.82), prolonged length of stay (OR 2.81, 95% CI 2.70-2.90), vasopressor use (OR 8.65, 95% CI 7.45-10.03), mechanical ventilation (OR 6.90, 95% CI 6.47-7.35), and intensive care unit admission (OR 7.17, 95% CI 6.71-7.66) were significantly higher among the group of frail patients.

CONCLUSION

Our findings show that frailty could be used for assessing and risk stratifying patients for improved hospital outcomes.

Comparing Common Risk Assessment Tools to Predict Outcomes in Total Knee Arthroplasty

BACKGROUND

A number of tools exist to aid surgeons in risk assessment, including the Charlson Comorbidity Index (CCI), the Elixhauser Comorbidity Index (ECI), and various measures of frailty, such as the Hospital Frailty Risk Score (HFR). While all of these tools have been validated for general use, the best risk assessment tool is still debated. Risk assessment is particularly important in elective surgery, such as total joint arthroplasty. The aim of this study is to compare the predictive power of the CCI, ECI, and HFR in the setting of total knee arthroplasty (TKA).

METHODS

All patients who underwent TKA were identified via International Statistical Classification of Diseases and Related Health Problems, Tenth Revision code from the National Readmissions Database, years 2016 to 2019. Patient demographics, perioperative complications, and hospital-associated outcomes were recorded. Receiver operating characteristic (ROC) curves were created and area under the curves (AUCs) evaluated to gauge the predictive capabilities of each risk assessment tool (CCI, ECI, and HFR) across a range of outcomes.

RESULTS

A total of 1,930,803 patients undergoing TKA were included in our analysis. For mortality, ECI was most predictive (0.95 AUC), while HFR and CCI were 0.75 and 0.74 AUC, respectively. For periprosthetic fractures, ECI was 0.78 AUC, HFR was 0.68 AUC, and CCI was 0.66 AUC. For joint infections, the ECI was 0.78 AUC, the HFR was 0.63 AUC, and the CCI was 0.62 AUC. For 30-day readmission, ECI was 0.79 AUC, while HFR and CCI were 0.6 AUC. For 30-day reoperation, ECI was 0.69 AUC, while HFR was 0.58 AUC and CCI was 0.56 AUC.

CONCLUSIONS

Our analysis shows that ECI is superior to CCI and HFR for predicting 30-day postoperative outcomes following TKA. Surgeons should consider assessing patients using ECI prior to TKA.

5-Factor Modified Frailty Index as a Predictor of Outcomes After Hemiarthroplasty or Total Hip Arthroplasty for Femoral Neck Fracture

INTRODUCTION

Although the 5-factor modified frailty index (mFI-5) has been shown to be an independent predictor of complications after primary total hip arthroplasty (THA), its predictive value has not been evaluated in the setting of hip fracture. We therefore assessed the utility of mFI-5 score as an independent predictor of morbidity and mortality in patients who underwent THA or hemiarthroplasty for femoral neck fracture.

METHODS

The American College of Surgeons National Surgical Quality Improvement database was queried for all patients with femoral neck fractures treated with THA or hemiarthroplasty between 2006 and 2020. A multivariate logistic regression analysis was done using mFI-5 as a predictor while controlling for baseline demographic and clinical variables.

RESULTS

In total, 45,185 patients (hemiarthroplasty: 37,645; THA: 7,540) were identified. For hemiarthroplasty patients, the mFI-5 strongly predicted risk of any complication (OR, 1.1; 95% CI, 1.1 to 1.2; P < 0.001), bleeding (OR, 1.2; 95% CI, 1.1 to 1.3; P < 0.001), and readmission (OR, 1.2; 95% CI, 1.1 to 1.3; P < 0.001). For THA patients, the mFI-5 was a strong predictor of any complication (OR, 1.2; 95% CI, 1.0 to 1.3; P = 0.023), pneumonia (OR, 1.4; 95% CI, 1.0 to 2.0; P = 0.047), and readmission (OR, 1.3; 95% CI, 1.1 to 1.6; P = 0.004).

