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PubMed2002

Multicolored simplified asthma guideline reminder (MSAGR) for better adherence to national/global asthma guidelines.

BACKGROUND: Clinicians in general have not widely and consistently used asthma guidelines in their practices around the world. This study identifies reasons for the poor adherence to asthma guidelines by primary care physicians (PCPs), and simultaneously introduces multicolored simplified asthma guideline reminder (MSAGR) as a practical tool to enhance adherence to asthma guidelines. METHODS: Sixty-nine PCPs were given a simple, one-page, fill-in-the-blank questionnaire on the classification of asthma severity as defined in National Asthma Education and Prevention Program guidelines, using patients' symptoms, peak expiratory flow rate (PEFR)/forced expiratory volume in 1 second (FEV1) value, PEFR variability, and step therapy based on asthma severity. Also, they were given a questionnaire on barriers to using asthma guidelines and MSAGR for evaluation. In one targeted community, free copies of MSAGR were made available to PCPs, and data on emergency room visits and hospitalization of asthmatic patients were analyzed. RESULTS: Of the PCPs, 16% correctly classified mild, intermittent asthma, 13% mild, persistent asthma, 8% moderate, persistent asthma, and 8% severe, persistent asthma based on the combined patient's symptoms, PEFR or FEV1 value and PEFR variability as defined in National Asthma Education and Prevention Program guidelines. One hundred percent of the PCPs chose inhaled beta2-agonists as quick relief medication. Fifty percent of the PCPs chose inhaled steroids, leukotriene antagonists, oral theophylline, and long acting beta-agonists in various combinations for different severity of asthma. Eighty percent of the physicians failed to select the appropriate dosages of inhaled steroids for different severities of asthma. Ninety-five percent of PCPs reported that MSAGR made using the guidelines easier for them. In the targeted community, asthma-related emergency room visits decreased 22.5% and hospitalizations by 26.9%. CONCLUSIONS: This is the first study that identified the reasons for poor adherence to asthma guidelines by PCPs, and introduced MSAGR as a practical "low-tech" tool to promote better adherence to asthma guidelines. MSAGR presents patient-specific recommendations, based on asthma guidelines in a user-friendly format that can save the physician time in real-world primary care settings, where such information is often needed instantly. The overwhelming majority of PCPs strongly agreed that MSAGR helped them recall the classification of asthma severity in a timely manner, to inquire about various triggers, and to use step therapy accurately and confidently. In one targeted community, MSAGR helped clinicians in primary care settings to achieve better asthma outcomes and to reduce both emergency room visits and hospitalizations.

Adult↗

PubMed2002

Airborne carbonyls from motor vehicle emissions in two highway tunnels.

