Stand-alone Predictor Research Articles

Preservice Teachers and Self-Assessing Digital Competence

This study compares matched surveys of subjective self-assessment and objective assessment on seven domains of digital competence for preservice teachers at a large Southwest public university. The results, consistent with earlier studies, confirm that the participating preservice teachers inaccurately self-assessed their digital competence. The study concluded that subjective self-assessment lacks appropriate validity and is not an accurate stand-alone predictor of digital competence among preservice teachers. However, if considered in conjunction with other means, self-assessment may prove to be useful for preservice teachers to aid in their reflection of their competence, skills, and knowledge and to aid them in adjusting their perceptions and attitudes regarding technology throughout their professional practice. In addition, self-assessment in conjunction with other means may assist teacher educators in providing opportunities to improve the competence in teacher training programs.

Validation of the chronic disease score-infectious disease (CDS-ID) for the prediction of hospital-associated clostridium difficile infection (CDI) within a retrospective cohort

BackgroundAggregate comorbidity scores are useful for summarizing risk and confounder control in studies of hospital-associated infections. The Chronic Disease Score – Infectious Diseases (CDS-ID) was developed for this purpose, but it has not been validated for use in studies of Clostridium difficile Infection (CDI). The aim of this study was to assess the discrimination, calibration and potential for confounder control of CDS-ID compared to age alone or individual comorbid conditions.MethodsSecondary analysis of a retrospective cohort study of adult inpatients with 2 or more days of antibiotic exposure at a tertiary care facility during 2005. Logistic regression models were used to predict the development of CDI up to 60 days post-discharge. Model discrimination and calibration were assessed using the c-statistic and Hosmer-Lemeshow (HL) tests, respectively. C-statistics were compared using chi-square tests.ResultsCDI developed in 185 out of 7,792 patients. The CDS-ID was a better standalone predictor of CDI than age (c-statistic 0.653 vs 0.609, P=0.04). The best discrimination was observed when CDS-ID and age were both used to predict CDI (c-statistic 0.680). All models had acceptable calibration (P>0.05).ConclusionThe CDS-ID is a valid tool for summarizing risk of CDI associated with comorbid conditions.

Severity of Asthma Score Predicts Clinical Outcomes in Patients With Moderate to Severe Persistent Asthma

The severity of asthma (SOA) score is based on a validated disease-specific questionnaire that addresses frequency of asthma symptoms, use of systemic corticosteroids, use of other asthma medications, and history of hospitalization/intubation for asthma. SOA does not require measurements of pulmonary function. This study compared the ability of SOA to predict clinical outcomes in the EXCELS (Epidemiological Study of Xolair [omalizumab]: Evaluating Clinical Effectiveness and Long-term Safety in Patients with Moderate to Severe Asthma) patient population vs three other asthma assessment tools. EXCELS is a large, ongoing, observational study of patients with moderate to severe persistent asthma and reactivity to perennial aeroallergens. Baseline scores for SOA, asthma control test (ACT), work productivity and impairment index-asthma (WPAI-A), and FEV(1) % predicted were compared for their ability to predict five prespecified adverse clinical outcomes in asthma: serious adverse events (SAEs) reported as exacerbations, SAEs leading to hospitalizations, the incidence of unscheduled office visits, ED visits, and po or IV corticosteroid bursts related to asthma. Logistic regression analysis, area under receiver operating characteristic curves (AUCROCs), and classification and regression tree (CART) analysis were used to evaluate the ability of the four tools to predict adverse clinical outcomes using baseline and 1-year data from 2,878 patients enrolled in the non-omalizumab cohort of EXCELS. SOA was the only assessment tool contributing significantly in all five statistical models of adverse clinical outcomes by logistic regression analysis (full model AUCROC range, 0.689-0.783). SOA appeared to be a stand-alone predictor for four of five outcomes (reduced model AUCROC range, 0.689-0.773). CART analysis showed that SOA had the greatest variable importance for all five outcomes. SOA score was a powerful predictor of adverse clinical outcomes in moderate to severe asthma, as evaluated by either logistic regression analysis or CART analysis. ClinicalTrials.gov; No.: NCT00252135; URL: www.clinicaltrials.gov.

