Learned Irrelevance and Cue Competition Using an Eriksen Flanker Task

2016 ◽  
Vol 63 (5) ◽  
pp. 287-296 ◽  
Author(s):  
Melissa Tapia ◽  
Kirkwood Meyers ◽  
Rachel Richardson ◽  
Rodica Ghinescu ◽  
Todd R. Schachtman
Keyword(s):  
Predictive Value ◽  
Flanker Task ◽  
Predictive Ability ◽  
Cue Competition ◽  
Learning Research ◽  
Learned Irrelevance

Abstract. Many studies have examined competition between cues for learning. Research examining cue competition has used cues that predict the occurrence of an outcome, or, in some rare cases, competition between cues that predict the absence of an outcome (predicting that an outcome explicitly will not occur). Alternatively, learned irrelevance occurs when a cue lacks the ability to predict the occurrence or absence of an outcome. Using an Eriksen flanker task, the present study evaluated competition among cues that do not have predictive value, that is, competition for learning that an outcome is unpredictable. Subjects’ inability to predict the occurrence of compatible and incompatible trials was manipulated by presenting cues that were uncorrelated with these trial types. Accuracy results showed competition between cues possessing a lack of predictive ability. The results are discussed in terms of propositional and associative theories of learning.

Predicting the risk of respiratory distress in newborns with congenital pulmonary malformations

2021 ◽  
pp. 2100949
Author(s):  
Christophe Delacourt ◽  
Nathalie Bertille ◽  
Laurent J. Salomon ◽  
Makan Rashenas ◽  
Alexandra Benachi ◽  
...  
Keyword(s):  
Respiratory Distress ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Volume Ratio ◽  
Predictive Ability ◽  
Population Based ◽  
Term Infants ◽  
Predictive Variable ◽  
Study Results ◽  
Roc Area

ObjectivesMost children with prenatally diagnosed congenital pulmonary malformations (CPM) are asymptomatic at birth. We aimed to develop a parsimonious prognostic model for predicting the risk of neonatal respiratory distress (NRD) in preterm and term infants with CPM, based on the prenatal attributes of the malformation.MethodsMALFPULM is a prospective population-based nationally representative cohort including 436 pregnant women. The main predictive variable was the CPM volume ratio (CVR) measured at diagnosis (CVR first) and the highest CVR measured (CVR max). Separate models were estimated for preterm and term infants and were validated by bootstrapping.ResultsIn total, 67 of the 383 neonates studied (17%) had NRD. For infants born at term (>37 weeks, N=351), the most parsimonious model included CVR max as the only predictive variable (ROC area: 0.70±0.04, negative predictive value: 0.91). The probability of NRD increased linearly with increasing CVR max and remained below 10% for CVR max<0.4. In preterm infants (N=32), both CVR max and gestational age were important predictors of the risk of NRD (ROC area: 0.85±0.07). Models based on CVR first had a similar predictive ability.ConclusionsPredictive models based exclusively on CVR measurements had a high negative predictive value in infants born at term. Our study results could contribute to the individualised general risk assessment to guide decisions about the need for newborns with prenatally diagnosed CPM to be delivered at specialised centers.

Predictive value of short-term migration in determining long-term stable fixation in cemented and cementless total knee arthroplasties

2019 ◽  
Vol 101-B (7_Supple_C) ◽  
pp. 55-60 ◽  
Author(s):  
E. K. Laende ◽  
C. G. Richardson ◽  
M. J. Dunbar
Keyword(s):  
Predictive Value ◽  
Predictive Ability ◽  
Porous Metal ◽  
Short Term ◽  
Long Term Follow Up ◽  
Total Knee ◽  
Total Point ◽  
Cementless Components

