Utility of Revised Risk Analysis Index as a Predictor of Mortality and Morbidity in Orthopaedic Trauma

Abstract

Objectives:

The aim of this study was to determine the applicability of the Revised Risk Analysis Index (RAI-Rev) in orthopaedic trauma and compare the predictive discrimination for the RAI-Rev and the 5-Item Modified Frailty Index (mFI-5) for 30-day postoperative outcomes.

Design:

This is a retrospective cohort study.

Setting:

The American College of Surgeons National Surgical Quality Improvement database was used.

Patient Selection:

All patients aged 18 or older who underwent surgical treatment for forearm, humerus, pelvis, acetabulum, femur, tibia, and hindfoot fractures from 2015 to 2020 were included.

Outcome:

30-day postoperative mortality, major complications, and wound complications consisting of surgical site infection, and wound dehiscence were measured.

Results:

A total of 206,352 patients met inclusion criteria. The mean age was 69 years, with 64.2% (n = 132,514) being female. Multivariate regression analysis showed that increasing frailty tiers in both RAI-Rev and mFI-5 were independent predictors of mortality, major complications, readmission, and wound complications. The cohort with the highest degree of frailty in both RAI-Rev and mFI-5 had the greatest risk of poor outcomes. RAI-Rev had significantly superior predictive discriminatory thresholds compared with mFI-5 for predicting 30-day mortality (C-statistic: RAI-Rev [0.84] and mFI-5 [0.67], P < 0.001), major complications (C-statistic: RAI-Rev [0.73] and mFI-5 [0.65], P < 0.001), and readmission (C-statistic: RAI-Rev [0.68] and mFI-5 [0.63], P < 0.001). However, mFI-5 outperformed RAI-Rev when predicting wound complications (C-statistic: RAI-Rev [0.52] and mFI-5 [0.55], P < 0.001).

Conclusion:

The RAI-Rev tool demonstrated superior predictability of postoperative morbidity, mortality, and readmission rates compared with mFI-5 but was less effective in predicting surgical site complications. These findings demonstrate the utility of RAI-Rev in anticipating postoperative complications in the setting of orthopaedic trauma, where optimizing surgical candidate selection is not always possible. Assessing the predicted morbidity and mortality through RAI-Rev enables surgeons to accurately identify patients at high risk of complications, which can further research investigation to mitigate this risk.

Orthopaedic trauma is a major cause of mortality and morbidity, placing a substantial burden on the US healthcare system.¹ A growing patient demographic is the elderly population with a notable degree of comorbidities that lead to worse postoperative outcomes.^1-3 With the American elderly population estimated to surpass 80 million individuals by the year 2050, the incidence of low-energy orthopaedic trauma can be expected to subsequently increase as well.⁴ While orthopaedic traumatologists do not always have the ability to wait for surgical optimization of their patient population, an emphasis should still be placed on preoperative identification of patients at risk of developing postoperative complications to help guide informed consent and clinical decision making with the patient.

Frailty, or a state of decreased physiologic reserve, offers insight into a patient's vulnerability to stressors and has been used to predict postoperative morbidity and mortality in multiple surgical populations.^5-7 As the average age of the general population rises and the subsequent incidence of low-energy traumatic orthopaedic injuries continues to increase, orthopaedic traumatologists may look to use risk assessment tools, such as frailty, to stratify patients and potentially decrease patient morbidity and mortality after surgical management.⁸ Numerous frailty indices have been investigated in the orthopaedic literature to predict the risk of postoperative morbidity and mortality, most commonly the 11-Item Modified Frailty Index (mFI-11) and 5-Item Modified Frailty Index (mFI-5).^9-12 However, there is a lack of consensus regarding the effectiveness and reliability of such indices when predicting postoperative complications within orthopaedics.^13-17 Furthermore, the mFI-11 and mFI-5 have been criticized for oversimplifying the multiple domains of frailty by focusing primarily on comorbidities, with more recent studies in favor of the externally validated Risk Analysis Index (RAI) proposed by Hall et al.^18,19 The RAI incorporates multiple patient factors beyond comorbidity. In 2020, Arya et al²⁰ published the Revised RAI (RAI-Rev) in an attempt to improve the discrimination along with the generalization of the model toward nonveteran surgical patients. Although RAI-Rev is superior in predictive value and discriminatory accuracy regarding postoperative adverse events within neurosurgery compared with mFI-5, RAI-Rev has not yet been investigated among the orthopaedic trauma population.^21,22

This study sought to determine the utility of the RAI-Rev in the orthopaedic trauma population and compare the predictive discrimination for the RAI-Rev and mFI-5 for 30-day postoperative outcomes. We hypothesize that the RAI-Rev will offer a more reliable risk assessment tool for short-term, postoperative adverse events compared with mFI-5.

