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Improving intensive care unit discharge decisions: supplementing physician judgment with predictions of next day risk for life support.

OBJECTIVE: To develop predictive equations, estimating the probability that an individual intensive care unit (ICU) patient will receive life support within the next 24 hrs. DESIGN: Prospective, multicenter, inception cohort study. SETTING: Forty-two ICUs in 40 U.S. hospitals, including 26 that were randomly selected and 14 volunteer hospitals, primarily university or large tertiary care centers. PATIENTS: A consecutive sample of 17,440 ICU admissions. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A series of multivariate equations were developed to create daily estimates of probability of life support in the next 24 hrs. These equations used demographic, physiologic, and treatment information obtained at the time of ICU admission and during the first 7 ICU days. The most important determinants of next day risk for life support were the current day's therapy and Acute Physiology Score of the Acute Physiology and Chronic Health Evaluation (APACHE) III score. Other predictor variables included diagnosis, age, chronic health status, emergency surgery, previous day Acute Physiology Score, and hospital stay and location before ICU admission. The cross-validated ICU day 1, 2, and 3 predictive equations had receiver operating characteristic areas of 0.90. Survival, ICU readmission rate, and the number and type of therapies received by patients predicted at < 10% risk for active treatment suggest that discharge of patients meeting these criteria to an intermediate care unit or hospital ward could reduce ICU bed demand without compromising patient safety. CONCLUSIONS: Accurate, objective predictions of next day risk for life support can be developed, using readily available patient information. Supplementing physician judgment with these objective risk assessments deserves evaluation for the role of these assessments in enhancing patient safety and improving ICU resource utilization.

Adolescent↗

Interferon-alpha for chronic hepatitis C: an analysis of pretreatment clinical predictors of response.

To identify predictors of short-term and sustained ALT normalization after interferon treatment in adult patients with chronic hepatitis C, we performed a meta-analysis of individual patients' data, with construction and cross-validation of a prediction rule, in 361 patients from two randomized trials. In one trial, 116 subjects with transfusion-related chronic hepatitis C were treated with lymphoblastoid interferon (5 MU/m2 three times a week for 2 mo, then 3 MU/m2 three times a week for 4 or 10 mo). In the other study, 245 patients with community-acquired chronic hepatitis C received recombinant interferon-alpha 2b (10 MU three times a week for 2 mo, then 5 MU three times a week for 4 mo; then random allocation of subjects with normal aminotransferase levels to stop or continue interferon for a further 6 mo). Overall, 164 subjects (45%; 95% confidence interval, 40% to 50%) had short-term responses; 61 (18%; 95% confidence interval, 14% to 22%) maintained sustained responses. Sixty patients (17%; 95% confidence interval, 13% to 21%) withdrew from treatment because of side effects or subjective intolerance. Logistic regression analysis showed that short-term and sustained response were independently predicted by lobular structure on pretreatment liver biopsy (p < 0.0001) and by short disease duration, defined as the time elapsed since transfusion in posttransfusion cases or since the first observation of abnormal aminotransferase levels in cryptogenic disease (p < 0.01). Rules to predict short-term and sustained response to interferon were derived from these items, showing a discriminatory ability of 0.73 and 0.70.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗

A neural network classifier for cerebral perfusion imaging.

UNLABELLED: Artificial neural networks have been applied to a variety of pattern recognition tasks in medical imaging and have been shown to be a powerful classification tool. The potential usefulness to discriminate normal from abnormal cerebral perfusion patterns was investigated. METHODS: Cerebral perfusion imaging with 99mTc-labeled hexamethylpropyleneimine oxime was performed on 52 normal control subjects, 29 patients with clinically diagnosed Alzheimer's disease (AD) and 25 patients with chronic cocaine polydrug abuse. Each study was registered and scaled to a common anatomic coordinate system, yielding 120 standardized cortical regions. A back-propagation neural network classifier based on regional perfusion was used to classify normal and abnormal perfusion patterns. The neural network was trained to discriminate patients with AD from age-matched normal controls and cocaine polydrug abuse patients from normal controls. The performance of the neural network in these two tasks was evaluated quantitatively by receiver operating characteristic (ROC) analysis using cross-validation. RESULTS: For patients with AD, the area under the ROC curve was 0.93 +/- 0.04. When testing with the cocaine polydrug abuser data, the area under the ROC curve was 0.89 +/- 0.04. CONCLUSION: Neural networks provide a potentially useful tool in the decision-making task to discriminate patients with AD and cocaine abuse from normal controls.

