Biomedical subjects
Publications and source records attributed to S Lemeshow.
Relative excess risk due to interaction, the proportion of disease among those with both exposures that is attributable to their interaction, and the synergy index have been proposed as measures of interaction in epidemiologic studies. This paper presents the methodology for obtaining confidence interval estimates of these indices utilizing routinely available output from multiple logistic regression software.
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BACKGROUND: There is considerable evidence that members of managed care organizations use fewer hospital resources than patients covered by traditional health insurance. While intensive care might seem to be an unlikely setting for such differences to exist, the relationship between health coverage and use of intensive care has not been examined. METHODS: We conducted a cross-sectional analysis of consecutive intensive care unit admissions at a regional tertiary care teaching hospital. Patients in managed care plans (n = 159) and with traditional insurance (n = 389) were compared with respect to length of stay, hospital charges, charges for specific services, and use of mechanical ventilation. The analysis controlled for severity of illness, as measured by the Mortality Probability Model, case mix, and mortality. The whole sample as well as subsamples representing medical, emergency surgery, and elective surgery patients were examined. RESULTS: The managed care group, on average, had short stays (both hospital and intensive care unit), lower charges, and less use of mechanical ventilation than the traditionally insured group. Average differences of about 30% to 40% were observed. The finding held for the whole sample as well as the medical and emergency surgery subsamples. The differences were more pronounced in the patients with lowest severity of illness. CONCLUSION: Even in a setting where there would appear to be relatively little room for discretion in treatment decisions, incentives associated with type of health insurance seemed to affect resource use.
A Monte Carlo model simulating actual populations was employed to evaluate the precision in estimation of a standardized sampling method proposed by the Global Programme on AIDS of the World Health Organization, for general use in collecting population-based data on HIV seroprevalence. It appears that in real populations, where there is likely to be 'pocketing' of infection, the proposed methodology will generally fail to provide estimates accurate to within 1% of the true population value. However, if the primary objective of a particular survey is to construct confidence intervals that include the true population HIV seroprevalence rate, then this survey method appears to be a reasonable choice. This study also suggests that selection of only one adult per household improves the precision of resulting estimates. However, since selection of only one adult per household would require that more households be visited, any gain in precision would need to be weighed against the likely increase in cost of household visits.
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BACKGROUND: The logistic regression model is being used with increasing frequency in all areas of public health research. In the calendar year 1989, over 30% of the articles published in the American Journal of Public Health employed some form of logistic regression modeling. In spite of this increase, there has been no commensurate increase in the use of commonly available methods for assessing model adequacy. METHODS: We review the current status of the use of logistic regression modeling in the American Journal of Public Health. We present a brief overview of currently available and easily used methods for assessing the adequacy of a fitted logistic regression model. RESULTS: An example is used to demonstrate the methods as well as a few of the adverse consequences of failing to assess the fit of the model. One important adverse consequence illustrated in the example is the inclusion of variables in the model as a result of the influence of one subject. CONCLUSIONS: Failure to address model adequacy may lead to misleading or incorrect inferences. Recommendations are made for the use of methods for assessing model adequacy and for future editorial policy in regard to the review of articles using logistic regression.
Precision in estimation of relative risks using a standardized sampling method proposed by the WHO Global Programme on AIDS was evaluated using a Monte Carlo model simulating actual populations; the proposed survey design represents a modification of the methodology used by the WHO Expanded Programme on Immunization (EPI) to estimate immunization coverage among children. This study suggests that in actual populations the proposed survey strategy is a reasonable alternative to the use of simple random sampling (SRS) at the second stage of cluster sampling. Although varying such population characteristics as the seroprevalence rate, nonresponse rate, and rate of misclassification of exposure failed to demonstrate a clear advantage of one method over the other, the added cost and difficulty of implementing SRS under field conditions warrant further consideration of the EPI-like methodology for use in estimating relative risks.
Lot quality assurance sampling (LQAS) was originally developed for industrial applications. This article discusses the extension of its application to a public health setting. When resources must be allocated to several communities based on whether or not each exceeds a target proportion of members with a characteristic, a sampling scenario arises which is different to the standard parameter estimation scenario. LQAS is an efficient procedure for sampling in this instance. Under certain conditions, double sampling may further enhance the efficiency of an LQAS plan. LQAS is discussed and illustrated by examples, and the theoretical foundations of single and double lot quality assurance sampling are presented. Examples of sample size and critical value tables are also presented.