Aims Early implant migration measured with radiostereometric analysis (RSA) has been proposed as a useful predictor of long-term fixation of tibial components in total knee arthroplasty. Evaluation of actual long-term fixation is of interest for cemented components, as well as for cementless fixation, which may offer long-term advantages once osseointegration has occurred. The objective of this study was to compare the long-term migration with one- and two-year migration to evaluate the predictive ability of short-term migration data and to compare migration and inducible displacement between cemented and cementless (porous metal monoblock) components at least ten years postoperatively. Patients and Methods Patients who had participated in RSA migration studies with two-year follow-up were recruited to return for a long-term follow-up, at least ten years from surgery. Two cemented tibial designs from two manufacturers and one porous metal monoblock cementless tibial design were studied. At the long-term follow-up, patients had supine RSA examinations to determine migration and loaded examinations (single leg stance) to determine inducible displacement. In total, 79 patients (54 female) returned, with mean time since surgery of 12 years (10 to 14). There were 58 cemented and 21 cementless tibial components. Results Migration at one year and two years was significantly correlated with long-term migration (p < 0.001). Median migration at the long-term follow-up was 0.6 mm (maximum total point motion; interquartile range (IQR) 0.4 to 0.9) for the cemented group and 0.6 mm (IQR 0.3 to 1.1) for the cementless group with no difference between groups (p = 0.99). Inducible displacement was significantly lower for the cementless components (p < 0.001). Conclusion Long-term migration was strongly correlated with two-year migration. Although long-term migration was not different for cemented or cementless tibial components, inducible displacement at the long-term visit was significantly lower for these cementless components, suggesting superior fixation. These findings support the predictive value of short-term migration in determining long-term fixation. Cite this article: Bone Joint J 2019;101-B(7 Supple C):55–60

scholarly journals Association between clinical risk scores and mortality in atrial fibrillation: Systematic review and network meta-regression of 669,000 patients

2018 ◽  
Vol 27 (6) ◽  
pp. 633-644 ◽  
Author(s):  
Marco Proietti ◽  
Alessio Farcomeni ◽  
Giulio Francesco Romiti ◽  
Arianna Di Rocco ◽  
Filippo Placentino ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Predictive Ability ◽  
Risk Scores ◽  
Clinical Risk ◽  
Increased Risk ◽  
High Negative Predictive Value ◽  
Meta Regression

Aims Many clinical scores for risk stratification in patients with atrial fibrillation have been proposed, and some have been useful in predicting all-cause mortality. We aim to analyse the relationship between clinical risk score and all-cause death occurrence in atrial fibrillation patients. Methods We performed a systematic search in PubMed and Scopus from inception to 22 July 2017. We considered the following scores: ATRIA-Stroke, ATRIA-Bleeding, CHADS2, CHA2DS2-VASc, HAS-BLED, HATCH and ORBIT. Papers reporting data about scores and all-cause death rates were considered. Results Fifty studies and 71 scores groups were included in the analysis, with 669,217 patients. Data on ATRIA-Bleeding, CHADS2, CHA2DS2-VASc and HAS-BLED were available. All the scores were significantly associated with an increased risk for all-cause death. All the scores showed modest predictive ability at five years (c-indexes (95% confidence interval) CHADS2: 0.64 (0.63–0.65), CHA2DS2-VASc: 0.62 (0.61–0.64), HAS-BLED: 0.62 (0.58–0.66)). Network meta-regression found no significant differences in predictive ability. CHA2DS2-VASc score had consistently high negative predictive value (≥94%) at one, three and five years of follow-up; conversely it showed the highest probability of being the best performing score (63% at one year, 60% at three years, 68% at five years). Conclusion In atrial fibrillation patients, contemporary clinical risk scores are associated with an increased risk of all-cause death. Use of these scores for death prediction in atrial fibrillation patients could be considered as part of holistic clinical assessment. The CHA2DS2-VASc score had consistently high negative predictive value during follow-up and the highest probability of being the best performing clinical score.

