Kuang Fu Cheng

Applying Cerebral Hypothermia and Brain Oxygen Monitoring in Treating Severe Traumatic Brain Injury

BACKGROUND Severe traumatic brain injury (TBI) was to be one of the major health problems encountered in modern medicine and had an incalculable socioeconomic impact. The initial cerebral damage after acute brain injury is often exacerbated by postischemic hyperthermia and worsens the outcome. Hypothermia is one of the current therapies designed to combat this deleterious effect. The brain tissue oxygen (P(ti)o(2))-guided cerebral perfusion pressure (CPP) management was successfully reduced because of cerebral hypoxic episodes following TBI. MATERIALS AND METHODS Forty-five patients with severe TBI whose Glasgow Coma Scale (GCS) score ranged between 4 and 8 during September 2006 and August 2007 were enrolled in China Medical University Hospital, Taichung, Taiwan. One patient with a GCS score of 3 was excluded for poor outcome. These patients were randomized into three groups. Group A (16 patients) was intracranial pressure/cerebral perfusion pressure (ICP/CPP)-guided management only, Group B (15 patients) was ICP/CPP guided with mild hypothermia, and Group C (14 patients) was combined mild hypothermia and P(ti)o(2) guided with CPP management on patients with severe TBI. All patients were treated with ICP/CPP management (ICP <20 mm Hg, CPP >60 mm Hg). However, the group with P(ti)o(2) monitoring was required to raise the P(ti)o(2) above 20 mm Hg. Length of intensive care unit stay, ICP, P(ti)o(2), Glasgow Outcome Scale (GOS) score, mortality, and complications were analyzed. RESULTS The ICP values progressively increased in the first 3 days but showed smaller changes in hypothermia groups (Groups B and C) and were significantly lower than those of the normothermia group (Group A) at the same time point. We also found out that the averaged ICP were significantly related to days and the daily variations [measured as (daily observation - daily group mean)(2)] of ICP were shown to the significantly different among three treatment groups after the third posttraumatic day. The values of P(ti)o(2) in Group C tended to rise when the ICP decreased were also observed. A favorable outcome is divided by the result of GOS scores. The percentage of favorable neurologic outcome was 50% in the normothermia group, 60% in the hypothermia-only group, and 71.4% in the P(ti)o(2) group, with statistical significance. The percentage of mortality was 12.5% in the normothermia group, 6.7% in the hypothermia-only group, and 8.5% in the P(ti)o(2) group, without statistical significance in three groups. Complications included pulmonary infections, peptic ulcer, and leukocytopenia (43.8% in the normothermia group, 55.6% in the hypothermia-only group, and 50% in the P(ti)o(2) group). CONCLUSIONS Therapeutic mild hypothermia combined with P(ti)o(2)-guided CPP/ICP management allows reducing elevated ICP before 24 hours after injury, and daily variations of ICP were shown to be significantly different among the three treatment groups after the third posttraumatic day. It means that the hypothermia groups may reduce the ICP earlier and inhibit the elicitation of acute inflammation after cerebral contusion. Our data also provided evidence that early treatment that lowers P(ti)o(2) may improve the outcome and seems the best medical treatment method in these three groups. We concluded that therapeutic mild hypothermia combined with P(ti)o(2)-guided CPP/ICP management provides beneficial effects when treating TBI, and a multicenter randomized trial needs to be undertaken.

Gout and subsequent increased risk of cardiovascular mortality in non-diabetics aged 50 and above: a population-based cohort study in Taiwan

BackgroundLimited data are available on the risk ratios for fatal cardiovascular disease (CVD) outcome from gout and chronic kidney disease (CKD) in non-diabetic individuals.MethodsNationwide population-based retrospective prospective study with a 5-year follow-up to investigate the association between physician-diagnosed gout and CKD in non-diabetics aged 50 and above who had no pre-existing serious CVD and the subsequent risk of death from CVD. Hazard ratios (HR) of CVD mortality were adjusted for gender, age, smoking- and alcoholism-related diagnoses, hypertension, hyperlipidemia, atrial fibrillation and Charlson’s comorbidity index score.ResultsA case cohort (n=164,463) having gout and a control cohort (n= 3,694,377) having no gout were formed. The prevalence of gout in this study was 4.26% whereas that of gout plus CKD was 8.17%. Male to female ratio among the individuals with gout was 3.2:1. The relative risk (RR) of subsequent cardiovascular mortality between the case and control cohort was 1.71 (95% confidence interval (CI), 1.66-1.75). The presence of CKD in nondiabetic subjects with no gout (control group) has a RR of CVD mortality at 3.05 (95% CI, 2.94-3.15). The presence of gout has protective effect on subjects with CKD with a RR of 1.84 (95% CI, 1.71-1.98). As compared with individuals with no gout, the adjusted HR (aHR) for CVD mortality among the individuals with gout was 1.10 (95% CI 1.07-1.13). In a Cox model, when compared with subjects having neither gout nor CKD, the aHR in subjects with no gout but with CKD is 1.76 (95% CI, 1.70-1.82); in subjects with gout but without CKD, 1.10 (1.07-1.13); interestingly, the aHR is attenuated in subjects with concomitant gout plus CKD which is 1.38 (1.29-1.48).ConclusionsAmong non-diabetic individuals aged 50 years or above who had no preceding serious CVD, those with gout were 1.1 times more likely to die from CVD as were individuals without gout. The presence of gout appears to attenuate the risk of subsequent CV mortality in subjects with CKD. Further studies should focus on finding an explanation for the protective effect of gout on CV mortality in patients with CKD.