Methods

Data Source

The American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database was designed in 1994 in an effort to improve the quality of healthcare delivery.²³ The database consists of cases submitted from 676 NSQIP-participating sites across the private center. In compliance with the NSQIP Data Use Agreement, we queried the NSQIP database from January 1, 2015, to December 31, 2020, encompassing roughly 6 million deidentified patient records and over 200 variables surrounding patient demographics, medical history, and postoperative outcomes. Quality assurance and data integrity are ensured by onsite surgical clinical reviewers and through internal audits.²³

Patient Population Baseline Characteristics and Outcomes

Inclusion criteria for this study were all patients aged 18 years or older who underwent surgical treatment for fractures of the forearm, humerus, pelvis, acetabulum, femur, tibia, or hindfoot as identified by the corresponding International Classification of Diseases (ICD)9/10-CM and Current Procedural Terminology codes (Supplementary File 1, http://links.lww.com/JG9/A412). Descriptive variables included patient demographics; body mass index; length of hospital stay (LOS); surgical time; American Society of Anesthesiologists status; discharge destination; and history of medical conditions or comorbidities such as diabetes mellitus, chronic obstructive pulmonary disease, congestive heart failure (CHF), dyspnea, hypertension, ascites, kidney failure, stroke, cancer, open wounds, bleeding disorders, preoperative transfusion, sepsis, functional dependence, and smoking status. The primary outcome assessed was 30-day mortality. Secondary outcomes assessed included 30-day wound complications (including wound dehiscence, as well as superficial, deep, and organ space surgical site infection), non-home discharge, 30-day readmission, 30-day revision surgery, extended LOS, and major complications (defined as prolonged intubation exceeding 48 hours, unplanned reintubation, sepsis, septic shock, pneumonia, deep vein thrombosis/thrombophlebitis, pulmonary embolism, acute cerebrovascular accident or stroke with neurological deficit(s), acute renal failure, myocardial infarction, or cardiac arrest requiring cardiopulmonary resuscitation).

Frailty Measures

Frailty, as rated by the mFI-5, was assessed by identifying the variables used in the mFI-5, which include the following: CHF, chronic obstructive pulmonary disease, hypertension, diabetes, and nonindependent functional status (Supplementary File 2, http://links.lww.com/JG9/A413). One point was assigned for each diagnosis, and the total number of points for each patient was calculated. Patients were grouped into four categories based on their mFI-5 frailty score: 0 = nonfrail, 1 = prefrail, 2 = frail, and ≥2 = severely frail. Frailty, as rated by the RAI-Rev, was assessed using the RAI-Rev scoring systems, adapted from previous studies by Hall et al and Arya et al.^19,20 RAI-Rev incorporates sex, age, cancer diagnosis (excluding melanoma), weight loss (unintentional weight loss of 4.5 kg over 3 months), renal failure, CHF, poor appetite, shortness of breath at rest, residence status (independence of living), cognitive decline, and activities of daily living (Supplementary File 3, http://links.lww.com/JG9/A414). RAI-Rev scores were categorized into robust, normal, frail, and very frail tiers based on the following ranges: robust ≤10, normal 11 to 20, frail 21 to 30, and very frail ≥31.

Statistical Analysis

Patients were grouped according to frailty status, and demographic characteristics were assessed using the chi square test for categorical variables and the Kruskal-Wallis test for continuous variables. Categorical variables were presented as counts with percentages, and continuous variables were presented as medians with interquartile range (IQR). We initially conducted univariate regression for each variable and the binary outcomes. Variables that were significantly associated with outcomes (P < 0.05) were used in a multivariate logistic regression, controlling for total operation time, LOS, fracture location, and open fracture for each cohort. Backward stepwise P value removal was used to build the final model, and model fit was assessed using the area under the curve. Only significant variables (<0.05) were retained in the final model. Receiver operating characteristic (ROC) curve analysis including area under the curve/C-statistics quantified the discrimination of each model. Differences in predictive performance (C-statistic) were assessed using the DeLong test. All statistical analyses were conducted using Statistical Package for Social Sciences 100 (SPSS, Version 29; IBM). For all purposes, a P value <0.05 was considered statistically significant.

