When you encounter data problems like this one, you have a few options:
Follow up with the authors of the study to clarify what they meant to write
Write “no data” when you can’t determine the correct answer
Use statistical tools to approximate the information. Just be sure to note that this number is an approximation and not the true, known value. This will help you account for the uncertainty in the analytic phase of your systematic review.
Regardless of what tools you use to address faulty data, you’re going to note and report that the study had inconsistent information. Those mistakes will affect your assessment of the quality of the study and its potential “risk of bias.”
Make sense? Now let’s talk about another important aspect of data extraction: quality control.