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PubMedDate not supplied

Validation of a predictive model for automated external defibrillator placement in rural America.

OBJECTIVE: The development of Automated External Defibrillators (AEDs) to treat out-of-hospital cardiac arrest (OOHCA) has greatly expanded the availability of life saving defibrillatory shocks in various settings. However, placement of AEDs in rural areas remains perplexing since OOHCAs are rare and unpredictable. We set out to develop a cost-effective rural AED placement model and to test the validity of the resulting model using OOHCAs attended by EMS. METHODS DESIGN: A population-based cross-sectional study. Analytic Plan: An exhaustive literature search was conducted to identify community attributes correlated with successful placement of AEDs in rural regions. Identified attributes were characterized using U.S. Census and CDC heart disease mortality data to estimate the potential risk for AED use and applied this estimate to rural census tracts in all 50 states. Based upon risk, AEDS were assigned to each tract using a first responder model and cost effectiveness was assessed. Using Utah State EMS data, the predicted placement of AEDs in each tract was validated using the actual number of OOHCAs attended by EMS. RESULTS: A total of 14,586 rural census tracts in 50 U.S. states were evaluated. On average, 2,600 AEDs were situated within each state. AED placement in rural areas proved as cost effective as health screening programs. In Utah, predicted AED placement correlated with the frequency of OOHCAs attended by EMS personnel (rho= 0.55, p < 0.001). CONCLUSIONS: The resulting model illustrates one potential way to determine the most beneficial location for rural AED placement.

Adult↗
PubMed2003

[Predictive model for prostate cancer in patients with biopsy indication].

OBJECTIVE: Attemp to determine the probability of developing prostate carcinoma taking into acc age, digital rectal examination and PSA once a transrectal biopsy has been indicated, so that both doctors and patients have mor information to face such pathology. MATERIAL AND METHODS: Retrospective study of 633 biopsies, taken into acc the patient's age, digital rectal examination, PSA level and histology. The data were included in a database created with Access and were put a logistic regression by mens the software program SPSS. RESULTS: Once the biopsy is indicated, digital rectal examination is the parameter offesing a higher discriminatory valuer with an odd ratio of 5.9 (CI 95%, 3.9-8.9). The mathematical model obtained shows a sensitivity level of 57% and a level of specificity of 84%. Pre-test probability is 36%, the probability post-test increasing up to 70%, and a negative predictive value of 77% and a positive predictive value of 67%. CONCLUSIONS: The mathematical model obtained individually determines the probability of suffering from prostatic carcinoma. Moreover, using this model the probabilities obtained re more precise than those derived from the fact of fulfilling the criteria for a prostatic biopsy. Once a biopsy is indicated, the rectal examination becomes the parameter with a higher predictive value of PC, irrespective of PSA and age. The PPV of the model is higher than of the PSA or the digital recta examination used separately.

Adenocarcinoma↗
PubMed2002

Insulin release in impaired glucose tolerance: oral minimal model predicts normal sensitivity to glucose but defective response times.

The availability of quantitative indexes describing beta-cell function in normal life conditions is important for the characterization of impaired mechanisms of insulin secretion in pathophysiological states. Recently, an oral C-peptide minimal model has been proposed and applied to subjects with normal glucose tolerance (NGT) during graded up-and-down glucose infusion protocols (40-min periods at 4, 8, 16, 8, 4, and 0 mg.kg(-1).min(-1)) and oral glucose tolerance tests. These tests are characterized by slow glucose and C-peptide dynamics, which reproduce prandial conditions. In view of the importance of beta-cell dysfunction in the pathogenesis of type 2 diabetes, our aim was to test and use the oral minimal model in subjects with impaired glucose tolerance (IGT) to identify deranged mechanisms of beta-cell function. Plasma C-peptide and glucose data from graded up-and-down glucose infusions were analyzed in nine NGT and four IGT subjects using the classic deconvolution approach and the oral minimal model, and indexes of beta-cell function were derived. An index of insulin sensitivity was also obtained for each subject from minimal model analysis of glucose and insulin levels achieved during the test. Both deconvolution and minimal model analyses revealed that individuals with IGT have a relative defect in the ability to secrete enough insulin to adequately compensate for insulin resistance. Additionally, minimal model analysis suggests that insulin secretory defect in IGT arises from delays in the timing of the beta-cell response to glucose.

Adult↗
PubMed2026

How negative sampling shapes the performance of transcription factor binding site prediction models.

