Biomedical subjects

G J McLachlan

Publications and source records attributed to G J McLachlan.

12 recordsLinked to original sources

PubMed1997

An analysis of valve re-replacement after aortic valve replacement with biologic devices.

Biologic valve re-replacement was examined in a series of 1343 patients who underwent aortic valve replacement at The Prince Charles Hospital, Brisbane, with a cryopreserved or 4 degrees C stored allograft valve or a xenograft valve. A parametric model approach was used to simultaneously model the competing risks of death without re-replacement and re-replacement before death. One hundred eleven patients underwent a first re-replacement for a variety of reasons (69 patients with xenograft valves, 28 patients with 4 degrees C stored allograft valves, and 14 patients with cryopreserved allograft valves). By multivariable analysis younger age at operation was associated with xenograft, 4 degrees C stored allograft, and cryopreserved allograft valve re-replacement. However, this effect was examined in the context of longer survival of younger patients, which increases their exposure to the risk of re-replacement as compared with that in older patients whose decreased survival reduced their probability of requiring valve re-replacement. In patients older than 60 years at the time of aortic valve replacement, the probability of re-replacement (for any reason) before death was similar for xenografts and cryopreserved allograft valves but higher for 4 degrees C stored valves. However, in patients younger than 60 years, the probability of re-replacement at any time during the remainder of the life of the patient was lower with the cryopreserved allograft valve compared with the xenograft valve and 4 degrees C stored allografts.

Adolescent↗

PubMed1997

On the EM algorithm for overdispersed count data.

In this paper, we consider the use of the EM algorithm for the fitting of distributions by maximum likelihood to overdispersed count data. In the course of this, we also provide a review of various approaches that have been proposed for the analysis of such data. As the Poisson and binomial regression models, which are often adopted in the first instance for these analyses, are particular examples of a generalized linear model (GLM), the focus of the account is on the modifications and extensions to GLMs for the handling of overdispersed count data.

Algorithms↗

PubMed1994

On the role of finite mixture models in survival analysis.

In this paper we review the role of finite mixture models in the field of survival analysis. Finite mixture models can be used to analyse failure-time data in a variety of situations. In particular, they provide a way of modelling time to failure in the case of competing risks.

Algorithms↗

PubMed1994

Parametric estimation in a genetic mixture model with application to nuclear family data.

The apparent conflict between the biometrician and Mendelian genetics has been recently resolved by the introduction of a genetic mixed model to analyze continuous traits measured on human families and to elucidate the mechanism of underlying major genes. The mixed model formulated by Elston and Stewart (1971, Human Heredity 21, 523-542), extended by Morton and MacLean (1974, American Journal of Human Genetics 26, 489-503), and reviewed, with further extensions, by Boyle and Elston (1979, Biometrics 35, 55-68) has become an extremely useful tool of wide applicability in the field of genetic epidemiology. This model allows for segregation at a major locus, a polygenic effect, and a sibling environmental variation. The main concern of this paper is with estimating the model parameters by the method of maximum likelihood. The expectation-maximization (EM) algorithm is developed to derive the estimates iteratively. An approximation of the information matrix when using the EM algorithm is given. We illustrate the methodology by fitting the model to the arterial blood pressure data collected by Miall and Oldham (1955, Clinical Science 14, 459-487).

Biometry↗

PubMed1993

An analysis of risk factors for death and mode-specific death after aortic valve replacement with allograft, xenograft, and mechanical valves.

From September 1967 to January 1990, a total of 2100 patients underwent 2366 aortic valve replacements with a variety of allograft, xenograft, and mechanical valves. Concomitant procedures were performed in 764 patients. Actuarial survival at 12 years was 59.6% (70% confidence limits 57.8% to 61.4%). Hazard function for death was highest immediately after operation, falling to merge with a slowly rising phase of risk at approximately 3 months. Actuarial freedom from sudden death at 12 years was 88.0% (70% confidence limits 86.7% to 89.3%). The shape of the hazard function for sudden death was similar to that for death. Actuarial freedom from death with cardiac failure at 12 years was 87.9% (70% confidence limits 86.5% to 89.2%). The shape of the hazard function for death with cardiac failure was also similar to that for death. Risk factor analysis revealed the important deleterious impact on long-term survival resulting from impaired left ventricular structure and function because of aortic valve disease. No current-era valve used in this study (allograft, xenograft, or mechanical) was a risk factor for death. Both aortic wall disease and endocarditis necessitating aortic valve replacement substantially decreased long-term patient survival. Aortic valve replacement is advisable much earlier in the natural history of aortic valve disease before secondary left ventricular damage occurs.

Actuarial Analysis↗

PubMed1992

Cluster analysis and related techniques in medical research.

In this paper we review methods of cluster analysis in the context of classifying patients on the basis of clinical and/or laboratory type observations. Both hierarchical and non-hierarchical methods of clustering are considered, although the emphasis is on the latter type, with particular attention devoted to the mixture likelihood-based approach. For the purposes of dividing a given data set into g clusters, this approach fits a mixture model of g components, using the method of maximum likelihood. It thus provides a sound statistical basis for clustering. The important but difficult question of how many clusters are there in the data can be addressed within the framework of standard statistical theory, although theoretical and computational difficulties still remain. Two case studies, involving the cluster analysis of some haemophilia and diabetes data respectively, are reported to demonstrate the mixture likelihood-based approach to clustering.

Algorithms↗

PubMed1992

Aortic valve infection. Risk factors for death and recurrent endocarditis after aortic valve replacement.

