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RISS 인기검색어
- 검색키워드
- 저자 : Boscolo Annalisa (검색결과 5 건)
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Boscolo Annalisa,Spiezia Luca,Campello Elena,Bertini Diana,Lucchetta Vittorio,Piasentini Eleonora,De Cassai Alessandro,Simioni Paolo 대한마취통증의학회 2020 Korean Journal of Anesthesiology Vol.73 No.3
Background: Hypocoagulability and impaired platelet function have been associated with a high risk of death in sepsis. The aim of this cohort study was to determine whether sepsis-induced hypocoagulability and platelet dysfunction (assessed by ROTEM® and MULTIPLATE®, respectively) are increased in sepsis patients who died within 28 days after diagnosis compared with patients who died between 29 and 90 days after diagnosis. Methods: Consecutive patients admitted to the intensive care unit of Padova University Hospital from March 2015 to March 2018 for severe sepsis were considered. We collected blood samples from all patients to determine ROTEM® and MULTIPLATE® parameters. Each enrolled patient underwent a 90-day follow-up and the mortality rate was recorded. Results: Of 120 patients, 36 (30%) died within 28 days post-diagnosis (Group A), 23 (19%) died between days 29 and 90 post-diagnosis (Group B), and 61 (51%) were alive after 90 days (survivors). The clotting time in the ROTEM® test and clot formation time in the EXTEM test were significantly more prolonged in Group A than in B. Both groups showed a significantly higher hypocoagulability than survivors in the EXTEM test. MULTIPLATE® platelet function analysis showed that platelet function was significantly lower in Group A than in Group B. Conclusions: The present study showed that the combination of thromboelastometry and impedance aggregometry may help identifying sepsis patients at high risk of short-term death. Larger studies are warranted to corroborate our results.
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Alessandro De Cassai,Annalisa Boscolo,Tommaso Tonetti,Irina Ban,Carlo Ori 대한마취통증의학회 2019 Korean Journal of Anesthesiology Vol.72 No.1
Background: The American Society of Anesthesiologists physical status (ASA-PS) is a grading system adopted worldwide by anesthesiologists to classify the overall health status of patients. Its importance is demonstrated not only by its routine use in clinical practice, but also by its deployment in other healthcare-related environments. However, a weak/ moderate inter-rater reliability for ASA-PS has been previously shown, and although definitions and clinical examples of each class are provided by ASA, doubts remain on the individual factors influencing assignment to an ASA-PS class. The aim of this study was to investigate whether and how an anesthesiologist’s experience affects classification into a specific ASA-PS class. Methods: An online survey presenting eight fictitious patients was administered to a group of Italian anesthesiologists and residents. Respondents were asked to assign each of the eight patients to a specific ASA-PS class. Anesthesiologists were subdivided into five classes according to years of experience as an anesthesiologist. Results: Six hundred one surveys were correctly completed. The highest mean number of correct answers was obtained by residents (3.95 ± 1.13), with the number decreasing progressively with increasing work experience. The lowest value was recorded in the most experienced group (3.13 ± 1.25). Inter-rater reliability was weak/moderate in all experience level groups (k = 0.38). Conclusions: Low inter-reliability of the ASA-PS and the experience-dependence of the anesthesiologist in assigning classifications must be taken into account when evaluating a patient, particularly in settings where wide differences in experience are present.
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A brief introduction to Propensity Score for anesthesiologists
Alessandro De Cassai,Giulio Andreatta,Annalisa Boscolo,Marina Munari,Paolo Navalesi 대한마취통증의학회 2020 Korean Journal of Anesthesiology Vol.73 No.4
Intergroup comparability is of paramount importance in clinical research since it is impossible to draw conclusions on a treatment if populations with different characteristics are compared. While an adequate randomization process in randomized controlled trials (RCTs) ensures a balanced distribution of subjects between groups, the distribution in observational prospective and retrospective studies may be influenced by many confounders. Propensity score (PS) is a statistical technique that was developed more than 30 years ago with the purpose of estimating the probability to be assigned to a group. Once evaluated, the PS could be used to adjust and balance the groups using different methods such as matching, stratification, covariate adjustment, and weighting. The validity of PS is strictly related to the confounders used in the model, and confounders that are either not identified or not available will produce biases in the results. RCTs will therefore continue to provide the highest quality of evidence, but PS allows fine adjustments on otherwise unbalanced groups, which will increase the strength and quality of observational studies.
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De Cassai Alessandro,Tassone Martina,Geraldini Federico,Sergi Massimo,Sella Nicolò,Boscolo Annalisa,Munari Marina 대한마취통증의학회 2021 Korean Journal of Anesthesiology Vol.74 No.5
Background: Trial sequential analysis (TSA) is a recent cumulative meta-analysis method used to weigh type I and II errors and to estimate when the effect is large enough to be unaffected by further studies. The aim of this study was to illustrate possible TSA scenarios and their significance using meta-analyses published in the Korean Journal of Anesthesiology (KJA) as working material. Methods: We performed a systematic medical literature search for meta-analyses published in the KJA. TSA was performed on each main outcome, estimating the required sample size on the calculated effect size for the intervention, considering a type I error of 5% and a power of 90% or 99%. Results: Six meta-analyses with a total of ten main outcomes were included in the analysis. Seven TSAs confirmed the results of the meta-analyses. However, only three of them reached the required sample size. In the two TSAs, the cumulative z-lines were not statistically significant. One TSA boundary for effect was reached with the 90% analysis, but not with the 99% analysis. Conclusions: In TSA, a meta-analysis pooled effect may be established to assess if the cumulative sample size is large enough. TSA can be used to add strength to the conclusions of meta-analyses; however, pre-registration of the TSA protocol is of paramount importance. This study could be useful to better understand the use of TSA as an additional statistical tool to improve meta-analysis quality.
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