MOTIVATION: Transcription factors (TFs) are key players in gene regulation and development, where they activate and repress gene expression through DNA binding. Predicting transcription factor binding sites (TFBSs) has long been an active area of research, with many deep learning methods developed to tackle this problem. These models are often trained on TF ChIP-seq data, which is generally seen as only providing positive samples. The choice of datasets and negative sampling techniques is a critical yet often overlooked aspect of this work. RESULTS: In this study, we investigate the impact of different negative sampling techniques on TFBS prediction performance. We create high-quality test datasets based on ChIP-seq and ATAC-seq data, where true negatives can be identified as positions that are accessible but not bound by the TF in question. We then train models using various negative sampling techniques, including genomic sampling, shuffling, dinucleotide shuffling, neighborhood sampling, and cell line specific sampling, simulating cases where matching ATAC-seq data is not available. Our results show that, generally, metrics calculated on training datasets give inflated performance scores. Of the tested techniques, genomic sampling of negatives based on similarity to the positives performed by far the best, although still not reaching the performance of baseline models trained on high-quality datasets. Models trained on dinucleotide shuffled negatives performed poorly, despite being a common practice in the field. Our findings highlight the importance of carefully selecting negative sampling techniques for TFBS prediction, as they can significantly impact model performance and the interpretation of results. AVAILABILITY AND IMPLEMENTATION: The code used in this study is available at https://github.com/NatanTourne/TFBS-negatives (DOI: 10.5281/zenodo.18007567).

Binding Sites↗
PubMed1994

Comparison of model predictions with LDEF satellite radiation measurements.

Some early results are summarized from a program under way to utilize LDEF satellite data for evaluating and improving current models of the space radiation environment in low Earth orbit. Reported here are predictions and comparisons with some of the LDEF dose and induced radioactivity data, which are used to check the accuracy of current models describing the magnitude and directionality of the trapped proton environment. Preliminary findings are that the environment models underestimate both dose and activation from trapped protons by a factor of about two, and the observed anisotropy is higher than predicted.

Cosmic Radiation↗
PubMed1999

A mathematical model predicting anti-hepatitis B virus surface antigen (HBs) decay after vaccination against hepatitis B.

The determination of serum levels of antibodies against hepatitis B virus surface antigen (anti-HBs) after hepatitis B vaccination is currently the only simple test available to predict the decay of protection and to plan the administration of booster doses. A total of 3085 vaccine recipients of plasma-derived and recombinant vaccine have been followed for 10 years to determine the kinetics of anti-HBs production and to construct a mathematical model which could efficiently predict the anti-HBs level decline. The anti-HBs peak level was reached 68 days after the last dose of recombinant vaccine and 138 days after the last dose of plasma-derived vaccines. The age of vaccinees negatively influenced the anti-HBs levels and also the time necessary to reach the anti-HBs peak. A bilogarithmic mathematical model (log10 level, log10 time) of anti-HBs decay has been constructed on a sample of recombinant vaccine recipients and subsequently validated on different samples of recombinant or plasma-derived vaccine recipients. Age, gender, type of vaccine (recombinant or plasma-derived), number of vaccine doses (three or four) did not influence the mathematical model of antibody decay. The program can be downloaded at the site: http:@www2.stat.unibo.it/palareti/vaccine.htm . Introducing an anti-HBs determination obtained after the peak, the program calculates a prediction of individual anti-HBs decline and allows planning of an efficient booster policy.

Algorithms↗
PubMed2003

Biomechanical model predicting electromyographic activity in three shoulder muscles from 3D kinematics and external forces during cleaning work.

BACKGROUND: The shoulder region is a common site of work-related musculoskeletal disorders. Biomechanical models may reveal the relative importance of force, joint-moments, and angular velocity for predicting muscle activity, thereby contributing to identify risk factors. OBJECTIVE: The aim of the present study was to predict muscle activity patterns from joint kinetics during cleaning work and to identify the most important variables requesting muscle activity.Design. A comparative study of six cleaners performing five different floor cleaning tasks (combinations of tool and working method) in a laboratory setting. METHODS: Net forces and moments at the glenohumeral joint were estimated using a video-based 3D link segment model together with 3D force-transducers at each hand, separately. Angular velocities of the upper arm were calculated, and electromyographic activity was recorded bilaterally from the muscles trapezius, deltoideus, and infraspinatus. RESULTS: The biomechanical model revealed abduction moment in the glenohumeral joint to be the most important factor for development of muscle activity in m. deltoideus and m. infraspinatus, while for m. trapezius vertical force was most important. CONCLUSION: Muscle specific determinants for shoulder muscle activity could be identified from glenohumeral joint kinetics. RELEVANCE: This study documents that mechanical work requirements in terms of joint forces, moments of force and angular velocities can predict major fractions of muscle activity patterns in the upper extremities. The biomechanical model used for this prediction revealed different factors of importance for individual muscles. This knowledge is fundamental for work place interventions aiming at minimizing overloading of specific muscles to prevent or rehabilitate muscle disorders.