Carbonyls (aldehydes and ketones) continue to receive scientific and regulatory attention as toxic air contaminants, mutagens, and carcinogens. Vehicle emissions are a major source of carbonyls in outdoor air, but information about the nature and magnitude of carbonyl emissions by motor vehicles is limited. The objective of this study was to identify speciated carbonyls emitted by motor vehicles under real-world, on-road conditions and to calculate on-road carbonyl emission factors. We collected air samples at the inlet and outlet of two highway tunnels, the Caldecott Tunnel near San Francisco and the Tuscarora Mountain Tunnel in Pennsylvania. At the Caldecott Tunnel, the fleet consisted almost entirely of light-duty (LD) vehicles that used California phase 2 reformulated gasoline. Vehicle count, speed and other parameters relevant to carbonyl emissions were nearly the same from one assessment to the next. At the Tuscarora Mountain Tunnel, the fleet included LD vehicles and heavy-duty (HD) diesel trucks. This part of the study was designed to capture differences in percentage of LD and HD vehicles from one assessment to the next. Air downstream of KI oxidant scrubbers was sampled on silica gel cartridges coated with 2,4-dinitrophenylhydrazine (DNPH). Carbonyls were identified as their DNPH derivatives by liquid chromatography (LC) with detection by diode-array, UV-visible spectroscopy and by atmospheric pressure negative-ion chemical ionization mass spectrometry (MS). About 100 carbonyls were identified. For about 30 of these carbonyls, concentrations were measured at the inlet and outlet of both tunnels. This information was used to calculate on-road carbonyl emission factors for LD vehicles (Caldecott Tunnel) and for the overall fleet (Tuscarora Mountain Tunnel). At the Tuscarora Mountain Tunnel, data for the fleet were used to calculate carbonyl emission factors for LD vehicles and for HD diesel trucks, the majority of which were weight class 7-8 trucks. Carbonyl emission factors at the Caldecott Tunnel were calculated as milligrams of emissions per liter of fuel consumed. Those at the Tuscarora Mountain Tunnel were calculated as milligrams of emissions per distance traveled and then converted to milligrams per liter using the fuel economy reported by Gertler et al (2000) for this tunnel (14.75 km/L for LD vehicles and 3.15 km/L for HD vehicles). At the Caldecott Tunnel, the LD vehicles emission factor was 68.4 mg/L for total measured carbonyls; the ten most abundant carbonyls were, in decreasing order, formaldehyde, acetaldehyde, benzaldehyde, acetone, m-tolualdehyde, p-tolualdehyde, methacrolein, o-tolualdehyde, 2,5-dimethylbenzaldehyde, and crotonaldehyde. At the Tuscarora Mountain Tunnel, the LD emission factor was 94.9 mg/L for total measured carbonyls; the ten most abundant carbonyls were formaldehyde, acetone, acetaldehyde, heptanal, crotonaldehyde, 2-butanone, propanal, acrolein, methacrolein, and benzaldehyde. The weight class HD 7-8 vehicle emission factor at the Tuscarora Mountain Tunnel was 82.1 mg/L for total measured carbonyls; the ten most abundant carbonyls were formaldehyde, acetaldehyde, acetone, crotonaldehyde, m-tolualdehyde, 2-pentanone, a C5 saturated aliphatic carbonyl, 2-butanone, benzaldehyde, and methacrolein. The most abundant carbonyl was formaldehyde, which accounted for 45.4% (Caldecott, LD vehicles), 40.1% (Tuscarora Mountain, LD vehicles), and 25.8% (Tuscarora Mountain, HD vehicles) of total measured carbonyl emissions. The three most abundant carbonyls, formaldehyde, acetaldehyde, and acetone, together accounted for 63.0% (Caldecott, LD vehicles), 76.5% (Tuscarora Mountain, LD vehicles), and 50.5% (Tuscarora Mountain, HD vehicles) of total carbonyl emissions. At the Tuscarora Mountain Tunnel, HD vehicles emitted more unsaturated carbonyls, aromatic carbonyls, and dicarbonyls (as a percentage of total carbonyl emissions) than did LD vehicles. For LD vehicles, less acetone and more aromatic carbonyls (as a percentage of total carbonyl emissions) were emitted at the Caldecott Tunnel than at the Tuscarora Mountain Tunnel. The highway tunnel studies described in the main body of the report also offered an opportunity to examine the role of the sampling substrate, a critical aspect of the carbonyl sampling protocol. The results are described in Appendix A. Co-located samples, one collected using a DNPH-coated silica gel cartridge and the other using a DNPH-coated C18 cartridge, were collected downstream of KI oxidant scrubbers at the inlet and outlet of the Caldecott Tunnel. Statistical comparisons of the concentrations measured for about 30 carbonyls indicated good agreement between silica gel cartridges and C18 cartridges for about 25 carbonyls, including formaldehyde and acetaldehyde. Concentrations of acetone and 2-butanone measured using C18 cartridges were lower than those measured using silica gel cartridges.

Air Pollutants↗

PubMed1993

The case for chaos in childhood epidemics. II. Predicting historical epidemics from mathematical models.

The case for chaos in childhood epidemics rests on two observations. The first is that historical epidemics show various 'fieldmarks' of chaos, such as positive Lyapunov exponents. Second, phase portraits reconstructed from real-world epidemiological time series bear a striking resemblance to chaotic solutions obtained from certain epidemiological models. Both lines of evidence are subject to dispute: the algorithms used to look for the fieldmarks can be fooled by short, noisy time series, and the same fieldmarks can be generated by stochastic models in which there is demonstrably no chaos at all. In the present paper, we compare the predictive abilities of stochastic models with those of mechanistic scenarios that admit to chaotic solutions. The main results are as follows: (i) the mechanistic models outperform their stochastic counterparts; (ii) forecasting efficacy of the deterministic models is maximized by positing parameter values that induce chaotic behaviour; (iii) simple mechanistic models are equal if not superior to more detailed schemes that include age structure; and (iv) prediction accuracy for monthly notifications declines rapidly with time, so that, from a practical standpoint, the results are of little value. By way of contrast, next amplitude maps can successfully forecast successive changes in maximum incidence one or more years into the future.