Results

Patient Population Baseline Characteristics

A total of 206,352 patients (35.8% male) with a median age of 69 years (IQR: 54 to 80 years) were included in this study (Table 1). The median body mass index was 26.6 kg/m² (IQR: 23.8 to 29.0 kg/m²), and 18.5% (n = 34,443) of patients were reported as active smokers within 1 year. The most common medical comorbidities were hypertension (n = 100,748; 48.8%) and type 2 diabetes mellitus (n = 34,443; 16.7%). Stratification by frailty status as defined by the mFI-5 was as follows: 93,049 (45.1%) nonfrail; 73,395 (35.6%) prefrail; 34,548 (16.7%) frail; and 5,360 (2.6%) severely frail. Frailty status as defined by RAI-Rev was as follows: 26,926 (13.0%) robust; 69,360 (28.8%) normal; 86,409 (41.9%) frail; and 33,657 (16.3%) very frail.

Table 1.

Baseline Demographic Variables; Clinical Characteristics; and Postoperative Outcomes, Including Incidence of 30-Day Mortality, Readmission, Revision Surgery, Major Complications, and Discharge Disposition of Patients Undergoing Surgical Management of Orthopaedic Trauma

Variable	Cohort (n = 206,352)
Age (median, IQR)	69 years (54-80)
Female (n, %)	132,514 (64.2)
BMI (median, IQR)	26.6 kg/m2 (23.8-29.0)
Surgery indication (n, %)
Open fracture	3783 (1.8)
Elective case	71,242 (34.5)
Fracture location (n, %)
Forearm	34,100 (16.5)
Humerus	12,317 (6.0)
Pelvis	205 (0.1)
Acetabulum	771 (0.4)
Femur	109,359 (53.0)
Tibia	50,147 (24.3)
Hindfoot	819 (0.4)
Length of stay (median, IQR)	3 days (0-6)
Surgical time (median, IQR)	69 minutes (47-102)
Mortality	4745 (2.3)
Readmission	11,224 (5.4)
Revision surgery	4323 (2.1)
Frailty distribution based on mFI-5 (n, %)
Nonfrail	93,049 (45.1)
Prefrail	73,395 (35.6)
Frail	34,548 (16.7)
Severely frail	5360 (2.6)
Frailty distribution based on RAI-Rev (n, %)
Robust	26,926 (13.0)
Normal	59,360 (28.8)
Frail	86,409 (41.9)
Very frail	33,657 (16.3)
Preoperative clinical status/comorbidities (n, %)
Diabetes mellitus	34,443 (16.7)
Severe COPD	16,128 (7.8)
CHF	4177 (2.0)
Current smoker	38,195 (18.5)
Disseminated cancer	4858 (2.4)
Weight loss	2869 (1.4)
Bleeding disorders	19,405 (9.4)
Functional health status (n, %)
Independent	181,103 (87.8)
Partially dependent	19,463 (9.4)
Totally dependent	3572 (1.7)
Major postoperative complications (n, %)	10,701 (5.2)
Minor postoperative complications (n, %)	11,904 (5.8)
Discharge destination (n, %)
Home	118,446 (57.4)
Nonroutine (rehab, SNF, and others)	87,906 (42.6)

BMI = body mass index; CHF = congestive heart failure; IQR = interquartile range; mFI-5 = 5-Item Modified Frailty Index; RAI-Rev = Revised Risk Analysis Index

Major complications were defined as a patient experiencing one or more of the following: prolonged intubation exceeding 48 hours, unplanned reintubation, sepsis, septic shock, pneumonia, deep vein thrombosis (DVT)/thrombophlebitis, pulmonary embolism (PE), acute cerebrovascular accident or stroke with neurological deficit(s), acute renal failure, myocardial infarction (MI), cardiac arrest requiring cardiopulmonary resuscitation, superficial surgical site infection (SSI), deep incisional SSI, organ space SSI, or wound disruption.