Increasing Prevalence of Erosive Esophagitis Among Taiwanese Aged 40 Years and Above: A Comparison Between Two Time Periods

Background Earlier prevalence studies have reported an increasing trend of gastroesophageal reflux disease in Asia, and obesity may be the promoting factor. Goals This study compared the prevalence of erosive esophagitis and obesity status among the same source of subjects in Taiwan between 1995 and 2002. Study In the same routine health checkup unit, we recruited 1902 apparently healthy adults in 2002 matched by sex and age with 2044 individuals recruited in 1995. The prevalence of esophagitis and body mass index between these 2 groups were compared. Results The crude prevalence of esophagitis increased from 5% in 1995 to 12.6% in 2002 (P<0.0001). Comparing by age stratum, there was an increase of esophagitis among subjects aged 40 years and above, with a dose-response relationship of adjusted prevalence ratios 2.65 [95% confidence interval (CI): 1.10, 4.20] in those aged 40 to 49 years, 3.15 (95% CI: 1.51, 4.79) in those aged 50 to 59 years, and 4.33 (95% CI: 2.56, 6.11) in those aged 60 years and above. The prevalence of esophagitis increased in both sexes. BMI was positively associated with the presence of esophagitis in women, but the proportion of overweight or obesity did not increase in women aged 40 years and above over time. Conclusions There was a 2.5-fold of increase in prevalence of erosive esophagitis among Taiwanese adults from 1995 to 2002, particularly in those aged 40 years and above. Factors other than obesity seem to contribute to the increasing trend of erosive esophagitis in Taiwanese women.

Assessment of performance of survival prediction models for cancer prognosis

BackgroundCancer survival studies are commonly analyzed using survival-time prediction models for cancer prognosis. A number of different performance metrics are used to ascertain the concordance between the predicted risk score of each patient and the actual survival time, but these metrics can sometimes conflict. Alternatively, patients are sometimes divided into two classes according to a survival-time threshold, and binary classifiers are applied to predict each patient’s class. Although this approach has several drawbacks, it does provide natural performance metrics such as positive and negative predictive values to enable unambiguous assessments.MethodsWe compare the survival-time prediction and survival-time threshold approaches to analyzing cancer survival studies. We review and compare common performance metrics for the two approaches. We present new randomization tests and cross-validation methods to enable unambiguous statistical inferences for several performance metrics used with the survival-time prediction approach. We consider five survival prediction models consisting of one clinical model, two gene expression models, and two models from combinations of clinical and gene expression models.ResultsA public breast cancer dataset was used to compare several performance metrics using five prediction models. 1) For some prediction models, the hazard ratio from fitting a Cox proportional hazards model was significant, but the two-group comparison was insignificant, and vice versa. 2) The randomization test and cross-validation were generally consistent with the p-values obtained from the standard performance metrics. 3) Binary classifiers highly depended on how the risk groups were defined; a slight change of the survival threshold for assignment of classes led to very different prediction results.Conclusions1) Different performance metrics for evaluation of a survival prediction model may give different conclusions in its discriminatory ability. 2) Evaluation using a high-risk versus low-risk group comparison depends on the selected risk-score threshold; a plot of p-values from all possible thresholds can show the sensitivity of the threshold selection. 3) A randomization test of the significance of Somers’ rank correlation can be used for further evaluation of performance of a prediction model. 4) The cross-validated power of survival prediction models decreases as the training and test sets become less balanced.

Asymptomatic ratio for seasonal H1N1 influenza infection among schoolchildren in Taiwan

BackgroundStudies indicate that asymptomatic infections do indeed occur frequently for both seasonal and pandemic influenza, accounting for about one-third of influenza infections. Studies carried out during the 2009 pH1N1 pandemic have found significant antibody response against seasonal H1N1 and H3N2 vaccine strains in schoolchildren receiving only pandemic H1N1 monovalent vaccine, yet reported either no symptoms or only mild symptoms.MethodsSerum samples of 255 schoolchildren, who had not received vaccination and had pre-season HI Ab serotiters <40, were collected from urban, rural areas and an isolated island in Taiwan during the 2005–2006 influenza season. Their hemagglutination inhibition antibody (HI Ab) serotiters against the 2005 A/New Caledonia/20/99 (H1N1) vaccine strain at pre-season and post-season were measured to determine the symptoms with the highest correlation with infection, as defined by 4-fold rise in HI titer. We estimate the asymptomatic ratio, or the proportion of asymptomatic infections, for schoolchildren during the 2005–6 influenza season when this vaccine strain was found to be antigenically related to the circulating H1N1 strain.ResultsFever has the highest correlation with the 2005–06 seasonal influenza A(H1N1) infection, followed by headache, cough, vomiting, and sore throat. Asymptomatic ratio for the schoolchildren is found to range between 55.6% (95% CI: 44.7-66.4)-77.9% (68.8-87.0) using different sets of predictive symptoms. Moreover, the asymptomatic ratio was 66.9% (56.6-77.2) when using US-CDC criterion of fever + (cough/sore throat), and 73.0 (63.3-82.8) when under Taiwan CDC definition of Fever + (cough or sore throat or nose) + ( headache or pain or fatigue).ConclusionsAsymptomatic ratio for children is found to be substantially higher than that of the general population in literature. In providing reasonable quantification of the asymptomatic infected children spreading pathogens to others in a seasonal epidemic or a pandemic, our estimates of symptomatic ratio of infected children has important clinical and public health implications.

