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Thursday, September 21, 2017

FDA Repairs its MAUDE Database

I have posted several times this year about an error in the FDA MAUDE database (see here, here and here for previous posts).

To summarize, the FDA's MAUDE database captures reports of malfunctions and injuries associated with medical devices. The MAUDE database is supposed to capture patient outcome information like:

  • Did the patient die during/as a result of the device malfunction?
  • Was the patient hospitalized due to the malfunction?
  • Was the patient disabled?
  • etc.


About 2 years ago, the FDA's MAUDE database stopped reporting patient outcomes and replaced these outcomes with a cryptic code of "8.".

As you might imagine, this is a pretty serious omission. It seems kind of important to know what happened to the patients when a device malfunctions.

I contacted the FDA earlier this year and informed them of the error.

Today, I received an email indicating that the database has been fixed and the outcomes are back!



FDA was also kind enough to explain what "8." meant:


Wednesday, August 30, 2017

Update # 2 on "8." MAUDE Database

I've previously written (here and here) about an error in the FDA medical device adverse events database known as MAUDE. The error prevents the database from reporting patient outcomes (death, hospitalization, etc.).

I received correspondence from someone at the FDA last week indicating that they may have found a fix (see screenshot of email).


However, so far, they have not implemented the fix. You can see this in two ways:

First, if you download the patient outcome file from the FDA website and open it up, you see a series of "8"s where the outcome data should be (see pic).

Second, you can query the MAUDE database using the OpenFDA platform and count the distribution of patient outcomes in the year:
As of this moment, if you click on this link, you will see the distribution of patient outcomes in the MAUDE database from the beginning of 2016 until yesterday. You can see from the pic below that there are no outcomes, only variations on "8."



Monday, August 7, 2017

Update on "8." and MAUDE Patient Outcomes

I have previously posted about the FDA's adverse events database for medical devices (known as MAUDE). In past years, the MAUDE database had captured patient outcome information (whether the patient died, was hospitalized, suffered some form of disability, etc.).

The database no longer reports patient outcomes (it stopped doing so in late 2015). Instead, the database field that should contain outcome data contains the cryptic entry of "8." (the number 8 with a period). I recently contacted the FDA, asking why MAUDE no longer provided patient outcome data. I received the following responses (thus far). I've edited out identifying information (and superfluous text).

This is from an email dated 28 July 2017. It's moderately encouraging. In particular, it's encouraging to know that the patient outcome information  is _still_ captured, and it will probably be added back to the database once they determine what the error is.

I will post updates as they develop.

 Dear Dr. Danese,
Thank you for contacting the Division of Industry and Consumer Education (DICE) at FDA's Center for Devices and Radiological Health (CDRH) xxxxxxx@fda.hhs.gov e-mail account. As far as I am aware, patient outcome information is still collected on so adverse event reporting forms. So, at this time I am not clear on why this information is not included in the data sets for 2015 and beyond. I am in the process of researching the issue and contacting the medical device reporting staff. I apologize for the delay but hope to have an answer for you next week. .... Sincerely, xxxxxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxxx Division of Industry and Consumer Education Office of Communication and Education Center for Devices and Radiological Health U.S. Food and Drug Administration
I then received a follow-up email on 4 August (Friday)
Dear Dr. Danese, 
Thank you for your patience while I looked into your inquiry. I have spoken with a member of the Information Analysis Branch and it seems some of the patient outcome information may have been inadvertently excluded from the downloadable zip files. xxxxxx has kindly agreed to look into this issue to figure out what happened and how the problem may be corrected. Please feel free to contact xxxx directly. xxxxx name is xxxxxxxxxxxxxx and xxxxx email address is xxxxxxxx@fda.hhs.gov. I hope you have a pleasant weekend. Sincerely, 
xxxxxxxxxxxxxxxxxxxxxxxxxxx 
xxxxxxxxxxxxxxxxxxxxxxxxxx
Division of Industry and Consumer Education Office of Communication and Education Center for Devices and Radiological Health U.S. Food and Drug Administration
And then this email from the Information Analysis Branch (dated 7 August)
Paul, I was notified of the issue by xxxxxx on Friday, and we are currently investigating. We will get back to you when we know more. Thank you. xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Information Analysis Branch Division of Post Market Surveillance Office of Surveillance and Biometrics Center for Devices and Radiological HealthUS Food & Drug Administration 

Tuesday, May 30, 2017

Clustering of Drugs by Side Effect Profile

Others (here, herehere + others) have clustered medications based on side effect profiles. Everyone has done it a little differently.

In this post, I perform a similar type of clustering using slightly different methods (details forthcoming). I'm not providing m̶u̶c̶h̶ any of the methodological details in this post, but I just wanted to show a pretty plot with nice clusters.

Drugs were clustered using t-SNE (here and here), which is a method that is remarkably good at taking high-dimensional data (in this case, thousands of different side effects) and clustering it into 2-dimensions while maintaining much of the "nearest neighbor" information that was present at high dimensions.

You can see the 2-D "cluster plot" (after t-SNE transformation) below.


