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G Samsa

Publications and source records attributed to G Samsa.

24 records · Page 2Linked to original sources
PubMed1988

Schwann cell vulnerability to demyelination is associated with internodal length in tellurium neuropathy.

The frequency of demyelinated fibers in mixed nerve and cutaneous nerve and the relationship of the frequency of demyelination to internodal length were assessed in a model of tellurium neuropathy in the rat. Twenty-day-old Long-Evans rats were fed chow containing 1.25% elemental tellurium for seven days and subsequently killed at 34 or 41 days of age. Teased-fiber preparations revealed a higher frequency of demyelinated fibers in sciatic nerve (mixed nerve) than in sural nerve (cutaneous nerve). The frequency of demyelinated fibers was positively associated with internodal length in both nerves. The type of nerve (mixed or cutaneous) was not a significant predictor of the frequency of demyelinated fibers once internodal length had been taken into account. These data indicate that there is a hierarchy of vulnerability within the population of myelinating Schwann cells to tellurium toxicity, and that this hierarchy is related to internodal length. The hierarchy of vulnerability may reflect intrinsic differences among Schwann cells, such as the volume of myelin each cell is synthesizing and maintaining, or a gradient of unrecognized axonal abnormalities.

Animals↗
PubMedDate not supplied

Predicting the outcomes of electrophysiologic studies of patients with unexplained syncope: preliminary validation of a derived model.

PURPOSE: To develop and validate a predictive model that would allow clinicians to determine whether an electrophysiologic (EP) study is likely to result in useful diagnostic information for a patient who has unexplained syncope. PATIENTS: One hundred seventy-nine consecutive patients with unexplained syncope who underwent EP studies at two university medical centers comprised the training sample. A test sample to validate the model was made up of 138 patients from the clinical literature who had undergone EP studies for syncope. DESIGN: Retrospective analysis of patients undergoing EP studies for syncope. The data collector was blinded to the study hypothesis; the electrophysiologist assessing outcomes was blinded to clinical and historical data. Clinical predictor variables available from the history, the physical examination, electrocardiography (ECG), and Holter monitoring were analyzed via two multivariable predictive modeling strategies (ordinal logistic regression and recursive partitioning) for their abilities to predict the results of EP studies, namely tachyarrhythmic and bradyarrhythmic outcomes. These categories were further divided into full arrhythmia and borderline arrhythmia groups. RESULTS: Important outcomes were 1) sustained monomorphic ventricular tachycardia (VT) and 2) bradyarrhythmias, including sinus node and atrioventricular (AV) conducting disease. The results of the logistic regression (in this study, the superior strategy) showed that the presence of organic heart disease [odds ratio (OR) = 3.0, p less than 0.001] and frequent premature ventricular contractions on ECG (OR = 6.7, p less than 0.004) were associated with VT, while the following abnormal ECG findings were associated with bradyarrhythmias: first-degree heart block (OR = 7.9, p less than 0.001), bundle-branch block (OR = 3.0, p less than 0.02), and sinus bradycardia (OR = 3.5, p less than 0.03). Eighty-seven percent of the 31 patients with important outcomes at EP study had at least one of these clinical risk factors, while 95% of the patients with none of these risk factors had normal or nondiagnostic EP studies. In the validation sample, the presence of one or more risk factors would have correctly identified 88% of the test VT patients and 65% of the test bradyarrhythmia patients as needing EP study. CONCLUSION: These five identified predictive factors, available from the history, the physical examination, and the initial ECG, could be useful to clinicians in selecting those patients with unexplained syncope who will have a serious arrhythmia identified by EP studies.

Arrhythmias, Cardiac↗
PubMedDate not supplied

General performance on a numeracy scale among highly educated samples.

