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Biomedical subjects

H S Fraser

Publications and source records attributed to H S Fraser.

At least 19 recordsLinked to original sources
PubMed2001

Using patient-reportable clinical history factors to predict myocardial infarction.

Using a derivation data set of 1253 patients, we built several logistic regression and neural network models to estimate the likelihood of myocardial infarction based upon patient-reportable clinical history factors only. The best performing logistic regression model and neural network model had C-indices of 0.8444 and 0.8503, respectively, when validated on an independent data set of 500 patients. We conclude that both logistic regression and neural network models can be built that successfully predict the probability of myocardial infarction based on patient-reportable history factors alone. These models could have important utility in applications outside of a hospital setting when objective diagnostic test information is not yet be available.

Databases, Factual↗
PubMed2001

Elevated systemic concentrations of soluble ICAM-1 (sICAM) are not reflected in the gingival crevicular fluid of smokers with periodontitis.

Raised serum levels of soluble intercellular adhesion molecule-1 (sICAM-1) in smokers could have immunomodulatory effects in periodontitis. The aim of this study was to compare serum and gingival crevicular fluid (GCF) concentrations of sICAM-1 in smokers and non-smokers with periodontal disease. sICAM-1 in serum and GCF collected from age- and gender-matched smokers (n = 14) and non-smokers (n = 14) with periodontitis were measured by ELISA. Mean serum sICAM-1 concentrations were significantly elevated in smokers (331 ng mL(-1)), compared with non-smokers (238 ng mL(-1), p = 0.008). However, the concentration of sICAM-1 in the GCF was significantly lower in the smokers (83 ng mL(-1)), compared with non-smokers (212 ng mL(-1), p = 0.013). The difference between concentrations of sICAM-1 in GCF and serum was significant only in smokers (p < 0.001). Since GCF is a serum-derived tissue exudate, these results suggest that, in smokers, circulating sICAM-1 molecules are affected either in their passage from the periodontal microvasculature or within the periodontal tissues.

Adult↗
PubMed2001

TeleMedMail: free software to facilitate telemedicine in developing countries.

Telemedicine offers the potential to alleviate the severe shortage of medical specialists in developing countries. However lack of equipment and poor network connections usually rule out video-conferencing systems. This paper describes a software application to facilitate store-and-forward telemedicine by email of images from digital cameras. TeleMedMail is written in Java and allows structured text entry, image processing, image and data compression, and data encryption. The design, implementation, and initial evaluation are described.

Computer Communication Networks↗
PubMed2001

Research, health policies and health care in the Caribbean. The role of the University of the West Indies.

The University of the West Indies has had a major impact on the provision of health care and the health of Caribbean nations over the last 50 years, through undergraduate, postgraduate and continuing medical education, research, outreach and public service. These roles are fully accepted, and the Faculties of Medical Sciences and School of Clinical Medicine and Research have provided most of the doctors now serving the English-speaking Caribbean, including academic leaders and chief medical officers. The design of a curriculum to produce doctors "designed" for the region has been a well-articulated goal, and the need to carry out relevant and essential national health research is now accepted. But the broader roles of ensuring translation of research into policy and practice, and developing effective ways of promoting on-going continuing training and behaviour change are far from understood or seriously attempted. Communication of research findings and evidence-based practice is crucial. The West Indian Medical Journal clearly has a valuable role to play here and this requires expansion and support. But a multi-faceted approach to communicating research findings and translating evidence into policy, planning and care is necessary. One possible approach would be a University Unit of Health Policy Research and Development.

Delivery of Health Care↗
PubMed2001

Fifty years of clinical examinations at the University of the West Indies.

The University of the West Indies was founded at Mona, Jamaica, in 1948. After fifty-two years, the format of the final Bachelor of Medicine clinical examination in Medicine and Therapeutics has been radically revised. The change from the traditional to an evidence-based, objective structured clinical examination (OSCE) was undertaken in November/December 2000. Assessment drives learning and both the methods chosen for assessment and the manner in which they are applied determine how students learn. The philosophical underpinnings of the change in format are discussed in this paper.

Clinical Competence↗
PubMed2000

New approaches to measuring the performance of programs that generate differential diagnoses using ROC curves and other metrics.

INTRODUCTION: Evaluation of computer programs which generate multiple diagnoses can be hampered by a lack of effective, well recognized performance metrics. We have developed a method to calculate mean sensitivity and specificity for multiple diagnoses and generate ROC curves. METHODS: Data came from a clinical evaluation of the Heart Disease Program (HDP). Sensitivity, specificity, positive and negative predictive value (PPV, NPV) were calculated for each diagnosis type in the study. A weighted mean of overall sensitivity and specificity was derived and used to create an ROC curve. Alternative metrics Comprehensiveness and Relevance were calculated for each case and compared to the other measures. RESULTS: Weighted mean sensitivity closely matched Comprehensiveness and mean PPV matched Relevance. Plotting the Physician's sensitivity and specificity on the ROC curve showed that their discrimination was similar to the HDP but sensitivity was significantly lower. CONCLUSIONS: These metrics give a clear picture of a program's diagnostic performance and allow straightforward comparison between different programs and different studies.