Adult↗

The Social Physique Anxiety Scale: construct validity in adolescent females.

Hart, Leary, and Rejeski have developed the Social Physique Anxiety Scale (SPA), a measure of the anxiety experienced in response to having one's physique evaluated by other people. The present study cross-validated the psychometric properties of this measure in a sample (N = 236) of adolescent competitive female gymnasts. Employing structural equation modeling, the proposed unidimensional factor structure of the SPA was supported, although some questions regarding the robustness of the fit are raised. Construct validity was demonstrated by significant inverse relationships between aspects of physical efficacy (perceived physical ability and physical self-presentation confidence) and degree of social physique anxiety. These findings are discussed in terms of possible alternative factor structures and integration of social anxiety and other psychosocial constructs to better understand physical activity behavior.

Adolescent↗

Predicting behavior of an enzyme-linked immunoassay model by using commercially available neural network software.

Setting up new immunoassays can be a laborious and expensive task. A relatively new form of multivariate analysis known as neural networks can be applied to this problem with potential savings in reagents and technician time. Neural network software programs for personal computers are now available. We applied one such software package (Brainmaker) to a model ELISA system for measuring human serum albumin. Random combinations of four variable ELISA conditions (antigen concentration, primary and secondary antibody titers, and time for chromagen development) were used to train a three-layered feed-forward network. The trained network was then used to predict measured absorbances as a function of the four input variables in separate cross-validation sets. The network adequately predicted the effect of the input variables on the absorbance produced. With use of such methods, optimal conditions for the linear dependence of absorbance on antigen concentration can be evaluated on the computer rather than in the laboratory, with subsequent savings of time and money.

Antibodies↗

Schooling, occupational motivation, and personality as related to success in paramedical training.

Measures of prior school experience, motivation for working in a health care job, and personality were evaluated as potential predictors of success in Navy paramedical training. When, by multiple regression procedures, years of school completed, numbers of suspensions or expulsions from school, occupational motivation, and Comrey personality scale scores were combined with an aptitude measure that is used for guiding recruits into paramedical training, the cross-validity for predicting training completion was significantly increased (P less than 0.001) from 0.40 to 0.50. Practical means for applying these measures to the screening of candidates for paramedical training were developed. Results of the evaluation suggest that guiding people into jobs that they neither prefer nor perceive as congruent with their abilities and interests can significantly reduce the chances for occupational success.

Achievement↗

Neural-network classification of normal and Alzheimer's disease subjects using high-resolution and low-resolution PET cameras.

UNLABELLED: Neural-network classification methods were applied to studies of FDG-PET images of the brain acquired from a total of 77 "probable" Alzheimer's disease and 124 normal subjects at two different centers. METHODS: Classification performances, as determined by relative-operating-characteristic (ROC) analyses of cross-validation experiments, were measured for FDG PET images obtained with either a 15-mm FWHM PETT V or a 6-mm FWHM Scanditronix PC-1024-7B camera for various methods of data representation. Neural networks were trained to distinguish between normal and abnormal subjects on the basis of regional metabolic patterns. For both databases, classification performance could be improved by increasing the "resolution" of the representation (decreasing the region size) and by normalizing the regional metabolic values to the value of a reference region (occipital region). RESULTS: The optimal classification performance for Scanditronix data (ROC area = 0.95) was higher than that for PETT V data (ROC area = 0.87). Under Bayesian theory, the classification performance with Scanditronix data corresponded to an ability to change a pre-test probability of disease of 50% to a post-test probability of either 90% for a positive classification or 10% for a negative classification. CONCLUSION: This classification can be used to either strongly confirm or rule out the presence of abnormalities.

Aged↗

Prognosis of rehabilitation outcome in head injury using the Disability Rating Scale.

In this correlational study, we investigated the prediction of functional status on discharge from head injury rehabilitation in 64 adults with traumatic closed head injury. Subjects were rated on Rappaport's Disability Rating Scale during rehabilitation to obtain the Disability Rating Score on admission to rehabilitation, recovery rate during the first month of rehabilitation, and discharge Disability Rating Score. Potential prognostic variables included demographic and social characteristics, severity of injury indicators, head injury deficits present on admission to rehabilitation, and initial Disability Rating Score, and recovery rate. Multiple regression analyses were performed to determine if discharge Disability Rating Score could be predicted from subsets of the potential prognostic variables. Significant contributions were made to the regression equations by initial Disability Rating Score, recovery rate, post-traumatic amnesia and cognitive deficits. A single multiple regression containing the four significant predictors retained initial Disability Rating Score and recovery rate as significant. The findings were cross-validated on a new sample of 30 head injury patients. Initial Disability Rating Score on admission to rehabilitation emerged as a useful predictor of rehabilitation outcome.