BACKGROUND: Numeracy, how facile people are with basic probability and mathematical concepts, is associated with how people perceive health risks. Performance on simple numeracy problems has been poor among populations with little as well as more formal education. Here, we examine how highly educated participants performed on a general and an expanded numeracy scale. The latter was designed within the context of health risks. METHOD: A total of 463 men and women aged 40 and older completed a 3-item general and an expanded 7-item numeracy scale. The expanded scale assessed how well people 1) differentiate and perform simple mathematical operations on risk magnitudes using percentages and proportions, 2) convert percentages to proportions, 3) convert proportions to percentages, and 4) convert probabilities to proportions. RESULTS: On average, 18% and 32% of participants correctly answered all of the general and expanded numeracy scale items, respectively. Approximately 16% to 20% incorrectly answered the most straightforward questions pertaining to risk magnitudes (e.g., Which represents the larger risk: 1%, 5%, or 10%?). A factor analysis revealed that the general and expanded risk numeracy items tapped the construct of global numeracy. CONCLUSIONS: These results suggest that even highly educated participants have difficulty with relatively simple numeracy questions, thus replicating in part earlier studies. The implication is that usual strategies for communicating numerical risk may be flawed. Methods and consequences of communicating health risk information tailored to a person's level of numeracy should be explored further.

Adult↗
PubMedDate not supplied

Global judgments versus decision-model-facilitated judgments: are experts internally consistent?

A widely used method for evaluating the appropriateness of medical procedures and practices is the "modified Delphi" approach using expert panelists' global ratings. However, several difficulties in the assignment of global ratings have led to a search for alternative methods, including the use of decision models. To examine the potential impact of using decision models with an expert panel, the authors compared a panel's global ratings for the appropriateness of carotid endarterectomy with the results of a decision-analytic model in which expert panelists estimated probabilities and utilities that were used as inputs for the model. For 17 different patient scenarios, the nine expert panelists showed variability in "calibration" between the two methods, with their expected utilities calculated from the model generally being higher than their global ratings. However, the correlation between the two methods was excellent. When the panel's median global utility was compared with the panel's median expected utility calculated from the model, the Spearman correlation coefficient was 0.88. This study demonstrated that an expert panel's appropriateness ratings and their expected utilities were highly correlated. In addition, the panelists appeared to be internally consistent in that their judgments about individual probabilities and utilities were correlated with their global judgments. These results should encourage additional efforts to incorporate decision models into the process of clinical guideline development. The authors believe that decision models can help improve a panel's capacity to understand and reconcile discordance, and increase their satisfaction that the process reflects the best possible judgments.

Carotid Stenosis↗
PubMedDate not supplied

Predicting the cost of illness: a comparison of alternative models applied to stroke.

Predictions of cost over well-defined time horizons are frequently required in the analysis of clinical trials and social experiments, for decision models investigating the cost-effectiveness of interventions, and for macro-level estimates of the resource impact of disease. With rare exceptions, cost predictions used in such applications continue to take the form of deterministic point estimates. However, the growing availability of large administrative and clinical data sets offers new opportunities for a more general approach to disease cost forecasting: the estimation of multivariable cost functions that yield predictions at the individual level, conditional on intervention(s), patient characteristics, and other factors. This raises the fundamental question of how to choose the "best" cost model for a given application. The central purpose of this paper is to demonstrate how to evaluate competing models on the basis of predictive validity. This concept is operationalized according to three alternative criteria: 1) root mean square error (RMSE), for evaluating predicted mean cost; 2) mean absolute error (MAE), for evaluating predicted median cost; and 3) a logarithmic scoring rule (log score), an information-theoretic index for evaluating the entire predictive distribution of cost. To illustrate these concepts, the authors conducted a split-sample analysis of data from a national sample of Medicare-covered patients hospitalized for ischemic stroke in 1991 and followed to the end of 1993. Using test and training samples of about 500,000 observations each, they investigated five models: single-equation linear models, with and without log transform of cost; two-part (mixture) models, with and without log transform, to directly address the problem of zero-cost observations; and a Cox proportional-hazards model stratified by time interval. For deriving the predictive distribution of cost, the log transformed two-part and proportional-hazards models are superior. For deriving the predicted mean or median cost, these two models and the commonly used log-transformed linear model all perform about the same. The untransformed models are dominated in every instance. The approaches to model selection illustrated here can be applied across a wide range of settings.

Cerebrovascular Disorders↗