Background and objectiveMarkov micro-simulation models are being increasingly used in health economic evaluations. An important feature of the Markov micro-simulation model is its ability to consider transition probabilities of heterogeneous subgroups with different risk profiles. A survival analysis is generally performed to accurately estimate the transition probabilities associated with the risk profiles. This study aimed to apply a flexible parametric survival model (FPSM) to estimate individual transition probabilities.Materials and methodsThe data were obtained from a cohort study investigating ischemic stroke outcomes in Western China. In total, 585 subjects were included in the analysis. To explore the goodness of fit of the FPSM, we compared the estimated hazard ratios and baseline cumulative hazards, both of which are necessary to the calculate individual transition probabilities, and the Markov micro-simulation models constructed using the FPSM and Cox model to determine the validity of the two Markov micro-simulation models and cost-effectiveness results.ResultsThe flexible parametric proportional hazards model produced hazard ratio and baseline cumulative hazard estimates that were similar to those obtained using the Cox proportional hazards model. The simulated cumulative incidence of recurrent ischemic stroke and 5-years cost-effectiveness of Incremental cost-effectiveness Ratios (ICERs) were also similar using the two approaches. A discrepancy in the results was evident between the 5-years cost-effectiveness and the 10-years cost-effectiveness of ICERs, which were approximately 0.9 million (China Yuan) and 0.5 million (China Yuan), respectively.ConclusionsThe flexible parametric survival model represents a good approach for estimating individual transition probabilities for a Markov micro-simulation model.
Objective: To compare the difference between severe and non-severe COVID-19 pneumonia and figure out the potential symptoms lead to severity. Methods:Articles from PubMed, Embase, Cochrane database, and google up-to 24 February 2020 were systematically reviewed. Eighteen Literatures were identified with cases of COVID-19 pneumonia. The extracted data includes clinical symptoms, age, gender, sample size and region et al were systematic reviewed and meta analyzed.Results: 14 eligible studies including 1,424 patients were analyzed. Symptoms like fever (89.2%), cough (67.2%), fatigue (43.6%) were common, dizziness, hemoptysis, abdominal pain and conjunctival congestion/conjunctivitis were rare. Polypnea/dyspnea in severe patients were significantly higher than non-severe (42.7% vs.16.3%, P<0.0001). Fever and diarrhea were higher in severe patients(p=0.0374and0.0267).Further meta-analysis showed incidence of fever(OR1.70,95%CI 1.01-2.87), polypnea/dyspnea(OR3.53, 95%CI 1.95-6.38) and diarrhea(OR1.80,95%CI 1.06-3.03) was higher in severe patients, which meant the severe risk of patients with fever, polypnea/dyspnea, diarrhea were 1.70, 3.53, 1.80 times higher than those with no corresponding symptoms.Conclusions: Fever, cough and fatigue are common symptoms in COVID-19 pneumonia. Compared with non-severe patients, the symptoms as fever, polypnea/dyspnea and diarrhea are potential symptoms lead to severity.
Smoking has a negative effect on most diseases, yet it is under-investigated in people with epilepsy; thus its role is not clear in the general population with epilepsy. We performed a retrospective pilot study on males with epilepsy to determine the smoking rate and its relationship with seizure control using univariate analysis to calculate odds ratios (ORs) and also used a multi-variate logistic regression model. The smoking rate in our sample of 278 individuals was 25.5%, which is lower than the general Chinese population smoking rate among males of 52.1%. We used two classifications: the first classified epilepsy as generalized, or by presumed topographic origin (temporal, frontal, parietal and occipital). The second classified the dominant seizure type of an individual as generalized tonic clonic seizure (GTCS), myoclonic seizure (MS), complex partial seizure (CPS), simple partial seizure (SPS), and secondary GTCS (sGTCS). The univariable analysis of satisfactory seizure control profile and smoking rate in both classifications showed a trend towards a beneficial effect of smoking although most were not statistically significant. Considering medication is an important confounding factor that would largely influence seizure control, we also conducted multi-variable analysis for both classifications with drug numbers and dosage. The result of our model also suggested that smoking is a protective factor. Our findings seem to suggest that smoking could have a potential role in seizure control although confounders need exploration particularly in view of the potential long term health effects. Replication in a much larger sample is needed as well as case control studies to elucidate this issue.
Background and Purpose: Although obesity is an established risk factor for the occurrence of a primary stroke, the association between obesity with post-stroke mortality remains unclear. We evaluated the association of dynamic obesity status with mortality among first-ever stroke survivors in China. Methods: Data from 775 patients with first-ever ischaemic stroke from a longitudinal study, 754 patients were categorized 4 categories of BMI (underweight, normal weight, overweight and obese) and 2 categories of WC (normal WC and abdominal obesity) according to Chinese-specific criteria. Mortality information and obesity status were obtained through every 3 months via telephone follow-up, beginning in 2010 and continuing through 2016. Chi-square tests were used to compare different obesity status at admission and personal characteristics. Time-dependent Cox proportional hazards models were used to estimate the unadjusted and adjusted hazard ratios (HRs) for relationship between all-cause mortality and dynamic obesity status. Results: Of 754 analyzed patients, 60.87% were males, with a mean age of 61.45 years. After adjusting for possible confounders, there were significant inverse associations between BMI and WC with all-cause mortality: compared with normal BMI or WC counterparts, overweight and abdominal obesity patients significantly decrease risk of all-cause mortality (HR and 95% confidence interval (CI):0.521(0.303,0.897),0.545(0.352,0.845),respectively), whereas under-weight patients have the highest risk and obese have decreased risk of mortality, though significance was not obtained (1.241(0.691,2.226),0.486(0.192,1.231), respectively). Conclusions: Overweight and abdominal obesity was paradoxically associated with reduced risk of mortality among first-ever ischaemic stroke survivors in China. Body weight management recommendations ought to not be based on mere projection from primary prevention of stroke.
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