Our paper on co-infections, secondary infections & antimicrobial use in patients hospitalised with #COVID19 in UK during the 1st wave is out in @LancetMicrobe!
2/ Of 48,902 hospitalised Covid19 patients enrolled in CCP-UK study (6 Feb - 8 June 20):
- 8,649 (17.7%) had >=1 microbiological investigation
- 1,107 had Covid19-related bacterial infection (blood or respiratory); 70.6% (n=762) were secondary infection (>48 hrs from admission)
3/ Most frequently identified organisms:
- Respiratory co-infection: Staph aureus & Haemophilus influenzae (differ from flu)
- Respiratory 2ry infection: Gram negative organisms & Staph aureus (similar to non-Covid HAI)
- Bloodstream co-/2ry infections: E Coli & Staph aureus
4/ Antimicrobial use:
- 37.0% had pre-hosp antibx
- 85.2% had >=1 antibx during hospital stay
- Co-amoxiclav & piperacillin-tazobactam comprise 30% of total prescriptions. Narrower spectrum antibx for LRTI (amoxicillin, doxycycline) less freq prescribed (19.2%)
5/ Limitations:
- We suspect preferential recording of micro results based on high culture-positivity rate (sputum 42%, deep resp 51.5%, blood cx 8.1%) therefore refrained from estimating prevalence of co-/2ry infection
- Timing of initiation & duration of antibx not recorded
6/ 🌟Take-home messages 🌟:
- During 1st wave, bacterial infections in hospitalised Covid19 pts were rare
- 71% were 2ry infections (>48h post admission)
- Gram negs & S aureus predominate
- High inpatient antimicrobial use (85%) - may have long-term consequences for #AMR
7/ Recommendations:
- Data supports restrictive empirical use antibx at hosp admission
- Ideally obtain blood & sputum cultures b4 empiric antibx
- Regular review of drug chart & discontinue antibx if co-infection deemed unlikely
8/ Need to monitor co-/2ry infections in second wave. Increasing use of steroids/immunomodulators may change epidemiology of 2ry infections.
Some reports of increasing multi-drug resistant organisms in US & invasive fungal infection (#mucormycosis) in India
2/ We developed & validated an easy-to-use 8-variable risk stratification score to predict inpatient mortality in hospitalised adults with #COVID19
The 4C Mortality Score uses patient demographics, clinical & blood parameters commonly available at the time of hospital admission:
3/ The 4C Mortality Score (range 0-21 pt) stratifies hospitalised patients into 4 risk groups, which can help clinicians optimise treatment:
- Low (<3) - 1% inhospital death
- Intermediate (4-8) - 10%
- High (9-14) - 31%
- Very high (15-21) - 62%
Summary estimates:
- early basic reproduction number (R0), i.e. the average number of persons that a new case will infect in a fully susceptible population, is 3.6-4.0. This is higher than the @WHO
estimate of 1.4-2.5, but within the range reported for #SARS in 2002/3 (R0 2-5)