This study assessed the relationship between admission time (from hospital admission to ICU admission) and mortality predicted by the Mortality Prediction Model (MPM), actual mortality, and resource use. All admissions, except elective surgery patients, to the general medical/surgical ICU of a tertiary care hospital during a 24-month period were studied (n = 1,889). Patients admitted to the ICU within 1 day of hospital admission had lower predicted and actual mortality, and used fewer resources than patients admitted later. Predicted mortality was higher than actual mortality for patients admitted to the ICU early and was lower than actual mortality for later ICU admissions. Transfers had higher predicted and actual mortality, and used more resources than nontransfer patients. Time from hospital admission to ICU admission can be a potentially useful variable in models of ICU outcome.
Factors related to hospital resource use by intensive care unit (ICU) patients, including severity of illness at admission and intensity of therapy during the first 24 ICU hours were explored in this study. Analysis was based on 2,749 patients admitted to the general medical-surgical ICU at Baystate Medical Center, Springfield, Massachusetts, between February 1, 1983 and January 10, 1985. Resource use was indexed by hospital length of stay (LOS) adjusted for differences between ICU and other hospital days. Severity of illness was measured by the Mortality Prediction Model (MPM0), a validated predictor of outcome but not previously used to analyze resource consumption. Intensity of therapy was measured using the Therapeutic Intervention Scoring System (TISS). The 10% of patients with longest ICU stays were significantly different from the other 90% with respect to previous ICU use, MPM probability, and TISS score. Variability in resource use was analyzed using four diagnosis-related groups (DRGs) accounting for large numbers of ICU patients. The relationship between severity of illness and resource was nonlinear: as severity increased from low levels, resource use increased at a decreasing rate, reached a plateau, and eventually declined. Within each DRG, MPM0 explained a statistically significant percentage of the variability in resource use.
Six months after hospital discharge, we followed up 1545 patients who had received care in the general medical-surgical intensive care unit (ICU) of a tertiary care hospital. Vital status could not be ascertained for 200 of these patients. Of the 1345 former ICU patients for whom a determination of vital status could be made, 1261 (94%) were alive and 84 (6%) had died. Of those known to be living, 887 (70%) responded to a questionnaire regarding employment, functional, and social status. A large proportion of survivors less than 40 years of age had returned to work. Younger patients admitted to the hospital for elective surgery reported as much compromise of physical and psychological activity as did older patients admitted for emergency reasons. Older survivors reported an increase of interaction with family members and a decrease of social interaction with those other than family.
This paper presents formulae for determining the number of subjects necessary, in either a case-control or a cohort study, to estimate the odds ratio or relative risk, respectively, to within a selected percentage (epsilon) of the true population value with some specified probability. This approach differs somewhat from previous comparable work that estimated the log odds ratio within a stated fixed distance rather than as a percentage of the actual odds ratio. Comparable development for relative risk has not previously appeared in the literature. These formulae provide guidelines for determination of study size that does not depend on hypothesis testing considerations.
Estimating prognosis is potentially useful as a measure of ICU performance and as a guide for the clinical care of individual patients. In this study, mortality prediction models (MPMs) for patients in an adult general medical-surgical ICU were derived from data gathered at ICU admission and after 24 and 48 h of ICU care. A predictive model was developed which incorporated a sequence of probabilities collected over time in the ICU. The results of this study suggest that using serial observations may enhance substantially the usefulness of the MPM as a vehicle for helping families anticipate the patients' likely outcome.
We investigated prospectively clinical bleeding in 1,328 consecutive patients admitted to a medical/surgical ICU over 1 yr. One hundred thirty-eight (10.4%) patients bled after ICU admission, and an additional 388 (29.2%) bled coincident with admission. The upper GI tract was the site of bleeding in 34.8% of patients whose bleeds commenced in the ICU, and accounted for 22% of total sites. Patients with clinical bleeding after ICU admission had a significantly (p less than .001) higher likelihood of death than those who did not bleed, and those with multiple bleeding sites had a higher mortality (54.9%) than those with single sites (31%) (p less than .006). Multiple logistic regression analyses revealed that risk ratios (RR) for bleeding after ICU admission were mechanical ventilation (RR = 1.82), nutritional failure (RR = 3.45), acute renal failure (RR = 3.36), antiulcer medication (RR = 3.36), and anticoagulants (RR = 4.19). No antibiotics could be specifically incriminated. This study defines the scope, characteristics, and importance of bleeding in ICU patients and establishes risk factors.
