生物与医学2020nature.com
葡萄糖代谢对感知糖摄入的反应强于实际摄入
Glucose metabolism responds to perceived sugar intake more than actual intake
进阶 · 约 30 分钟读完前置知识：糖尿病与血糖调节基础、统计假设检验、实验设计
导读
这项发表在 Scientific Reports 的研究让2型糖尿病患者饮用实际含糖量被暗中调换、但标签标注与实际不符的饮料，比较"以为高糖"和"以为低糖"两种情况下的血糖反应。结果显示，主观感知的糖摄入量对血糖代谢的影响大于实际摄入量，提示预期/心理因素可能参与血糖调节。样本约30人（每组约15人），属短期实验室研究。
HN 关注点："心理预期能左右血糖"这一反直觉结论很有传播力，但HN读者很快把焦点转向样本量小、统计功效不足、血糖仪测量误差和混杂因素控制等可复现性问题。
HN 评论精选
这几条评论里：质疑 2 补充 1 亲历 1
亲历1型糖尿病患者用CGM的亲历：甜味感知并未实际升高血糖，希望做换标签的T1D实验。
我是1型糖尿病患者。我曾相信人工甜味剂会因为饮料尝起来甜而让身体升高血糖，但用上连续血糖监测（CGM）后我验证了并非如此。我希望能做一个调换标签、用CGM监测1型患者的实验，因为（如果真有）胰岛素反应在这种情况下是不存在的。我明白这项研究有诸多限定（2型、餐前<200mg/dL、实验室环境、假标签、短期），也赞赏压力与空腹血糖升高之间可能的联系（类似睡眠与血糖升高的联系）。我读过论文，只是补充一个个例。
1123581321查看英文原文
I'm type 1. I used to believe artificial sweeteners caused the body to raise its blood sugar because the drink is perceived to be sweet, but when I got a CGM I was able to verify that they do not. I'd be interested in a switched label test with CGMs and T1s because a potential insulin response would be absent. I realize this study is qualified (type 2, preprandial < 200mgdl, lab setting, fake labels, short term) and laud the potential connection between stress and elevated fasting glucose (seems similar to the connection between sleep and elevated glucose.) I've read the study and am just adding a personal anecdote to the thread.
补充预期机制在解渴中同样存在；不应据此否定人工甜味剂，实际摄入的糖在体内的存量影响更持久。
类似的预期机制也存在于解渴：喝水的那一刻我们就感觉没那么渴了，但新摄入的水真正改变渗透压环境需要几十分钟。我也认为拿这个结果去抨击人工甜味剂过于草率——它们会增加食欲/渴望、减肥者需警惕，这点早已为人所知。但初始进食只是糖代谢的一部分；真正可生物利用的糖留在血液、肌肉和肝脏（糖原）中的量，会在之后数天里持续影响能量代谢，并带来减重等下游后果。
acituan查看英文原文
A similar anticipatory mechanism exists for thirst quenching. We feel a decrease in thirst the moment we drink water but in reality it takes tens of minutes for the osmotic landscape to change with that newly ingested water.[1] I also think it is overeager to take this result and run with it to condemn artificial sweeteners. It has been known for long that they can indeed increase cravings and cautioned against for dieters. However, the initial intake of food is only one part of the glucose metabolism. How much actual glucose is left in your bloodstream, muscles and liver (in the form of glycogen) will keep effecting your energy metabolism for days if you've ingested real, bioavailable sugars, with all the downstream consequences e.g. for weight loss. [1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6014472/
质疑统计功效不足、模型p值可疑，需复现研究才能相信该效应。
不确定这项研究能否复现：约30名参与者、每组15人，统计功效本来就不高。低糖标签组和高糖标签组在摄入后实测血糖都出现峰值，两组差异只有约10%。两组的原始p值在2%、6%、2%，勉强显著，但p值来自一个复杂模型，可能存在p-hacking问题，需要做p值校正。我会等复现研究再说。如果效应真实，只要把样本量翻倍，就能把t值从2提到3，p值从2–6%降到0.2%。不过还是赞赏作者探索这一理论，鼓励复现把p值压下去。
fanzhang查看英文原文
Not sure if this study will replicate: The study had about 30 participants, with 15 in each arm, so that's not a lot of statistical power to begin with. Both the low-glucose-label and high-glucose-label arms showed a spike in actual measured blood sugar after ingestion. The difference in blood glucose between the two arms was just about 10%. The naïve p-value between the two arms was barely significant at 2%, 6%, and 2%, but the p-values were taken from a complex model that probably has p-hacking problems and needs p-value correction. I would wait for the replication study before believing in this effect. If the effect is real, they only need to double their sample size to get a t-stat of 3 instead of 2, which would give a much more convincing p-value of 0.2% instead of the 2-6% right now. I applaud the authors for exploring this theory though, and encourage replications to push the p-value down.
质疑未控制胰岛素敏感性、用药和体重等混杂因素，且血糖测量误差可能吞掉约20 mg/dL的差异。
这里有很多问题：一个根本缺陷是没有做基线葡萄糖敏感性测定。糖尿病患者（尤其2型）的胰岛素分泌与敏感性差异很大，各组平均值不同会强烈影响结果。他们似乎连药物剂量都没纳入，只记录是否服用双胍类，甚至没提体重——另一个影响胰岛素敏感性的重要因素。第二是血糖升幅：血糖检测本身有误差，而本研究测到的差异只有约20 mg/dL。抽血化验的总误差约8%，若是这类检测，8%的波动就能让结果变得不显著；若用快速血糖仪（即便诊所用的那种），更糟：结果落在实验室值15%以内就算准确，也就是在一个本身有8%总误差的数值上再±15%。每组约15人的控制欠佳研究，问题实在太多。而且很可能不久就会出现"糖尿病：以为糖重要？再想想"之类的标题。
ineedasername查看英文原文
There's a lot to dig into here that's wrong: One fundamental problem with this is the lack of baseline determination of glucose sensitivity. People with diabetes, especially type 2, have different sensitivities & levels of insulin production. A group with greater or lesser averages on those factors would strongly influence results. They don't even appear to have accounted for medication dosage, merely whether or not the person was on biguanide. Or even mention weight, another significant factor for insulin sensitivity. Second is the glucose increase: Glucose tests have margins of error, an issue not addressed here, and the difference in glucose levels this study measure were small considering that factor, about 20 points. Specifically: Even a blood-drawn lab test has a total error of about 8%. If that's tge type of test they did, then an 8% swing could reduce the results to insignificance. If they used a rapid test, even the sort used in a doctor's office, it's even worse: those are considered accurate if it produces results that are within 15% of what a lab test would produce, meaning +/- 15% of a value that already has a total error of 8%. There's just too much wrong with a study like this that's poorly controlled with ~15 people in each group. And unfortunately there's a decent chance we'll see headlines soon along the lines of "Diabetes: Think sugar matters? think again ::lol lol we made a pun::"
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