Activities of Daily Living↗
PubMed1997

Force from cat soleus muscle during imposed locomotor-like movements: experimental data versus Hill-type model predictions.

Muscle is usually studied under nonphysiological conditions, such as tetanic stimulation or isovelocity movements, conditions selected to isolate specific properties or mechanisms in muscle. The purpose of this study was to measure the function of cat soleus muscle during physiological conditions, specifically a simulation of a single speed of slow walking, to determine whether the resulting force could be accurately represented by a Hill-type model. Because Hill-type models do not include history-dependent muscle properties or interactions among properties, the magnitudes of errors in predicted forces were expected to reveal whether these phenomena play important roles in the physiological conditions of this locomotor pattern. The natural locomotor length pattern during slow walking, and the action potential train for a low-threshold motor unit during slow walking, were obtained from the literature. The whole soleus muscle was synchronously stimulated with the locomotor pulse train while a muscle puller imposed the locomotor movement. The experimental results were similar to force measured via buckle transducer in freely walking animals. A Hill-type model was used to simulate the locomotor force. In a separate set of experiments, the parameters needed for a Hill-type model (force-velocity, length-tension, and stiffness of the series elastic element) were measured from the same muscle. Activation was determined by inverse computation of an isometric contraction with the use of the same locomotor stimulus pattern. During the stimulus train, the Hill-type model fit the locomotor data fairly well, with errors < 10% of maximal tetanic tension. A substantial error occurred during the relaxation phase. The model overestimated force by approximately 30% of maximal tetanic tension. A nonlinear series elastic element had little influence on the force predicted by a Hill model, yet dramatically altered the predicted muscle fiber lengths. Further experiments and modeling were performed to determine the source of errors in the Hill-type model. Isovelocity ramps were constructed to pass through a selected point in the locomotor movement with the same velocity and muscle length. The muscle was stimulated with the same locomotor pulse train. The largest errors again occurred during the relaxation phase following completion of the stimulus. Stretch during stimulation caused the Hill model to underestimate the relaxation force. Shortening movements during stimulation caused the Hill model to overestimate the relaxation force. These errors may be attributed to the effects of movement on crossbridge persistence, and/or the changing affinity of troponin for calcium between bound and unbound crossbridges, neither of which is well represented in a Hill model. Other sources of error are discussed. The model presented represents the limit of accuracy of a basic Hill-type model applied to cat soleus. The model had every advantage: the parameters were measured from the same muscle for which the locomotion was simulated and errors that could arise in the estimation of activation dynamics were avoided by inverse calculation. The accuracy might be improved by compensating for the apparent effects of velocity and length on activation. Further studies are required to determine to what degree these conclusions can be generalized to other movements and muscles.

Animals↗
PubMed2004

[Predictive model for community acquired bacteremia in patients from an Internal Medicine Unit].

BACKGROUND AND OBJECTIVE: Clinical suspicion of bacteremia lacks of sensitivity, specificity or predictive values enough to be clinically useful. The aim of this study was to develop a clinical prediction rule of bacteremia for patients hospitalized in an internal medicine department, with community-acquired symptoms, who had blood cultures obtained. PATIENTS AND METHOD: A prospective study, including all patients who had blood cultures in the first 48 h after admission, was performed. A clinical prediction rule of bacteremia was derived from a random sample of two thirds of the patients (derivation cohort) and validated in the remaining (validation cohort). After bivariate analysis, significant variables were included in a stepwise logistic regression analysis. In every patient out of the derivation and validation cohorts a score, derived from the addition of points for each of the significant predictor variables of logistic regression, was obtained; according to this score, 4 groups were formed, and the prevalence of bacteremia in each of them was calculated. Calibration and discrimination were evaluated by the Hosmer-Lemeshow test and area under the ROC curve respectively. RESULTS: Four hundred and forty-eight blood cultures were obtained; the prevalence of bacteremia was 25.2%. Independent predictors of bacteremia in the bivariate analysis were urinary focus of infection, body temperature >= 38.3 degrees C, presence of band forms, ESR >= 70 mm, platelets < 200 * 103/microl, blood glucose >= 140 mg/dl, urea >= 50 mg/dl, C-reactive protein >= 12 mg/dl, and albumin < 3 g/dl. According to the score, in the derivation cohort, four groups with increasing prevalence of bacteremia were identified; in the group with a score between 0 and 3, the prevalence was 2.4%; between 4 and 5: 15.7%; between 6 and 7: 42.9%; and score >= 8: 65%. In the validation cohort, the prevalence was 4.1%, 22.6%, 29.3%, and 80%, respectively. The model showed good calibration (Hosmer-Lemeshow *2 = 4.91; p = 0.77). Area under the ROC curve was 0.81 (95% confidence interval, 0.76-0.86) in the derivation cohort, and 0.77 (95% confidence interval, 0.69-0.85) in validation cohort. CONCLUSIONS: Our model, constructed with 9 variables and a simple additive point system, had good calibration and discrimination, which points at its usefulness to estimate the probability of bacteremia in patients admitted in an Internal Medicine department. Used in conjunction with clinical judgement, the model can be useful in the decision-making process, concerning blood cultures obtention, clinical monitoring, and empirical antimicrobial therapy. Before application, additional prospective validation in other settings is warranted.