  • Hover over the data points to see drug names.
  • I colored the data points by running k-means on the 2-D data (very quick and dirty and probably not the best approach).
  • Still, you can see pretty good functional clustering. For example: 
    • the dark green points on the left edge of the plot are almost all related to cholesterol and lipid pharmacotherapy. If you zoom in, you will also find daptomycin (an anti-bacterial), but it clusters there b/c it is associated with reports of myopathy and rhabdomyolysis (adverse events that are somewhat characteristic of the "statins").
    • red and blue points on the left edge are primarily involved w/ Type 2 diabetes.



Friday, March 17, 2017

Trump submitting adverse event reports?


Found this "classic" adverse event report submitted to the FDA in 1994. 76 year old male patient taking Sinemet and Xanax with a report of the following issues:

  • asthenia
  • coordination abnormal
  • dysphagia
  • med error

The kicker is in the comments section: 'Pharmacist "jokingly" told patient to take the medication with Vaseline, [which] the patient did.'

  • First, I'm not sure why jokingly is in quotes. Was the reporter quoting the pharmacist, in which case the quotation marks emphasize a literal and sincere description of the communication between pharmacist and patient? Or are the quotation marks meant in the ironic-2017-Sean-Spicer-fake-news sense, in which case the pharmacist comes across as malevolent? Tough call.

  • Second, the report labels the Sinemet as the suspect medication! I'm going to go out on a limb and speculate that the Vaseline itself was causing the dysphagia, but don't quote me on that.

Saturday, February 25, 2017

I'm trying to make a dictionary of drugs named in FAERS and their active ingredient(s).

Let's see how many ways we can abbreviate, misspell name a drug that contains paracetamol/acetaminophen:
  1. acamol
  2. aceminophen
  3. acetam
  4. acetametamin
  5. acetamilnophen
  6. acetamin
  7. acetaminaphine
  8. acetamino
  9. acetaminofen
  10. acetaminohen
  11. acetaminop
  12. acetaminopehn
  13. acetaminopen
  14. acetaminoph
  15. acetaminopham
  16. acetaminophe
  17. acetaminophen
  18. acetaminophen0
  19. acetaminophin
  20. acetaminophn
  21. acetaminphen
  22. acetamiophen
  23. acetamonophen
  24. aceteminophen
  25. acetminophen
  26. acetomeniphen
  27. acetominopehn
  28. acetominophen
  29. actigrip
  30. actyaminphen
  31. adetaminophen
  32. algisedal
  33. algotropyl
  34. alpiny
  35. alvedon
  36. alvedone
  37. amidrine
  38. anhiba
  39. antalvic
  40. apap
  41. aplexil
  42. aracetamol
  43. atasol
  44. butal cf acetamn
  45. calonal
  46. calpol
  47. car panadol
  48. claradol
  49. cocodamol
  50. codamol
  51. codoliprane
  52. coltalin
  53. combiflam
  54. comtrex
  55. dafagan
  56. dafalgan
  57. daflagan
  58. defalgan
  59. depalgos
  60. depon
  61. dexamol
  62. dextr neo citran
  63. di antalvic
  64. dolipran
  65. doliprane
  66. dristan
  67. efferalgan
  68. endocet
  69. esgic
  70. excedrin
  71. excedrin migraine
  72. exedrin
  73. exedrin asa
  74. fervex
  75. feverall
  76. fioricet
  77. frenadol
  78. grippostad
  79. hycet
  80. hydroc/apap
  81. hydroco apap
  82. hydroco/acetaminophen
  83. hydroco/apap
  84. hydrocod/acetam
  85. hydroodone/apap
  86. ixprim
  87. kolibri
  88. lamaline
  89. liq tyelnol
  90. loratab
  91. lorcet
  92. lortab
  93. mapap
  94. maxidone
  95. maxiumum midol pms
  96. midol
  97. midol pms
  98. midrin
  99. migrazone
  100. miradol
  101. mission supac
  102. neo citran
  103. neocibalena
  104. norco
  105. ofirmev
  106. osteo panadol
  107. oxy/apap
  108. oxycod/apap
  109. pactiv
  110. panadeine
  111. panadol
  112. panodil
  113. parace
  114. paracematol
  115. paracemtamol
  116. paracet
  117. paraceta
  118. paracetam
  119. paracetamil
  120. paracetamo
  121. paracetamol
  122. paracetamol0
  123. paracetamolo
  124. paracetmol
  125. paracetmol aporex
  126. paracetramol
  127. paractol
  128. parad
  129. paralgin
  130. paralyoc
  131. paramol
  132. percocet
  133. perfalan
  134. perfalgan
  135. pro dafagan
  136. prontalgine
  137. proparacetamol
  138. pyrinazin
  139. roxicet
  140. saridon
  141. sinex
  142. sinutab
  143. tachidol
  144. tachipirina
  145. traiminic
  146. tramcet
  147. trimanic
  148. tyelnol
  149. tyenol
  150. tylenol
  151. tylenolpm
  152. tylonal
  153. ultracet
  154. ultraset
  155. xartemis
  156. xolox
  157. zapain
  158. zydone

                                                                                                                                                                                                                                                                                                                          Thursday, January 19, 2017