Adolescent↗

Evaluation of laboratory data by conventional statistics and by three types of neural networks.

Sixty-three patients with lung (34 small-cell, 18 squamous, 11 adeno-) carcinomas and 43 patients with benign lung diseases were characterized with seven tumor markers: neuron-specific enolase (NSE); cancer antigens CA 19-9, CA 125, CA 15-3, and CA 50; carcinoembryonic antigen (CEA); and tissue polypeptide antigen. Diagnosis had been established by histological examination after surgery and used for classification. After vector transformation, the tumor marker data were fed into neural networks (NNs) based on three different types of learning algorithms: backpropagation (BP), competitive learning (CL), and Hopfield (H). For comparison, the data were evaluated with multivariate stepwise discriminant analysis (MVSDA). BP-NNs are equal to (NSE, CA 19-9, CEA) or better than (100% correct classification when using all seven markers) MVSDA in assigning the correct diagnosis to the patients. Cross-validation data yielded shrinkage effects ranging from 0% to 12.5%. Quality-control (QC) data were evaluated by traditional QC algorithms and compared with the results obtained by a BP-NN. The results show that the BP-NNs could only partly fulfill the tasks of three QC algorithms regarding the violation of static borders but gave good results with respect to dynamic changes.

Biomarkers, Tumor↗

Factors which discriminate rural and urban family physicians practicing in South Carolina.

A sample of 28 rural and urban private practicing family physicians was compared on a number of attitudes and practice characteristics based on results from a mailed questionnaire. Results cross-validated previous findings and provided new ones. A number of self-report discriminators are discussed to better predict which physicians will locate in rural areas.

Adult↗

Radioimmunological analysis of ethinylestradiol in human serum. Validation of the method and comparison with a gas chromatographic/mass spectrometric assay.

The majority of combination oral contraceptives contain ethinylestradiol (EE2, CAS 57-63-6) as estrogenic component at doses between 50 and 20 micrograms/unit. Since the concentrations of EE2 in the serum of women under oral contraceptive (OC) therapy are in the lower pg-range, highly sensitive and specific analytical methods are required. Radioimmunoassay (RIA) has been the method of choice, but evidence of specificity in the presence of the coadministered progestogens and their metabolites has not always been provided. The present study compares two radioimmunological methods, which use the same antiserum but different sample volumes and standard curves (extracted vs. non-extracted), with a newly developed gas chromatographic/mass spectrometric (GC/MS) method, in order to cross-validate the methods. For that purpose, 51 serum samples obtained from women who had been taking two different combination oral contraceptives were analysed independently by all three methods. The specificity of the antiserum was further examined by submitting ex vivo serum samples obtained from OC-users to a combination of high pressure liquid chromatography (HPLC) and RIA. The results obtained by the three methods were very similar and correlation coefficients (r) obtained from linear regression analysis were about 0.7. There was no interference from the coadministered progestins on the analysis of EE2 as carried out by the three methods. There were no metabolites in the extracts of ex vivo serum samples which showed cross-reactivity with the antiserum used. Modifications of the radioimmunoassay procedure did not markedly affect the results of EE2 determination. If properly validated, radioimmunoassay can be used as an alternative to GC/MS in pharmacokinetic studies.

Chromatography, High Pressure Liquid↗

Effect of stepping rate on energy costs during StairMaster exercise.

The responses to a self-selected stepping pattern (random) on a StairMaster 4000PT were compared with those obtained in response to the rates established by the manufacturer (cadence) in men (N = 14) and women (N = 14). During the random test the subjects stepped at their own natural, self-selected rate and distance. In cadence trial the subjects were required to step in time with a metronome at a predetermined rates of 60, 77, 95, and 112 steps.min-1. Each trial consisted of four, 5-min continuous workloads during which HRs were recorded and expired air was analyzed using an automated open-circuit gas system each minute. All size dependent variables (i.e., VE and lO2.min-1) as well as relative VO2 (mlO2.kg-1.min-1) were significantly (P < 0.01) higher for the men across all stages and between methods. Although the random test produced slightly higher oxygen consumption values than the cadence trial, these differences were not significant (P > 0.05). The actual METs were significantly (P < 0.01) higher at all stages except at the lowest stepping rate for both methods compared with those estimated by the manufacturer. Equations were established to estimate actual MET costs: Men's METs = 2.675 + 0.935 (rate); women's METs = 2.934 + 0.817 (rate). Cross-validations of 0.975 and 0.957 were obtained on an additional group of men (N = 8) and women (N = 11), respectively.

