I'm curious what proportion of issues like chronic lower back pain can be treated with strength training. To answer this question, we need to know a few quantities. The first of those is: what's the effect of strength training on chronic lower back pain? If we consult some meta-analytic data, we get to a pretty sizable effect that looks like it might have some publication bias, but it's not major. To account for potential publication bias, let's assume the effect lies somewhere in the range of 0.85 to 0.15. We'll say the midpoint is still 0.50 and we'll just sample throughout. We'll also have to convert from an SMD to an odds ratio. The conversion is approximately exp{d*\frac{\pi}{\sqrt{3}}}, which turns 0.50 into an OR of ~2.477. We would use an OR of 2.477 for the interpretation of odds of a good outcome, but for an adverse event, we would invert it, so 1/2.477 ~= 0.404. This conversion is approximate and assumes equal standard deviations and a logistic link, but I think those are reasonable enough. Given a baseline risk P_0 of "still in clinically-significant pain" at follow-up, the treated risk is P_1 = \frac{OR_{pain}P_0}{1-P_0+OR_{pain}P_0}. We'll sample among a range of values for P_0, assuming that between 10 and 20% of chronic lower back pain cases resolve on their own. So, what's the prevalence of chronic lower back pain? To figure this quantity out, I consulted a systematic review. The review estimated a chronic lower back pain prevalence of 4.2% for people aged 24-39 and 19.6% for those aged 20-59, so let's just simplify and say 10-20%, based on a systematic review I found. I'm not sure how realistic this value is, because I assume some amount of people who achieve resolution are actively doing something, and this draws them apart from the estimand we see in trials. Moreover, if the baseline to talk about is people who do nothing, then maybe the trials aren't so great, since they tend to have active controls instead of passive ones, thus underselling the population benefits of exercise. Now we have what we need and we can compute the "PIF", the "Potential Impact Fraction". This effect size is used to estimate the change in risk after a change in an exposure with a given size of effect. It's very similar to the PAF (Population Attributable Fraction) that you might've seen me use before. Be warned, the use of this for categorical things has been criticized. I'll link a study on that. My seed for this is 12345. I'm taking 100,000 draws, and the other details will be in the picture. TL;DR: It looks like given these assumptions, you could eliminate about 20% of chronic lower back pain if people committed to strength training. At a 5% prevalence, 0.85% or so of the population is no longer in significant pain due to exercise; at a 20% prevalence, 3.4% of the population is no longer in significant pain. That's huge! Two final remarks. First, if you want changes to the simulation, tell me. I'll gladly output runs with different parameters. Second, I think this really undersells it. I've known so many people who fixed their backs with strength training, and I think the strength training and commitment to it in RCTs is not all that great. If people were on more effective exercise plans and gained more muscle, I think they'd probably do even better. Plus, I think there's even more room to get strong prevention going on here, if more people go into midlife with strong backs. Thoughts? Questions? If you're wondering what the take-home message is, it's get out there and lift. That's always a good message. Sources: (see also:

I'm curious what proportion of issues like chronic lower back pain can be treated with strength training. To answer this question, we need to know a few quantities. The first of those is: what's the effect of strength training on chronic lower back pain? If we consult some meta-analytic data, we get to a pretty sizable effect that looks like it might have some publication bias, but it's not major. To account for potential publication bias, let's assume the effect lies somewhere in the range of 0.85 to 0.15. We'll say the midpoint is still 0.50 and we'll just sample throughout. We'll also have to convert from an SMD to an odds ratio. The conversion is approximately exp{d*\frac{\pi}{\sqrt{3}}}, which turns 0.50 into an OR of ~2.477. We would use an OR of 2.477 for the interpretation of odds of a good outcome, but for an adverse event, we would invert it, so 1/2.477 ~= 0.404. This conversion is approximate and assumes equal standard deviations and a logistic link, but I think those are reasonable enough. Given a baseline risk P_0 of "still in clinically-significant pain" at follow-up, the treated risk is P_1 = \frac{OR_{pain}P_0}{1-P_0+OR_{pain}P_0}. We'll sample among a range of values for P_0, assuming that between 10 and 20% of chronic lower back pain cases resolve on their own. So, what's the prevalence of chronic lower back pain? To figure this quantity out, I consulted a systematic review. The review estimated a chronic lower back pain prevalence of 4.2% for people aged 24-39 and 19.6% for those aged 20-59, so let's just simplify and say 10-20%, based on a systematic review I found. I'm not sure how realistic this value is, because I assume some amount of people who achieve resolution are actively doing something, and this draws them apart from the estimand we see in trials. Moreover, if the baseline to talk about is people who do nothing, then maybe the trials aren't so great, since they tend to have active controls instead of passive ones, thus underselling the population benefits of exercise. Now we have what we need and we can compute the "PIF", the "Potential Impact Fraction". This effect size is used to estimate the change in risk after a change in an exposure with a given size of effect. It's very similar to the PAF (Population Attributable Fraction) that you might've seen me use before. Be warned, the use of this for categorical things has been criticized. I'll link a study on that. My seed for this is 12345. I'm taking 100,000 draws, and the other details will be in the picture. TL;DR: It looks like given these assumptions, you could eliminate about 40% of chronic lower back pain if people committed to strength training. At a 5% prevalence, 1.1% or so of the population is no longer in significant pain; at a 20% prevalence, 4.4% of the population is no longer in significant pain. That's huge! Two final remarks. First, if you want changes to the simulation, tell me. I'll gladly output runs with different parameters. Second, I think this really undersells it. I've known so many people who fixed their backs with strength training, and I think the strength training and commitment to it in RCTs is not all that great. If people were on more effective exercise plans and gained more muscle, I think they'd probably do even better. Plus, I think there's even more room to get strong prevention going on here, if more people go into midlife with strong backs. Thoughts? Questions? If you're wondering what the take-home message is, it's get out there and lift. That's always a good message. Sources: (piece on this:

DOGPILE: LA STORIA DELLA BARCA DI DONALD Il testo completo, cronologico e integrale è ora disponibile su donald boat dot com.

Discussione sul poll degli agonisti del recettore GLP-1🧵 Prima domanda: Hai mai assunto un farmaco GLP-1RA? Questo include sostanze come liraglutide, albiglutide, semaglutide, tirzepatide, retatrutide, ecc.

La parola "grok" è una parola reale con un significato reale. Deriva da "Stranger in a Strange Land" e significa comprendere intuitivamente qualcosa.

Poiché alcune persone sembrano non saperlo: "Grok" è un termine reale con un significato effettivo. Proviene da "Stranger in a Strange Land" e significa comprendere intuitivamente qualcosa.

Non è un segmento molto buono Era pieno di insidie, e puoi comprendere tutte le cose corrette leggendo ~un articolo molto più breve Includeva molte fastidiose astuzie retoriche e cercava di far sembrare gli studi citati più importanti, credibili e inconfutabili di quanto non siano realmente.

"Perché pensi che ci sarebbero più regolamenti quando Trump ha fatto campagna per la deregolamentazione?" Come ha senso? Puoi sia regolamentare alcune cose che deregolamentarne altre.

Sto guardando il segmento di John Oliver su MAHA, e inizia male. Cita questo rapporto in modo positivo nonostante sia completamente spazzatura. Dice "ci sono studi a supporto" dell'idea che i coloranti alimentari artificiali siano dannosi, citando questo, e dimostrando di non saper leggere la letteratura.

Nelle elezioni del 2028, Polymarket ha registrato un piccolo guadagno per Newsom nell'ultimo giorno circa, ma tutto questo guadagno è venuto a scapito delle possibilità di AOC. Vance rimane in testa, con le stesse probabilità di prima.