Abstract T P113: Orpington Prognostic Scale: A Predictive Tool for Discharge Outcome in a Hyper Acute Stroke Unit

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
Sushmita Mohapatra ◽  
Amy M Jones
Keyword(s):  
Acute Stroke ◽  
Predictive Value ◽  
Stroke Unit ◽  
Predictive Ability ◽  
Inpatient Setting ◽  
Discharge Destination ◽  
Predictive Tool ◽  
Co Morbidity ◽  
Acute Stroke Unit ◽  
Rehabilitation Needs

Introduction: An accurate assessment of the severity of impairment and prediction of prognosis following stroke is important for determining rehabilitation needs of stroke patients. The study investigated the predictive ability of the Orpington Prognostic Scale (OPS) administered within 72 hours of stroke onset, in determining discharge destination post admission to a Hyper Acute Stroke Unit (HASU) in the United Kingdom. Method: Prospective analysis of OPS data were collected from 247 patients with confirmed diagnosis of stroke admitted to HASU. OPS scores were recorded between 0 to 72hours of admission and compared to discharge destination at 72 hours. Predictive ability of the tool and association with other variables were analysed using logistic regression and multivariate analysis. Results: Low OPS score (<3.2) had high positive predictive value (PPV 88.63%)for discharge home and high OPS score (>3.2) had high predictive value (PPV 98.39) for patients requiring further inpatient rehabilitation. OPS had high specificity and sensitivity for the above, independent of age, gender, type and site of stroke, stroke severity, previous social support and co-morbidity. Conclusions: OPS could be a valuable tool in predicting the discharge destination from a HASU and thereby facilitate the identification of early rehabilitation needs, 72 hours post stroke by predicting the need for further management. OPS < 3.2 were highly likely to go home with or without support/therapy. Whereas OPS > 3.2 were highly likely to require further medical/therapy input in an inpatient setting.

P1633Age, creatinine, and ejection fraction (ACEF) score continues to predictive prognosis in patients with ischemic cardiomyopathy

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
W Z Chen ◽  
P Ran ◽  
A P Cai
Keyword(s):  
Ejection Fraction ◽  
Predictive Value ◽  
Ischemic Cardiomyopathy ◽  
Malignant Tumors ◽  
Predictive Ability ◽  
Adverse Outcomes ◽  
Cardiac Mortality ◽  
Elective Cardiac Surgery ◽  
All Cause Mortality

Abstract Purpose ACEF (Age, Creatinine, and Ejection Fraction) andACEFMDRD (Modification of Diet in Renal Disease) score have been validated as effective predictors for prognosis in patients undergoing elective cardiac surgery or PCI. However, the predictive value for ICM (Ischemic Cardiomyopathy)was not clear. This study sought to investigate their predictive value in patients with ICM. Methods 862 ICM patients hospitalized in the Department of Cardiology were prospectively enrolled during November 2014 and December 2017.Inclusion criteria: previous definite diagnosis of myocardial infarction, previous PCI, CABG, or coronary angiographic findings of one or more vessel stenosis >70%; Simpson echocardiography showed LVEF <45%. Exclusion criteria: malignant tumors of any organ or once had a history of malignancies; and other serious diseases with estimated survival time less than one year.The ACEF score was calculated by the formula: age/ejection fraction + 1 (if creatinine >176 μmol/L). As for ACEFMDRD score, estimated glomerular filtration rate (eGFR) was calculated using the MDRD formula. Then using the formula: age/EF +1 point for every 10 mL/min reduction in eGFRMDRD below 60 ml/min per 1.73 m2 (up to a maximum of 6 points). Patients were divided into low, middle and high ACEF, ACEFMDRD tertiles. The median duration of follow-up was 13 months (IQR: 7–23 months). The clinical endpoints were all-cause mortality, cardiac mortality, major adverse cardiovascular and cerebrovascular events (MACCEs) and re-hospitalization for heart failure (HF). Results The mean original ACEF and ACEFMDRD score were 1.99±0.63 and 2.53±1.42. Patients in high ACEF and ACEFMDRD tertile were associated with significantly higher all-cause and cardiac mortality, MACCEs and re-hospitalization for HF. Compared with ACEFMDRD score, original ACEF exhibited similar discrimination and predictive ability on all-cause mortality (AUC: 0.739 vs. 0.724, P=0.567), cardiac mortality (AUC: 0.733 vs. 0.717, P=0.525), MACCEs (AUC: 0.635 vs. 0.624, P=0.587) and rehospitalizaiotn (AUC: 0.642 vs. 0.632, P=0.757). In multivariate Cox analysis, the original ACEF or ACEFMDRD score were related with increasing risks of all-cause mortality (HR: 2.00 vs. 1.32, 95% CI: 1.46–2.73 vs. 1.13–1.53, P<0.001), cardiac mortality (HR: 1.97 vs. 1.28, 95% CI: 1.43–2.70 vs. 1.10–1.50, P<0.001 vs. P=0.002), MACCEs and re-hospitalization for HF, respectively. ROC curves of cardiac mortality Conclusions In patients with ICM, the original ACEF and ACEFMDRD score are independent predictors of adverse outcomes during 13-month follow-up, respectively. Acknowledgement/Funding None

