Except for cannabis related diagnoses, their effect size (change in the incidence rate ratio dIRR) is of a similar magnitude as opioid-related diagnoses which they included for falsification testing and said it did not change.
Am I misinterpreting their statistics?
> Cannabis-related diagnoses (∆IRR 1.138, 95% CI 1.066 to 1.214, p<0.001), AF (∆IRR 1.023, 95% CI 1.010 to 1.035, p<0.001), HF (∆IRR 1.037, 95% CI 1.029 to 1.046, p<0.001), MI (∆IRR 1.031, 95% CI 1.014 to 1.048, p<0.001), ischaemic stroke (∆IRR 1.011, 95% CI 0.999 to 1.024, p=0.078), VTE (∆IRR 1.009, 95% CI 0.999 to 1.020, p=0.066) and VT (∆IRR 1.019, 95% CI 0.993 to 1.046, p=0.161). For falsification testing, there was no change in hospitalisations for urinary stones (∆IRR 1.006, 95% CI 0.986 to 1.027, p=0.535) or opioid-related diagnoses (∆IRR 0.966, 95% CI 0.927 to 1.006, p=0.091).
This paper seems to lack rigour. It starts with a premise then does not look at anything that might prove or disprove that premise. Hospital applications were not screened for cannabis use, only Colorado legalised but they used data from the whole western region, most importantly Medicaid also started at the same time as legalisation, do they investigate whether the availability of medical care prompted people to get medical treatment for their existing heart condition? They don't check whether the rise in cannabis use after legalisation was large enough to produce increases of this size across the whole population. An increase larger than the additional users would point to some other cause...
There is a whole website of similar spurious correlations (https://www.tylervigen.com/spurious-correlations). Will they now bring out a paper stating that Nicolas Cage films cause death by drowning? How about Solar power generation in Belize causing Fire inspectors in Florida, which both saw a very highly correlated jump in 2018?
In the way the study is designed, it could also be the non-using spouses having to pick up more work. Or the loss of motivation (and regular aerobic activity) by the users.
It's not totally worthless. It shows that recreational usage may lead to cardiovascular issues. Is it from the THC itself, way of administration, eating crap on munchies or having no motivation to move your ass is something for another paper.
Am I misinterpreting their statistics?
> Cannabis-related diagnoses (∆IRR 1.138, 95% CI 1.066 to 1.214, p<0.001), AF (∆IRR 1.023, 95% CI 1.010 to 1.035, p<0.001), HF (∆IRR 1.037, 95% CI 1.029 to 1.046, p<0.001), MI (∆IRR 1.031, 95% CI 1.014 to 1.048, p<0.001), ischaemic stroke (∆IRR 1.011, 95% CI 0.999 to 1.024, p=0.078), VTE (∆IRR 1.009, 95% CI 0.999 to 1.020, p=0.066) and VT (∆IRR 1.019, 95% CI 0.993 to 1.046, p=0.161). For falsification testing, there was no change in hospitalisations for urinary stones (∆IRR 1.006, 95% CI 0.986 to 1.027, p=0.535) or opioid-related diagnoses (∆IRR 0.966, 95% CI 0.927 to 1.006, p=0.091).
There is a whole website of similar spurious correlations (https://www.tylervigen.com/spurious-correlations). Will they now bring out a paper stating that Nicolas Cage films cause death by drowning? How about Solar power generation in Belize causing Fire inspectors in Florida, which both saw a very highly correlated jump in 2018?