43 research outputs found
SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study
Background
Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling.
Methods
The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18β49, 50β69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty.
Results
NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year.
Conclusion
As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population
ΠΠ»ΡΠ½ΡΠΊΠΎ-Π³Π΅ΠΌΠΎΠ΄ΠΈΠ½Π°ΠΌΡΡΠ½ΠΈΠΉ Π΅ΡΠ΅ΠΊΡ ΡΡΡΠΊΡΠΎΠ·ΠΎ-1,6-Π΄ΠΈΡΠΎΡΡΠ°ΡΡ ΠΈ ΡΠΎΡΡΠΎΠΊΡΠ΅Π°ΡΠΈΠ½Ρ Ρ Ρ Π²ΠΎΡΠΈΡ Π½Π° Π³ΠΎΡΡΡΠΈΠΉ ΠΊΠΎΡΠΎΠ½Π°ΡΠ½ΠΈΠΉ ΡΠΈΠ½Π΄ΡΠΎΠΌ
One of the promising areas of treating cardiovascular diseases is the use of drugs with metabolic action.Β Metabolic drugs have not only the ability to improve myocardial energy metabolism, but also strong antioxidant properties.ΠΠ΄Π½ΠΈΠΌ ΠΈΠ· ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π½ΡΡ
Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΠΉΒ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ ΡΠ΅ΡΠ΄Π΅ΡΠ½ΠΎ-ΡΠΎΡΡΠ΄ΠΈΡΡΡΡ
Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ ΡΠ²Π»ΡΠ΅ΡΡΡΒ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠΎΠ² Ρ ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠ΅ΡΠΊΠΈΠΌ Π΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ΠΌ.Β ΠΠ΅ΡΠ°Π±ΠΎΠ»ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΡ ΠΎΠ±Π»Π°Π΄Π°ΡΡ Π½Π΅ ΡΠΎΠ»ΡΠΊΠΎ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΡΡ ΡΠ»ΡΡΡΠ°ΡΡ ΡΠ½Π΅ΡΠ³Π΅ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΎΠ±ΠΌΠ΅Π½ ΠΌΠΈΠΎΠΊΠ°ΡΠ΄Π°, Π½ΠΎΒ ΠΈ Π²ΡΡΠ°ΠΆΠ΅Π½Π½ΡΠΌΠΈ Π°Π½ΡΠΈΠΎΠΊΡΠΈΠ΄Π°Π½ΡΠ½ΡΠΌΠΈ ΡΠ²ΠΎΠΉΡΡΠ²Π°ΠΌΠΈ.ΠΠ΄Π½ΠΈΠΌ ΡΠ· ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π½ΠΈΡ
Π½Π°ΠΏΡΡΠΌΠΊΡΠ² ΡΠ΅ΡΠ°ΠΏΡΡ ΡΠ΅ΡΡΠ΅Π²ΠΎ-ΡΡΠ΄ΠΈΠ½Π½ΠΈΡ
Π·Π°Ρ
Π²ΠΎΡΡΠ²Π°Π½Ρ Ρ Π·Π°ΡΡΠΎΡΡΠ²Π°Π½Π½Ρ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΡΠ²Β ΠΌΠ΅ΡΠ°Π±ΠΎΠ»ΡΡΠ½ΠΎΡ Π΄ΡΡ. ΠΠ΅ΡΠ°Π±ΠΎΠ»ΡΡΠ½Ρ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠΈ Π²ΠΎΠ»ΠΎΠ΄ΡΡΡΡ Π½Π΅ Π»ΠΈΡΠ΅ Π·Π΄Π°ΡΠ½ΡΡΡΡ ΠΏΠΎΠΊΡΠ°ΡΡΠ²Π°ΡΠΈ Π΅Π½Π΅ΡΠ³Π΅ΡΠΈΡΠ½ΠΈΠΉ ΠΎΠ±ΠΌΡΠ½ ΠΌΡΠΎΠΊΠ°ΡΠ΄Π°, Π°Π»Π΅Β ΠΉ ΠΌΠ°ΡΡΡ Π²ΠΈΡΠ°ΠΆΠ΅Π½Ρ Π°Π½ΡΠΈΠΎΠΊΡΠΈΠ΄Π°Π½ΡΠ½Ρ Π²Π»Π°ΡΡΠΈΠ²ΠΎΡΡΡ