scholarly journals Heart Score for Predicting in Hospital Major Cardiovascular Event in Patient with Non ST Segment Elevation Acute Coronary Syndrome

2020 ◽  
Vol 6 (2) ◽  
pp. 85-90
Author(s):  
Kamal Kharrazi Ilyas ◽  
Sutomo Kasiman ◽  
Harris Hasan ◽  
Zulfikri Mukhtar ◽  
Refli Hasan ◽  
...  
Keyword(s):  
Acute Coronary Syndrome ◽  
General Hospital ◽  
Cardiovascular Event ◽  
Roc Curve ◽  
Predictive Value ◽  
Predictive Ability ◽  
St Segment Elevation ◽  
Heart Score ◽  
Coronary Syndrome ◽  
St Segment

Background: Acute Coronary Syndrome (ACS) is one of the main problems in the field of cardiovascular diseases because of high hospitalization rate, high mortality and high medical cost. Rapid and accurate risk stratification is needed to calculate the risk of complication and right now exist two most used score which is GRACE and TIMI. Heart score has 5 simple variables that can be calculated easily and this score considered to have better predictive ability compared to other score. The aim of this study is to examine HEART score as a predictor for in hospital Major Cardiovascular Event (MACE) in patient diagnosed as Non ST Segment Elevation Acute Coronary Syndrome (NSTEACS) that hospitalized at Haji Adam Malik (HAM) General Hospital Medan. Methods: This is a prospective cohort study that includes 52 NSTEACS patient that hospitalized at HAM General Hospital since November 2018 until January 2019. Patient that diagnosed as NSTEACS were calculated for GRACE, TIMI, and HEART score then observed during hospitalization. Outcome of this study is MACE during hospitalization. Statistical analysis was performed to test HEART score as MACE predictor and then comparison was done with GRACE and TIMI Results: By using ROC curve analysis, the cut-off value of HEART score was 5 (AUC 0.947, 95% CI 0.883-0.997, p<0.01). Study subject that experienced MACE with HEART score ≥5 was 21 patients (87.5%) compared to 2 patients (7.1%). HEART score ≥5 can predict MACE with sensitivity 87.5%, specificity 92.9%, negative predictive value (NPV) 89.7% and positive predictive value (PPV) 91.3%. ROC curve comparison was done between HEART with GRACE and TIMI then it was found that HEART score has better predictive ability compared to TIMI and GRACE (AUC 0.947 vs 0.829 vs 0.807, p < 0.01). Conclusion: HEART score can be used as MACE predictor which is relatively simpler but have better predictive ability compared to GRACE and TIMI.

scholarly journals Predicting asthma-related crisis events using routine electronic healthcare data

2021 ◽  
pp. BJGP.2020.1042
Author(s):  
Michael Noble ◽  
Annie Burden ◽  
Susan Stirling ◽  
Allan Clark ◽  
Stanley Musgrave ◽  
...  
Keyword(s):  
High Risk ◽  
Predictive Value ◽  
External Validation ◽  
Predictive Ability ◽  
Prediction Algorithm ◽  
Validation Dataset ◽  
Practice Research ◽  
Clinical Practice Research Datalink ◽  
Healthcare Data ◽  
Crisis Events