Patients (n = 195) undergoing aortic valve replacement (n = 209) for native or prosthetic valve endocarditis were studied to determine risk factors for death and recurrent endocarditis and also to determine the valve type least likely to be associated with recurrent endocarditis. Ten-year survival was 60%, the highest risk of dying occurring within the first 3 postoperative months. Risk factors for death in this early phase included increased urea concentration, higher New York Heart Association functional class, prosthetic valve endocarditis, infection status (lower in patients with healed endocarditis), longer duration of cardiopulmonary bypass, and nonuse of an allograft valve. In the late phase (beyond 3 months), risk factors included age at operation and Staphylococcus aureus infection (only in New York Heart Association functional class V). Ten years after aortic valve replacement, 79% of valves were free of recurrent endocarditis. The highest risk of recurrence was in the first 4 months. Longer duration of cardiopulmonary bypass was a weak risk factor for recurrent endocarditis in the early phase, and in the late phase risk factors were S. aureus infection (only in New York Heart Association functional classes III, IV, and V) and the use of now discontinued biologic valves. Allograft aortic valve replacement was shown to be associated with a low and constant risk of recurrent endocarditis, whereas other valve types were associated with a high early risk. The allograft valve should be the preferred replacement device for aortic root infection.

Adult↗

PubMed1991

Allograft aortic valve replacement: long-term comparative clinical analysis of the viable cryopreserved and antibiotic 4 degrees C stored valves.

Aortic valve replacement with or without concomitant procedures was performed using an allograft aortic valve in 534 patients. From December 1969 to May 1975 (group I), a 4 degrees C stored valve was used (124 patients) and from June 1975 to July 1990 (group II), a cryopreserved valve (410 patients) was used. The 30-day mortality was 8.9% (confidence limits [CL] 6.2%-12.3%) for group I and 2.7% (CL 1.9%-3.8%) for group II. Actuarial patient survival including early hospital mortality at 14 years was 57% for group I and 71% for group II (p = 0.014). Actuarial freedom from thromboembolism for all patients (n = 534) was 94% at 14 years, and for patients who underwent isolated aortic valve replacement with or without coronary artery bypass graft (n = 457) was 97% at 14 years (p = 0.017). Actuarial freedom from allograft valve endocarditis at 14 years was 92% in group I and 94% in group II (p = 0.36). The actuarial freedom from moderate or severe allograft valve incompetence at 14 years was 50% (group I) and 78% (group II) (p = 0.27). Reoperation was undertaken for endocarditis, leaflet structural deterioration (SD), or technical reasons. The actuarial freedom from reoperation (all causes) at 14 years was 63% (group I) and 86% (group II) (p = 0.39). Reoperation for SD occurred in 34 patients in group I and three patients in group II. The actuarial freedom from reoperation for SD at 14 years was 67% (group I) and 95% (group II) (p = 0.001). To reflect a more accurate depiction of the prevalence of SD, patients were analyzed according to the development of "assumed structural deterioration" (at reoperation, at death with moderate or severe allograft valve incompetence and macroscopic valve deterioration on autopsy, and in the presence of moderate or severe allograft valve incompetence in patients not undergoing reoperation). The actuarial freedom from "assumed structural deterioration" at 14 years was 51% (group I) and 85% (group II) (p = 0.000003). The long-term results confirm the low incidence of thromboembolism and endocarditis regardless of the method of preservation and demonstrate the overall acceptable performance of the viable cryopreserved allograft valve and its superiority over the 4 degrees C stored valve.

Actuarial Analysis↗

PubMed1991

Fitting mixture distributions to phenylthiocarbamide (PTC) sensitivity.

A technique for fitting mixture distributions to phenylthiocarbamide (PTC) sensitivity is described. Under the assumptions of Hardy-Weinberg equilibrium, a mixture of three normal components is postulated for the observed distribution, with the mixing parameters corresponding to the proportions of the three genotypes associated with two alleles A and a acting at a single locus. The corresponding genotypes AA, Aa, and aa are then considered to have separate means and variances. This paper is concerned with estimating the parameters of the model, and their standard errors, by using an application of the EM algorithm. This technique also caters for the fact that the sensitivity measurements are only known to lie between the endpoints of certain intervals and that the exact measurement of the attribute is not possible.

Algorithms↗

PubMed1989

Mixture models for partially unclassified data: a case study of renal venous renin in hypertension.

In many applications of discriminant analysis in medicine, data of known origin which can be reasonably assumed to be a random sample from the entire class may not be available for each of the possible classes. In this paper we note how such situations can be handled by using finite mixture models to formulate the estimation problem. This approach is adopted to model the distribution of the renal venous renin ratio (RVRR) between left and right kidneys in patients with hypertension. This distribution is used in the formation of a probabilistic allocation rule as an aid in the diagnosis of renal artery stenosis, which is potentially curable by surgery.

Chi-Square Distribution↗

PubMed1988

Fitting mixture models to grouped and truncated data via the EM algorithm.

The fitting of finite mixture models via the EM algorithm is considered for data which are available only in grouped form and which may also be truncated. A practical example is presented where a mixture of two doubly truncated log-normal distributions is adopted to model the distribution of the volume of red blood cells in cows during recovery from anemia.

Algorithms↗

PubMed1975

Confidence intervals for the conditional probability of misallocation in discriminant analysis.

In this study we are concerned with the construction of confidence intervals for the conditional probability of misallocation associated with Anderson's classification statistics, W. The available methods of computing confidence intervals for the conditional probability are not satisfactory in practice, mainly because the intervals obtained are fairly inaccurate. A new method is presented which enables intervals with almost the desired level of confidence to be easily computed from the initial samples on which W is based.

Monte Carlo Method↗