DISCUSSION

The mFI-5 is an independent predictor of morbidity and complications after hemiarthroplasty and THA for femoral neck fracture. Importantly, readmission risk was predicted by the mFI-5. The mFI-5 may present a valuable clinical tool for assessment of high-risk patients who might require additional resources and specialized care after femoral neck fracture.

Patient Frailty is Correlated With Increased Adverse Events and Costs After Revision Knee Arthroplasty

BACKGROUND

Frailty can predict adverse outcomes after various orthopaedic procedures, but is not well-studied in revision total knee arthroplasty (rTKA). We investigated the correlation between the Hospital Frailty Risk Score (HFRS) and post-rTKA outcomes.

METHODS

Using the Nationwide Readmissions Database, we identified rTKA patients discharged from January 2017 to November 2019 for the most common diagnoses (mechanical loosening, infection, and instability). Using HFRS, we compared 30-day readmission rate, length of stay, and hospitalization cost between frail and nonfrail patients with multivariate and binomial regressions. The 30-day complication and reoperation rates were compared using univariate analyses. We identified 25,177 mechanical loosening patients, 12,712 infection patients, and 9,458 instability patients.

RESULTS

Frail patients had higher rates of 30-day readmission (7.8 versus 3.7% for loosening, 13.5 versus 8.1% for infection, 8.7 versus 3.9% for instability; P < .01), longer length of stay (4.1 versus 2.4 days for loosening, 8.1 versus 4.4 days for infection, 4.9 versus 2.4 days for instability; P < .01), and greater cost ($32,082 versus $27,582 for loosening, $32,898 versus $28,115 for infection, $29,790 versus $24,164 for instability; P < .01). Frail loosening patients had higher 30-day complication (6.8 versus 2.9%, P < .01) and reoperation rates (1.8 versus 1.2%, P = .01). Frail infection patients had higher 30-day complication rates (14.0 versus 8.3%, P < .01). Frail instability patients had higher 30-day complication (8.0 versus 3.5%, P < .01) and reoperation rates (3.2 versus 1.6%, P < .01).

CONCLUSIONS

The HFRS may identify patients at risk for adverse events and increased costs after rTKA. Further research is needed to determine causation and mitigate complications and costs.

Frailty Among Revision Total Knee Arthroplasty Recipients: Epidemiology and Propensity Score-weighted Analysis of Effect on In-hospital Postoperative Outcomes

BACKGROUND

Frailty has been shown to correlate with worse outcomes after total knee arthroplasty (TKA), although less is known regarding its effect on revision TKA (rTKA). This study examines the epidemiologic characteristics and inpatient outcomes of patients with frailty undergoing rTKA.

METHODS

Discharge data from National Inpatient Sample registry were used to identify all patients aged 50 years or older who underwent rTKA between 2006 and 2015. Patients were stratified into frail and nonfrail groupings, based on the presence of specific International Classification of Diseases-9 diagnostic coding. An analysis comparing the epidemiology, medical comorbidities, and propensity score-weighted postoperative clinical and economic outcomes of the two groups was done.

RESULTS

From 2006 to the third quarter of 2015, a total of 576,920 patients (17,727 frail) who underwent rTKA were included. The average age in the study's population was 67.2 years, with a female distribution of 57.4%. Frail patients were more likely to exhibit markedly higher rates of almost all modified Elixhauser Comorbities than their nonfrail counterparts. Frail patients were also more likely to undergo different types of revisions, including an increased rate of removal of the prosthesis without replacement. In addition, frail patients displayed increased likelihood of experiencing any postoperative complication, deep vein thrombosis, postoperative anemia, respiratory complications, and wound dehiscence. Frail patients experienced lower rates of discharge home and increased length of stay than the nonfrail cohort.

DISCUSSION

Patients with frailty undergoing rTKA are at markedly higher risk for inpatient postoperative complications and increased length of stay. Understanding the implications of frailty within rTKA is essential for risk assessment and preoperative optimization for this expanding population.