Is leaf dry matter content a better predictor of soil fertility than specific leaf area?

Specific leaf area (SLA), a key element of the 'worldwide leaf economics spectrum', is the preferred 'soft' plant trait for assessing soil fertility. SLA is a function of leaf dry matter content (LDMC) and leaf thickness (LT). The first, LDMC, defines leaf construction costs and can be used instead of SLA. However, LT identifies shade at its lowest extreme and succulence at its highest, and is not related to soil fertility. Why then is SLA more frequently used as a predictor of soil fertility than LDMC? SLA, LDMC and LT were measured and leaf density (LD) estimated for almost 2000 species, and the capacity of LD to predict LDMC was examined, as was the relative contribution of LDMC and LT to the expression of SLA. Subsequently, the relationships between SLA, LDMC and LT with respect to soil fertility and shade were described. Although LD is strongly related to LDMC, and LDMC and LT each contribute equally to the expression of SLA, the exact relationships differ between ecological groupings. LDMC predicts leaf nitrogen content and soil fertility but, because LT primarily varies with light intensity, SLA increases in response to both increased shade and increased fertility. Gradients of soil fertility are frequently also gradients of biomass accumulation with reduced irradiance lower in the canopy. Therefore, SLA, which includes both fertility and shade components, may often discriminate better between communities or treatments than LDMC. However, LDMC should always be the preferred trait for assessing gradients of soil fertility uncoupled from shade. Nevertheless, because leaves multitask, individual leaf traits do not necessarily exhibit exact functional equivalence between species. In consequence, rather than using a single stand-alone predictor, multivariate analyses using several leaf traits is recommended.

Comment on a new ocular trauma score in pediatric penetrating eye injuries

Sir, We read with interest Acar et al's1 article on their newly proposed paediatric penetrating ocular trauma score (POTS). The authors have designed POTS to be used specifically in paediatric penetrating injuries to prognosticate for future visual acuity (VA) rather than using the more widely recognised but non-specific ocular trauma score (OTS) designed by Kuhn et al2 as part of the United States Eye Injury Registry. We appreciate that the authors felt that the age of the patient and location of the wound were important prognostic factors and so included them in the scoring system. The authors decided to downscale the amount of points scored for initial VA due to problems that were inherently present when trying to obtain an accurate VA in children, especially those with a significant injury. They identified that the POTS was statistically significant in predicting final VA. As the article stands, the authors have not demonstrated any reasons why POTS should be used instead of OTS for paediatric penetrating injuries. VA still needs to be obtained to enter into the POTS system. We therefore suggest two ways in which POTS could be more rigorously tested to demonstrate any benefit. First, the POTS could be calculated without using the VA score. As the authors pointed out, the relationship between initial VA and final VA is statistically significant. It would be interesting to see whether POTS without any VA inclusion gives a statistically significant result or whether it is purely the initial VA prognostic factor that makes POTS statistically significant in predicting final VA. Second, the authors could apply the OTS to their data and compare the two scores directly to identify any benefit of one over the other. Unless a clear benefit of POTS over OTS can be demonstrated, there would be no reason to use POTS preferentially. As the authors demonstrated in their study, VA can usually be obtained in all but the very youngest children, and so it may be that VA is the most important factor and can be used as a stand-alone predictor of final VA.

Determining the economic cost of ICU treatment: a prospective “micro-costing” study

To prospectively assess the cost of patients in an adult intensive care unit (ICU) using bottom-up costing methodology and evaluate the usefulness of "severity of illness" scores in estimating ICU cost. A prospective study costing 64 consecutive admissions over a 2-month period in a mixed medical/surgical ICU. The median daily ICU cost (interquartile range, IQR) was 2,205 euro (1,932 euro-3,073 euro), and the median total ICU cost (IQR) was 10,916 euro (4,294 euro-24,091 euro). ICU survivors had a lower median daily ICU cost at <euro>2,164 per day, compared with 3,496 euro per day for ICU non-survivors (P = 0.08). The requirements for continuous haemodiafiltration, blood products and anti-fungal agents were associated with higher daily and overall ICU costs (P = 0.002). Each point increase in SAPS3 was associated with a 305 euro (95% CI 31 euro-579 euro) increase in total ICU cost (P = 0.029). However, SAPS3 accounted for a small proportion of the variance in this model (R (2) = 0.08), limiting its usefulness as a stand-alone predictor of cost in clinical practice. A model including haemodiafiltration, blood products and anti-fungal agents explained 54% of the variance in total ICU cost. This bottom-up costing study highlighted the considerable individual variation in costs between ICU patients and identified the major factors contributing to cost. As the requirement for expensive interventions was the main driver for ICU cost, "severity of illness" scores may not be useful as stand-alone predictors of cost in the ICU.

