∆QT Database

Frequently Asked Questions

What is ∆QT Database?
∆QT Database is a publicly available resource for exploring the effects of one or more drugs on the QT interval. Drug-induced prolongation of the QT interval can increase the risk of a potentially fatal arrhythmia. The effects of individual drugs on the QT interval are well-studied, and in recent work our group has computationally predicted and experimentally validated the QT-prolonging effects of multiple drugs taken at the same time (drug-drug interactions). See CredibleMeds.org for an excellent introduction to long QT syndrome.

This website provides a front-facing interface for users to investigate one or more drugs and drug classes. You can save the resulting plot, the subset of data currently viewed, or the entire database. All source code for the site is available on GitHub.

Why is my drug not in the database?
∆QT Database only includes 259 commonly prescribed drugs at NewYork-Presbyterian Hospital to ensure patient privacy. If the drug(s) you are interested in studying are not included, email Nick Tatonetti to discuss a potential collaboration where we can provide evidence using our entire electronic health record; in these cases we will not be able to share the underlying data.

Where did the data come from?
The ∆QT Database is a deidentified subset of electronic health record data originally collected at NewYork-Presbyterian Hospital/ Columbia University Medical Center and mapped to the OHDSI Common Data Model. To prepare the data for public release we performed the following deidentification procedure (available as a Python script on GitHub):

  1. Removed 18 HIPAA Safe Harbor identifiers.
  2. Only included patients taking one or more commonly prescribed drugs (>3000 patients prescribed drug in EHR, N=259) and with at least 2 electrocardiograms (ECGs).
  3. Excluded patients younger than 18 or older than 89 at time of ECG; randomly adjusted age ±0-5 years.
  4. Defined global baseline for each patient: median QTc (heart rate-corrected QT) interval across all of that patient's ECGs.
  5. Defined one or more "ECG era"s for each patient: one or more ECGs combined into an era, such that each subsequent ECG occurs no more than 36 days after the previous one (otherwise create new ECG era). For each ECG era, defined maxECG as the ECG date with the most prolonged QTc interval.
  6. Collected all drugs a patient was taking 0-36 days inclusive before the maxECG date.
  7. Randomly swapped small subset of drug exposures from one patient to another to further deidentify the data. 6.5% of patients had at least one swapped drug. To perform swap:
  8. Each entry in the database then contains:

How can I use these data?
We are providing ∆QT Database as a publicly available dataset to enable researchers, clinicians, and patients to have access to investigate the effects of drug(s) of interest or to conduct new data mining studies. Take a look at an example here.