Child↗

PubMed2026

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certainty of evidence. METHODS: PubMed, Embase, Cochrane Library, Web of Science, and IEEE Xplore were searched from January 2014 to April 2026. Eligible peer-reviewed diagnostic accuracy studies developed or validated ML or DL models for 1 of the 3 prespecified tasks, used an accepted reference standard, and provided data for a 2×2 contingency table. Bivariate random-effects meta-analyses with the Hartung-Knapp-Sidik-Jonkman adjustment were used to pool sensitivity and specificity. We reported 95% prediction intervals (PIs), assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies for Artificial Intelligence tool (QUADAS-AI; Viknesh Sounderajah [Imperial College London]), and evaluated certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework for diagnostic test accuracy. RESULTS: Twenty-nine studies were included: 17 for SLE classification, 5 for LN diagnosis, and 7 for NPSLE discrimination. In the primary task-stratified analysis, pooled sensitivity was 0.91 (95% CI 0.86-0.94; 95% PI 0.56-0.99), and pooled specificity was 0.94 (95% CI 0.91-0.96; 95% PI 0.69-0.99), with low heterogeneity (I²=23.9% and 22.9%, respectively). DL models showed a sensitivity of 0.93 and specificity of 0.95, compared with 0.88 and 0.94 for traditional ML models. Certainty of evidence was high for most analyses but low for LN diagnosis because of inconsistency and imprecision. All studies were retrospective, and only 9 of 29 (31%) performed independent external validation. Overall risk of bias was high or unclear in 22 of 29 (75.9%) studies. No study reported model calibration, decision-curve analysis, or net clinical benefit. CONCLUSIONS: ML models showed promising diagnostic accuracy across 3 distinct SLE-related tasks, but wide PIs, limited external validation, and pervasive risk of bias restrict conclusions about real-world generalizability. Prospective multicenter studies with standardized tasks and reference standards, independent external validation, and formal assessment of calibration and clinical utility are required before clinical implementation.

Humans↗

PubMed1994

Use of transdermal nicotine in a state-level prescription plan for the elderly. A first look at 'real-world' patch users.

OBJECTIVE: To assess transdermal nicotine use patterns and outcomes in a population of low-income older smokers. DESIGN: A 6-month telephone follow-up survey of smokers filling prescriptions for transdermal nicotine in the first 3 months of 1992. SETTING: Pennsylvania's Pharmaceutical Assistance Plan for the Elderly, the nation's largest state-level prescription plan for the elderly. POPULATION: A total of 1070 noninstitutionalized male and female smokers aged 65 through 74 years. MAIN OUTCOME MEASURES: Self-reported physician/pharmacist advice and adjunctive treatments, concomitant smoking, and 6-month smoking abstinence. RESULTS: Respondents were predominantly long-term heavy smokers. They used nicotine patches for an average of 5 weeks, with few reporting use beyond 3 months or recalling bothersome side effects. Most of those with previous quit attempts rated quitting with the patch "easier." The 29% self-reported 6-month quit rate observed is encouraging. However, compliance with patch use guidelines was far from ideal in this high-risk population: only 54% of respondents received any initial advice or materials from their physicians or pharmacists, fewer than 2% took part in a formal clinic or one-to-one treatment program, and almost half (47%) smoked while using the patch, including 20% who smoked every day. Concomitant smoking was strongly associated with failure to achieve abstinence (P < .001). More frequent contact with physicians and/or pharmacists was associated with less concomitant smoking (P < .001) and higher quit rates (P = .005). CONCLUSIONS: This survey offers an important first look at problems and prospects for nicotine patch therapy in older adults, with implications for other groups as well. Prospective studies are needed to clarify optimal treatment regimens and adjuncts.

Administration, Cutaneous↗

PubMed2026

Real-World Experience With TRBC1 Immunohistochemistry Across Cutaneous T-Cell Lymphoma Subtypes: A Large Cohort Study.

