**Core Concept**
The sensitivity and specificity of a diagnostic test are measures of its performance in correctly identifying those with and without the disease, respectively. These metrics are crucial in evaluating the reliability of a test in clinical settings.

**Why the Correct Answer is Right**
A test with a sensitivity of 90% correctly identifies 90% of patients with the disease, while a specificity of 95% means that it correctly identifies 95% of patients without the disease. To find the true statement, we need to calculate the positive predictive value (PPV) and negative predictive value (NPV) of the test. The PPV is the proportion of patients with a positive test result who actually have the disease, while the NPV is the proportion of patients with a negative test result who do not have the disease.

**Why Each Wrong Option is Incorrect**
**Option B:** This option is incorrect because it does not accurately describe the relationship between sensitivity and specificity and the predictive values of the test.

**Option C:** This option is incorrect because it does not account for the fact that the test is not 100% accurate, and there may be false positives or false negatives.

**Clinical Pearl / High-Yield Fact**
When interpreting the results of a diagnostic test, it's essential to consider both the sensitivity and specificity, as well as the prevalence of the disease in the population being tested. This will help clinicians make informed decisions about further testing and treatment.

**Correct Answer:**
A. The test has a high positive predictive value, meaning that most patients with a positive test result actually have the disease.