Below is an email I have sent to Sentara Norfolk General Hospital, the editor of CHEST Journal, and prof Paul E Marik. As always an allegation against a multi-author paper is not an allegation against any individual author.
To:
The Editor in Chief of “CHEST” Peter J. Mazzone
cc: The Board of Norfolk Sentara Norfolk General Hospital
cc: The Compliance officer of Sentara Norfolk General Hospital
cc: Prof Paul E Marik
Dear Editor
Tonight on twitter a paper allegedly describing a 2017 study by a “Paul Marik” and team at Sentara Norfolk General Hospital describing a large survival benefit from Vitamin C was brought to my attention as a medical research finding that was not replicated in further studies and later reversed. The user stated that to their knowledge no evidence of fraud in the conduct of this study had been identified. The study is found at https://doi.org/10.1016/j.
Unfortunately within about 5 minutes of reading the study it became overwhelmingly clear that it is indeed research fraud and the data is fabricated.
While usually I would use cautious language of “unusual” or “unexpected” patterns in the data and describe “irregularities” and “concern”; no such caution is warranted in this case. This is frankly audacious fraud. I have not requested access to the raw data or contacted the authors for explanation as the case is audacious no other explanation is possible.
Allow me to explain.
This study allegedly describes a before and after study, examining the effect of a new treatment regime based on vitamin c on mortality in sepsis, claiming a roughly ten fold reduction in death. Each cohort had exactly 47 patients and the patients were not matched. We know this not just because matching was not mentioned but because the authors specify that these were two cohorts of “consecutive” patients, precluding patient matching by definition.
Based on this we would expect that if there was no systemic bias the p values for differences in dichotomous baseline characteristics (gender, demographics, comorbidities, diagnoses etc) would, of course, centre on 0.5. If systemic differences existed however the groups may be less similar and p values may tend to numbers below 0.5, and this would not be suspicious in a non-randomised study. Systemic biases to p values greater than 0.5 are not possible without matching (or some very rare pseudo-block designs not relevant here) except