T-cell receptor β-chain constant region 1 (TRBC1) immunohistochemistry identifies clonal αβ T-cell populations on tissue sections, but its real-world performance across cutaneous T-cell lymphoma (CTCL) and related infiltrates is uncharacterized. The analytic cohort comprised 665 biopsies (566 patients) with paired T-cell receptor (TCR) clonality testing, classified clinicopathologically as mycosis fungoides (MF; MF-Patch, MF-Plaque, MF-Tumor, and MF-Folliculotropic); MF or Sézary syndrome; primary cutaneous small or medium T-cell lymphoproliferative disorders (LPDs); other CTCL-cutaneous LPDs; or reactive. At the primary <15%/>85% threshold, TRBC1 IHC achieved 85.8% sensitivity (337/393), 79.8% specificity (217/272), 86.0% positive and 79.5% negative predictive value, and 83.3% accuracy. Sensitivity was lowest in MF-Patch (84.2%). Three-reader agreement (Fleiss κ = 0.943) fell to κ = 0.776 in 176 reflexed biopsies, with disagreement concentrated on MF-Patch and CD30-positive LPDs. Monotypic TRBC1 predicted neoplasia, with odds rising with infiltrate density: MF-Patch (odds ratio, 5.41), MF-Plaque (10.40), MF/Sézary syndrome with MF-Tumor (15.19), and CTCL-cutaneous LPD (18.16). Polytypic TRBC1 was associated with reactive disease (odds ratio, 53.65), effectively excluded clonality (negative likelihood ratio, 0.18), and was uniformly observed in an independent 270-biopsy reactive cohort. For observer-independent validation, digital image analysis-derived TRBC1 quantification (QuPath) was applied to a stratified random subset of 250 biopsies representative of the cohort's tumor-burden distribution. The digital read-tracked molecular clonality (85.1% sensitivity, 80.1% specificity against TCR; area under the curve, 0.842) agreed with the dermatopathologist's manual read in 87.6% of cases (κ = 0.752), with the data-derived cutoff matching the prespecified <15%/>85% threshold value. Discordance was directional for both manual scoring and digital quantification: in MF-Patch, 25 of 38 (65.8%) and 12 of 17 (70.6%) cases were polytypic with monoclonal TCR (false-negative-dominant); in reactive biopsies, 34 of 45 (75.6%) and 19 of 20 (95%) were monotypic with polyclonal TCR (false-positive-dominant). These findings support a TRBC1-first approach, reserving reflex TCR testing for borderline expression or clinicopathologic discordance, preserving diagnostic accuracy while reducing molecular testing and reimbursement-based costs.

Sézary syndrome↗

PubMed1993

The health care status of the diabetic population as reflected by physician claims to a major insurer.

BACKGROUND: Conventional epidemiologic data suggest that diabetic patients use more health care resources than nondiabetic patients, yet overall health care use by diabetic individuals has never been fully quantitated. We took a new approach to this issue based on the actual economics of the provision of health care to diabetic insured individuals. METHODS: The claims records in the Mutual of Omaha Current Trends database, which contains information on more than 400,000 individuals, were surveyed to identify patients with diabetes and create the contrast population of nondiabetic patients by exclusion. International Classification of Diseases, Ninth Revision, Clinical Modification, codes and Physicians' Current Procedural Terminology, Fourth Edition, codes were used to determine all diagnoses recorded and all physician services rendered to the contrast populations. Age- and sex-adjusted comparisons were performed using Mantel-Haenszel procedures to determine an adjusted odds ratio (AOR). RESULTS: A total of 13,304 diabetic individuals and 388,053 nondiabetic individuals who received health care services from January 1, 1988, to January 1, 1989, were identified. Diabetic insured individuals constituted 3.1% of the overall insured population yet accounted for 8.3% of the charges (P < .01). Inpatient charges accounted for 81% of total diabetic charges but only 61.5% of total nondiabetic charges (P < .001). Diabetic insured individuals had twice as many physician office visits (AOR = 1.87; 95% confidence interval [CI], 1.79 to 1.96), with 2.5 times more physician hospital visits [AOR = 2.50; 95% CI, 2.27 to 2.75). However, the increases in physician care were not uniformly distributed across the diagnostic spectrum. The frequencies of well-established complications of diabetes, such as ischemic heart disease (AOR = 3.32; 95% CI, 3.12 to 3.53), peripheral vascular disease (AOR = 3.14; 95% CI, 2.79 to 3.53), and eye disease (AOR = 3.10; 95% CI, 2.94 to 3.27), were threefold higher in the diabetic group, with parallel increases in related medical services, such as cardiac catheterization (AOR = 3.02; 95% CI, 2.27 to 4.0), vascular surgery (AOR = 2.94; 95% CI, 2.64 to 3.27), and ophthalmologic procedures (AOR = 2.94; 95% CI, 2.72 to 3.18). In contrast, most diagnostic categories showed little or no increase. For example, the frequency of neoplasms (AOR = 1.11; 95% CI, 1.03 to 1.19) was minimally increased, and the associated procedural concomitants of therapeutic radiology (AOR = 0.81; 95% CI, 0.47 to 1.39) and chemotherapy (AOR = 0.98; 95% CI, 0.60 to 1.60) were not increased in the diabetic group. CONCLUSIONS: Our most important new finding is that diabetic patients have neither an elevated risk for a wide spectrum of diseases nor an increase in the receipt of physician services for diagnostic categories without increased risk, despite more frequent physician encounters. We provide real-world risk estimates that help in calculating the effect of offering specific insurance to diabetic individuals or including them in group health plans. The techniques we have developed to analyze computerized claims databases in this way may serve to better quantify the true impact of chronic diseases on the health care system.