Background: There is no published algorithm predicting asthma crisis events (Accident and Emergency (A&E) attendance, hospitalisation or death) using routinely available electronic health record (EHR) data. Aim: To develop an algorithm to identify individuals at high risk of an asthma crisis event. Design and Setting: Database analysis from primary care EHRs. Method: Multivariable logistic regression was applied to a dataset of 61,861 people with asthma from England and Scotland using the Clinical Practice Research Datalink. External validation was performed using the Secure Anonymised Information Linkage databank of 174,240 patients from Wales. Outcomes were one or more hospitalisation (development dataset) and asthma-related hospitalisation, A&E attendance or death (validation dataset) within a 12-month period. Results: Risk factors for asthma-related crisis events included previous hospitalisation, older age, underweight, smoking and blood eosinophilia. The prediction algorithm had acceptable predictive ability with a Receiver Operating Characteristic (ROC) of 0.71 (0.70, 0.72) in the validation dataset. Using a cut-point based on the 7% of the population at greatest risk results in a positive predictive value of 5.7% (95% CI 5.3 – 6.1) and a negative predictive value of 98.9% (98.9 – 99.0), with sensitivity of 28.5% (26.7 – 30.3) and specificity of 93.3% (93.2 – 93.4); they had an event risk of 6.0% compared 1.1% for the remaining population. Eighteen people would be “needed to follow” to identify one admission. Conclusions: This externally validated algorithm has acceptable predictive ability for identifying patients at high risk of asthma-related crisis events and excluding individuals not at high risk.

scholarly journals Predictive Value of Albumin-Bilirubin Grade For Intravenous Immunoglobulin Resistance In A Large Cohort Of Patients With Kawasaki Disease: A Prospective Study

2021 ◽  
Author(s):  
Yu Yan ◽  
Lina Qiao ◽  
Shuran Shao ◽  
Nanjun Zhang ◽  
Mei Wu ◽  
...  
Keyword(s):  
Risk Factor ◽  
Kawasaki Disease ◽  
Intravenous Immunoglobulin ◽  
Predictive Value ◽  
Independent Risk Factor ◽  
Laboratory Data ◽  
Multivariate Logistic Regression Analysis ◽  
Predictive Ability ◽  
Ivig Infusion ◽  
Ivig Resistance

Abstract Background: Intravenous immunoglobulin (IVIG) resistance, which defined that Kawasaki disease (KD) patients have recrudescence fever more than 36 hours after IVIG infusion, and its prediction is one of the primary clinical issues and study hotspots in KD. This study aimed to prospectively investigated the value of albumin-bilirubin grade (ALBI) in predicting IVIG resistance in KD, and assessed whether ALBI has more predictive value or accuracy than either ALB or TBil alone in predicting IVIG resistance.Methods: A total of 823 patients with KD were prospectively enrolled. The clinical and laboratory data were compared between IVIG-response group (n=708) and IVIG-resistance group (n=115). Multivariate logistic regression analysis was performed to identify the independent risk factors of IVIG resistance. Receiver operating characteristic (ROC) curves analysis was applied to assess the validity of ALBI, ALB, and TBil in predicting IVIG resistance. Results: ALBI was significantly higher in patients with IVIG resistance and was identified as an independent risk factor for IVIG resistance in KD. The parameter of ALBI ≥ –2.57 (AUC: 0.705, 95%CI: 0.672–0.736), ALB ≤ 33.0g/L (AUC: 0.659, 95%CI: 0.626–0.692), and TBil ≥16.0μmol/L (AUC: 0.626, 95%CI: 0.592–0.659), produced a sensitivity, specificity, PPV, and NPV of 0.617, 0.657, 0.226, 0.914, and 0.651; 0.374, 0.850, 0.289, 0.893, and 0.783; 0.269, 0.941, 0.425, 0.888, and 0.847, respectively.Conclusion: A higher ALBI was an independent risk factor for IVIG resistance. It yielded better predictive ability than ALB and TBil alone for initial IVIG resistance.