Diagnosis, Computer-Assisted↗
PubMed1998

Using classification tree and logistic regression methods to diagnose myocardial infarction.

Early and accurate diagnosis of myocardial infarction (MI) in patients who present to the Emergency Room (ER) complaining of chest pain is an important problem in emergency medicine. A number of decision aids have been developed to assist with this problem but have not achieved general use. Machine learning techniques, including classification tree and logistic regression (LR) methods, have the potential to create simple but accurate decision aids. Both a classification tree (FT Tree) and an LR model (FT LR) have been developed to predict the probability that a patient with chest pain is having an MI based solely upon data available at time of presentation to the ER. Training data came from a data set collected in Edinburgh, Scotland. Each model was then tested on a separate Edinburgh data set, as well as on a data set from a different hospital in Sheffield, England. Previously published models, the Goldman classification tree[1] and Kennedy LR equation[2], were evaluated on the same test data sets. On the Edinburgh test set, results showed that the FT Tree, FT LR, and Kennedy LR performed equally well, with ROC curve areas of 94.04%, 94.28%, and 94.30%, respectively, while the Goldman Tree's performance was significantly poorer, with an area of 84.03%. The difference in ROC areas between the first three models and the Goldman model is significant beyond the 0.0001 level. On the Sheffield test set, results showed that the FT Tree, FT LR, and Kennedy LR ROC areas were not significantly different (p > = 0.17), while the FT Tree again outperformed the Goldman Tree (p = 0.006). Unlike previous work[3], this study indicates that classification trees, which have certain advantages over LR models, may perform as well as LR models in the diagnosis of patients with MI.

Algorithms↗
PubMed1998

Neurological and neurosurgical referrals overseas from the Queen Elizabeth Hospital, Barbados, 1987-1996.

This paper reports on neurological and neurosurgical referrals overseas from the Queen Elizabeth Hospital (QEH) for the period November 1987 to November 1996, and is a follow up to an earlier report for the period January 1984 to November 1987. It outlines the pattern of referral, diagnoses, referral centres and costs based on examination of the files of all QEH patients transferred overseas under a government aided scheme. There were 203 transfers of 191 patients (69 males, 122 females) including 10 patients who were transferred twice and one patient who was transferred three times. Patients' ages ranged from 1 to 80 years (mean 37 years). Twenty overseas centres were used during the period but most patients were transferred to Brooklyn Hospital, New York in 1988, Mount Sinai Medical Center, New York, between 1989 and 1994, and Hospital de Clinicas Caracas, Venezuela (1992 to 1996). 65% of the referrals were for neurosurgery and 25% were for magnetic resonance imaging scans for diagnosis. The largest diagnostic categories were central nervous system tumors (40%) and subarachnoid haemorrhage (25%). Estimated costs reached almost BDS$11 million, but the mean actual cost was BDS$63,916 based on information from 123 patient transfers. Thus, the actual total government expenditure was probably closer to BDS$13 million. This study demonstrates the urgent need to establish a neurosurgical service at the QEH and the cost effectiveness of doing so.

Barbados↗
PubMed1998

Improving machine learning performance by removing redundant cases in medical data sets.

Neural network models and other machine learning methods have successfully been applied to several medical classification problems. These models can be periodically refined and retrained as new cases become available. Since training neural networks by backpropagation is time consuming, it is desirable that a minimum number of representative cases be kept in the training set (i.e., redundant cases should be removed). The removal of redundant cases should be carefully monitored so that classification performance is not significantly affected. We made experiments on data removal on a data set of 700 patients suspected of having myocardial infarction and show that there is no statistical difference in classification performance (measured by the differences in areas under the ROC curve on two previously unknown sets of 553 and 500 cases) when as many as 86% of the cases are randomly removed. A proportional reduction in the amount of time required to train the neural network model is achieved.

Area Under Curve↗
PubMed1998

Differential diagnoses of the heart disease program have better sensitivity than resident physicians.

We describe a prospective clinical evaluation of a computer program to assist with the diagnosis of heart disease. The Heart Disease Program (HDP) is a large diagnostic program covering most areas of heart disease and some related areas of general medicine. The program's output is a set of differential diagnoses with explanations and it can be deployed in a clinical setting using a web interface. A framework for assessing the complex diagnostic summaries generated by the HDP was developed and the program's diagnostic accuracy in a clinical setting was assessed. The diagnoses used for comparison came from the physician entering the case, a "gold standard" assigned by review of patient charts and investigations, and the opinions of expert cardiologists. The data collection, methods of comparison, example analyses and results on 114 cases are presented here. The HDP had a significantly higher sensitivity for both the gold standard (60%) and the cardiologist's diagnoses (58%) than the physicians did (39%, 34%). These findings were consistent in the 2 collection cohorts and for the more serious diagnoses alone. The significance of these findings and the many challenges in comparing these different diagnoses and minimizing bias are discussed.

