On risk, rationality and the predictive ability of European short-term adjusted yield spreads

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

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PCA Forecast Averaging—Predicting Day-Ahead and Intraday Electricity Prices

Energies ◽

10.3390/en13143530 ◽

2020 ◽

Vol 13 (14) ◽

pp. 3530

Author(s):

Katarzyna Maciejowska ◽

Bartosz Uniejewski ◽

Tomasz Serafin

Keyword(s):

Predictive Accuracy ◽

Expert Knowledge ◽

Predictive Ability ◽

Principal Component ◽

Absolute Error ◽

Electricity Prices ◽

Short Term ◽

White Test ◽

The Mean ◽

Short Term Forecasting

Recently, the development in combining point forecasts of electricity prices obtained with different length of calibration windows have provided an extremely efficient and simple tool for improving predictive accuracy. However, the proposed methods are strongly dependent on expert knowledge and may not be directly transferred from one to another model or market. Hence, we consider a novel extension and propose to use principal component analysis (PCA) to automate the procedure of averaging over a rich pool of predictions. We apply PCA to a panel of over 650 point forecasts obtained for different calibration windows length. The robustness of the approach is evaluated with three different forecasting tasks, i.e., forecasting day-ahead prices, forecasting intraday ID3 prices one day in advance, and finally very short term forecasting of ID3 prices (i.e., six hours before delivery). The empirical results are compared using the Mean Absolute Error measure and Giacomini and White test for conditional predictive ability (CPA). The results indicate that PCA averaging not only yields significantly more accurate forecasts than individual predictions but also outperforms other forecast averaging schemes.

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Efficacy of VBHOM to Predict Outcome Following Major Lower Limb Amputation

Vascular and Endovascular Surgery ◽

10.1177/1538574412445600 ◽

2012 ◽

Vol 46 (5) ◽

pp. 369-373 ◽

Cited By ~ 3

Author(s):

Andrew J. Patterson ◽

Andrew J. Degnan ◽

Stewart R. Walsh ◽

Mohammed Eltayeb ◽

Earl F. Scout ◽

...

Keyword(s):

Lower Limb ◽

White Cell Count ◽

Predictive Ability ◽

Lower Limb Amputation ◽

Limb Amputation ◽

Stepwise Logistic Regression ◽

Short Term ◽

Sodium Potassium ◽

Lack Of Fit ◽

Short Term Mortality

Purpose: This study tests an existing Vascular Biochemistry and Haematology Outcome Model (VBHOM) on independent data and presents further refinements to the model. Methods: Data from 306 patients who underwent lower limb amputation over a 4-year period were collated. Urea, creatinine, sodium, potassium, hemoglobin, white cell count, albumin, age, gender, mode-of-admission, and short-term mortality events were extracted from the database. This study tests an existing model and trains a new model for predicting mortality using forward stepwise logistic regression. Results: The existing model suggests a significant lack of fit (c-index = 0.665, P = .04). For the exception of gender and mode-of-admission, all predictor variables had significant univariate associations with short-term mortality ( P < .05). The refined model included age, sodium, potassium, creatinine, and albumin and had good discriminatory power (c-index = 0.8, no evidence of lack of fit, P = .616). Conclusions: Our simplified model had good predictive ability and suggests redundancy in input variables used by the existing models.

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Do cancer-specific variables improve risk-adjusted hospital quality comparisons?

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.4_suppl.585 ◽

2012 ◽

Vol 30 (4_suppl) ◽

pp. 585-585 ◽

Cited By ~ 1

Author(s):

Ryan P. Merkow ◽

Thomas E. Kmiecik ◽

David J Bentrem ◽

Mark E Cohen ◽

Bruce L Hall ◽

...