Predicting Postthyroidectomy Hypocalcemia: Improving Predictive Ability of Parathyroid Hormone Level

2020 ◽  
Vol 86 (2) ◽  
pp. 121-126 ◽  
Author(s):  
Veljko Strajina ◽  
Benzon M. Dy ◽  
Travis J. Mckenzie ◽  
Geoffrey B. Thompson ◽  
Melanie L. Lyden
Keyword(s):  
Parathyroid Hormone ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Calcium Level ◽  
Predictive Ability ◽  
Postoperative Hypocalcemia ◽  
Total Blood ◽  
Blood Calcium ◽  
Large Patient ◽  
Pth Level

We performed a retrospective study of our large patient cohort aiming to examine the ability to predict postthyroidectomy hypocalcemia. A retrospective review of patients who underwent total or near-total thyroidectomy at our institution between 2008 and 2018 was performed. Postoperative hypocalcemia was defined as Ca level <8.0 mg/dL (reference range: 8.9–10.1 mg/dL) within 30 days of operation. Logistic regression was used to develop models for prediction of the occurrence of postoperative hypocalcemia. Inclusion criteria were met by 1463 patients. Hypocalcemia was documented in 223 patients (15%). Models based on parathyroid hormone (PTH) levels alone had an associated receiver operator characteristic with an areas under the curve (AUC) of 0.79. There was an inverse relationship between time of measurement and PTH levels within the first two hours after thyroidectomy ( P < 0.01). When measured two to six hours after closure, the predictive ability of PTH compared favorably (AUC = 0.82) with either earlier (within the first two hours after closure, AUC = 0.79) or later measurement (6–24 hours after closure, AUC = 0.77). When measured between two and six hours postoperatively, PTH < 19 pg/mL had a sensitivity of 90 per cent and negative predictive value of 96 per cent for postoperative hypocalcemia. The model that included the PTH level, concurrently measured total blood calcium level, and time of measurement had an improved predictive ability with an AUC of 0.87. PTH level of 19 pg/mL measured two to six hours after thyroidectomy had a sensitivity of 90 per cent and a negative predictive value of 96 per cent in our cohort. The model including postoperative PTH level, calcium level, and time of measurement may further improve the ability to predict postthyroidectomy hypocalcemia.

scholarly journals Predicting Disease in Transition Dairy Cattle Based on Behaviors Measured Before Calving

Animals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 928
Author(s):  
Mohammad W. Sahar ◽  
Annabelle Beaver ◽  
Marina A. G. von Keyserlingk ◽  
Daniel M. Weary
Keyword(s):  
Dairy Cattle ◽  
Sensitivity And Specificity ◽  
Roc Curve ◽  
Predictive Value ◽  
Predictive Ability ◽  
Training Dataset ◽  
Test Dataset ◽  
Increased Risk ◽  
High Prevalence ◽  
Random Method

Dairy cattle are particularly susceptible to metritis, hyperketonemia (HYK), and mastitis in the weeks after calving. These high-prevalence transition diseases adversely affect animal welfare, milk production, and profitability. Our aim was to use prepartum behavior to predict which cows have an increased risk of developing these conditions after calving. The behavior of 213 multiparous and 105 primiparous Holsteins was recorded for approximately three weeks before calving by an electronic feeding system. Cows were also monitored for signs of metritis, HYK, and mastitis in the weeks after calving. The data were split using a stratified random method: we used 70% of our data (hereafter referred to as the “training” dataset) to develop the model and the remaining 30% of data (i.e., the “test” dataset) to assess the model’s predictive ability. Separate models were developed for primiparous and multiparous animals. The area under the receiver operating characteristic (ROC) curve using the test dataset for multiparous cows was 0.83, sensitivity and specificity were 73% and 80%, positive predictive value (PPV) was 73%, and negative predictive value (NPV) was 80%. The area under the ROC curve using the test dataset for primiparous cows was 0.86, sensitivity and specificity were 71% and 84%, PPV was 77%, and NPV was 80%. We conclude that prepartum behavior can be used to predict cows at risk of metritis, HYK, and mastitis after calving.

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