Adult↗

PubMed2026

2024-2025 BNT162b2 KP.2 COVID-19 full season vaccine effectiveness from vaccine registries linked to administrative claims in two states: A cohort study in non-immunocompromised adults.

BACKGROUND: Data on effectiveness of COVID-19 vaccinations during the 2024-2025 respiratory season are limited, particularly among those with underlying medical conditions (UMC). We estimated BNT162b2 KP.2 vaccine effectiveness (VE) against COVID-19-associated hospital admission, emergency department (ED), and urgent care (UC) visits in two U.S. states. METHODS: Retrospective cohort study of non-immunocompromised adults living in Louisiana or California, with ≥1 year prior continuous enrollment in insurance plans contributing to the HealthVerity claims database beginning August 22, 2024. The effectiveness of BNT162b2 KP.2 vaccine (2024-2025 formulation, hereafter referred to as BNT162b2), measured as a time-varying exposure against hospital admission, ED, or UC encounters with International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code U07.1 was calculated as 1 - adjusted hazard ratio using Cox proportional hazard models adjusted for age group, sex, state, insurance payor, presence or absence of UMCs, and pre-index healthcare utilization. Stratifications included those aged 65 years and older, those aged 18-64 years with UMCs, and those aged 18-64 years without UMCs. RESULTS: The cohort included 6,256,421 individuals (93% California, 7% Louisiana); 330,565 (5%) received the BNT162b2 vaccine. Vaccinated individuals were older and had more comorbidities, wellness visits, and prior influenza vaccination. Overall, 66% of the study population had ≥1 UMC; the most prevalent conditions were obesity (25%), history of immunocompromised conditions (23%), and mental health conditions (19%). COVID-19-related encounter rates for ED, UC or hospitalization were lower among vaccinated compared to unvaccinated persons (25.1 vs 36.3 per 100,000 person-months). Among all adults, VE was 37% against hospitalization, 12% against ED/UC encounters, and 16% against ED/UC/hospitalization encounters. Results were similar across age groups and UMCs. CONCLUSIONS: BNT162b2 provided protection against COVID-19-associated outcomes of ED, UC or hospitalization among non-immunocompromised U.S. adults, including those with UMCs, over the course of the 2024-2025 respiratory virus season, supporting continued vaccine recommendations. REGISTRATION: This study was posted on clinicaltrials.gov prior to analyses (NCT06923137).

Adolescent↗

PubMed2000

Helmets for preventing head and facial injuries in bicyclists.

