Validation of the Nottingham Hip Fracture Score in Predicting Postoperative Outcomes Following Hip Fracture Surgery

Sun, Lili; Liu, Zhiwei; Wu, Hao; Liu, Baichuan; Zhao, Bin

doi:10.1111/os.13624

Cited by 9 publications

(10 citation statements)

References 21 publications

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“…Urinary tract infections (UTIs) significantly contribute to an increased incidence and adverse prognosis in fracture patients, particularly those with hip fractures [ 58 , 59 ]. A retrospective analysis of 93,637 Danish patients with hip fractures revealed that UTIs were a substantial factor associated with elevated mortality rates, specifically in females [ 58 ].…”

Section: Discussionmentioning

confidence: 99%

Correlation between admission hypoalbuminemia and postoperative urinary tract infections in elderly hip fracture patients

Yao,

Tang,

Wang

et al. 2023

J Orthop Surg Res

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Purpose This study aimed to evaluate the correlation between hypoalbuminemia upon admission and the incidence of postoperative urinary tract infections (UTIs) in elderly patients with hip fractures. Methods A retrospective analysis was performed on the medical records of elderly patients who underwent surgical treatment for hip fractures at a level I trauma center from 2013 to 2023. Serum albumin levels were measured upon admission, and hypoalbuminemia was defined as a total albumin level < 35 g/L. Multivariable logistic regression and propensity score matching analysis were utilized to control and reduce potential confounding factors, aiming to obtain adjusted odds ratios (ORs) and 95% confidence intervals (CI) for UTIs to determine the strength of the association. Results This observational cohort study included 1279 patients, among whom 298 (23.3%) developed UTIs. Patients with albumin levels < 35 g/L had significantly greater odds of developing UTIs compared to those with albumin levels ≥ 35 g/L (OR 1.86, 95% CI 1.28–2.70). Further analysis, dividing albumin levels into quartiles, demonstrated that patients in the Q2 group (38.0–40.9 g/L; OR 1.38, 95% CI 0.88–2.17), Q3 group (35.0–37.9 g/L; OR 1.69, 95% CI 1.06–2.71), and Q4 group (15.3–34.9 g/L; OR 2.67, 95% CI 1.61–4.43) had notably higher odds of developing UTIs compared to those in the Q1 group (41.0–52.0 g/L). Conclusions The presence of hypoalbuminemia upon admission in elderly patients undergoing hip fracture surgery is strongly correlated with the occurrence of postoperative UTIs. Furthermore, this association exhibits a clear dose–response relationship.

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Section: Discussionmentioning

confidence: 99%

Correlation between admission hypoalbuminemia and postoperative urinary tract infections in elderly hip fracture patients

Yao,

Tang,

Wang

et al. 2023

J Orthop Surg Res

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“…The following data for patients were collected by reviewing the medical record system: sex, age, body mass index (BMI), hospital stay, smoking history, drinking history, number of co‐morbidities, diabetes, hypertension, osteoporosis, fracture type (garden typing), preoperative nutritional risk score (NRS), and American Society of Anesthesiologists (ASA) score; operative manners (SHA and THA); anesthesia method (general anesthesia and lumbar anesthesia); operation time (> = 2h / joint); preoperative laboratory examination indicators, including white blood cell (WBC), red blood cell (RBC), hemoglobin (HB), hematocrit (HCT), percentage of neutrophils (NEUT%), C‐reactive protein (CRP), serum K + , blood urea nitrogen (BUN), creatinine (CR), albumin (ALB), aspartate aminotransferase (AST), alanine aminotransferase (ALT), international normalized ratio (INR), activated partial thromboplastin time (APTT), fibrinogen (FIB), thrombin time (TT), and prothrombin time (PT); associated operation indicators, including bleeding volume; blood transfusion volume; and postoperative laboratory examination indicators, including RBC, HB, 12,13 ALB, 14,15 K + , 12,16 in agreement with many previous studies. Based on the follow‐up results, the postoperative survival time and death rates of patients were collected.…”

Section: Methodsmentioning

confidence: 99%

The Nomogram Model and Factors for the Postoperative Mortality of Elderly Patients with Femoral Neck Fracture Undergoing Artificial Hip Arthroplasty: A Single‐Institution 6‐Year Experience