Adult↗

VO2max estimation from a submaximal 1-mile track jog for fit college-age individuals.

The primary purpose of this study was to develop a submaximal field test for the estimation of maximal oxygen uptake (VO2max) using a 1-mile track jog. A second purpose was to determine the accuracy of the 1.5-mile run in estimating VO2max for both male and female subjects. VO2max was measured in 149 relatively fit college students (males = 88, females = 61) 18-29 yr using a treadmill protocol (mean +/- SD; VO2max = 47.7 +/- 6.3 ml.kg-1 x min-1). Multiple regression analysis (N = 54) to estimate VO2max from the submaximal, steady-state 1-mile track jog yielded the following validation (V) model (r(adi) = 0.87, SEE = 3.0 ml.kg-1 x min-1): VO2max = 100.5 + 8.344* GENDER (0 = female; 1 = male) - 0.1636* BODY MASS (kg) - 1.438* JOG TIME (min.mile-1) - 0.1928* HEART RATE (bpm). To help ensure that a submaximal level of exertion was realized for the 1-mile track jog, elapsed jog time was restricted to > or = 8.0 min for males and > or = 9.0 min for females and exercise HR to < or = 180 bpm. Cross-validation (CV) of the 1-mile track jog comparing observed and estimated VO2max (N = 52) resulted in radj = 0.84, SEE = 3.1 ml.kg-1 x min-1. Multiple regression analysis (N = 50) to estimate VO2max from the 1.5-mile run (V:N = 49, radj = 0.90, SEE = 2.8 ml.kg-1 x min-1; CV: N = 47, radj = 0.82, SEE = 3.9 ml.kg-1 x min-1), used elapsed run time, body mass, and gender as independent variables.(ABSTRACT TRUNCATED AT 250 WORDS)

Adolescent↗

Development of a submaximal treadmill jogging test for fit college-aged individuals.

The purpose of this study was to develop a single-stage submaximal treadmill jogging test for the estimation of maximal oxygen uptake (VO2max). VO2max was measured in 129 relatively fit individuals (males = 84, females = 45), 18-29 yr, using a maximal treadmill protocol (mean +/- SD; VO2max = 48.3 +/- 6.2 ml.kg-1 x min-1, range = 35.6 to 62.3 ml.kg-1 x min-1). The treadmill test required subjects to sustain a comfortable, submaximal jogging pace (4.3-7.5 mph; level grade) until a steady-state heart rate was achieved (approximately 3 min). To help ensure that a submaximal level of exertion was realized for the treadmill jogging test, treadmill speed and exercise HR criteria were established that restricted treadmill speed to < or = 7.5 mph for males and < or = 6.5 mph for females and steady-state exercise HR < or = 180 bpm. Multiple regression analysis (N = 66) to estimate VO2max from the treadmill jogging test yielded the following validation (V) model (r(adj) = 0.84, SEE = 3.2 ml.kg-1 x min-1): VO2max = 54.07 + 7.062 * GENDER (0 = female; 1 = male) - 0.1938 * WEIGHT (kg) + 4.47* SPEED (miles.h-1) - 0.1453 * HEART RATE (bpm). Cross-validation (CV) of the treadmill jogging test comparing observed and estimated VO2max (N = 63) resulted in r(adj) = 0.88, SEE = 3.1 ml.kg-1 x min-1. The results indicate that this submaximal single-stage treadmill jogging test based on multiple linear regression provides a valid and convenient method for estimating VO2max.

Adolescent↗

Predictive accuracy of bioimpedance equations in estimating fat-free mass of Hispanic women.

