Israel Medical Association Journal

Background: Hip fracture rates are increasing worldwide, and the risk for a second hip fracture is high. The decision to administer antiresorptive treatment is based mainly on bone mineral density and/or a history of previous osteoporotic fractures.

Objectives: To evaluate the contribution of BMD[1], previous fractures, clinical and laboratory parameters to hip fracture risk assessment.

Methods: The study population included 113 consecutive hip fracture patients, aged 72.5 ± 9.4 years, discharged from the Department of Orthopedic Surgery113 consecutive patients, 87 women and 26 men, aged 50-90 years, mean ag. BMD was assessed at the lumbar spine, femoral neck and total hip. The results were expressed in standard deviation scores as T-scores – compared to young adults and Z-scores – compared to age-matched controls. Plasma or serum levels of parathyroid hormone, 25-hydroxyvitamin 3 and urinary deoxypyridinoline cross-links were evaluated.

Results: We observed T-scores ≤-2.5 in 43 patients (45.3%) at the lumbar spine, in 47 (52.2%) at the femoral neck and in 33 (38%) at the total hip. Twenty-eight patients (29.5%) had neither low BMD nor previous osteoporotic fractures. Using a T-score cutoff point of (-1.5) at any measurement site would put 25 (89%) of these patients into the high fracture risk group. Mean DPD level was 15.9 ± 5.8 ng/mg (normal 4–7.3 ng/mg creatinine). Vitamin D inadequacy was observed in 99% of patients.

Conclusions: Using current criteria, about one-third of elderly hip fracture patients might not have been diagnosed as being at risk. Lowering the BMD cutoff point for patients with additional risk factors may improve risk prediction yield.

Background: Oral anticoagulation with warfarin can lead to life-threatening events as a result of either over-anticoagulation or undertreatment. One of the main contributors to an undesirable warfarin effect is the need to adjust its daily dose for a specific patient. The dose is adjusted empirically based on the experience of the clinician, a method that is often imprecise. There is currently no other well-accepted method for predicting the maintenance dose of warfarin.

Objective: To describe the application of an artificial neural network to the problem of warfarin maintenance dose prediction.

Methods: We designed a neural network that predicts the maintenance dose of warfarin. Data on 148 patients attending a large anticoagulant clinic were collected by file review. Using correlational analysis of the patients' data we selected the best input variables. The network was trained by using the back-propagation algorithm on a subset of our data and the results were validated against the rest of the data. We used a multivariate linear regression to create a comparable model.

Results: The neural network generated reasonable predictions of the maintenance dose (r = 0.823). The results of the linear regression model were similar (r = 0.800).

Conclusion: Neural networks can be applied successfully for warfarin maintenance dose prediction. The results are promising, but further investigation is needed.
 

Background: The preconception and intraconception parameters that are relevant to outcome in women with underlying renal disease remain controversial.  

Objectives: To analyze the types and frequencies of short- and long-term (2 years after delivery) maternal and neonatal complications in 38 patients with primary renal disease (46 pregnancies), most of them with mild renal insufficiency.  

Methods: Logistic regression models were formulated to predict successful outcome.  

Results: Successful pregnancy outcome (live, healthy infant without severe handicap 2 years after delivery) was observed in 98% of the patients with primary renal disease. Factors found to be significantly predictive of successful outcome were absence of pre-existing hypertension, in addition to low preconception serum uric acid level.

Conclusions: Most women with primary renal disease who receive proper prenatal care have a successful pregnancy outcome. Worse pregnancy outcome was observed in women with moderate or severe renal failure. Fitted logistic models may provide useful guidelines for counseling women with preexisting renal disease about their prospects for a successful pregnancy in terms of immediate and long-term maternal and neonatal outcome.