Chronicity of Uncorrected Hyponatremia and Clinical Outcomes in Older Patients Undergoing Hip Fracture Repair

Ayus, Juan Carlos; Fuentes, Nora; Go, Alan S.; Achinger, Steven G.; Moritz, Michael L.; Nigwekar, Sagar U.; Waikar, Sushrut S.; Negri, Armando

doi:10.3389/fmed.2020.00263

Cited by 10 publications

(17 citation statements)

References 33 publications

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“…Ayus et al [17] found that nearly 25% of patients with hip fracture suffered from hyponatremia, which was associated with increased post-operative mortality after hip fracture surgery in geriatrics. Ryan et al [8] found that anemia at admission was associated with greater 30-day postoperative morbidity and mortality in geriatrics with hip fracture.…”

Section: Article In Pressmentioning

confidence: 99%

Prognostic nomogram for risk of mortality after hip fracture surgery in geriatrics

Pan¹,

Ning²,

Wu³

et al. 2022

Injury

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Hip fracture is a significant public health problem, with associated high morbidity and mortality. Orthopedic surgeons are concerned to improve prognosis and stratify mortality risk after hip fracture surgery. This study established a nomogram that combines the Charlson Comorbidity Index (CCI) with specific laboratory parameters to predict mortality risk after hip fracture surgery in geriatrics. Methods: The records of consecutive patients who underwent hip fracture surgery from January 2015 through May 2020 at one medical center were reviewed for perioperative factors and mortality. Patients with age ≥ 70 years who were diagnosed with intertrochanteric or femoral neck fractures were included. Patients who were diagnosed with pathological fracture, received only conservative treatment or lost to follow-up were excluded. A multivariate Cox proportional hazards regression model was used to identify risk factors. A nomogram was established with R software and evaluated using concordance (C)-index, area under receiver operating characteristic (AUC), calibration curves, and decision curve analysis (DCA). Results: In total, 454 patients were included with a mean age of 81.6 years. The mean follow-up and oneyear mortality rate were 37.2 months and 10.4%, respectively. Five identified risk variables for mortality after hip fracture surgery in geriatrics comprised age (HR 1.05, 95% CI 1.01-1.08; P = 0.003), CCI (HR 1.38, 95% CI 1.24-1.54; P = 0.0 0 0), albumin (HR 1.78, 95% CI 1.31-2.43; P = 0.0 0 0), sodium (HR 1.59, 95% CI 1.18-2.15; P = 0.002) and hemoglobin (HR 1.46, 95% CI 1.07-2.00; P = 0.02). A nomogram was proposed and evaluated, showing a C-index of 0.76 ± 0.02. The AUCs for 6-month, 1-year, and 3-year mortality predictions were 0.83, 0.79, and 0.77, respectively. The calibration curve and DCA showed good discrimination and clinical usefulness. Conclusion: This novel nomogram for stratifying the mortality risk after hip fracture surgery in geriatrics incorporated age, CCI, serum albumin, sodium, and hemoglobin. Internal validation indicated that the model has good accuracy and usefulness. This nomogram had improved convenience and precision compared with other models. External validation is warranted to confirm its performance.

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Section: Article In Pressmentioning

confidence: 99%

Prognostic nomogram for risk of mortality after hip fracture surgery in geriatrics

Pan¹,

Ning²,

Wu³

et al. 2022

Injury

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“…The prevalence of geriatric hip fracture (HF) patients is increasing in the rapidly aging population, which has become a growing public health concern worldwide ( 1 – 4 ). In addition, geriatric HF patients are associated with high post-operative mortality ( 5 , 6 ). Previous studies revealed that the overall post-operative mortality of geriatric HF patients in 1 year was as high as 31% ( 7 , 8 ).…”

