Discussion
Our study is the first to develop and validate a frailty score tailored to the assessment of mortality in patients with hip fracture. In this study, the OFS outperformed all other indices in predicting both 30-day and 90-day mortality, except the NHFS which performed at a similar level. The cut-off that maximized Youden’s index was OFS ≥2, indicating that this can be considered as a threshold for defining patients as frail. Patients with an OFS ≥2 were 3.4 times more likely to die within 30 days postoperatively and 2.7 times more likely to die within 90 days postoperatively, compared with patients with a lower OFS. The OFS could accordingly be a useful and simple tool for incorporating frailty into research and clinical decision-making among patients with hip fracture.
To develop a frailty score, it is first essential to agree on a definition of frailty. Unfortunately, there remains a clinical equipoise regarding this subject. However, frailty is often characterized as a condition in which patients have a reduced physiological reserve to withstand stressors due to the degeneration of multiple organ systems, which results in an increased risk of morbidity, disability, and mortality.14 35–38 It should also be considered disparate from the concept of comorbidity.39 At the same time, these two concepts cannot be definitively extricated from each other; while frailty can promote the development of diseases, comorbidities may also precipitate the progression of frailty.39
The question then remains, if the OFS actually succeeds in capturing the concept of frailty. Most of the variables included in the score, institutionalization, non-independent functional status, and a history of malignancy, have been used previously to measure frailty and are widely accepted and validated as markers of frailty.20 28 40 41 Including age might be considered to be a more contentious decision. It is important to note that frailty is an independent process from aging; however, frailty also becomes more prevalent at higher ages and has been used previously as a component when assessing frailty.42 43 Furthermore, with the OFS, an age ≥85 on its own is insufficient for a patient to be classified as frail. The inclusion of CHF as a variable also bears discussing. While it is clearly a comorbidity, it should also be seen as a marker of frailty. Heart failure can be defined as an inability for the heart to maintain an adequate cardiac output to meet the body’s demands, or the inability to maintain an adequate output without compensatory mechanisms.44 45 This fits together neatly with the concept of frailty, as according to this definition, CHF would indicate that a patient has a reduced physiological reserve to respond to external stressors. This is further corroborated by the inclusion of CHF in the 5-mFI.28 40
Of the indices that are compared with the OFS, only the NHFS and Sernbo Score can be considered to achieve an acceptable predictive ability with AUCs ≥0.7 for both 30-day and 90-day mortality. However, it is worth noting that the underlying reason for this discriminative ability differs significantly. While the NHFS and Sernbo Score demonstrate superior specificity, the OFS instead excels in sensitivity; the OFS is the only score with a diagnostic statistic ≥0.8 at the threshold that maximizes Youden’s Index. A uniting factor for all frailty indices is that none truly measure frailty itself, instead they all use different surrogates for frailty to identify which patients can be classified as frail. Consequently, if the goal of the OFS is to identify frail patients with an elevated risk of postoperative mortality, then a high sensitivity can be argued to be more important than a high specificity in identifying those patients who have the most to gain from additional interventions.
The OFS could accordingly be useful for identifying these high-risk patients early on, which could aid in a more effective allocation of expertise and resources, such as multidisciplinary interventions.15 It could also be a useful tool for communicating with patients and their relatives. Frailty as a concept can be challenging for patients to understand, which is understandable given that even clinicians at times struggle with the subject.46 However, this process could be simplified if a number with a concrete reasoning behind it could be provided. The OFS may also be useful for further research into frailty among patients with hip fracture. Most retrospective databases lack the granular data required to capture frailty, but the variables used in the OFS tend to be readily available, which might allow more of these databases to be used in investigating the role of frailty in hip fracture management and outcomes.
The OFS’s utility in research is further aided by its simplicity. Many frailty indices are significantly more complex or require measurements which may be challenging or unfeasible to assess in the emergency setting.47–49 The OFS, on the other hand, only requires five binary variables, which can easily be retrieved from a patient’s electronic medical records or determined with little delay after arrival to the emergency room. Despite this simplicity, the OFS still demonstrates the same level of discriminatory ability for mortality as the NHFS. This is despite the NHFS making use of preoperative blood tests along with requiring more variables that each contribute different amounts of points to the final score. For any screening tool used for risk stratification in clinical practice, simplicity is essential. This is of particular importance in orthopedic surgery, where there is a preference for straightforward tools over more complex or purely physical measures.46
There are several limitations in the current study that bear mentioning. While the local dataset is based on patients from all hospitals within Orebro County, the generalizability may be limited due to this geographic restriction. Future validating studies will consequently be required. This study also focused on predicting short-term postoperative mortality in patients with hip fracture. However, there is nothing in the OFS that limits it to either this particular outcome or patient population. Future studies should accordingly also determine the OFS’s discriminative ability for alternative adverse outcomes as well as consider other patient populations. The weaknesses inherent in using retrospective datasets is also apparent when comparing the predictive ability of the OFS in the local dataset with the national dataset. While the Swedish National Quality Registry for Hip Fractures constitutes a prospectively collected, nationwide sample population that is contributed to by almost all Swedish orthopedic departments and boasts a high case coverage between 80% and 90%,50 certain variables were less readily registered than others, particularly in regard to institutionalization and non-independent functional status. In the local dataset, missing data as well as any errors that occurred during registration could be corrected using the patients’ electronic medical records, which could explain why the OFS demonstrated a higher performance in the validation dataset.
