First observational study to assess FH patients made in Bulgaria using NLP algorithm

First observational study to assess FH patients made in Bulgaria using NLP algorithm

  • company News
  • 10 months ago

Advances in Therapy, an international medical journal, has published the Research Article "Familial Hypercholesterolemia identification algorithm in patients with acute cardiovascular event in a large hospital electronic database in Bulgaria – a call for implementation" 

Sqilline is extremely honored to be co-writer among such extreme professionals and experts in the field.

Our advanced solution Danny Platform® played a key role in the process and analyses of this fundamental article.

Click to play the abstract video of the article:



  • Using all available medical records from EHR systems to extract treated patients admitted for ASCVD acute events to screen for FH
  • Reinforce early FH identification and improving patient pathways and outcomes


  • Limited data on the proportion and management of FH among adults
  • Under diagnosed, an acute event is usually the 1st clinical manifestation of FH
  • Most patients are unaware they have it until a significant cardio event occures


  • Danny Platform’s NLP algorithm was developed to identify patients with arcus Cornealis, tendon xanthoma, or stated FH
  • Danny Platform’s algorithms search the EHR of patients admitted to hospital for the treatment of an acute CV event to identify those with undiagnosed FH
  • The platform can automatically calculate the Dutch Lipid Clinic Network Score(DLCNS)


  • 11 090 patients recorded an acute cardiovascular event
  • 44% of patients to have possible FH and 56% to have probable/definite FH
  • 37% of patients discharged with high-intensity satin therapy
  • 96% of patients had poorly controlled cholesterol during the first year after discharge


  • Systematic screening and early identification of FH during hospitalization will improve patients’ treatment and outcomes
  • Empowering physicians to reinforcing early FH identification to improve futurepatient outcomes
  • Reducing burden on the healthcare system via automated screening tool during hospitalization may allow for rapid and effective lipid management, prevention of recurrent events



  • Prof. Ivo Petrov (Head of Cardiology, Angiology and Electrophysiology Department: Acibadem City Clinic Cardiovascular Center)
  • Assos. Prof. Arman Postadzhiyan (Department of General Medicine, Emergency University Hospital “St. Anna”, Medical University of Sofia)
  • Dr. Dobrin Vasilev (Head Cardiology Clinic at Alexandrovska University Hospital)
  • Dr. Ruslan Kasabov (Department of Interventional Cardiology: Hospital “Pulmed” Plovdiv
  • Prof. Dr. Fedya Nikolov and Assos. Prof. Mariya Tokmakova (Department of Cardiology, Medical University of Plovdiv)
  • Reneta Petkova (Department of General Medicine, Amgen Bulgaria)
  • Veselin Istatkov, Boyang Zhao, and Dimiter Mutafchiev (Sqilline)

Click here to read the full publication in Advances in Therapy:

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