Usefulness of Diastolic Dominant Pulmonary Vein Flow to Predict Hospitalization for Heart Failure and Mortality in Ambulatory Patients With Coronary Heart Disease (from the Heart and Soul Study)

Diastolic dysfunction is usually identified by the combination of characteristic mitral and pulmonary vein flow patterns. However, obtaining a complete set of echocardiographic parameters can be technically difficult and data may conflict. We hypothesized that as a stand-alone variable, (ventricular) diastolic dominant pulmonary vein flow would predict heart failure (HF) hospitalizations and cardiovascular death. Standard transthoracic echocardiograms were obtained in 906 subjects from the Heart and Soul Study, a prospective study of the effects of depression on coronary heart disease. Pulmonary vein flow pattern was determined using the dominant velocity-time integral. Cardiac events were determined by 2 independent adjudicators, and Cox proportional hazards models were used. Systolic dominant pulmonary vein flow was present in 89% of subjects, and diastolic dominant, in the remaining 11%. During an average 4.1 years of follow-up, subjects with diastolic dominant pulmonary vein flow had a 25% rate of HF hospitalization and 9% rate of cardiovascular death. After multivariate adjustment including left ventricular ejection fraction, diastolic pulmonary vein flow was associated with a 3-fold risk of HF hospitalization (p = 0.001) and a 2-fold risk of HF hospitalization or death (p = 0.004). In conclusion, diastolic dominant pulmonary vein flow pattern was a stand-alone predictor of adverse cardiac events, and its presence was associated with significantly higher rates of HF hospitalizations and cardiovascular death.

Prediction of cooling time in injection molding by means of a simplified semianalytical equation

AbstractA simplified semianalytical equation, used successfully in food freezing/chilling time prediction, is proposed as a potential simple alternative for cooling time prediction in injection molding of polymer parts, amorphous or semicrystalline. This equation is based on a convective boundary condition for the mold‐part interface and requires information on the thermal contact resistance (TCR) or thermal contact conductance (TCC) at this interface, as well as information on the initial and final product temperatures, the mold surface temperature, and the thermal properties of the part. Eighty‐five data points for four polymers, Polystyrene (PS), Polycarbonate (PC), Polypropylene (PP), and Polyethylene (PE) were generated with C‐MOLD™, a commercial injection molding design software, and the performance of the proposed equation was tested. The % mean error and its standard deviation (SD) in cooling time prediction were, respectively, −11.61 and 2.27 for PS, −6.04 and 2.13 for PC, −7.27 and 6.55 for PP, and −8.88 and 2.93 for PE. It was also shown that the accuracy of the proposed equation is not affected significantly by the exact knowledge of the TCC, provided that the latter is not smaller than 1000–2000 W m−2 K−1. Since in this comparison all necessary temperatures were obtained from C‐MOLD™, methods of using the proposed equation independently were tested. The use of the inlet melt temperature as the initial product temperature increased the % mean error by mostly 1.5% while its SD remained practically the same. By incorporating a literature based heat balance method in the proposed equation, it was possible to use it as a stand‐alone predictor of polymer cooling time. The % mean error and its SD calculated this way were, respectively, −9.44 and 0.97 for PS, −9.44 and 0.83 for PC, −14.22 and 5 for PP, and −20.12 and 1.38 for PE. The proposed equation, at least in a preliminary stage, can be used successfully to predict the cooling time of the selected semicrystalline or amorphous polymers with the accuracy being higher for amorphous polymers. © 2003 Wiley Periodicals, Inc. Adv Polym Techn 22: 188–208, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/adv.10048