In a study of pediatric patients predicting wrist fractures, the prediction rule indicates tenderness over the distal radius and grip strength loss. Do the results support the effectiveness of this rule for screening?

• A. Yes, the positive likelihood ratio is strong
• B. No, the negative likelihood ratio is insufficient
• C. Yes, sufficient sample size validates the finding
• D. No, the sample was not appropriately controlled

Answer: (B)

The rationale behind choosing the answer regarding the negative likelihood ratio is grounded in understanding the effectiveness of a prediction rule for screening. In this context, a strong negative likelihood ratio would indicate that the absence of the predictors—such as tenderness over the distal radius and grip strength loss—effectively rules out the diagnosis of a wrist fracture. A high negative likelihood ratio suggests that a patient without these signs is very unlikely to have a wrist fracture, making it a powerful tool for screening.

If the negative likelihood ratio is deemed insufficient, it implies that the prediction rule does not reliably rule out the diagnosis in those who do not present with tenderness or grip strength loss. In this case, the prediction rule may not provide adequate confidence for clinicians to use it as a screening tool, raising concerns about its clinical applicability. Thus, the effectiveness of the prediction rule for screening pediatric patients for wrist fractures would be questionable if the negative likelihood ratio does not support the conclusions drawn from the data.

Having a sufficient sample size gives more reliability to study findings, but if the prediction rule fails to effectively discriminate between those with and without wrist fractures based on the negative likelihood ratio, then simply having a larger sample size does not validate its effectiveness. Similarly, issues of sample control and a strong positive likelihood