BACKGROUND: Each year, in the United states, approximately 900 persons die from injuries due to bicycle crashes and over 500,000 persons are treated in emergency departments. Head injury is by far the greatest risk posed to bicyclists, comprising one-third of emergency department visits, two-thirds of hospital admissions, and three-fourths of deaths. Facial injuries to cyclists occur at a rate nearly identical to that of head injuries. Although it makes inherent sense that helmets would be protective against head injury, establishing the real-world effectiveness of helmets is important. A number of case-control studies have been conducted demonstrating the effectiveness of bicycle helmets. Because of the magnitude of the problem and the potential effectiveness of bicycle helmets, the objective of this review is to determine whether bicycle helmets reduce head, brain and facial injury for bicyclists of all ages involved in a bicycle crash or fall. OBJECTIVES: To determine whether bicycle helmets reduce head, brain and facial injury for bicyclists of all ages involved in a bicycle crash or fall. SEARCH STRATEGY: We searched The Cochrane Controlled Trials Register, MEDLINE, EMBASE, Sport, ERIC, NTIS, Expanded Academic Index, CINAHL, PsycINFO, Occupational Safety and Health, and Dissertations Abstracts. We checked reference lists of past reviews and review articles, studies from government agencies in the United States, Europe and Australia, and contacted colleagues from the International Society for Child and Adolescent Injury Prevention, World Injury Network, CDC funded Injury Control and Research Centers, and staff in injury research agencies around the world. SELECTION CRITERIA: Controlled studies that evaluated the effect of helmet use in a population of bicyclists who had experienced a crash. We required that studies have complete outcome ascertainment, accurate exposure measurement, appropriate selection of the comparison group and elimination or control of factors such as selection bias, observation bias and confounding. DATA COLLECTION AND ANALYSIS: Five published studies met the selection criteria. Two abstractors using a standard abstraction form independently abstracted data. Odds ratios with 95% CI were calculated for the protective effect of helmet for head and facial injuries. Study results are presented individually. Head and brain injury results were also summarized using meta-analysis techniques. MAIN RESULTS: No randomized controlled trials were found. This review identified five well conducted case control studies which met our selection criteria. Helmets provide a 63%-88% reduction in the risk of head, brain and severe brain injury for all ages of bicyclists. Helmets provide equal levels of protection for crashes involving motor vehicles (69%) and crashes from all other causes (68%). Injuries to the upper and mid facial areas are reduced 65%. REVIEWER'S CONCLUSIONS: Helmets reduce bicycle-related head and facial injuries for bicyclists of all ages involved in all types of crashes including those involving motor vehicles.

Bicycling↗

PubMed2026

Real-world clinical utility of exome sequencing in pediatric drug-resistant epilepsy: Experience from a tertiary center in Thailand.

BACKGROUND: Genomic testing has increasingly contributed to the diagnosis and management of pediatric drug-resistant epilepsy (DRE), particularly in patients with suspected genetic etiologies. This study evaluated the diagnostic yield and real- world clinical utility of whole-exome sequencing (WES) in children with DRE. METHODS: Children with DRE and seizure onset before 15 years of age were enrolled between January 2020 and December 2023. Clinical data, including demographics, seizure characteristics, developmental history, electroencephalography (EEG), brain magnetic resonance imaging (MRI), and prior investigations, were reviewed. WES was performed in all probands and, when available, their parents. Variants were interpreted according to standard guidelines. Clinical utility and 1-year seizure and developmental outcomes were assessed from follow-up records. RESULTS: Fifty-six patients (23 males, 33 females) were included. The median age at seizure onset was 1 year (interquartile range [IQR] 0.3-4 years), and 96.4% had developmental comorbidities. Pathogenic or likely pathogenic variants were identified in 39% (22/56), with the highest diagnostic yield in children with seizure onset before 3 years of age. Channelopathies accounted for most genetically solved cases (68%), predominantly involving sodium channel genes. Genetic diagnoses provided clinical utility in 73% (16/22) of solved cases by guiding treatment and precision management. At 1-year follow-up, genetically solved patients showed more favorable seizure and developmental outcomes than those with genetically unsolved patients. CONCLUSION: WES achieved a 39% diagnostic yield and substantial clinical utility in pediatric DRE, particularly in early-onset and channelopathy-related disorders. These findings support early molecular diagnosis to facilitate genotype-informed management in appropriately selected children. However, the more favorable developmental and seizure outcomes observed in genetically solved patients should be interpreted with caution, as they may have been influenced by multiple factors beyond genetic diagnosis. In resource-limited settings, careful clinical phenotyping remains essential for treatment decisions and for prioritizing children for genomic testing.

Clinical utility↗

PubMed1998

Comparative performance of species richness estimation methods.

In most real-world contexts the sampling effort needed to attain an accurate estimate of total species richness is excessive. Therefore, methods to estimate total species richness from incomplete collections need to be developed and tested. Using real and computer-simulated parasite data sets, the performances of 9 species richness estimation methods were compared. For all data sets, each estimation method was used to calculate the projected species richness at increasing levels of sampling effort. The performance of each method was evaluated by calculating the bias and precision of its estimates against the known total species richness. Performance was evaluated with increasing sampling effort and across different model communities. For the real data sets, the Chao2 and first-order jackknife estimators performed best. For the simulated data sets, the first-order jackknife estimator performed best at low sampling effort but, with increasing sampling effort, the bootstrap estimator outperformed all other estimators. Estimator performance increased with increasing species richness, aggregation level of individuals among samples and overall population size. Overall, the Chao2 and the first-order jackknife estimation methods performed best and should be used to control for the confounding effects of sampling effort in studies of parasite species richness. Potential uses of and practical problems with species richness estimation methods are discussed.