Intraoperative characteristics included median surgical time of 69 minutes (IQR: 47 to 102 minutes), and 26,750 patients (13.0%) required blood transfusions, with 4,973 patients (2.4%) requiring greater than one unit of blood. Postoperatively, the mean length of stay was 3 days (IQR: 0 to 6 days) and major complications occurred in 10,701 patients (5.2%). A total of 87,906 patients (42.6%) were discharged with non-home discharge, with 11,224 patients (5.4%) and 4323 patients (2.1%) undergoing unplanned readmission or revision surgery within 30 days, respectively. The overall 30-day mortality rate was 2.3% (n = 4,745).

Multivariate Analysis

A multivariate analysis was conducted to assess the predictive values of the mFI-5 and RAI-Rev for poor postoperative outcomes (Table 2). Increasing frailty measured by the RAI-Rev was an independent predictor of mortality (normal: OR 4.63 [95% CI 2.26 to 9.47]; frail: OR 18.63 [95% CI 9.22 to 37.63]; very frail: OR 76.31 [95% CI 37.77 to 154.20], P < 0.001), major complications (normal: OR 2.05 [95% CI 1.81 to 2.32]; frail: OR 3.79 [95% CI 3.34 to 4.29]; very frail: OR 8.78 [95% CI 7.73 to 9.96], P < 0.001), readmission (normal: OR 2.02 [95% CI 1.79 to 2.27]; frail: OR 3.75 [95% CI 3.33 to 4.23]; very frail: OR 6.01 [95% CI 5.31 to 6.79], P < 0.001), and wound complications (normal: OR 1.51 [95% CI 1.30 to 1.75]; frail: OR 1.73 [95% CI 1.48 to 2.02]; very frail: OR 1.94 [95% CI 1.62 to 2.32], P < 0.001).

Table 2.

Multivariate Analysis Controlling for Age, Sex, Ethnicity/Race, Body Mass Index, Transfer Status, Nonelective Surgical Status, Fracture Location, Open Fracture, and Total Operation Time for Each Cohort for Each Primary Outcome

Factor or Variable	Odds (95% Confidence Interval)
	RAI-Rev				mFI-5
	Normal	Frail	Very Frail	P	Prefrail	Frail	Severely Frail	P
Mortality	4.63 (2.26-9.47)	18.63 (9.22-37.63)	76.31 (37.77-154.20)	<0.001	1.56 (1.44-1.69)	2.19 (2.01-2.39)	4.28 (3.80-4.82)	<0.001
Major complications	2.05 (1.81-2.32)	3.79 (3.34-4.29)	8.78 (7.73-9.96)	<0.001	1.61 (1.53-1.68)	2.29 (2.17-2.40)	4.09 (3.78-4.42)	<0.001
Readmission	2.02 (1.79-2.27)	3.75 (3.33-4.23)	6.01 (5.31-6.79)	<0.001	1.69 (1.61-1.78)	2.28 (2.16-2.41)	3.69 (3.38-4.02)	<0.001
Wound complications	1.51 (1.30-1.75)	1.73 (1.48-2.02)	1.94 (1.62-2.32)	<0.001	1.43 (1.30-1.58)	1.77 (1.58-1.99)	2.07 (1.67-2.58)	<0.001

mFI-5 = 5-Item Modified Frailty Index; RAI-Rev = Revised Risk Analysis Index

Results are presented as odds ratio (OR) and 95% confidence interval.

Similarly, increasing mFI-5 odds ratio across frailty tiers (prefrail, frail, and severely frail) was an independent predictor of mortality (prefrail: OR 1.56 [95% CI 1.44 to 1.69]; frail: OR 2.19 [95% CI 2.01 to 2.39]; severely frail: OR 4.28 [95% CI 3.80 to 4.82], P < 0.001), major complications (prefrail: OR 1.61 [95% CI 1.53 to 1.68]; frail: OR 2.29 [95% CI 2.17 to 2.40]; severely frail : OR 4.09 [95% CI 3.78 to 4.42], P < 0.001), readmission (prefrail: OR 1.69 [95% CI 1.61 to 1.78]; frail: OR 2.28 [95% CI 2.16 to 2.41]; severely frail: OR 3.69 [95% CI 3.38 to 4.02], P < 0.001), and wound complications (prefrail: OR 1.43 [95% CI 1.30 to 1.58]; frail: OR 1.77 [95% CI 1.58 to 1.99]; severely frail: OR 2.07 [95% CI 1.67 to 2.58], P < 0.001).

