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GidMK's profile
Health Nerd
Health Nerd
Health Nerd
Verified account
@GidMK

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Health NerdVerified account

@GidMK

Epidemiologist. Writer (Guardian, Observer etc). "Well known research trouble-maker". PhDing at @UoW Host of @senscipod Email gidmk.healthnerd@gmail.com he/him

Sydney, New South Wales
theguardian.com/profile/gideon…
Joined November 2015

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    1. Nicola Guess‏ @Dr__Guess 21 Jun 2019
      Replying to @dnunan79 @DrSarahHallberg @bigfatsurprise

      Have a read David and let us know your thoughts. For me this type of study (very very difficult to do) is exactly what is needed to avoid the “well it’s not clear if it’s weight loss or carb restriction which is the effective part...”

      3 replies 0 retweets 10 likes
    2. Health Nerd‏Verified account @GidMK 21 Jun 2019
      Replying to @Dr__Guess @dnunan79 and

      I can't speak to the experimental design, but it appears that they've done dozens of anovas and t-tests without any control for multiple comparisons, which is not ideal

      2 replies 0 retweets 10 likes
    3. Pauli Ohukainen, PhD‏ @POhukainen 21 Jun 2019
      Replying to @GidMK @Dr__Guess and

      What I'm curious about is that LC group ate 2,5x more SFA yet looks like no change in LDL-C and apoB is not reported. This data is in the supplement although quite a remarkable result. Rises a lot of questions about the protocol.

      2 replies 1 retweet 7 likes
    4. Nicola Guess‏ @Dr__Guess 21 Jun 2019
      Replying to @POhukainen @GidMK and

      Cheese? NCT02918422

      2 replies 0 retweets 4 likes
    5. Health Nerd‏Verified account @GidMK 21 Jun 2019
      Replying to @Dr__Guess @POhukainen and

      Makes sense when you look at the funders. Also looks like there's some sneaky outcome switching going on!pic.twitter.com/JoVM5Twfl8

      3 replies 0 retweets 4 likes
    6. David Nunan‏ @dnunan79 21 Jun 2019
      Replying to @GidMK @Dr__Guess and

      Checked http://clinicaltrials.org  entry. MetS not mentioned. Prim outcome = change in PFAs + lipoproteins. These reported 3rd/4th after MetS & secondary outcomes (e.g. DEXA). Unclear allocation concealment + all unblinded. n=16, P-values only and no 95% CIs anywhere in text.

      1 reply 2 retweets 16 likes
    7. David Nunan‏ @dnunan79 21 Jun 2019
      Replying to @dnunan79 @GidMK and

      Use of "P < 0.05" and “trend” when >0.05 suggests wide CIs close to no stat difference. No mention by authors re: size of effect. Others can comment as to whether effect sizes = meaningful. For me = exploratory findings at best. Need replicating w >n, >robust, w <COI.

      2 replies 1 retweet 14 likes
    8. Nicola Guess‏ @Dr__Guess 21 Jun 2019
      Replying to @dnunan79 @GidMK and

      Can’t do this type of study blinded though. That wil also be issue with diet study?

      1 reply 0 retweets 3 likes
    9. David Nunan‏ @dnunan79 21 Jun 2019
      Replying to @Dr__Guess @GidMK and

      Outcome assessors?

      1 reply 0 retweets 1 like
    10. David Nunan‏ @dnunan79 21 Jun 2019
      Replying to @dnunan79 @Dr__Guess and

      I guess the main thing is how big are the effects? I’m guessing fairy small. You could overlook some of the biases (IMO) when effects are large/likely 2 b large. But most effects are small - this means even small biases potentially have big impact. = need strong methods

      3 replies 0 retweets 6 likes
      Health Nerd‏Verified account @GidMK 21 Jun 2019
      Replying to @dnunan79 @Dr__Guess and

      If I were a cynical person I'd say that this is exactly what you'd expect from an industry-funded trial that found a null effect but had to report a positive outcome regardless

      11:59 PM - 21 Jun 2019
      • 2 Likes
      • Tak Pauli Ohukainen, PhD
      0 replies 0 retweets 2 likes

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