The ideal temperature and hematocrit level of blood cardioplegia has not been clearly established. This study was undertaken (a) to determine the optimal temperature of blood cardioplegia and (b) to study the effect of hematocrit levels in blood cardioplegia. A comparison of myocardial preservation was done among seven groups of animals on the basis of variations in hematocrit levels and temperature of oxygenated cardioplegic solution. The experimental protocol consisted of a 2-hour hypothermic cardioplegic arrest followed by 1 hour of normothermic reperfusion. Group 1 received oxygenated crystalloid cardioplegic solution at 10 degrees C. Groups 2 through 7 received oxygenated blood cardioplegic solution with the following hematocrit values and temperatures: (2) 10%, 10 degrees C; (3) 10%, 20 degrees C; (4) 10%, 30 degrees C; (5) 20%, 10 degrees C; (6) 20%, 20 degrees C; and (7) 20%, 30 degrees C. Parameters studied include coronary blood flow, myocardial oxygen extraction, myocardial oxygen consumption, and myocardial high-energy phosphate levels of adenosine triphosphate and creatine phosphate during control (prearrest), arrest, and reperfusion. Myocardial oxygen consumption at 30 degrees C during arrest was significantly higher than at 10 degrees C and 20 degrees C, which indicates continued aerobic metabolic activity at higher temperature. Myocardial oxygen consumption and the levels of adenosine triphosphate and creatine phosphate during reperfusion were similar in all seven groups. Myocardial oxygen extraction (a measure of metabolic function after ischemia) during initial reperfusion was significantly lower in the 30 degrees C blood group than in the 10 degrees C blood group at either hematocrit level and in the oxygenated crystalloid group, which suggests inferior preservation. The hematocrit level of blood cardioplegia did not affect adenosine triphosphate or myocardial oxygen consumption or extraction. It appears from this study that blood cardioplegia at 10 degrees C and oxygenated crystalloid cardioplegia at 10 degrees C are equally effective. Elevating blood cardioplegia temperature to 30 degrees C, however, reduces the ability of the solution to preserve metabolic function regardless of hematocrit level. Therefore, the level of hypothermia is important in blood cardioplegia, whereas hematocrit level has no detectable impact, and cold oxygenated crystalloid cardioplegia is as effective as hypothermic blood cardioplegia.
We tested recently developed admission and 24-h models of hospital mortality on 1,997 consecutive admissions to a general medical/surgical ICU. This study population was independent of the group used to develop the models. The admission prediction model estimated each patient's probability of hospital mortality based on seven routinely collected admission variables. The 24-h model utilized seven variables routinely available at 24 h in the ICU. The admission model accurately described the mortality experience of the new cohort, while the 24-h model did not. Advantages of the admission model are that it is evaluable at the time of ICU admission, is independent of ICU treatment, and can be used to stratify patients by severity of illness, thereby making ICU comparisons possible. Its excellent goodness-of-fit, correct classification rate, sensitivity, and specificity suggest that this model is now ready for multihospital testing.
This paper presents results of the first study explicitly designed to compare three methods for predicting hospital mortality of ICU patients: the Acute Physiology Score (APS), the Simplified Acute Physiology Score (SAPS), and the Mortality Prediction Model (MPM). With respect to sensitivity, specificity, and total correct classification rates, these methods performed comparably on a cohort of 1,997 consecutive ICU admissions. In these patients from a single hospital, the APS overestimated and the SAPS underestimated the probability of hospital mortality. The MPM probabilities most closely matched the observed outcomes. Each method holds considerable promise for assessing the severity of illness of critically ill patients. The MPM should be particularly useful for comparing ICU performance, since it is independent of ICU treatment and can be calculated at the time a patient is admitted.