Receiver Operating Characteristic Analysis

AUROC curve analysis was conducted to determine the discriminatory accuracy of the mFI-5 and RAI-Rev for primary postoperative outcomes (Figure 1). The RAI-Rev significantly outperformed the mFI-5 regarding discriminatory accuracy for prediction of mortality (RAI-Rev: C-statistic = 0.84, 95% CI [0.84 to 0.85]; mFI-5: C-statistic = 0.67, 95% CI [0.67 to 0.67], P < 0.001), major complications (RAI-Rev: C-statistic = 0.73, 95% CI [0.73 to 0.73]; mFI-5: C-statistic = 0.65, 95% CI [0.65 to 0.65], P < 0.001), and readmission (RAI-Rev: C-statistic = 0.68, 95% CI [0.68 to 0.68]; mFI-5: C-statistic = 0.63, 95% CI [0.63 to 0.64], P < 0.001). The mFI-5 was shown to have performed significantly better than RAI-Rev regarding wound complications (RAI-Rev: C-statistic = 0.52, 95% CI [0.52 to 0.56]; mFI-5: C-statistic = 0.55, 95% CI [0.55 to 0.56], P < 0.001).

Figure 1.

Curves demonstrating AUROC analysis quantifying the discriminatory accuracy of frailty as measured by the RAI-Rev and mFI-5. RAI-Rev (mortality: C-statistic = 0.84, 95% CI [0.84 to 0.85]; major complications: C-statistic = 0.68, 95% CI [0.68 to 0.68]; readmission: C-statistic = 0.68, 95% CI [0.68 to 0.68]; wound complications: C-statistic = 0.52, 95% CI [0.52 to 0.56]) and mFI-5 (mortality: C-statistic = 0.67, 95% CI [0.67 to 0.67]; major complications: C-statistic = 0.65, 95% CI [0.65 to 0.65]; readmission: C-statistic = 0.63, 95% CI [0.63 to 0.64]; wound complications: C-statistic = 0.55, 95% CI [0.55 to 0.56]); P < 0.001 for all.

Discussion

With an aging US population, older patients have considerably worse outcomes after surgical management of orthopaedic trauma.^1-3 Thus, measures such as frailty have been used to identify patients at greater risk of postoperative complications and mortality.^24-26 This study sought to determine the utility of the novel RAI-Rev frailty index in the orthopaedic trauma population and compare its discriminatory accuracy with that of the established mFI-5. We found that RAI-Rev had markedly better discriminatory thresholds when predicting 30-day postoperative mortality, major complications, and readmission. This study presents the first investigation of the applicability of RAI-Rev in orthopaedic trauma.

The mFI is among the more commonly used tools for predicting morbidity, mortality, and other adverse outcomes after a variety of surgical procedures.^27-29 The mFI was initially developed as an 11-item instrument; however, owing to necessary variables no longer being recorded in the American College of Surgeons National Surgical Quality Improvement database, the 11-item instrument was largely phased out.²⁹ For this reason, the original instrument was truncated to create a newer five-item tool known as mFI-5. mFI-5 was validated using the NSQIP database and demonstrated similar effectiveness in the predictive power of morbidity and mortality compared with mFI-11 in multiple surgical specialties.²⁹ The mFI has predicted adverse outcomes in studies evaluating traumatic orthopaedic injuries such as fractures of the distal radius, forearm, proximal humerus, hip, pelvis, and acetabulum.^9,30-35 Our analysis demonstrated similar associations, with increasing frailty tiers as measured by mFI-5, exhibiting significantly increased odds of mortality, major complications, readmission, and wound complications.

Despite mFI-5's advantages of being concise and easy to implement in clinical settings, there are many concerns regarding its use as a frailty measure, largely regarding its accuracy as a true measure of frailty, rather than multimorbidity.¹⁸ Indices must balance between simplicity for ease of use in clinical preoperative screening and risk of oversimplification potentially diluting the predictive capacity of frailty.¹⁸ The limited coverage of variables and domains creates the potential for inaccurate stratification of frail patients with an increased possibility of oversimplification of patient risk. Our data set demonstrates this as the severely frail cohort in mFI-5 consisted of 5,360 patients (2.6%) while the severely frail tier in RAI-Rev consisted of 33,657 patients (16.3%). In addition, unlike mFI-5, RAI is a weighted model giving more importance to increasingly morbid deficits and allowing for more granular stratification as it is scored from 0 to 81.

