[ad_1]
"Our EHR derived FH clbadifier is effective in finding candidate patients for more in-depth screening for FH," the authors concluded. "Such automated learning-guided strategies can lead to an effective identification of the most at-risk patients for improved management strategies."
The co-author of the study, Nigam Shah, MBBS, PhD, also from Stanford, explained the main problem that the project aimed to solve.
Because FH is so rare, he told the institution's information division, it makes no sense to do general screening for all heart patients.
"Theoretically, when someone arrives at the clinic with high cholesterol or heart disease, we would use this algorithm," Shah said. "If they are reported, it means that there is a 80% chance that they will have FH. These few people could then be sequenced to confirm the diagnosis and immediately start a treatment to reduce LDL." . "
Source link
