Biomedical subjects

X M Tu

Publications and source records attributed to X M Tu.

24 records · Page 2Linked to original sources

PubMed1994

Impact of acute psychiatric inpatient treatment on major depression in late life and prediction of response.

OBJECTIVE: The authors conducted a prospective study to examine the sociodemographic and clinical characteristics of elderly inpatients with major depression and their response to acute psychiatric hospitalization. The relation between the descriptive variables and clinical response was also investigated. METHOD: The subjects were 205 consecutively admitted inpatients, whose mean age was 71 years, who met the DSM-III-R criteria for major depression. Each subject received detailed physical, psychiatric, and mental status examinations, along with quantitative assessments of psychiatric symptoms and cognitive performance at admission and at discharge. Management of physical problems was optimized, and patients were treated with a combination of somatic and psychotherapeutic interventions. The average duration of hospitalization was approximately 1 month. RESULTS: Despite considerable medical and psychiatric comorbidity, the patients responded well to treatment, as reflected by a 50% reduction in the average score on the Hamilton Depression Rating Scale. Nearly one-half of the patients had experienced the resolution of their depressive symptoms by the time of discharge. Race, cognitive performance at admission, number of medical problems, use of ECT, and length of hospitalization independently contributed to the prediction of clinical response. Response to treatment was not related to the other sociodemographic variables examined or to any of the indexes of severity of depressive episode. CONCLUSIONS: Short-term psychiatric hospitalization offers an effective and efficient vehicle for the treatment of severe or complicated cases of major depression in the elderly, even when considerable medical and psychiatric comorbidity is present.

Age Factors↗

PubMed1994

Modelling progression of CD4-lymphocyte count and its relationship to survival time.

The purpose of this article is to model the progression of CD4-lymphocyte count and the relationship between different features of this progression and survival time. The complicating factors in this analysis are that the CD4-lymphocyte count is observed only at certain fixed times and with a high degree of measurement error, and that the length of the vector of observations is determined, in part, by the length of survival. If probability of death depends on the true, unobserved CD4-lymphocyte count, then the survival process must be modelled. Wu and Carroll (1988, Biometrics 44, 175-188) proposed a random effects model for two-sample longitudinal data in the presence of informative censoring, in which the individual effects included only slopes and intercepts. We propose methods for fitting a broad class of models of this type, in which both the repeated CD4-lymphocyte counts and the survival time are modelled using random effects. These methods permit us to estimate parameters describing the progression of CD4-lymphocyte count as well as the effect of differences in the CD4 trajectory on survival. We apply these methods to results of AIDS clinical trials.

Acquired Immunodeficiency Syndrome↗

PubMed1994

Regression analysis of censored and truncated data: estimating reporting-delay distributions and AIDS incidence from surveillance data.

AIDS surveillance provides a vital source of information for health departments to assess the AIDS epidemic and to plan for future health-care needs. However, the use of surveillance data requires proper adjustments for the underreporting of AIDS cases caused by the delay in reporting diagnosed AIDS cases to the surveillance system. The statistical problem of adjusting for this underreporting concerns making inferences about an unobservable random sample of which only a portion is observed in a chronologic time interval defined by the analysis. Most regression methods for making inferences using right-truncated data employ a reverse-time hazard function, which requires that the observed data be transformed so that methods for left-truncated data can be applied. In this paper, we discuss fitting regression models to data that can be truncated and even censored in arbitrary intervals. The proposed methodology was applied to the national AIDS surveillance data provided by the Centers for Disease Control to analyze the trend of delays over chronologic time and variation among different geographic regions as well as across risk groups.

Acquired Immunodeficiency Syndrome↗

PubMed1993

Survival differences and trends in patients with AIDS in the United States.

The AIDS surveillance system maintained by the Centers for Disease Control and Prevention (CDC) provides a unique data base for estimating survival after a diagnosis of AIDS for the general AIDS population in the United States. Because patients enrolled in most AIDS clinical trial studies receive unusual medical care that may not be available to the general public and typically have relatively longer survival time, estimates obtained from these studies may not be of direct use in assessing the national health-care needs. Furthermore, such studies are usually of short duration and may not be very informative for long-term health-policy planning. We present survival estimates obtained from the CDC surveillance data for the adult/adolescent AIDS population in the United States and compare their survival and trend in survival on gender, sexual behavior, and injection-drug use status. These estimates provide information for mortality risk after an AIDS diagnosis over a period of 8 years and for trend of survival during the period between 1983 and 1991.

Acquired Immunodeficiency Syndrome↗

PubMed1992

Issues in human immunodeficiency virus (HIV) screening programs.

Unlike test sensitivity and specificity, the false positive and negative predictive values (probabilities of mislabeling an individual being tested) depend heavily on the prevalence of the infection of the human immunodeficiency virus (HIV) as well as the quality of the kit. A consequence of this dependence is that the false positive predictive value can reach a high magnitude such as 0.9; that is, 90% of the positive tests are false. This raises many important issues pertaining to the current practice of HIV screening such as to how to control these misclassification errors, how to interpret test results, and how to estimate prevalence using test results. These issues are examined in detail here by considering the factors that dictate the quality of a screening program. Some real data examples are used to illustrate the importance of this consideration in designing programs to achieve the desired goals. The rationale behind the common two-step sequential protocol in HIV screening is examined to point out its limitations under practical situations. Finally, the use of entropy in evaluating the informativeness of a screening program is discussed.

AIDS Serodiagnosis↗

PubMedDate not supplied

Studies of AIDS and HIV surveillance. Screening tests: can we get more by doing less?

Estimating the prevalence of the human immunodeficiency virus (HIV) in a group is challenging; this is especially so when the prevalence is small. One reason is that the presence of measurement errors resulting from the limited precision of tests makes estimation, using traditional methods, impossible in some screening situations. Measurement error is real, ignoring it leads to severe bias, and inference about the prevalence becomes unsatisfactory. Indeed, in a low prevalence situation the expected number of false positives is very high, often even higher than the number of true positives. The second reason is that in the low prevalence areas the large sample is needed in order to obtain non-zero estimate. This is usually a very costly, and often unrealistic, solution. This paper considers the advantages and disadvantages of pooled testing as an alternative solution to this problem. We show that by pooling sera samples we not only achieve a cost saving but also, which is counterintuitive, an increase in the estimation accuracy. We also discuss the statistical issues associated with the resulting estimator.

Acquired Immunodeficiency Syndrome↗