Keyword(s):

Neoadjuvant Therapy ◽

Colorectal Resection ◽

Predictive Ability ◽

Hospital Quality ◽

Short Term ◽

Combined Model ◽

Related Factors ◽

Fit Statistics ◽

C Statistic ◽

Improved Model

585 Background: For patients undergoing surgery for cancer, it has been suggested that risk-adjustment with cancer-specific variables is needed when evaluating short-term outcomes. Our objectives were to assess the influence of cancer-related variables on postoperative complications and hospital quality comparisons. Methods: Patients from ACS NSQIP and NCDB who underwent colorectal resection for cancer were linked (2006-2008) to create a dataset containing robust information on comorbidities, complications, and oncologic variables. Three hierarchical models were developed predicting the NSQIP outcome 30-day mortality or any serious morbidity using variables from (1) NSQIP only, (2) NCDB only, and (3) a combined model using NSQIP and NCDB. Models were compared with fit statistics and hospital outlier agreement. Results: From 146 NSQIP hospitals, 11401 patients underwent a colorectal resection for cancer, of which, 1954 (17%) experienced a mortality or serious morbidity event. The first five variables selected in the NCDB-only model were Charlson comorbidity score, neoadjuvant therapy use, T stage, primary payer, and M stage (c-statistic, 0.64; AIC, 9886). The first five variables selected in the NSQIP-only model were ASA class, preop sepsis, albumin, surgical procedure, and COPD (c-statistic, 0.66; AIC, 9787). In the combined model, neoadjuvant therapy use was the only cancer-specific variable selected in the top five. The remaining variables were ASA class, preop sepsis, albumin, and wound class (c-statistic, 0.67; AIC, 9455). At the hospital-level, the NCDB-only model identified three high outliers (worse than expected) and one low outlier (better than expected). Both the NSQIP-only and combined models identified the same four high and two low outlying hospitals (kappa: 1.0), which agreed marginally with the NCDB-only model (kappa: 0.59). Conclusions: Addition of cancer-specific variables to NSQIP models slightly improved model fit; however, hospital outcome comparisons were identical. For patients with colorectal cancer undergoing resection, cancer-related factors have limited predictive ability for short-term outcomes and did not influence hospital quality comparisons.

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Insolvency or Liquidity Squeeze? Explaining Very Short-Term Corporate Yield Spreads

SSRN Electronic Journal ◽

10.2139/ssrn.347321 ◽

2003 ◽

Cited By ~ 5

Author(s):

Daniel M. Covitz ◽

Chris T. Downing

Keyword(s):

Short Term ◽

Yield Spreads

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Perfusion Index Trajectory Analysis: Predictive Ability for Short-Term Complications in Preterm Newborns

Neonatology & Clinical Pediatrics ◽

10.24966/ncp-878x/100067 ◽

2021 ◽

Vol 8 (1) ◽

pp. 1-8

Author(s):

Julián Alfredo Fernández-Niño ◽

Keyword(s):

Trajectory Analysis ◽

Predictive Ability ◽

Perfusion Index ◽

Behavior Patterns ◽

Short Term ◽

Trajectory Model ◽

Clinical Complications ◽

Preterm Newborns

The aim of this study was to determine the predictability of clinical complications by analyzing the perfusion index historical behavior patterns with polynomial group-based trajectory model.

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Technical trading revisited: evidence from the Asian stock markets

Corporate Ownership and Control ◽

10.22495/cocv11i2c5p6 ◽

2014 ◽

Vol 11 (2) ◽

pp. 511-532 ◽

Cited By ~ 1

Author(s):

Thorben Lubnau ◽

Neda Todorova

Keyword(s):

Transaction Costs ◽

Moving Average ◽

Predictive Ability ◽

Excess Returns ◽

Short Term ◽

Technical Trading ◽

Developed Markets ◽

Stock Indices ◽

Bootstrap Tests

We examine the forecasting power and profitability of moving average (MA) and trading range break (TRB) rules for the daily prices of ten Asian stock indices from January 1990 to September 2012 using bootstrap tests. The results confirm the predictive ability of MA rules whereas the picture uncovered by the TRB rules is more mixed. The MA rules consistently generate positive excess returns after transaction costs, with highest magnitudes often achieved for less developed markets. However, more developed markets surprisingly seem to be far from informationally efficient as well. Furthermore, short-term variants of the trading rules outperform systematically long-term variants.

