
AbstractBackground: There are few quantitative assessments of how anaesthesia management affects perioperativemorbidity and mortality. The authors conducted a study to determine risk variables for anaesthetic care aboutsevere morbidity and mortality within 24 hours of surgery.Methods: In a case-control study conducted in 2021–2022, anaesthetized patients were evaluated. Within 24hours of being put under anaesthesia, some patients in the cases passed away or went into a coma; in contrast, thecontrols did not experience any of these outcomes. The Anaesthesia and Recovery Form was used to gather data,and confounder-corrected odds ratios were the result.Results: The cohort comprised 869,483 patients; 705 cases and 711 controls were studied. The frequency of 24-hour postoperative death was 8.8 per 10,000 anaesthetics, while the rate of unconsciousness was 0.5. Somesignificant anaesthetic management factors associated with decreased risk were using a checklist and protocol tocheck equipment (odds ratio: 0.64), recording equipment checks (odds ratio: 0.61), having a directanaesthesiologist available (odds ratio: 0.46), having the same anaesthesiologist present during anaesthesia (oddsratio: 0.44); having a full-time working anaesthetic nurse (odds ratio: 0.41); having two people present atemergence (odds ratio: 0.69); and reversing anaesthesia (odds Postoperative pain medicine also carried a lowerrisk profile, mainly when administered intramuscularly or epidurally as opposed to intravenously.Conclusions: Preoperative unconsciousness and death are associated, making postoperative mortality a severeproblem. Anaesthetic management factors that impact this association include using medications during and aftertherapy, the type of anaesthetic care given during and after surgery, and the presence of anaesthesiologiststhroughout the procedure
AbstractBackground: There are few quantitative assessments of how anaesthesia management affects perioperativemorbidity and mortality. The authors conducted a study to determine risk variables for anaesthetic care aboutsevere morbidity and mortality within 24 hours of surgery.Methods: In a case-control study conducted in 2021–2022, anaesthetized patients were evaluated. Within 24hours of being put under anaesthesia, some patients in the cases passed away or went into a coma; in contrast, thecontrols did not experience any of these outcomes. The Anaesthesia and Recovery Form was used to gather data,and confounder-corrected odds ratios were the result.Results: The cohort comprised 869,483 patients; 705 cases and 711 controls were studied. The frequency of 24-hour postoperative death was 8.8 per 10,000 anaesthetics, while the rate of unconsciousness was 0.5. Somesignificant anaesthetic management factors associated with decreased risk were using a checklist and protocol tocheck equipment (odds ratio: 0.64), recording equipment checks (odds ratio: 0.61), having a directanaesthesiologist available (odds ratio: 0.46), having the same anaesthesiologist present during anaesthesia (oddsratio: 0.44); having a full-time working anaesthetic nurse (odds ratio: 0.41); having two people present atemergence (odds ratio: 0.69); and reversing anaesthesia (odds Postoperative pain medicine also carried a lowerrisk profile, mainly when administered intramuscularly or epidurally as opposed to intravenously.Conclusions: Preoperative unconsciousness and death are associated, making postoperative mortality a severeproblem. Anaesthetic management factors that impact this association include using medications during and aftertherapy, the type of anaesthetic care given during and after surgery, and the presence of anaesthesiologiststhroughout the procedure
Medical Error, Human Factors, Patient Safety, Critical Events.
Medical Error, Human Factors, Patient Safety, Critical Events.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