Animals↗

PubMed2002

Assessing heart rate variability from real-world Holter reports.

Real world clinical Holter reports are often difficult to interpret from a heart rate variability (HRV) perspective. In many cases HRV software is absent. Step-by-step HRV assessment from clinical Holter reports includes: making sure that there is enough usable data, assessing maximum and minimum heart rates, assessing circadian HRV from hourly average heart rates, and assessing HRV from the histogram of R-R intervals and from the plot of R-R intervals or heart rate vs. time. If HRV data are available, time domain HRV is easiest to understand and less sensitive to scanning errors. SDNN (the standard deviation of all N-N intervals in ms) and SDANN (the standard deviation of the 5-min average of N-N intervals in ms) are easily interpreted. SDNN < 70 ms post-MI is a cut point for increased mortality risk. Two times ln SDANN is a good surrogate for ln ultra low frequency power and can be compared with published cut points. SDNNIDX (the average of the standard deviations of N-N intervals for each 5-min in ms) < 30 ms is associated with increased risk in patients with congestive heart failure. RMSSD (the root mean square of successive N-N interval difference in ms) < 17.5 ms has also been associated with increased risk post-myocardial infarction. Frequency domain HRV values are often not comparable to published data. However, graphical power spectral plots can provide additional information about whether the HRV pattern is normal and can also identify some patients with obstructive sleep apnea.

Diagnosis, Computer-Assisted↗

PubMed2000

Determination of biokinetic interactions in chemical mixtures using real-time breath analysis and physiologically based pharmacokinetic modeling.

Regulatory agencies are challenged to conduct risk assessments on chemical mixtures without full information on toxicological interactions that may occur at real-world, low-dose exposure levels. The present study was undertaken to investigate the pharmacokinetic impact of low-dose coexposures to toluene and trichloroethylene in vivo in male F344 rats using a real-time breath analysis system coupled with physiologically based pharmacokinetic (PBPK) modeling. Rats were exposed to compounds alone or as a binary mixture, at low (5 to 25 mg/kg) or high (240 to 800 mg/kg) dose levels. Exhaled breath from the exposed animals was monitored for the parent compounds and a PBPK model was used to analyze the data. At low doses, exhaled breath kinetics from the binary mixture exposure compared with those obtained during single exposures, thus indicating that no metabolic interaction occurred with these low doses. In contract, at higher doses the binary PBPK model simulating independent metabolism was found to underpredict the exhaled breath concentration, suggesting an inhibition of metabolism. Therefore the binary mixture PBPK model was used to compare the measured exhaled breath levels from high- and low-dose exposures with the predicted levels under various metabolic interaction simulations (competitive, noncompetitive, or uncompetitive inhibition). Of these simulations, the optimized competitive metabolic interaction description yielded a Ki value closest to the Km of the inhibitor solvent, indicating that competitive inhibition is the most plausible type of metabolic interaction between these two solvents.

Anesthetics, Inhalation↗

PubMed2000

Development of a microscale emission factor model for CO for predicting real-time motor vehicle emissions.

The U.S. Environmental Protection Agency's (EPA) National Exposure Research Laboratory has initiated a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source through the air pathway to human exposure in significant microenvironments of exposure. This paper presents the technical description of a newly developed model for CO emissions. The sensitivity analysis and evaluation of this emission model is presented in a companion paper titled "Sensitivity Analysis and Evaluation of MicroFacCO: A Microscale Motor Vehicle Emission Factor Model for CO Emissions." The MOBILE models (used in the United States, except California) and EMFAC models (used in California only) used to estimate emissions are suitable for supporting mostly regional (county)-scale modeling and emission inventory because of their dependence on vehicle-miles-traveled aggregate data. These emission models are not designed to estimate real-time emissions needed for human exposure studies near roadways. A number of independent studies have found that current mobile source emission factor models are not very reliable at estimating microscale emissions and are, therefore, inappropriate for use with microscale modeling necessary to estimate human exposures near roadways. A microscale emission factor model for predicting real-world real-time motor vehicle CO emissions (MicroFacCO) has been developed. It uses available information on the vehicle fleet composition. The algorithm used to calculate emission factors in MicroFacCO is disaggregated based on the on-road vehicle fleet. The emission factors are calculated from a real-time fleet rather than from a fleet-wide average estimated by a vehicle-miles-traveled weighting of the emission factors for different vehicle classes. MicroFacCO uses the same database used to develop the MOBILE6 model. As compared with MOBILE emission models, MicroFacCO requires only a few input variables, which are necessary to characterize the real-time fleet being modeled. The main input variables required are on-road vehicle fleet, time and day of year, ambient temperature, and relative humidity.