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Amino Acids and Lipids Associated with Long-Term and Short-Term Red Meat Consumption in the Chinese Population: An Untargeted Metabolomics Study

Nutrients ◽

10.3390/nu13124567 ◽

2021 ◽

Vol 13 (12) ◽

pp. 4567

Author(s):

Fangxu Guan ◽

Wenwen Du ◽

Jiguo Zhang ◽

Chang Su ◽

Bing Zhang ◽

...

Keyword(s):

Amino Acids ◽

Prediction Model ◽

Chinese Population ◽

Characteristic Curve ◽

Predictive Ability ◽

Red Meat ◽

Short Term ◽

Nutrition Survey ◽

Negatively Associated

Red meat (RM) consumption is correlated with multiple health outcomes. This study aims to identify potential biomarkers of RM consumption in the Chinese population and evaluate their predictive ability. We selected 500 adults who participated in the 2015 China Health and Nutrition Survey and examined their overall metabolome differences by RM consumption by using elastic-net regression, then evaluate the predictivity of a combination of filtered metabolites; 1108 metabolites were detected. In the long-term RM consumption analysis 12,13-DiHOME, androstenediol (3α, 17α) monosulfate 2, and gamma-Glutamyl-2-aminobutyrate were positively associated, 2-naphthol sulfate and S-methylcysteine were negatively associated with long-term high RM consumption, the combination of metabolites prediction model evaluated by area under the receiver operating characteristic curve (AUC) was 70.4% (95% CI: 59.9–80.9%). In the short-term RM consumption analysis, asparagine, 4-hydroxyproline, and 3-hydroxyisobutyrate were positively associated, behenoyl sphingomyelin (d18:1/22:0) was negatively associated with short-term high RM consumption. Combination prediction model AUC was 75.6% (95% CI: 65.5–85.6%). We identified 10 and 11 serum metabolites that differed according to LT and ST RM consumption which mainly involved branch-chained amino acids, arginine and proline, urea cycle and polyunsaturated fatty acid metabolism. These metabolites may become a mediator of some chronic diseases among high RM consumers and provide new evidence for RM biomarkers.

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Preoperative Controlling Nutritional Status (CONUT) Score Predicts Short-Term Surgical Prognosis in Patients with Gastric Cancer After Laparoscopy-Assisted Radical Gastrectomy

10.21203/rs.3.rs-53990/v1 ◽

2020 ◽

Author(s):

Yun Qian ◽

Huaying Liu ◽

Junhai Pan ◽

Weihua Yu ◽

Jiemin Lv ◽

...

Keyword(s):

Gastric Cancer ◽

Multivariate Analysis ◽

Postoperative Complications ◽

Nutritional Status ◽

Assessment Tool ◽

Predictive Ability ◽

Short Term ◽

Optimal Cutoff ◽

Cutoff Value ◽

Conut Score

Abstract Background: The Controlling Nutritional Status (CONUT) score is an emerging nutrition assessment tool that is very useful in patients with gastric cancer who usually experience weight loss and malnutrition. The aim of our study was to assess the predictive ability of the preoperative CONUT score for short-term prognosis in patients with gastric cancer undergoing laparoscopy-assisted gastrectomy.Methods: We retrospectively reviewed medical records of 309 patients who underwent curative laparoscopy-assisted gastrectomy. The patients were divided into two groups according to the optimal cutoff value of the CONUT score. The clinical association for the CONUT score, characteristics, and postoperative complications were evaluated and analyzed. The risk factors for complications were identified by univariate and multivariate analysis.Results: The preoperative CONUT score showed a good predictive ability for postoperative complications (AUC=0.718，Youden index=0.343)，with an optimal cutoff value of 2.5. The patients with high CONUT scores had a higher incidence of overall complications (P<0.001) and mild complications (P<0.001). Univariate and multivariate analysis revealed that the CONUT score was independently associated with postoperative complications (P=0.012；OR=2.433；95%CI：1.218-4.862).Conclusions：The preoperative CONUT score was identified as a reliable nutritional assessment tool for predicting short-term prognosis in patients with gastric cancer after laparoscopy-assisted gastrectomy.

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