Noor Azina Ismail

Statistical Methods Used to Test for Agreement of Medical Instruments Measuring Continuous Variables in Method Comparison Studies: A Systematic Review

Background Accurate values are a must in medicine. An important parameter in determining the quality of a medical instrument is agreement with a gold standard. Various statistical methods have been used to test for agreement. Some of these methods have been shown to be inappropriate. This can result in misleading conclusions about the validity of an instrument. The Bland-Altman method is the most popular method judging by the many citations of the article proposing this method. However, the number of citations does not necessarily mean that this method has been applied in agreement research. No previous study has been conducted to look into this. This is the first systematic review to identify statistical methods used to test for agreement of medical instruments. The proportion of various statistical methods found in this review will also reflect the proportion of medical instruments that have been validated using those particular methods in current clinical practice. Methodology/Findings Five electronic databases were searched between 2007 and 2009 to look for agreement studies. A total of 3,260 titles were initially identified. Only 412 titles were potentially related, and finally 210 fitted the inclusion criteria. The Bland-Altman method is the most popular method with 178 (85%) studies having used this method, followed by the correlation coefficient (27%) and means comparison (18%). Some of the inappropriate methods highlighted by Altman and Bland since the 1980s are still in use. Conclusions This study finds that the Bland-Altman method is the most popular method used in agreement research. There are still inappropriate applications of statistical methods in some studies. It is important for a clinician or medical researcher to be aware of this issue because misleading conclusions from inappropriate analyses will jeopardize the quality of the evidence, which in turn will influence quality of care given to patients in the future.

The influence of firm age on the relationships of airline performance, economic situation and internal operation

Abstract The ways in which airline performance depends on the economic situation and internal operation are well established in the literature. One of the contextual factors that may change the nature of these relationships is firm age. As such, the aim of this study is to investigate the moderating influence of firm age on airline performance outcomes. Thirty airline companies from the Asia Pacific region were selected, and relevant data from 2006 to 2011 were collected. It can be deduced that company experience or firm age can help in taking control of the relationship between the constructs; thus, this measurement acts as a moderator in the research model.

Assessment of haematocrit status using bioelectrical impedance analysis in dengue patients

Abstract This paper investigates bioelectrical impedance analysis as a non-invasive tool to monitor haematocrit status for dengue patients in The University Kebangsaan Malaysia Hospital (HUKM), Malaysia. BIA measurements were conducted on 180 (97 males and 83 females) serologically confirmed dengue patients during their hospitalization. The clinical diagnosis and severity grading I to IV of DHF were in accordance to WHO recommendations. We investigated the prognostic relevance of electrical tissue conductivity in BIA, patients demographic variables and symptoms. Among 7 parameters (resistance, reactance, sex, age, weight, anorexia and vomiting) estimated using the multiple linear regression model, 4 were found to be significant. They were reactance, weight, sex and vomiting. Although the model can only explain approximately 40% of the variation in HCT status. bio-impedance using single frequency stand-alone technique is insufficient in monitoring HCT for the dengue patients.

Testing the agreement of medical instruments: Overestimation of bias in the Bland-Altman analysis

OBJECTIVES The Bland-Altman method is the most popular method used to assess the agreement of medical instruments. The main concern about this method is the presence of proportional bias. The slope of the regression line fitted to the Bland-Altman plot should be tested to exclude proportional bias. The aim of this study was to determine whether the overestimation of bias in the Bland-Altman analysis is still present even when the proportional bias has been excluded. METHODS Data were collected from participants attending a workplace health screening program in a public university in Malaysia between 2009 and 2010. Variables collected were blood glucose level, body weight and systolic blood pressure (n=300 per variable). Readings from the original clinical dataset were compared with twenty randomly generated datasets for each variable. The Bland-Altman limits of agreement was used to determine the agreement. The presence of proportional bias was excluded for all datasets using the recommended method. RESULTS The range of predicted bias was higher than the simulated bias for all datasets. The overestimation of bias increased as the range of actual bias increased. CONCLUSION Testing the slope of regression line of the Bland-Altman plot does not remove the artifactual bias in the prediction.

Analysis of Water Compartment in Dengue Patients

This paper describes the water compartments in healthy subjects and dengue patients on the day of defervescence of fever using bioelectrical impedance analysis. A total of 223 healthy subjects (65 males and 158 females) and 210 dengue patients (119 males and 91 females) in Hospital Universiti Kebangsaan Malaysia (HUKM), were studied. The ages for healthy subjects vary between 14 and 60 years old with mean age of 26.05 years while the ages for the dengue patients vary between 12 and 83 years old with mean age of 30.14 years. The parameters of water compartments investigated were total body water (TBW), extracellular water (ECW) and intracellular water (ICW). There were significant difference between healthy subjects and dengue patients for both male (p<0.05) and female (p<0.001) beginning on fever day 0 till fever day 4. The mean TBW and ECW values of dengue patients obtained were found to be higher than the normal healthy subjects while the mean ICW was lower. The mean TBW and ICW for male were higher than female while the mean ECW for male was lower than female for healthy subjects and dengue patients

An Application of Bayesian Approach in Modeling Risk of Death in an Intensive Care Unit.

