BackgroundIt is unclear if anaesthesia maintenance with propofol is advantageous or beneficial over inhalational agents. This study is intended to compare the effects of propofol vs. inhalational agents in maintaining general anaesthesia on patient-relevant outcomes and patient satisfaction.MethodsStudies were identified by electronic database searches in PubMed™, EMBASE™ and the Cochrane™ library between 01/01/1985 and 01/08/2016. Randomized controlled trials (RCTs) of peer-reviewed journals were studied. Of 6688 studies identified, 229 RCTs were included with a total of 20,991 patients. Quality control, assessment of risk of bias, meta-bias, meta-regression and certainty in evidence were performed according to Cochrane. Common estimates were derived from fixed or random-effects models depending on the presence of heterogeneity. Post-operative nausea and vomiting (PONV) was the primary outcome. Post-operative pain, emergence agitation, time to recovery, hospital length of stay, post-anaesthetic shivering and haemodynamic instability were considered key secondary outcomes.ResultsThe risk for PONV was lower with propofol than with inhalational agents (relative risk (RR) 0.61 [0.53, 0.69], p < 0.00001). Additionally, pain score after extubation and time in the post-operative anaesthesia care unit (PACU) were reduced with propofol (mean difference (MD) − 0.51 [− 0.81, − 0.20], p = 0.001; MD − 2.91 min [− 5.47, − 0.35], p = 0.03). In turn, time to respiratory recovery and tracheal extubation were longer with propofol than with inhalational agents (MD 0.82 min [0.20, 1.45], p = 0.01; MD 0.70 min [0.03, 1.38], p = 0.04, respectively). Notably, patient satisfaction, as reported by the number of satisfied patients and scores, was higher with propofol (RR 1.06 [1.01, 1.10], p = 0.02; MD 0.13 [0.00, 0.26], p = 0.05). Secondary analyses supported the primary results.ConclusionsBased on the present meta-analysis there are several advantages of anaesthesia maintenance with propofol over inhalational agents. While these benefits result in an increased patient satisfaction, the clinical and economic relevance of these findings still need to be addressed in adequately powered prospective clinical trials.Electronic supplementary materialThe online version of this article (10.1186/s12871-018-0632-3) contains supplementary material, which is available to authorized users.
We developed a general model for estimating and comparing disease-and treatment-specific lost paid/unpaid production (due to premature death and reduced ability) and informal care received (due to reduced ability) in Italy, starting from survival, demographic and Health-Related Quality of Life (HRQoL) data. Assuming the disease is not selecting a systematically different population in terms of mean wage than the general public, age-and gender-specific yearly production values are estimated combining data from the last Italian Time-Use-Survey on time dedicated to paid and unpaid (household, caring and volunteering) activities, with a) the last Italian Wage-Structure-Survey, for paid activities (Human Capital approach), and b) market prices for an equivalent service, for unpaid production (Proxy Good approach). To avoid double counting, age-and gender-specific maximum care needs are approximated with time dedicated to eating and personal care, reported in TUS. Present monetary values of future productivity and informal care are estimated applying a 3.5% annual discount rate. Lost life years due to a particular condition/treatment are estimated by comparison of its survival curve with the corresponding age-and gender-normalized survival curve of the general Italian population. The degrees of reduced productivity and need for informal care for remaining life years are estimated by comparison of condition-/treatment-specific reported HRQoL data with demographically matched Italian norms. Our results will be useful for cost-effectiveness and budget impact analyses conducted from the perspective of the Italian society and we encourage the inclusion of these costs in economic evaluations to allow decision makers to be fully informed about the costs and consequences of their decisions on healthcare interventions.