Combining the Hospital Frailty Risk Score With the Charlson and Elixhauser Multimorbidity Indices to Identify Older Patients at Risk of Poor Outcomes in Acute Care

OBJECTIVE

The Hospital Frailty Risk Score (HFRS) can be applied to medico-administrative datasets to determine the risks of 30-day mortality and long length of stay (LOS) in hospitalized older patients. The objective of this study was to compare the HFRS with Charlson and Elixhauser comorbidity indices, used separately or combined.

DESIGN

A retrospective analysis of the French medical information database. The HFRS, Charlson index, and Elixhauser index were calculated for each patient based on the index stay and hospitalizations over the preceding 2 years. Different constructions of the HFRS were considered based on overlapping diagnostic codes with either Charlson or Elixhauser indices. We used mixed logistic regression models to investigate the association between outcomes, different constructions of HFRS, and associations with comorbidity indices.

SETTING

743 hospitals in France.

PARTICIPANTS

All patients aged 75 years or older hospitalized as an emergency in 2017 (n=1,042,234).Main outcome measures: 30-day inpatient mortality and LOS >10 days.

RESULTS

The HFRS, Charlson, and Elixhauser indices were comparably associated with an increased risk of 30-day inpatient mortality and long LOS. The combined model with the highest c-statistic was obtained when associating the HFRS with standard adjustment and Charlson for 30-day inpatient mortality (adjusted c-statistics: HFRS=0.654; HFRS + Charlson = 0.676) and with Elixhauser for long LOS (adjusted c-statistics: HFRS= 0.672; HFRS + Elixhauser =0.698).

CONCLUSIONS

Combining comorbidity indices and HFRS may improve discrimination for predicting long LOS in hospitalized older people, but adds little to Charlson's 30-day inpatient mortality risk.

Understanding the role of frailty in local and systemic complications and healthcare resource utilization in acute pancreatitis: Findings from a national cohort

BACKGROUND

Acute pancreatitis (AP) is a significant gastrointestinal cause of hospitalization with increasing incidence. Risk stratification is crucial for determining AP outcomes, but the association between frailty and AP outcomes is poorly understood. Moreover, age disparities in severity indices for AP complicate risk assessment. This study investigates frailty's impact on local and systemic complications in AP, readmission rates, and healthcare resource utilization.

METHODS

Using the National Readmission Database from 2016 to 2019, we identified adult AP patients and assessed frailty using the Frailty Risk Score. Our analysis included local and systemic complications, resource utilization, readmission rates, procedures performed, and hospitalization outcomes. Multivariate regression was employed, and statistical significance was set at P < 0.05 using Stata version 14.2.

RESULTS

Among 1,134,738 AP patients, 6.94 % (78,750) were classified as frail, with a mean age of 63.42 years and 49.71 % being female. Frail patients experienced higher rates of local complications (e.g., pseudocyst, acute pancreatic necrosis, walled-off necrosis) and systemic complications (e.g., pleural effusion, acute respiratory distress syndrome, sepsis, abdominal compartment syndrome) compared to non-frail patients. Frailty was associated with increased readmission rates and served as an independent predictor of readmission. Frail patients had higher inpatient mortality (7.11 % vs. 1.60 %), longer hospital stays, and greater hospitalization costs.

CONCLUSION

Frailty in AP patients is linked to elevated rates of local and systemic complications, increased mortality, and higher healthcare costs. Assessing frailty is crucial in AP management as it provides a valuable tool for risk stratification and identifying high-risk patients, thereby improving overall outcomes.

Six-Item Modified Frailty Index independently predicts complications following total shoulder arthroplasty

Background

In the realm of orthopedic surgery, frailty has been associated with higher rates of complications following total hip and total knee arthroplasties. Among various measures of frailty, the Six-Item Modified Frailty Index (MF-6) has recently gained popularity as a predictor for postoperative complications. The purpose of this study was to investigate MF-6 as a predictor for early postoperative complications in the elderly patient population following total shoulder arthroplasty (TSA).