This study assessed the predictive accuracy of previously published bioelectrical impedance analysis equations for estimating fat-free mass of young (20-39 yr) Hispanic women (N = 29). The reference method was hydrostatic weighing at residual lung volume. Body density was converted to percent body fat using the Siri equation. Resistance and reactance were measured with a Valhalla bioimpedance analyzer. The bioelectrical impedance analysis equations of Lohman, Rising, Stolarczyk, Segal, Gray, and Van Loan were cross-validated. There were significant correlations between criterion and predicted fat-free mass (r = 0.86-0.95) for all equations. The standard error of estimate for each equation was acceptable; however, the total error for the Stolarczyk (3.2 kg) and the Van Loan (4.6 kg) equations exceeded the recommended value (2.8 kg). For all equations, the difference between average criterion and predicted fat-free mass was significant (P < 0.05). However, the mean differences for the Lohman (0.8 kg), Segal (0.8 kg), and Gray (0.9 kg) equations were small. In conclusion, the Segal, Lohman, and Gray equations may have potential for assessing the body composition of healthy, acculturated, Hispanic women.

Acculturation↗

Validity of skinfold equations for estimating body density in youth wrestlers.

The present investigation examined the validity of 16 skinfold equations for predicting body density (BD) in youth wrestlers (mean age +/- SD = 11.0 +/- 1.3 yr) by comparing the values to those obtained from underwater weighing. Forty-eight members of youth wrestling clubs (mean BD +/- SD = 1.0634 +/- 0.0125 g.cm-3) volunteered to serve as subjects. The statistical analyses included examination of the constant error (CE), standard error of estimate (SEE), correlation coefficient (r), and total error (TE). The results of this investigation indicated that all of the equations resulted in TE values that were > or = 0.0106 g.cm-3 (range = 0.0106-0.0229 g.cm-3) which corresponded to > or = 4.9% body fat. The TE values were too large to provide accurate estimates of body composition in the present sample of youth wrestlers. Future studies should use the CE values from the present investigation to adjust the intercepts of the skinfold equations in the present study and cross-validate the modified equations on young male athletes.

Body Composition↗

[Body density assessment utilizing skinfold thickness and age in Japanese men].

A study was conducted to investigate the validity of skinfold-based prediction equations for body density (g/ml) by Nagamine and Suzuki (1964), and to formulate more convenient and more useful equations for predicting body density from skinfold and age in men. Subjects of the study were 257 healthy men aged 19-60 years in or near Nagasaki City. The regression equation for the dependent variable, body density, was determined by hydrostatic weighing. Independent variables included eight skinfolds, the sum of two skinfolds (triceps, subscapular), the sum of three skinfolds (triceps, subscapular, and abdominal), age, and body surface area. Skinfolds were measured with an Eiken-model skinfold caliper. Age (mean 33.1, range 19-60 yrs.), weight (mean 65.3, range 46.6-107.7 kg), height (mean 168.8, range 152.3-185.4 cm), and body density (mean 1.05874, range 1.00860-1.09020 g/ml) were also recorded. Percent body fat was calculated using the formula by Brozek et al. and ranged from 6.1% to 38.9%. Multiple correlation coefficients (MR) and standard error (SE) of 10 regression equations (A-J) for predicting body density in men were obtained. The best-fitting and the most convenient prediction equation for body density was equation-E.: body density = 1.09556-0.00062 x sum of three skinfolds (mm)-0.00028 x age (MR = 0.815 and SE = 0.0087 g/ml). The equation was cross-validated on a different sample of 45 men. The correlation coefficient between predicted and hydrostatically determined body density was 0.781 (p < 0.001). Equation-E (Tahara's equation) appears to be useful in body density analysis particularly when the subjects are Japanese men, aged 18-50 yrs, with percent body fat 10 to 30%.

Adult↗

Interaction between consumers and providers of health services: new roles and their implications.

In the last few years, there has been an active effort in Italy to involve the population in solving health problems at the community level. This movement had its origin in the industrial setting, where workers succeeded in promoting legislation which gives them control over matters affecting their health. This experience lead to the development of a health education methodology based on the following principles: (a) the assessment of health needs must be based on the subjective experience of the people who have acquired knowledge and interest in health problems; (b) the evaluation of health needs by professionals serves to complement and integrate the assessment of needs as experienced by the community; (c) the self-diagnosis of the community -- in particular of homogenous community groups exposed to similar health risks and experiencing the same needs--and the diagnosis of the professionals must undergo cross-validation and be accepted by both parties; (d) on the basis of this mutual agreement, community health programmes should be planned and carried out jointly by the professionals and the people.

Community Participation↗