Background Emerging and re-emerging infectious diseases such as Zika, SARS, ncovid19 and Pertussis, pose a compelling challenge for epidemiologists due to their significant impact on global public health. In this context, computational models and computer simulations are one of the available research tools that epidemiologists can exploit to better understand the spreading characteristics of these diseases and to decide on vaccination policies, human interaction controls, and other social measures to counter, mitigate or simply delay the spread of the infectious diseases. Nevertheless, the construction of mathematical models for these diseases and their solutions remain a challenging tasks due to the fact that little effort has been devoted to the definition of a general framework easily accessible even by researchers without advanced modelling and mathematical skills. Results In this paper we describe a new general modeling framework to study epidemiological systems, whose novelties and strengths are: (1) the use of a graphical formalism to simplify the model creation phase; (2) the implementation of an R package providing a friendly interface to access the analysis techniques implemented in the framework; (3) a high level of portability and reproducibility granted by the containerization of all analysis techniques implemented in the framework; (4) a well-defined schema and related infrastructure to allow users to easily integrate their own analysis workflow in the framework. Then, the effectiveness of this framework is showed through a case of study in which we investigate the pertussis epidemiology in Italy. Conclusions We propose a new general modeling framework for the analysis of epidemiological systems, which exploits Petri Net graphical formalism, R environment, and Docker containerization to derive a tool easily accessible by any researcher even without advanced mathematical and computational skills. Moreover, the framework was implemented following the guidelines defined by Reproducible Bioinformatics Project so it guarantees reproducible analysis and makes simple the developed of new user-defined workflows.
We developed a general model for estimating and comparing disease-and treatment-specific lost paid/unpaid production (due to premature death and reduced ability) and informal care received (due to reduced ability) in Italy, starting from survival, demographic and Health-Related Quality of Life (HRQoL) data. Assuming the disease is not selecting a systematically different population in terms of mean wage than the general public, age-and gender-specific yearly production values are estimated combining data from the last Italian Time-Use-Survey on time dedicated to paid and unpaid (household, caring and volunteering) activities, with a) the last Italian Wage-Structure-Survey, for paid activities (Human Capital approach), and b) market prices for an equivalent service, for unpaid production (Proxy Good approach). To avoid double counting, age-and gender-specific maximum care needs are approximated with time dedicated to eating and personal care, reported in TUS. Present monetary values of future productivity and informal care are estimated applying a 3.5% annual discount rate. Lost life years due to a particular condition/treatment are estimated by comparison of its survival curve with the corresponding age-and gender-normalized survival curve of the general Italian population. The degrees of reduced productivity and need for informal care for remaining life years are estimated by comparison of condition-/treatment-specific reported HRQoL data with demographically matched Italian norms. Our results will be useful for cost-effectiveness and budget impact analyses conducted from the perspective of the Italian society and we encourage the inclusion of these costs in economic evaluations to allow decision makers to be fully informed about the costs and consequences of their decisions on healthcare interventions.
Cutaneous squamous cell carcinoma (CSCC) is a common cancer that in most cases is curable with surgery. About 3-5% of patients develop advanced CSCC (aCSCC) and are no longer responsive to surgery or radiation therapy. The aim of this study was to assess the cost-effectiveness and cost-utility of cemiplimab, the first systemic therapy approved in Italy for patients with aCSCC, vs platinum-based chemotherapy from the Italian National Health Service (SSN) perspective. Methods: A partitioned survival model, which included three mutually exclusive health states, was developed to estimate costs and outcomes for patients with aCSCC, over a 30year time horizon (lifetime). No direct evidence of the comparative efficacy and safety of cemiplimab versus other therapies currently exists. Therefore, a simulated treatment comparison (STC) was conducted to estimate the comparative efficacy of cemiplimab versus chemotherapy. Individual patient data for cemiplimab were collected from the EMPOWER-CSCC 1 trial whereas chemotherapy data were derived from a retrospective study. In the STC a regression model was used to predict outcomes for cemiplimab in the population observed in the comparator study. Costs of drug acquisition/administration and management of adverse events were included. Costs and outcomes were discounted at 3% per year. Incremental costeffectiveness ratio (ICER) and incremental cost-utility ratio (ICUR) were calculated; sensitivity and scenario analyses were performed to assess the robustness of results. Results: In the base-case, treatment with cemiplimab was associated with a gain of 4.89 LYs and 3.99 QALYs, compared with a platinum-based chemotherapy regimen, resulting in an estimated ICER of 27,821 €/LY gained and an ICUR of 34,110 €/QALY gained. Both ICER and ICUR were below the commonly used Italian SSN willingness to pay thresholds. Conclusion: The use of cemiplimab, compared with a platinum-based chemotherapy regimen, can be considered a cost-effective option for the treatment of aCSCC patients in Italy.
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