Section: Introductionmentioning

confidence: 99%

A New Random Forest Algorithm-Based Prediction Model of Post-operative Mortality in Geriatric Patients With Hip Fractures

et al. 2022

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BackgroundPost-operative mortality risk assessment for geriatric patients with hip fractures (HF) is a challenge for clinicians. Early identification of geriatric HF patients with a high risk of post-operative death is helpful for early intervention and improving clinical prognosis. However, a single significant risk factor of post-operative death cannot accurately predict the prognosis of geriatric HF patients. Therefore, our study aims to utilize a machine learning approach, random forest algorithm, to fabricate a prediction model for post-operative death of geriatric HF patients.MethodsThis retrospective study enrolled consecutive geriatric HF patients who underwent treatment for surgery. The study cohort was divided into training and testing datasets at a 70:30 ratio. The random forest algorithm selected or excluded variables according to the feature importance. Least absolute shrinkage and selection operator (Lasso) was utilized to compare feature selection results of random forest. The confirmed variables were used to create a simplified model instead of a full model with all variables. The prediction model was then verified in the training dataset and testing dataset. Additionally, a prediction model constructed by logistic regression was used as a control to evaluate the efficiency of the new prediction model.ResultsFeature selection by random forest algorithm and Lasso regression demonstrated that seven variables, including age, time from injury to surgery, chronic obstructive pulmonary disease (COPD), albumin, hemoglobin, history of malignancy, and perioperative blood transfusion, could be used to predict the 1-year post-operative mortality. The area under the curve (AUC) of the random forest algorithm-based prediction model in training and testing datasets were 1.000, and 0.813, respectively. While the prediction tool constructed by logistic regression in training and testing datasets were 0.895, and 0.797, respectively.ConclusionsCompared with logistic regression, the random forest algorithm-based prediction model exhibits better predictive ability for geriatric HF patients with a high risk of death within post-operative 1 year.

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“…We retrieved 11 051 abstracts from the initial database search and subsequently screened 11 011 records after removing duplicates. Eventually, 32 studies were included ( 5 , 7 , 9 , 14 , 16-18 , 24-48 ), and 29 studies were eligible for meta-analyses ( Table 1 ) ( 5 , 7 , 9 , 14 , 16-18 , 24 , 26-33 , 35-44 , 46 , 48 ). To prevent double representation of the same dataset, the study with the longest period of enrollment was selected when there were multiple studies using the same dataset to analyze the same outcomes ( 17 , 28 ).…”

Section: Resultsmentioning

confidence: 99%

Association of Preoperative Hyponatremia With Surgical Outcomes: A Systematic Review and Meta-analysis of 32 Observational Studies

Teo

Gan

Tay

et al. 2022

The Journal of Clinical Endocrinology &Amp; Metabolism

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Background Preoperative hyponatremia is prevalent in patients undergoing surgical procedures, but it is uncertain if hyponatremia will lead to increased risk of surgical mortality and morbidity. Methods A systematic search of Medline (PubMed), Embase and Cochrane Library from inception till 2 July 2021 was performed. Full length articles that reported on the association between surgical outcomes among adults ≥18 years with documented preoperative hyponatremia were included. Findings We identified 32 observational studies comprising 1,301,346 participants. All studies had low risk of bias. When adjusted for covariates, patients with hyponatremia had significantly higher odds of developing major complications (defined as a composite measure of 9 major complications) compared to patients with normal sodium concentrations (aOR = 1.37, 95%CI = 1.23-1.53, I2 = 78%. N = 10). Additionally, patients with preoperative hyponatremia also significantly higher hazards of early mortality (<90 days) compared to patients with normonatremia (aHR = 1.27, 95%CI = 1.13-1.43, I2 = 97%. N = 10) after adjustment for covariates. Preoperative hyponatremia also had significant associations with respiratory, renal and septic complications. In terms of prognostic performance, preoperative hyponatremia performed adequately in predicting major complications in surgical patients (AUC = 0.70, LR- 0.90) with a specificity of 88% and a sensitivity of 25%. Interpretation Our meta-analysis suggests that preoperative hyponatremia is associated with poorer early mortality and major morbidity outcomes in surgical patients. Hyponatremia is also a specific prognosticator for major complications in surgical patients, reiterating its potential use as a clinical indicator of poor outcomes.

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Chronicity of Uncorrected Hyponatremia and Clinical Outcomes in Older Patients Undergoing Hip Fracture Repair

Cited by 10 publications

References 33 publications

Prognostic nomogram for risk of mortality after hip fracture surgery in geriatrics

Prognostic nomogram for risk of mortality after hip fracture surgery in geriatrics

A New Random Forest Algorithm-Based Prediction Model of Post-operative Mortality in Geriatric Patients With Hip Fractures

Association of Preoperative Hyponatremia With Surgical Outcomes: A Systematic Review and Meta-analysis of 32 Observational Studies

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