Discover and read the best of Twitter Threads about #generalizability

Most recents (2)

1/ @STARRTAKI now published in @NEJM nejm.org/doi/full/10.10โ€ฆ โ€“ an updated thread follows below
#starrtaki #aki #FOAMcc @nephjc

@DrRonWald @CCCTG_ @anzicsctg @UKCCRGroup @ICCCTN @CIHR_IRSC @NIHRresearch @nhmrc @HRCNewZealand ๐Ÿ‡จ๐Ÿ‡ฆ๐Ÿ‡ฆ๐Ÿ‡บ๐Ÿ‡ฆ๐Ÿ‡น๐Ÿ‡ง๐Ÿ‡ช๐Ÿ‡ง๐Ÿ‡ท๐Ÿ‡จ๐Ÿ‡ณ๐Ÿ‡ฉ๐Ÿ‡ช๐Ÿ‡ซ๐Ÿ‡ฎ๐Ÿ‡ซ๐Ÿ‡ท๐Ÿ‡ฎ๐Ÿ‡ช๐Ÿ‡ฎ๐Ÿ‡น๐Ÿ‡ณ๐Ÿ‡ฟ๐Ÿ‡จ๐Ÿ‡ญ๐Ÿ‡บ๐Ÿ‡ธ๐Ÿ‡ฌ๐Ÿ‡ง
2/ Current CPGs do not make strong recommendations (Not Graded) on when to start RRT in ICU patients with AKI, in the absence of urgent indications, due largely to discrepant findings from prior RCTs (bit.ly/3fKqEZy) (bit.ly/39etR0N) @goKDIGO @NICEComms
3/ The @STARRTAKI trial is the largest multinational trial (168 sites, 15 countries) to address whether an accelerated (early) strategy compared with standard (delayed) strategy impacts mortality and kidney recovery in ICU patients with AKI #generalizability
Read 14 tweets
1/
Suppose you want to extend causal inferences from a randomized trial to a target population.

Is that #transportability or #generalizability?

Issa Dahabreh and I propose an answer in this brief commentary in the European Journal of Epidemiology:
ncbi.nlm.nih.gov/pubmed/31218483 Image
2/
For those interested in methods for extending inferences from randomized trials to a target population:

Take a look at our tutorial
arxiv.org/pdf/1805.00550โ€ฆ
(soon to appear in Statistics in Medicine)

You will find identification conditions AND three estimation approaches. Image
3/
Want more?

This article in @Biometrics_ibs considers estimators to generalize inferences from individuals in randomized trials to all trial-eligible individuals:
ncbi.nlm.nih.gov/pubmed/30488513

And this article in @EpidemiologyLWW clears some confusions:
journals.lww.com/epidem/fulltexโ€ฆ
Read 5 tweets

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