Impact of Stroke History on the Risk of Recurrent Hip Fracture or Major Osteoporotic Fractures among Patients with Incident Hip Fracture: A Nationwide Cohort Study

The effect of stroke on the bone mineral density: A systematic review and meta-analysis

OBJECTIVES

Stroke survivors frequently encounter physical complications. This study aimed to evaluate the impact of stroke on bone mineral density (BMD) and assess the risk of post-stroke osteoporosis or osteoporotic fractures.

DESIGN

Systematic review and meta-analysis.

SETTING AND PARTICIPANTS

We systematically searched Medline, Embase, and the Cochrane Database of Systematic Reviews to identify longitudinal studies reporting the influence of stroke on BMD, osteoporosis, and osteoporotic fractures. Pooled analyses were performed utilizing random-effects models.

RESULTS

This study included 21 studies with 1,029,742 participants. The mean difference of BMD in the paretic femoral neck between follow-up and initial measurements was -0.07 g/cm2 (95% CI, -0.09 to -0.04), and -0.03 g/cm2 (95% CI, -0.05 to -0.01) in the non-paretic femoral neck. A follow-up length exceeding six months was associated with a more pronounced decrease compared to a follow-up of under six months (MD, -0.08; 95% CI, -0.11 to -0.05 vs MD, -0.04; 95% CI, -0.06 to -0.02; P =  0.03). No significant change in lumbar spine BMD was detected post-stroke (MD, -0.00; 95% CI, -0.03 to 0.02), nor was significant change observed in the non-paretic distal radius, proximal humerus, tibia, trochanter, and total hip. Stroke was not associated with an increased risk of osteoporosis or osteoporotic fractures (HR, 1.43; 95% CI, 0.95-2.13).

CONCLUSION

Stroke survivors undergo significant BMD loss in paralyzed limbs, most notably in the femoral neck. However, BMD in the lumbar spine does not exhibit a significant decrease post-stroke. The risk of post-stroke osteoporosis or osteoporotic fractures should be interpreted with caution and needs further investigation.

Is there a difference between preoperative and postoperative delirium in elderly hip fracture patients?: A retrospective case control study

Delirium is associated with greater morbidity, higher mortality, and longer periods of hospital day after hip fracture. There are number of studies on postoperative delirium after a hip fracture. However, few studies have made a distinction between preoperative and postoperative delirium. The purpose of this study is to compare risk factors and clinical outcome between preoperative and postoperative delirium in elderly patients with a hip fracture surgery. A total of 382 consecutive patients aged > 65 years who underwent operation for hip fracture were enrolled. Among them, the patients diagnosed with delirium were divided into 2 groups (a preoperative delirium group and a postoperative delirium group) according to the onset time of delirium. To evaluate risk factors for preoperative and postoperative delirium, we analyzed demographic data, preoperative laboratory data, and perioperative data. To compare clinical outcomes between preoperative and postoperative delirium, we analyzed postoperative complications, KOVAL score, regression, readmission, and 2-year survival rate. Delirium was diagnosed in 150 (39.3%) patients during hospitalization. Preoperative and postoperative delirium occurred in 67 (44.6%) and 83 (55.4%) patients, respectively. Independent risk factors of preoperative delirium included age (odds ratio: 1.47, 95% confidential interval [CI]: 1.13-2.23, P = .004), stroke (odds ratio [OR]: 2.70, 95% CI: 1.11-6.01, P = .015), American Society of Anesthesiologist (OR: 1.68, 95% CI: 1.137-2.24, P = .033), and time from admission to operation (OR: 1.08, 95% CI: 1.01-1.16, P = .031). There was no significant difference in preoperative KOVAL score between the 2 groups. However, postoperative KOVAL score (5.1 ± 2.0 vs 4.4 ± 2.1, P = .027) and regression rate (68.7% vs 44.6%, P = .029) were significantly higher in the preoperative delirium group than in the postoperative delirium group. Moreover, the 2-year survival rate was significantly lower in the preoperative delirium group than in the postoperative delirium group (62.7% vs 78.3%, P = .046). Characteristics, risk factors, and prognosis are different for patients with preoperative delirium and postoperative delirium. Preoperative delirium patients showed different risk factors with poorer prognosis and higher mortality. Therefore, hip fracture patients with risk factors for preoperative delirium should be monitored more carefully due to their greater risk of mortality.

Development and validation of a predictive nomogram for subsequent contralateral hip fracture in elderly patients within 2 years after hip fracture surgery

Purpose

Contralateral hip refracture following initial hip fracture surgery is life-threatening in the elderly with high incidence and mortality. This study investigated the associated independent risk factors and established a nomogram prediction model.

Methods

Totally 734 elderly patients with hip fractures who underwent surgical treatment (January 2016-December 2020) were enrolled. Following analyses on demographic variables, clinical characteristics, and laboratory examination, independent risk factors of contralateral hip fractures in the elderly were identified through the least absolute shrinkage and selection operator (LASSO) regression, and univariate and multivariate logistic regression. Patients were randomly allocated into training (n = 513) and validation sets (n = 221). A training set-based nomogram prediction model was established and assessed for predictability, discriminatory ability, and clinical applicability using the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) in both sets.

Results

Contralateral hip refractures occurred in 7.08% (52/734) patients within 2 years after surgery. Age, hemoglobin (Hb), heart disease, neurovascular disease, Parkinson's disease (PD), Alzheimer's disease (AD), chronic obstructive pulmonary disease (COPD), and chronic kidney disease (CKD) were independent risk factors. The nomogram prediction model had a favorable discriminatory ability, as indicated by the areas under the ROC curves (AUC): 0.906 (95% CI, 0.845-0.967) in the training set and 0.956 (95% CI, 0.927-0.985) in the validation set. The calibration curves demonstrated a good consistency between the actual subsequent contralateral hip fracture incidence and the predicted probability. The DCA of the nomogram demonstrated the model's excellent clinical efficacy.

Conclusion

The nomogram model enabled accurate individualized prediction for the occurrence of subsequent contralateral hip fracture in the elderly within 2 years after surgical treatment, which might help clinicians with precise references for appropriate perioperative management and rehabilitation education following initial hip surgery for their patients.