Lipid Manager vs EBM Stats Calc

The ACC Lipid Manager app provides two clinical decision support tools in one app to help clinicians manage a patient’s triglycerides and LDL-C from therapy initiation through treatment calibration with the goal of lowering ASCVD risk: •  Lipid Lowering Therapy tool: Supports selection of lipid‑lowering therapies and individualized goals to reduce ASCVD risk through targeted management of LDL-C and triglycerides (previously known as LDL-C Lowering Therapy) •  Statin Intolerance tool: Evaluate the patient for possible statin intolerance, and determine appropriate next steps The information and recommendations in this clinical decision support app are not meant to represent the only or best course of care nor replace clinical judgement. Therapeutic options should be determined after discussion between the patient and their care provider. Financial support for Lipid Manager was provided by Esperion. All content was independently developed with no sponsor involvement.

Occasionally in medicine, we really need to "do the math". This app will help. EBM Stats Calc let's a clinician do calculations that are hard or impossible to do in one's head. A clinician can get NNT's (number needed to treat) from rates, percentages, or raw event and patient numbers. And a clinician can use sensitivity and specificity or likelihood ratios (LR+, LR-) to go from a pretest probability to posttest probability and positive predictive value and negative predictive value. Although these calculators themselves are somewhat novel for apps, the unique tool in this app is for educators. Students and residents have a hard time understanding how the utility of a test can vary with pretest probability. Instead of saying it in words and hoping they get it, now you can demonstrate it. A test might perform well, giving good PPV and NPV, when pretest probability is in a certain range. But slide that pretest probability up or down and see the diagnostic utility change with the numbers flying right before your eyes. The tool also shows a student that in many cases, an imprecise estimate of pretest probability doesn't much matter. Different doctors might judge a clinical case to suggest likelihood of disease (pretest probability) of 40%, 50%, or 60%. The slider tool shows that the differences may not matter, and the test in mind will render good clarity regardless of differing opinions on pretest probability. The app is written for clinicians, students, residents, and especially educators, in any discipline of medicine. As a clinician and educator myself, I would be grateful for feedback to make the tool better.