Methods

The authors queried the American College of Surgeons National Surgical Quality Improvement Program database for all patients who underwent TSA between 2015 and 2020. Patient demographics and comorbidities were compared between cohorts using bivariate logistic regression analysis. Multivariate logistic regression, adjusted for all significantly associated patient demographics and comorbidities, was used to identify associations between the MF-6 score and postoperative complications.

Results

Of total, 9228 patients were included in this study: 8764 (95.0%) had MF-6 <3, and 464 (5.0%) patients had MF-6 ≥3. Multivariate analysis found MF-6 ≥3 to be independently associated with higher rates of urinary tract infection (odds ratio [OR]: 2.79, 95% confidence interval [CI]: 1.49-5.23; P = .001), blood transfusion (OR: 1.53, 95% CI: 1.01-2.32; P = .045), readmission (OR: 1.58, 95% CI: 1.06-2.35; P = .024), and non-home discharge (OR: 2.60, 95% CI: 2.08-3.25; P < .001).

Conclusion

A high MF-6 score (≥3) in patients aged 65 and older is independently associated with higher rates of urinary tract infection, blood transfusion, readmission, and non-home discharge following TSA. The MF-6 score can be easily calculated preoperatively and may allow for better preoperative risk stratification.

Frailty, length of stay and cost in hip fracture patients

A hip fracture causes high morbidity and mortality. Frailty is associated with adverse outcomes and increased costs. Frailty measured using the Hospital Frailty Risk Score (HFRS) is associated with higher costs and adverse outcomes. HFRS is useful as a fuss-free frailty measurement in the management of older adults with hip fractures.

INTRODUCTION

Hip fractures account for an increasing number of hospital admissions around the world and are associated with high rates of morbidity and mortality. Frailty is increasingly recognized to be associated with adverse outcomes and increased costs. The purpose of this study is to determine the association of the Hospital Frailty Risk Score (HFRS) with the healthcare cost and outcomes in older adults who present with a hip fracture.

METHODS

A retrospective analysis was performed on 1014 patients ≥ 60 years who presented with a hip fracture between January 2016 to June 2020. Each patient was classified into HFRS low, intermediate or high frailty cohorts. Demographics, hip fracture type, comorbidities, Charlson Comorbidity Index (CCI), American Society of Anesthesiologist score (ASA), costs, length of stay, time to surgery, complications, readmission rate and mortality were compared between the cohorts.

RESULTS

Median total hospitalization costs were significantly higher in the highest HFRS (SGD$22,432) patients as compared to intermediate (SGD$18,759) and low HFRS (SGD$15,671) patients. The difference between the high and low groups remains significant after adjusting for covariates using quantile regression. Similar results were shown for median length of stay (14 vs 10 vs 8 days), total number of complications (2 vs 1 vs 0) and adjusted time to surgery (p < 0.05). HFRS was not associated with 30-day readmission or 30-day or 1-year mortality.

CONCLUSION

Frailty is associated with a marked increase in total costs in hip fracture patients. HFRS proved useful in estimating LOS and outcomes for older patients with hip fractures.

Phenotypic Frailty Score Predicts Perioperative Outcomes for Geriatric Total Joint Arthroplasty

