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SyfteAtt undersöka hur stor bedövningseffekt som kan uppnås efter injektion med aktiv (lidokain) eller in-aktiv substans (koksaltlösning) samt att undersöka om deltagarna korrekt kan identifiera vilken injektion de fått, när de vet att det är en 50/50 chans att de har fått lidokain eller koksalt.Material och metod20 friska frivilliga deltagare randomiserades in i två grupper. En grupp fick injektion med aktiv substans och en med in-aktiv substans. Deltagarna informerades om att chansen att få aktiv eller in-aktiv substans var lika, 50 %. Deltagarna utsattes för ett specifikt smärtsamt stimulus före och efter injektionen. De graderade sedan sin smärtintensitet på en 0-10 NRS-skala. Följande dag tillfrågades deltagarna vilken substans de trodde de hade fått.Students T-test användes för att beräkna skillnaden i smärtintensitet före och efter injektion i båda grupperna. Fischer’s exakta test användes för att beräkna kvalitativa data. P <0,05 ansågs vara statistiskt signifikant.ResultatDet var en statistiskt signifikant skillnad mellan den aktiva (NRS 2,9) och den in-aktiva (NRS 0,0) gruppen gällande förändringen i smärtintensitet före injektion och efter injektion. Alla deltagare kunde korrekt identifiera vilken injektion de fått.SlutsatsIngen bedövningseffekt kunde mätas efter injektion med inaktiv substans hos friska individer när deltagarna visste att det var en 50/50 möjlighet att de skulle få den aktiva substansen. Alla individer kunde korrekt avgöra om de fått injektion med aktivt bedövningsmedel eller in-aktivt koksalt. / AimTo investigate the amount of anesthetic effect that can be achieved following injection with active (lidocaine) or non-active (saline) agent and to examine if the participants correctly can identify which injection they received when there is a 50/50 chance that they have received lidocaine or saline.Materials and Method20 healthy volunteers were randomized in two groups. One group got injection with active agent and one with non-active agent. The participants were instructed that chances of receiving active versus non-active agent were equal, 50 %. The participants were exposed to a specific painful stimulus before and after the injection and they had to rate their pain score on an 0-10 NRS-scale. The following day, the participants were asked what agent they thought they had received.Students T-test was used to calculate the difference in pain intensity between pre- and post-injection in both groups. Fisher's exact test was used to calculate qualitative variables. P<0.05 was considered statistically significant.ResultsThere was a statistically significant difference between the active (NRS 2.9) and the non-active (NRS 0.0) group regarding the change in pain intensity rating from pre-injection to post-injection. All participants could correctly identify which injection they received.ConclusionNo anesthetic effect could be measured after injection with non-active substance in healthy individuals when there was a 50/50 level of uncertainty that the individual would receive the active agent. All individuals could correctly determine whether they received active anesthesia or non-active saline.

Introduction Postoperative medical complications are often preceded by a period with hypotension. Postoperative hypotension is poorly described in the literature. Data are needed to determine the incidence and risk factors for the development of postoperative clinically important hypotension after noncardiac surgery. Methods The incidence of postoperative clinically important hypotension was examined in a cohort of 40,004 patients enrolled in the VISION (Vascular Events in Noncardiac Surgery Patients Cohort Evaluation) Study. Eligible patients were ≥45 years of age, underwent an in-patient noncardiac surgery procedure, and required a general or regional anesthetic. I undertook a multivariable logistic regression model to determine the predictors for postoperative clinically important hypotension. Model validation was performed using calibration and discrimination. Results Of the 40,004 patients included, 20,442 patients were selected for the derivation cohort, and 19,562 patients were selected for the validation cohort. The incidence of clinically important hypotension in the entire cohort was 12.4% (4,959 patients) [95% confidence interval 12.1-12.8]. Using 41 variables related to baseline characteristics, preoperative hemodynamics, laboratory characteristics, and type of surgery, I developed a model to predict the risk of clinically important postoperative hypotension (bias-corrected C-statistics: 0.73) The prediction model was slightly improved by adding intraoperative variables (bias-corrected C-statistics: 0.75). A simplified prediction model using the following variables: high-risk surgery, preoperative systolic blood pressure <130 mm Hg, preoperative heart rate >100 beats per minute, and open surgery, also predicted clinically important hypotension, albeit with less accuracy (bias-corrected C-statistics 0.68). Conclusion Our clinical prediction model can accurately predict patients’ risk of postoperative clinically important hypotension after noncardiac surgery. This model can help identify which patients should have enhanced monitoring after surgery and patients to include in clinical trials evaluating interventions to prevent postoperative clinically important hypotension. / Thesis / Master of Science (MSc) / In patients undergoing noncardiac surgery, numerous patients will develop postoperative clinically important hypotension. This may lead to complications including death, stroke, and myocardial infarction. I performed a large observational study to examine which risk factors would predict clinically important postoperative hypotension. Once we have identified these risk factors, we will use them to conduct randomized trials in patients at risk of clinically important hypotension to determine if we can prevent major postoperative complications.

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