Serological Evidence of Subclinical Transmission of the 2009 Pandemic H1N1 Influenza Virus Outside of Mexico

Background Relying on surveillance of clinical cases limits the ability to understand the full impact and severity of an epidemic, especially when subclinical cases are more likely to be present in the early stages. Little is known of the infection and transmissibility of the 2009 H1N1 pandemic influenza (pH1N1) virus outside of Mexico prior to clinical cases being reported, and of the knowledge pertaining to immunity and incidence of infection during April–June, which is essential for understanding the nature of viral transmissibility as well as for planning surveillance and intervention of future pandemics. Methodology/Principal Findings Starting in the fall of 2008, 306 persons from households with schoolchildren in central Taiwan were followed sequentially and serum samples were taken in three sampling periods for haemagglutination inhibition (HI) assay. Age-specific incidence rates were calculated based on seroconversion of antibodies to the pH1N1 virus with an HI titre of 1∶40 or more during two periods: April–June and September–October in 2009. The earliest time period with HI titer greater than 40, as well as a four-fold increase of the neutralization titer, was during April 26–May 3. The incidence rates during the pre-epidemic phase (April–June) and the first wave (July–October) of the pandemic were 14.1% and 29.7%, respectively. The transmissibility of the pH1N1 virus during the early phase of the epidemic, as measured by the effective reproductive number R0, was 1.16 (95% confidence interval (CI): 0.98–1.34). Conclusions Approximately one in every ten persons was infected with the 2009 pH1N1 virus during the pre-epidemic phase in April–June. The lack of age-pattern in seropositivity is unexpected, perhaps highlighting the importance of children as asymptomatic transmitters of influenza in households. Although without virological confirmation, our data raise the question of whether there was substantial pH1N1 transmission in Taiwan before June, when clinical cases were first detected by the surveillance network.

Predicting bankruptcy using the discrete-time semiparametric hazard model

The usual bankruptcy prediction models are based on single-period data from firms. These models ignore the fact that the characteristics of firms change through time, and thus they may suffer from a loss of predictive power. In recent years, a discrete-time parametric hazard model has been proposed for bankruptcy prediction using panel data from firms. This model has been demonstrated by many examples to be more powerful than the traditional models. In this paper, we propose an extension of this approach allowing for a more flexible choice of hazard function. The new method does not require the assumption of a parametric model for the hazard function. In addition, it also provides a tool for checking the adequacy of the parametric model, if necessary. We use real panel datasets to illustrate the proposed method. The empirical results confirm that the new model compares favorably with the well-known discrete-time parametric hazard model.

Regression analysis for massive datasets

In the past decades, we have witnessed a revolution in information technology. Routine collection of systematically generated data is now commonplace. Databases with hundreds of fields (variables), and billions of records (observations) are not unusual. This presents a difficulty for classical data analysis methods, mainly due to the limitation of computer memory and computational costs (in time, for example). In this paper, we propose an intelligent regression analysis methodology which is suitable for modeling massive datasets. The basic idea here is to split the entire dataset into several blocks, applying the classical regression techniques for data in each block, and finally combining these regression results via weighted averages. Theoretical justification of the goodness of the proposed method is given, and empirical performance based on extensive simulation study is discussed.

Analysis of Case‐Only Studies Accounting for Genotyping Error

The case‐only design provides one approach to assess possible interactions between genetic and environmental factors. It has been shown that if these factors are conditionally independent, then a case‐only analysis is not only valid but also very efficient. However, a drawback of the case‐only approach is that its conclusions may be biased by genotyping errors. In this paper, our main aim is to propose a method for analysis of case‐only studies when these errors occur. We show that the bias can be adjusted through the use of internal validation data, which are obtained by genotyping some sampled individuals twice. Our analysis is based on a simple and yet highly efficient conditional likelihood approach. Simulation studies considered in this paper confirm that the new method has acceptable performance under genotyping errors.

Classical reflux symptoms, hiatus hernia and overweight independently predict pharyngeal acid exposure in patients with suspected reflux laryngitis

Aliment Pharmacol Ther 2011; 33: 89–98