Various assessment tools are often used to predict perioperative morbidity among patients older than 75 years who undergo total joint arthroplasty. Yet, few studies describe the use of phenotypic frailty as a predictor for outcomes. The goal of this study was to assess phenotypic frailty with the Sinai Abbreviated Geriatric Evaluation (SAGE) and compare its utility with established assessment tools used in practice. We specifically asked: (1) Can SAGE predict 30-day outcomes, including postoperative delirium? (2) Can SAGE determine the risk of prolonged hospital length of stay? (3) Is SAGE predictive for 30-day readmissions? (4) Can SAGE determine the risk of discharge to a specialized facility? Patients undergoing total hip arthroplasty and total knee arthroplasty were evaluated with the American Association of Anesthesiologists Physical Status (ASA), Charlson Comorbidity Index (CCI), 5-point Modified Frailty Score (5-FS), and SAGE. Assessment scores were determined for each patient, and every incremental change in score was used to predict the likelihood of perioperative complications. A receiver operating characteristic analysis was also performed to calculate testing sensitivity for each assessment tool. The SAGE scores were more likely to predict 30-day complications (odds ratio [95 CI], 2.21 [1.32-3.70]), postoperative delirium (6.40 [1.78-23.03]), and length of stay greater than 2 days (3.90 [1.00-15.7]) compared with ASA, CCI, and 5-FS values. The SAGE scores were not predictive of readmission (1.77 [0.66-4.72]) or discharge to a specialized facility (1.48 [0.80-2.75]). The SAGE score was a more sensitive predictor (area under the curve, 0.700) for perioperative morbidity compared with ASA (0.638), CCI (0.662), and 5-FS (0.644) values. Therefore, SAGE scores can reliably assess risk of perioperative morbidity and may have better clinical utility than ASA, CCI, and 5-FS values for patients undergoing total joint arthroplasty. [Orthopedics. 2022;45(6):e315-e320.].

[Preoperative screening for risk factors]

The demographic change and continuously improving healthcare lead to increasing numbers of older, comorbid patients in elective orthopedic surgery. Perioperative risk assessment is crucial for patient counseling and preoperative planning. Risk factors, such as heart failure, chronic obstructive pulmonary disease, peripheral arterial occlusive disease, anemia, malnutrition, obesity, smoking and insufficiently controlled diabetes mellitus are common in patients undergoing elective orthopedic surgery. A thorough and early screening not only enables the individual assessment of the risk profile but in an elective setting also enables the chance for modification of certain risk factors in order to reduce the individual perioperative risk. Meanwhile, recommendations regarding risk stratification and adjustment of modifiable risk factors are included in national guidelines on the indications for elective total hip arthroplasty.

Hospital frailty risk score predicts adverse events in spine surgery

PURPOSE

The Hospital Frailty Risk Score (HFRS) is derived from routinely collected data and validated as a geriatric risk stratification tool. This study aimed to evaluate the utility of the HFRS as a predictor for postoperative adverse events in spine surgery.

METHODS

In this retrospective analysis of 2042 patients undergoing spine surgery at a university spine center between 2011 and 2019, HFRS was calculated for each patient. Multivariable logistic regression models were used to assess the relationship between the HFRS and postoperative adverse events. Adverse events were compared between patients with high or low frailty risk.

RESULTS

Patients with intermediate or high frailty risk showed a higher rate of reoperation (19.7% vs. 12.2%, p < 0.01), surgical site infection (3.4% vs. 0.4%, p < 0.001), internal complications (4.1% vs. 1.1%, p < 0.01), Clavien-Dindo IV complications (8.8% vs. 3.4%, p < 0.001) and transfusion (10.9% vs. 1.5%, p < 0.001). Multivariable logistic regression analyses revealed a high HFRS as independent risk factor for reoperation [odds ratio (OR) = 1.1; 95% confidence interval (CI) 1.0-1.2], transfusion (OR = 1.3; 95% CI 1.2-1.4), internal complications (OR = 1.2; 95% CI 1.1-1.3), surgical site infections (OR = 1.3; 95% CI 1.2-1.5) and other complications (OR = 1.3; 95% CI 1.2-1.4).

CONCLUSION

The HFRS can predict adverse events and is an easy instrument, fed from routine hospital data. By identifying risk patients at an early stage, the individual patient risk could be minimized, which leads to less complications and lower costs.

LEVEL OF EVIDENCE

Level III - retrospective cohort study TRIAL REGISTRATION: The study was approved by the local ethics committee (20-1821-104) of the University of Regensburg in February 2020.