Consequently, there has been a shift away from mFI-5 with a recent increase in the utilization of RAI, an alternative frailty screening tool that incorporates multiple domains of frailty.^18,19 The RAI has been validated as a superior tool for predicting postoperative complications after neurosurgery and spine surgery when compared with mFI-5.^36–39 Our study found that the RAI-Rev frailty score is a notable predictor of mortality, major complications, and readmission in patients after orthopaedic trauma. Using ROC curve analysis, we also show that RAI-Rev has excellent diagnostic accuracy when predicting postoperative outcomes, namely mortality and major complications. Incorporating the RAI-Rev frailty score as part of a preoperative assessment may allow for better medical optimization and a more open discussion about surgical risk and surgical options and facilitate postoperative planning.¹⁹

While there are other studies analyzing frailty in orthopaedics, few analyze a comprehensive orthopaedic trauma population.^32,39 Amer et al³⁴ analyzed mFI-5 in patients with long bone fractures and reported increasing tier of frailty to be markedly associated with increased odds of wound disruption, major complication, unplanned revision surgery, unplanned readmission, surgical site infection, and nonhome discharge, similar to the results in this study. Although similar to the outcomes reported in this study, our study also included fractures of the pelvis, acetabulum, and hindfoot in addition to fractures of the long bones (excluding clavicle). In addition, no ROC analysis was conducted by Amer et al, limiting understanding of the model performance as a diagnostic tool. Gleason et al⁶ analyzed the utility of the FRAIL scale in patients older than 70 years with surgical fractures and reported association between the FRAIL score and increased length of stay and occurrence of a complication. They did not find association between the FRAIL score and 30-day readmission and 30-day mortality in contrast to this study. Possible explanations include their inclusion of patients aged 70 and older potentially limiting sizable differences between their robust and frail group and limited sample size. Phen et al analyzed the strength of mFI-5 in patients younger than 65 years with lower extremity fractures. Despite their reports of the significance of frailty and adverse outcomes, they noted that frailty and malnutrition in conjunction have a greater association with postoperative complications, indicating the deficiency in domains in the mFI-5 model.⁴⁰ Thus, given the superiority of the RAI-Rev demonstrated in this study, its implementation in preoperative risk stratification for orthopaedic trauma patients may be done to reduce adverse outcomes through administrative review from surgical house staff, optimization of perioperative plans, and preoperative palliative care consultation when appropriate.

As with any investigation, this study is not without limitations. Consistent with large national database studies, the findings of this study are limited by the nature of the variables reported within the database. Despite offering a breadth of patient variables, the NSQIP database inherently presented limitations in the context of RAI-Rev, including the exclusion of preoperative cognitive status from frailty measures and a smaller degree of granularity when considering nutritional status. Specifically, both “weight loss” and “poor appetite” were recorded under the same variable, “WTLOSS,” preventing a more granular analysis. In addition, lack of granularity limited analysis of polytraumatized patients as the NSQIP database was queried using primary postoperative diagnosis codes. Although patients were only accounted for once, this inherent limitation makes it difficult to isolate any multiple injured patients. Despite these limitations, we believe the large sample size analyzed in the study reduced potential confounding with likelihood that the large number of samples converged to the population mean. Furthermore, the data used in the study relied on accurate coding and data input. Finally, the retrospective nature of the study limits the determination of causation and the ability to control for all confounding variables.

Conclusion

Orthopaedic trauma remains an important contributor to morbidity and mortality worldwide, particularly given the increasing large proportion of frail and elderly patients. This study demonstrates that increasing frailty is associated with a greater risk of mortality, major complications, and readmission within 30 days after undergoing surgical fixation of traumatic orthopaedic injuries. Furthermore, we demonstrate the clinically significant discriminatory accuracy of the RAI-Rev when compared with the mFI-5 for predicting morbidity and mortality. These findings help to establish the RAI-Rev as an effective tool in frailty assessment, accurately capturing the frailty phenotype to provide surgeons with critical risk assessment data. Future studies should seek to understand the implications of the RAI-Rev in orthopaedic traumatology by understanding patient outcomes after implementation into clinical practice.