Cardiology↗
PubMed1997

An artificial neural network system for diagnosis of acute myocardial infarction (AMI) in the accident and emergency department: evaluation and comparison with serum myoglobin measurements.

Recent studies have confirmed that artificial neural networks (ANNs) are adept at recognising patterns in sets of clinical data. The diagnosis of acute myocardial infarction (AMI) in patients presenting with chest pain remains one of the greatest challenges in emergency medicine. The aim of this study was to evaluate the performance of an ANN trained to analyse clinical data from chest pain patients. The ANN was compared with serum myoglobin measurements--cardiac damage is associated with increased circulating myoglobin levels, and this is widely used as an early marker for evolving AMI. We used 39 items of clinical and ECG data from the time of presentation to derive 53 binary inputs to a back propagation network. On test data (200 cases), overall accuracy, sensitivity, specificity and positive predictive value (PPV) of the ANN were 91.8, 91.2, 90.2 and 84.9% respectively. Corresponding figures using linear discriminant analysis were 81.0, 77.9, 82.6 and 69.7% (P < 0.01). Using a further test set from a different centre (91 cases), the accuracy, sensitivity, specificity and PPV for the admitting physicians were 65.1, 28.5, 76.9 and 28.6% respectively compared with 73.6, 52.4, 80.0 and 44.0% for the ANN. Although myoglobin at presentation was highly specific, it was only 38.0% sensitive, compared with 85.7% at 3 h. Simple strategies to combine clinical opinion, ANN output and myoglobin at presentation could greatly improve sensitivity and specificity of AMI diagnosis. The ideal support for emergency room physicians may come from a combination of computer-aided analysis of clinical factors and biochemical markers such as myoglobin. This study demonstrates that the two approaches could be usefully combined, the major benefit of the decision support system being in the first 3 h before biochemical markers have become abnormal.

Adult↗
PubMed1996

Diabetes care in middle-income countries: a Caribbean case study.

Many middle-income countries now have a high prevalence of diabetes and need to address the problem of providing care for people with diabetes within limited resources. This study evaluated standards of preventive care in primary settings in three Caribbean countries. We studied case records at 17 clinics in 15 government health centres and 17 private general practitioners' offices in Barbados, Trinidad and Tobago and Tortola (British Virgin Islands). A census of all attenders over a 4 to 7 week period identified 1661 attenders with diabetes mellitus, approximately two-thirds were women with a median age over 60 years. Overall 676/1342 (50%) had 'poor' blood glucose control (> or = 8 mmol l-1 fasting or > or = 10 mmol l-1 random). The proportion with BP > or = 160/95 mmHg or receiving treatment for hypertension was 943/1661 (57%), of whom 781/943 (83%) were prescribed drug treatment. Among those treated for hypertension only 181/781 (23%) had blood pressures < 140/90 mmHg. Surveillance for complications affecting the feet (11%) or eyes (2%) was not performed systematically in any setting. Only 533 (32%) had recorded dietary advice and 79 (5%) had recorded exercise advice in the last 12 months. To begin to address some of these problems at a regional level, we incorporated results from this survey into a series of workshops held in collaboration with health ministries in 10 Caribbean countries, with participants from 13 countries. At these workshops health care workers participated in the process of developing guidelines for diabetes management in primary care. The guidelines have subsequently been widely disseminated through health ministries and non-governmental organizations in the region. Further research is needed to evaluate the effectiveness of this approach, the constraints on diabetes care, and the most cost-effective means of addressing them.

Aged↗
PubMed1996

Early diagnosis of acute myocardial infarction using clinical and electrocardiographic data at presentation: derivation and evaluation of logistic regression models.

The aim of this study was to determine which, and how many, data items are required to construct a decision support algorithm for early diagnosis of acute myocardial infarction using clinical and electrocardiographic data available at presentation. Logistic regression models were derived using data items from 600 consecutive patients at one centre (Edinburgh), then tested prospectively on 510 cases from the same centre and 662 consecutive cases from another centre (Sheffield). Although performance of the models increased with progressive addition of data inputs when applied to training data, a simple six-factor model was the most effective on test data, yielding accuracies of 84.3 and 83.6% on the two test sets. A model constructed solely of electrocardiographic data performed nearly as well as those incorporating clinical data. Previously published logistic regression models did not perform so well as the models derived from data collected for this study.

Adolescent↗