Thread by @Bob_Wachter

1/ Covid (@UCSF) Chronicles, Day 37

It’s Thursday, so Grand Rounds day: @YouTube bit.ly/352S9bW, w/ @Rutherford_UCSF on epidemiology, Charles Chiu on viral genomics/testing, & system leaders on challenges @UCSFHospitals. 90 min worth watching.

2/ First, a few updates: @UCSFHospitals: 14 inpatients (down from 17), 5 on vent. Still just 1 death @ucsf since start (Fig on L).

In San Francisco: 69 new cases, 1302 total. Citywide hospitalizations stable at 80, no new deaths for past 4 days; 21 total since start (Fig on R).

3/ Before Grand Rounds highlights, two papers that caught my eye. First, a scary study from Guangzhou, China, esp. with summer coming bit.ly/34ZYGEx Shows apparent spread of Covid in air-conditioned restaurant, from a pt (asymptomatic at the time) to 10 other people….

4/ If this holds up (& science seems sound), argues that – even when people are seated >6 ft apart (tables were separated by 3 ft, & some infected patients were across next table) – there’s a non-zero risk if there’s air conditioning or a fan blowing. Alarming.

5/ Second paper: given stakes, key to get messaging right in publications. I was irked by reporting @JAMA_current of study of 5700 Covid pts hospitalized Mar 1-Apr 4 at huge @NorthwellHealth system in NYC bit.ly/2VwhDeT Lots of useful info re: outcomes and risk factors…

6/ Abstract (Fig L): “Mortality for those requiring mech vent was 88.1%,” scary # since most studies say ~50%. But per Table (Fig R), looks like 1,151 pts intubated; 320 of them discharged or dead by 4/4, & 282 died (88.1%). But 831 pts were in hosp (? # still tubed) on 4/5….

7/ …Meaning that unless all 831 pts went on to die (seems highly unlikely), the true mortality rate for mechanical vent is lower, maybe much lower, than 88.1%. Since most folks just read the abstract, this seems misleading (& would freak me out if I had a loved one on a vent).

8/ On to grand rounds: bit.ly/352S9bW. My best friend from high school, who's never known/cared what I do for a living, has become avid watcher; which means they must be accessible to all. So do take 90 min (or 60 min on 1.5x speed) to watch if you can. My Cliff Notes:

9/ At 11:25, @Rutherford_UCSF walks thru @Stanford Santa Clara study bit.ly/2yyGtBy George joins others in thinking it way-overestimates prevalence. “Apparently Bayes theorem was forgotten.” Walks thru Bayesian analysis (@ 12:55) showing high prob of many false +s (fig)

10/ More controversy about these studies, with brutal review @mercnews today bayareane.ws/2x4UBlZ (Fig) incl. this headline: “The authors owe us all an apology.”

New seroprevalence study from NYC bit.ly/3byN1z5, w/ 21% positive antibodies, is more plausible…

11/ Why? 142K confirmed NYC cases, so 21% of city (8.4M) -> 1.76M, or 12.5x confirmed case count, more in sync with other studies. If right, then true mortality rate (~15K deaths in NYC) about 0.8%, which also seems credible. There’ll be lots more of these serology studies soon.

12/ At 20:20, George describes Korean quarantine/contact tracing: police take phone, see where you’ve been, nat’l banking authority queries credit card records, they check street-cams to see where you’ve been…Probably not feasible in the U.S.: both privacy laws & cultural norms.

13/ At 25:00, Q: When he sees “Liberate-STATE”, what are thoughts? A) “That we’re looking at a 2nd wave…more transmissions, more cases, more deaths, if you get out of this too soon.” @ 30:35: 10-20% chance there WON’T be 2nd wave,” prob in fall, w/ schools as key site of spread.

14/ At 31:47: Worth watching as George does lightning round, as I asked him whether he (assuming the city/state opened these up) would go to a) Restaurant; b) Gym; c) Haircut; d) Movie; e) Airplane.

15/ At 36:02, Charles Chiu @ucsf discusses his pioneering work in CRISPR-based testing. @NatureBiotech paper here go.nature.com/3cLrPpo & review here bit.ly/2Vw24Uy Advantage: fast, accurate, scalable (& potentially home- based)(Fig).

16/ At 40:35, Charles describes genomic surveys regarding entry of SARS-Co-V2 into Northern CA. Breathtaking science – unique genomic fingerprint of each individual virus allows him to trace the lineage of every case. Also can aid in contact tracing.

17/ Shifting to @UCSFHospitals & Covid, at 1:02:00, CEO Mark Laret: “I’m increasingly comfortable that we’ll manage this surge and [any] subsequent surge. What I worry about most is the devastation on the economy… this is much worse than anything I could have imagined.”

18/ At 1:06:08: On @ucsfhospital’s $ problem: we’ll lose ~$150M in April. Might get $50M from feds, “There’s not enough money in D.C., printing presses can’t run long enough…We have to…rethink our business model…There’s pain associated w/ that but also tremendous opportunity.”

19/ At 1:10:05: Q to Josh Adler: How did he balance “evidence-based-medicine-meets-existential dread.” A) I learned that “safety is in the eye of the beholder,” … if people didn’t feel safe…we had to make changes. Perhaps it was a different science, the science of psychology.”

20/ At 1:15:10: Susan Smith on transformation @UCSF from 2% to 60% telemedicine. “It turns out fear is an incredibly motivating emotion.” Pts really appreciate it, MDs mostly do, but sometimes w/ tech difficulties or challenges communicating w/ pts, “and that can be exhausting.”

21/ At 1:23:30: John Roberts: @ucsf surgical cases went 70->10/d. Ready to ramp back up, but backlog will take 40 wks to get thru. Some pts still scared & no visitors a big problem. He described one pt who wouldn’t undergo liver transplant because wife couldn’t be w/ him. Tragic.

22/ As always, these Grand Rounds remind me how lucky I am to be @ucsf and @ucsfhealth – exceptional colleagues, with a wonderful combination of brilliance, passion and soul. Hope you have a chance to watch the session.

More tomorrow…