Hospital Frailty Risk Score predicts adverse events in older patients with vertebral compression fractures: Analysis of data in a nationwide in-patient database in Japan

AIMS

This study investigated the usefulness of frailty for predicting adverse events in patients with vertebral compression fractures (VCFs) during hospitalization using data obtained from the Japanese health insurance system.

METHODS

This retrospective cohort study of patients with VCFs aged ≥65 years was conducted using a nationwide database in Japan. We examined the relationships between frailty risk, classified using the Hospital Frailty Risk Score (HFRS), in-hospital mortality, and complications such as pressure ulcers and pneumonia. Multivariate logistic regression analysis was used to estimate the association between the HFRS and the outcomes of patients with VCFs.

RESULTS

In this study, the data of 30 980 in-patients with VCFs were analyzed. Of these patients, 76.8%, 21.3%, and 1.9% had low, intermediate, and high risks of frailty, respectively. The higher the risk of frailty, the higher the rate of in-hospital mortality and the occurrence of all complications (P < 0.001 for trend). An intermediate risk of frailty was independently associated with in-hospital mortality (odds ratio [OR], 1.421; P < 0.001), whereas a high risk of frailty did not show statistical significance (OR, 1.385; P = 0.150). Each frailty risk was independently associated with the occurrence of all complications during hospitalization.

CONCLUSIONS

The HFRS, which can assess the risk of frailty based on routinely collected medical records, was predictive of adverse events in older patients with VCFs based on a nationwide database in Japan. Future studies need to assess approaches to preventing adverse events in frail VCF patients. Geriatr Gerontol Int 2022; ••: ••-••.

[Risk management in orthopedic surgery : Stratification and adjustment of patient-individual risk factors]

Preoperative identification of patients at risk of postoperative complications enables better patient education and surgical planning for the orthopedic surgeon. In addition to demographic and intervention-specific factors, a variety of instruments are available for individual risk assessment. The concept of frailty seems to be promising to identify patients at risk. Modifiable risk factors such as malnutrition, anemia, obesity, smoking, and insufficiently controlled diabetes mellitus are common in elective orthopedic patients. With the use of screening protocols, modifiable risk factors can be identified and optimized preoperatively in order to reduce the individual risk of complications. Recommendations regarding preoperative risk stratification and modification prior to elective hip replacement have meanwhile been incorporated in national guidelines.

Hospital Frailty Risk Score predicts adverse events in revision total hip and knee arthroplasty

Introduction

The Hospital Frailty Risk Score (HFRS) is a validated risk stratification model referring to the cumulative deficits model of frailty. The purpose of this study was to evaluate the HFRS as a predictor of 90-day readmission and complications after revision total hip (rTHA) and knee (rTKA) arthroplasty.

Methods

In a retrospective analysis of 565 patients who had undergone rTHA or rTKA between 2011 and 2019, the HFRS was calculated for each patient. Rates of adverse events were compared between patients with low and intermediate or high frailty risk. Multivariable logistic regression models were used to assess the relationship between the HFRS and post-operative adverse events.

Results

Patients with intermediate or high frailty risk showed higher rates of readmission (30days: 23.8% vs. 9.9%, p = 0.006; 90days: 26.2% vs. 13.0%, p < 0.018), surgical complications (28.6% vs. 7.8%, p < 0.001), medical complications (11.9% vs. 1.0%, p < 0.001), other complications (28.6% vs. 2.3%, p < 0.001), Clavien-Dindo grade IV complications (14.3% vs. 4.8%, p = 0.009), and transfusion (33.3% vs. 6.1%, p < 0.001). Multivariable logistic regression analyses revealed a high HFRS as independent risk factor for surgical complications (OR = 3.45, 95% CI 1.45-8.18, p = 0.005), medical complications (OR = 7.29, 95% CI 1.72-30.97, p = 0.007), and other complications (OR = 14.15, 95% CI 5.16-38.77, p < 0.001).

Conclusion

The HFRS predicts adverse events after rTHA and rTKA. As it derives from routinely collected data, the HFRS could be implemented automated in hospital information systems to facilitate identification of at-risk patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00264-021-05038-w.