Aged↗
PubMed2004

Development of a predictive model for ross river virus disease in Brisbane, Australia.

This paper describes the development of an empirical model to forecast epidemics of Ross River virus (RRV) disease using the multivariate seasonal auto-regressive integrated moving average (SARIMA) technique in Brisbane, Australia. We obtained computerized data on notified RRV disease cases, climate, high tide, and population sizes in Brisbane for the period 1985-2001 from the Queensland Department of Health, the Australian Bureau of Meteorology, the Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model was developed and validated by dividing the data file into two data sets: the data between January 1985 and December 2000 were used to construct a model, and those between January and December 2001 to validate it. The SARIMA models show that monthly precipitation (beta = 0.004, P = 0.031) was significantly associated with RRV transmission. However, there was no significant association between other climate variables (e.g., temperature, relative humidity, and high tides) and RRV transmission. The predictive values in the model were generally consistent with actual values (root mean square percentage error = 0.94%). Therefore, this model may have applications as a decision supportive tool in disease control and risk-management planning programs.

Alphavirus Infections↗
PubMed2005

The establishment of Bayesian Coronary Artery Disease Prediction model.

This poster will demonstrate how we build up the module of Bayesian Coronary Artery Disease Predicting Evidence-Based Medicine. The system-module may help the young professional understand the effect of factors for referring patients to take the invasive examination of Angiographic.Moreover, the non-invasive information-tech also can perform as the screening tool on a clinical or a community-based epidemiology.

Bayes Theorem↗
PubMed1996

Preliminary validation of a prediction model for the short-term growth response to growth hormone therapy in children with idiopathic short stature.

A discriminant scoring system, using multivariate analysis, has been developed for pretreatment prediction of responsiveness to a 6-month trial of growth hormone (GH) treatment in short children with subnormal growth velocity, but without GH deficiency. Inclusion criteria included a birth weight above 2.5 kg, height below the 3rd centile for chronological age, height velocity below the 25th centile for bone age, no signs of puberty, a maximal GH response to pharmacological stimulation of above 10 micrograms/l and treatment with GH at a dose of 12-16 IU/m2/week. Children with an increase in height velocity greater than 2.5 cm/year after therapy were considered to be responders. Pretreatment clinical data from 67 patients were employed in a discriminant analysis in order to establish the model. The scoring system developed was as follows: score = -0.4 + 0.92X1 - 0.87X2, where X1 is the height velocity SD score (SDS) for chronological age, and X2 is the bone age SDS for chronological age. This model had a specificity of 96.3% and a sensitivity of 92.5% in predicting the responsiveness to GH. The model has subsequently been applied to a group of 14 patients in order to establish its validity; in this group its sensitivity was 83.3% and its specificity 100%. These preliminary data suggest that the model can be used as a guideline for selecting short, slowly growing, non-GH-deficient children who will respond to short-term GH therapy.

Body Height↗
PubMedDate not supplied

Predictive models in cirrhosis: correlation with the final results and costs of liver transplantation in Chile.

Medical scores for predicting survival are essential to stratify patients with end-stage liver disease (ESLD) for prioritization for liver transplantation (OLT). Recently the UNOS has adopted the Mayo Model for End-stage Liver Disease (MELD) score as the basis for liver allocation in the United States. We retrospectively evaluated and assessed the prognostic impact, the length of stay (LOS), and hospital charges for OLT using two severity scores (Child-Turcotte-Pugh [CTP] versus MELD) to stratify cirrhotic patients before OLT. Twenty-six consecutive adult cirrhotic patients (11 women, mean age 46 years) underwent LT between 2000 and 2002. The main causes for transplantation were alcohol and primary biliary cirrhosis. The mean CTP and MELD scores at the moment of listing for OLT were 8.9 and 16.3 points, respectively. The best discriminative values with prognostic impact in terms of outcome and costs of OLT were a Child Pugh score >/=11 points or a MELD score >/=20 points. Patients in these strata showed a significant increase in LOS in the hospital (from a mean of 12 to 22 days) and intensive care stay (from a mean of 4 to 14 days) post-OLT when compared with patients with a lower CTP or MELD score (P <.05). There was also a trend toward higher hospital charges (P =.06). Organ allocation by MELD score will probably adversely affect the LOS and hospital charges of patients being transplanted due to ESLD.