Background and Objectives There are not many studies that attempt to model intensive care unit (ICU) risk of death in developing countries, especially in South East Asia. The aim of this study was to propose and describe application of a Bayesian approach in modeling in-ICU deaths in a Malaysian ICU. Methods This was a prospective study in a mixed medical-surgery ICU in a multidisciplinary tertiary referral hospital in Malaysia. Data collection included variables that were defined in Acute Physiology and Chronic Health Evaluation IV (APACHE IV) model. Bayesian Markov Chain Monte Carlo (MCMC) simulation approach was applied in the development of four multivariate logistic regression predictive models for the ICU, where the main outcome measure was in-ICU mortality risk. The performance of the models were assessed through overall model fit, discrimination and calibration measures. Results from the Bayesian models were also compared against results obtained using frequentist maximum likelihood method. Results The study involved 1,286 consecutive ICU admissions between January 1, 2009 and June 30, 2010, of which 1,111 met the inclusion criteria. Patients who were admitted to the ICU were generally younger, predominantly male, with low co-morbidity load and mostly under mechanical ventilation. The overall in-ICU mortality rate was 18.5% and the overall mean Acute Physiology Score (APS) was 68.5. All four models exhibited good discrimination, with area under receiver operating characteristic curve (AUC) values approximately 0.8. Calibration was acceptable (Hosmer-Lemeshow p-values > 0.05) for all models, except for model M3. Model M1 was identified as the model with the best overall performance in this study. Conclusion Four prediction models were proposed, where the best model was chosen based on its overall performance in this study. This study has also demonstrated the promising potential of the Bayesian MCMC approach as an alternative in the analysis and modeling of in-ICU mortality outcomes.

The Impact of the Wavelet Propagation Distribution on SEIRS Modeling with Delay

Previous models of disease spread involving delay have used basic SIR (susceptible – infectious – recovery) formulae and approaches. This paper demonstrates how time-varying SEIRS (S – exposed – I – R – S) models can be extended with delay to produce wave propagations that simulate periodic wave fronts of disease spread in the context of population movements. The model also takes into account the natural mortality associated with the disease spread. Understanding the delay of an infectious disease is critical when attempting to predict where and how fast the disease will propagate. We use cellular automata to model the delay and its effect on the spread of infectious diseases where population movement occurs. We illustrate an approach using wavelet transform analysis to understand the impact of the delay on the spread of infectious diseases. The results indicate that including delay provides novel ways to understand the effects of migration and population movement on disease spread.

Effects of Abnormal Total Cholesterol Level on Bodycomposition Parameters

This paper describes the effect of abnormal total cholesterol (TC) level on the bodycomposition parameters that can be measured non-invasively using bioelectrical Impedance analysis (BIA). A total of 190 subjects (86 males and 104 females) were recruited in the study which was conducted at the University of Malaya Student Health Clinic (UMHC), Kuala Lumpur, Malaysia. Subjects’ serum was collected for measurement of TC and bioelectrical impedance was measureed for bodycomposition. Subjects were divided into 2 groups according to their TC values. Group 1 (n=92) consists of subjects with normal TC value ( 5.2 mmol/L). Statistical analysis using independent sample t-test was used to investigate the relationship between BIA parameters and TC. The results revealed that there were differences in age, weight, body mass index(BMI), body capacitance (BC), extracellular mass (EM), lean body mass (LBM), fat mass (FM), basal metabolic rate (BMR) and total body water to total water ratio (TBW/TW) among the subjects with normal and abnormal TC. TC level was significantly higher in older subjects (p=0.000). In Group 2 the BC, FM, BMI, FM and BMR were significantly higher (p 0.05). In conclusion, the results show that there were differences in BIA parameters among the TC levels.

Expert System for Non-Invasive Classification of Total Cholesterol Level Using Bioelectrical Impedance

This paper describes the development of a Rule Based Expert System (ES) to classify the Total Cholesterol (TC) level using Bioelectrical Impedance Analysis (BIA). A total of 199 voluntary subjects were recruited in the study. The BIA parameters that are statistically significant predictors are body capacitance (BC), basal metabolic rate (BMR) extracellular mass (ECM) and lean body mass (LBM). The ES was developed using Bayesian reasoning method. The developed ES is able to classify subjects’ TC level between normal ( 5.2 mmol/L). From the analysis using 40 testing data, the system total accuracy for classifying TC level at 0.6 probability cutoff prediction was only 70.0%. The sensitivity was 67%, and specificity of 74%. From the validation data, this ES system can classify 6 from 10 subjects correctly.

Investigation of Household Debt through Multilevel Multivariate Analysis: Case of a Developing Country

This study focuses on investigating the relationships between different socioeconomic and demographic characteristics and households’ debt decision and demand. We used six survey rounds of data from Pakistan household integrated expenditure survey (HIES) 2001 to 2014. HIES is a nationally representative data collected by Pakistan Bureau of Statistics. Multilevel models were used to investigate the relationship in which the data on households was nested in primary sampling units (PSUs) and PSUs were nested in provinces. The decision of taking household debt varies 22% at PSU level and 18% at provincial level due to unobserved variables. We found that households having higher financial assets, higher income and larger household sizes tend to have a higher percentage of debt. The amount of debt also increases with education and age. In the case of demand for debt, the variation is 12% at the provincial level. Literature studying household debt decision in Pakistan often ignore the geographical differences (region/province specific studies). Considering socioeconomic characteristics habituating the usage of credit is of countless importance in guiding policy design and interventions that aim to improve financial inclusion.