Wang,

Zhang,

Zeng

et al. 2023

Orthopaedic Surgery

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ObjectiveArtificial hip arthroplasty (AHA) is widely accepted in elderly patients with femoral neck fractures, but it is associated with high risk of death and various postoperative complications due to old age and accompanying chronic diseases. Therefore, this study aimed to explore the risk factors for death in elderly patients with femoral neck fractures after AHA and to establish a nomogram risk prediction model, which is expected to reveal high‐risk patients and improve the postoperative quality of life and survival rate of patients.MethodsElderly patients who underwent AHA for femoral neck fractures in our hospital from September 2014 to May 2021were retrospectively analyzed. These patients were divided into a survival group and a death group according to their clinical outcomes. The following clinical data were recorded for the patients in the two groups: sex, age, underlying diseases, smoking and drinking history, preoperative nutritional risk score (NRS) and American Society of Anesthesiologists (ASA) score, as well as relevant indicators about the operation. These data were subject to univariate analysis and then logistic analysis to determine the risk factors of death. Subsequently, a nomogram risk prediction model was established and further validated with the receiver operating characteristic curve (ROC) and the Hosmer–Lemeshow test. Finally, the effects of predictive risk factors were analyzed using the Kaplan–Meier survival curve.ResultsFollow‐up was completed by 260 patients, including 206 patients in the survival group and 54 patients in the death group; the overall death rate was 20.77%, and the follow‐up time, age, postoperative 1, 3 and 5‐year death rates were 3.47 ± 1.93 years, 75.32 ± 9.12 years, 5.77%, 12.51%, and 25.61%, respectively. The top three causes of death in 54 patients were respiratory disease, cerebrocardiovascular disease, and digestive disease, respectively. The logistic analysis indicated that elderly patients with femoral neck fractures, the risk factors for death after AHA were age ≥ 80 years, preoperative NRS ≥ 4, HB ≤ 90 g/L, CR ≥ 110 umol/L, and ASA score ≥ 3, as well as postoperative albumin ≤ 35 g/L, the nomogram was established, and then its predictive performance was successfully validated using the ROC curve (AUC = 0.814, 95% confidence interval = 0.749–0.879) and the Hosmer–Lemeshow test (p = 0.840). Furthermore, Kaplan–Meier survival curve analysis revealed that the abovementioned six indicators were correlated with the post‐AHA survival time of elderly patients with femoral neck fractures (pLog Rank < 0.05).ConclusionOld age, preoperatively high NRS and ASA score, anemia, poor renal function, and postoperative hypoproteinemia are the major risk factors for death in elderly patients with femoral neck fractures after AHA; they are also associated with postoperative survival. Early identification and effective interventions for optimization of modifiable risk factors are recommended to improve the postoperative quality of life and survival rates.

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“…However, these features are not explicitly included in HF-specific risk assessment tools (e.g. in O-POSSUM only symptoms and clinical findings suggestive of cardiovascular disease are included and NHFS only the number of comorbidities is included as an input parameter) [7][8][9][10]. Moreover, neither PTH or vitamin D levels are included in any of the current tools, despite an increasing number of studies supporting the key role they play in bone metabolism and prevention of fracture [45-57] and, potentially, with increasing recognition of their importance in the immunity [58-60] prevention of post-operative complications such as hospital acquired infections.…”

Section: Feature Importance -Model Interpretation and Shap Analysismentioning

confidence: 99%

“…One key aspect in HF assessment and management challenge is the prognostication of poor short-term outcomes. There exists a substantial amount of analysis from traditional statistical methods (such as logistical regression, LR) in identifying key risk factors for predicting poor outcomes, notably mortality, following HF and scoring tools that have risen to prominence are the Nottingham Hip Fracture Score (NHFS) and the orthopaedic-Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (O-POSSUM) [7][8][9][10]. Most of these tools require a combination of both clinical, laboratory and intra-operative data; and the lack of laboratory and intra-operative data early during admission limits the use of such tools in early risk stratification.…”

Section: Introductionmentioning

confidence: 99%

Naïve Bayes is an interpretable and predictive machine learning algorithm in predicting osteoporotic hip fracture in-hospital mortality compared to other machine learning algorithms

Wang

2024

Preprint

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0. Abstract Osteoporotic hip fractures (HFs) in the elderly are a pertinent issue in healthcare, particularly in developed countries such as Australia. Estimating prognosis following admission remains a key challenge. Current predictive tools require numerous patient input features including those unavailable early in admission. Moreover, attempts to explain machine learning [ML]-based predictions are lacking. We developed 7 ML prognostication models to predict in-hospital mortality following minimal trauma HF in those aged ≥ 65 years of age, requiring only sociodemographic and comorbidity data as input. Hyperparameter tuning was performed via fractional factorial design of experiments combined with grid search; models were evaluated with 5-fold cross-validation and area under the receiver operating characteristic curve (AUROC). For explainability, ML models were directly interpreted as well as analyzed with SHAP values. Top performing models were random forests, naïve Bayes [NB], extreme gradient boosting, and logistic regression (AUROCs ranging 0.682 – 0.696, p>0.05). Interpretation of models found the most important features were chronic kidney disease, cardiovascular comorbidities and markers of bone metabolism; NB also offers direct intuitive interpretation. Overall, we conclude that NB has much potential as an algorithm, due to its simplicity and interpretability whilst maintaining competitive predictive performance.

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Validation of the Nottingham Hip Fracture Score in Predicting Postoperative Outcomes Following Hip Fracture Surgery

Cited by 9 publications

References 21 publications

Correlation between admission hypoalbuminemia and postoperative urinary tract infections in elderly hip fracture patients

Correlation between admission hypoalbuminemia and postoperative urinary tract infections in elderly hip fracture patients

The Nomogram Model and Factors for the Postoperative Mortality of Elderly Patients with Femoral Neck Fracture Undergoing Artificial Hip Arthroplasty: A Single‐Institution 6‐Year Experience

Naïve Bayes is an interpretable and predictive machine learning algorithm in predicting osteoporotic hip fracture in-hospital mortality compared to other machine learning algorithms

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