Adult↗
PubMed1996

Comparison of prediction models for the compression force on the lumbosacral disc.

The main objective of this research was to compare three representative methods of predicting the compressive forces on the lumbosacral disc: LP-based model, double LP-based model, and EMG-assisted model. Two subjects simulated lifting tasks that are frequently performed in the refractories industry of Korea, in which vertical and lateral distances, and weight of load were varied. To calculate the L5/S1 compressive forces, EMG signals from six trunk muscles were measured, and postural data and locations of load were recorded using the Motion Analysis System. The EMG-assisted model was shown to reflect well all three factors considered here, whereas the compressive forces from the two LP-based models were only significantly affected by weight of load. In addition, low lifting index (LI) values were observed for relatively high L5/S1 compressive forces from the EMG-assisted model, suggesting that the 1991 NIOSH lifting equations may not fully evaluate the risk of dynamic asymmetric lifting tasks.

Adult↗
PubMed2003

Pre-test prediction models of BRCA1 or BRCA2 mutation in breast/ovarian families attending familial cancer clinics.

OBJECTIVE: To test whether statistical models developed to calculate pre-test probability of being a BRCA1/2 carrier can differentiate better between the breast/ovarian families to be referred to the DNA test laboratory. STUDY DESIGN: A retrospective analysis was performed in 109 Spanish breast/ovarian families previously screened for germline mutations in both the BRCA1 and BRCA2 genes. Four easy to use logistic regression models originally developed in Spanish (HCSC model), Dutch (LUMC model), Finnish (HUCH model), and North American (U Penn model) families and one model based on empirical data of Frank 2002 were tested. A risk counsellor was asked to assign a subjective pre-test probability for each family. Sensitivity, specificity, negative and positive predictive values, and areas under receiver operator characteristics (ROC) curves were calculated in each case. Correlation between predicted probability and mutation prevalence was tested. All statistical tests were two sided. RESULTS: Overall, the models performed well, improving the performances of a genetic counsellor. The median ROC curve area was 0.80 (range 0.77-0.82). At 100% sensitivity, the median specificity was 30% (range 25-33%). At 92% sensitivity, the median specificity was 42% (range 33.3-54.2%) and the median negative predictive value was 93% (range 89.7-98%). BRCA1 families tended to score higher risk than BRCA2 families in all models tested. CONCLUSIONS: All models increased the discrimination power of an experienced risk counsellor, suggesting that their use is valuable in the context of clinical counselling and genetic testing to optimise selection of patients for screening and allowing for more focused management. Models developed in different ethnic populations performed similarly well in a Spanish series of families, suggesting that models targeted to specific populations may not be necessary in all cases. Carrier probability as predicted by the models is consistent with actual prevalence, although in general models tend to underestimate it. Our study suggests that these models may perform differently in populations with a high prevalence of BRCA2 mutations.

BRCA1 Protein↗
PubMed2001

Anisotropic and inhomogeneous tensile behavior of the human anulus fibrosus: experimental measurement and material model predictions.

The anulus fibrosus (AF) of the intervertebral disc exhibits spatial variations in structure and composition that give rise to both anisotropy and inhomogeneity in its material behaviors in tension. In this study, the tensile moduli and Poisson's ratios were measured in samples of human AF along circumferential, axial, and radial directions at inner and outer sites. There was evidence of significant inhomogeneity in the linear-region circumferential tensile modulus (17.4+/-14.3 MPa versus 5.6+/-4.7 MPa, outer versus inner sites) and the Poisson's ratio v21 (0.67+/-0.22 versus 1.6+/-0.7, outer versus inner), but not in the axial modulus (0.8+/-0.9 MPa) or the Poisson's ratios V12 (1.8+/-1.4) or v13 (0.6+/-0.7). These properties were implemented in a linear an isotropic material model of the AF to determine a complete set of model properties and to predict material behaviors for the AF under idealized kinematic states. These predictions demonstrate that interactions between fiber populations in the multilamellae AF significantly contribute to the material behavior, suggesting that a model for th

Adult↗