Carbon Monoxide↗

PubMed2001

Predictive modeling of the shelf life of fish under nonisothermal conditions.

The behavior of the natural microflora of Mediterannean gilt-head seabream (Sparus aurata) was monitored during aerobic storage at different isothermal conditions from 0 to 15 degrees C. The growth data of pseudomonads, established as the specific spoilage organisms of aerobically stored gilt-head seabream, combined with data from previously published experiments, were used to model the effect of temperature on pseudomonad growth using a Belehradek type model. The nominal minimum temperature parameters of the Belehradek model (T(min)) for the maximum specific growth rate (micro(max)) and the lag phase (t(Lag)) were determined to be -11.8 and -12.8 degrees C, respectively. The applicability of the model in predicting pseudomonad growth on fish at fluctuating temperatures was evaluated by comparing predictions with observed growth in experiments under dynamic conditions. Temperature scenarios designed in the laboratory and simulation of real temperature profiles observed in the fish chill chain were used. Bias and accuracy factors were used as comparison indices and ranged from 0.91 to 1.17 and from 1.11 to 1.17, respectively. The average percent difference between shelf life predicted based on pseudomonad growth and shelf life experimentally determined by sensory analysis for all temperature profiles tested was 5.8%, indicating that the model is able to predict accurately fish quality in real-world conditions.

Aerobiosis↗

PubMed2000

Social categorizations, social comparisons and stigma: presentations of self in people with learning difficulties.

Self-categorization theory stresses the importance of the context in which the meta-contrast principle is proposed to operate. This study is concerned with how 'the pool of psychologically relevant stimuli' (Turner, Hogg, Oakes, Reicher & Wetherell, 1987, p. 47) comprising the context is determined. Data from interviews with 33 people with learning difficulties were used to show how a positive sense of self might be constructed by members of a stigmatized social category through the social worlds that they describe, and therefore the social comparisons and categorizations that are made possible. Participants made downward comparisons which focused on people with learning difficulties who were less able or who displayed challenging behaviour, and with people who did not have learning difficulties but who, according to the participants, behaved badly, such as beggars, drunks and thieves. By selection of dimensions and comparison others, a positive sense of self and a particular set of social categorizations were presented. It is suggested that when using self-categorization theory to study real-world social categories, more attention needs to be paid to the involvement of the perceiver in determining which stimuli are psychologically relevant since this is a crucial determinant of category salience.

Adolescent↗

PubMed1997

A volumetric approach to virtual simulation of functional endoscopic sinus surgery.

Advanced display technologies have made the virtual exploration of relatively complex models feasible in many applications. Unfortunately, only a few human interfaces allow natural interaction with the environment. Moreover, in surgical applications, such realistic interaction requires real-time rendering of volumetric data-placing an overwhelming performance burden on the system. We report on a collaboration of an interdisciplinary group developing a virtual reality system that provides intuitive interaction with volume data by employing real-time volume rendering and force feedback (haptic) sensations. We describe our rendering methods and the haptic devices and explain its utility of this system in the real-world application of Endoscopic Sinus Surgery (ESS) simulation.

Computer Simulation↗

PubMed2000

Intelligent aids for parallel experiment planning and macromolecular crystallization.

This paper presents a framework called Parallel Experiment Planning (PEP) that is based on an abstraction of how experiments are performed in the domain of macromolecular crystallization. The goal in this domain is to obtain a good quality crystal of a protein or other macromolecule that can be X-ray diffracted to determine three-dimensional structure. This domain presents problems encountered in real-world situations, such as a parallel and dynamic environment, insufficient resources and expensive tasks. The PEP framework comprises of two types of components: (1) an information management system for keeping track of sets of experiments, resources and costs; and (2) knowledge-based methods for providing intelligent assistance to decision-making. The significance of the developed PEP framework is three-fold--(a) the framework can be used for PEP even without one of its major intelligent aids that simulates experiments, simply by collecting real experimental data; (b) the framework with a simulator can provide intelligent assistance for experiment design by utilizing existing domain theories; and (c) the framework can help provide strategic assessment of different types of parallel experimentation plans that involve different tradeoffs.

Animals↗