Monitoring credit risk in the social economy sector by means of a binary goal programming model

The final publication is available at Springer via http://dx.doi.org/10.1007/s11628-012-0173-7Monitoring the credit risk of firms in the social economy sector presents a considerable challenge, since it is difficult to calculate ratings with traditional methods such as logit or discriminant analysis, due to the relatively small number of firms in the sector and the low default rate among cooperatives. This paper intro- duces a goal programming model to overcome such constraints and to successfully manage credit risk using economic and financial information, as well as expert advice. After introducing the model, its application to a set of Spanish cooperative societies is described.García García, F.; Guijarro Martínez, F.; Moya Clemente, I. (2013). Monitoring credit risk in the social economy sector by means of a binary goal programming model. Service Business. 7(3):483-495. doi:10.1007/s11628-012-0173-7S48349573Alfares H, Duffuaa S (2009) Assigning cardinal weights in multi-criteria decision making based on ordinal rankings. J Multicriteria Decis Anal 15:125–133Altman EI (1968) Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J Financ 23:589–609Altman EI, Hadelman RG, Narayanan P (1977) Zeta analysis: a new model to identify bankruptcy risk of corporations. J Bank Financ 1:29–54Andenmatten A (1995) Evaluation du risque de défaillance des emetteurs d’obligations: Une approche par l’aide multicritère á la décision. Presses Polytechniques et Univertitaires Romandes, LausanneBeaver WH (1966) Financial ratios as predictors of failure. J Account Res 4:71–111Boritz JE, Kennedey DB (1995) Effectiveness of neural network types for prediction of business failure. Expert Syst Appl 9:503–512Bottomley P, Doyle J, Green R (2000) Testing the reliability of weight elicitation methods: direct rating versus point allocation. J Mark Res 37:508–513Casey M, McGee V, Stinkey C (1986) Discriminating between reorganized and liquidated firms in bankruptcy. Account Rev 61:249–262Cruz S, Gonzalez T, Perez C (2010) Marketing capabilities, stakeholders’ satisfaction, and performance. Serv Bus 4:209–223Díaz M, Marcuello C (2010) Impacto económico de las cooperativas. La generación de empleo en las sociedades cooperativas y su relación con el PIB. CIRIEC 67:23–44Dimitras AI, Zopounidis C, Hurson C (1995) A multicriteria decision aid method for the assessment of business failure risk. Found Comput Decis Sci 20:99–112Dimitras AI, Slowinski R, Susmaga R, Zopounidis C (1999) Business failure prediction using rough sets. Eur J Oper Res 114:263–280Elmer PJ, Borowski DM (1988) An expert system approach to financial analysis: the case of S&L bankruptcy. Financ Manage 17:66–76Frydman H, Altman EI, Kao DL (1985) Introducing recursive partitioning for financial classification: the case of financial distress. J Financ 40:269–291García F, Guijarro F, Moya I (2008) La valoración de empresas agroalimentarias: una extensión de los modelos factoriales. Rev Estud Agro-Soc 217:155–181Gupta MC, Huefner RJ (1972) A cluster analysis study of financial ratios and industry characteristics. J Account Res 10:77–95Jensen RE (1971) A cluster analysis study of financial performance of selected firms. Account Rev 16:35–56Juliá J (2011) Social economy: a responsible people-oriented economy. Serv Bus 5:173–175Keasey K, Mcguinnes P, Short H (1990) Multilogit approach to predicting corporate failure: further analysis and the issue of signal consistency. Omega-Int J Manage S 18:85–94Li H, Adeli H, Sun J, Han JG (2011) Hybridizing principles of TOPSIS with case-based reasoning for business failure prediction. Comput Oper Res 38:409–419Luoma M, Laitinen EK (1991) Survival analysis as a tool for firm failure prediction. Omega-Int J Manage S 19:673–678March I, Yagüe RM (2009) Desempeño en empresas de economía social. Un modelo para su medición. CIRIEC 64:105–131Martin D (1977) Early warning of bank failure: a logit regression approach. J Bank Financ 1:249–276Mateos A, Marín M, Marí S, Seguí E (2011) Los modelos de predicción del fracaso empresarial y su aplicabilidad en cooperativas agrarias. CIRIEC 70:179–208McKee T (2000) Developing a bankruptcy prediction model via rough sets theory. Int J Intell Syst Account Finan Manage 9:159–173Messier WF, Hansen JV (1988) Inducing rules for expert system development: an example using default and bankruptcy data. Manage Sci 34:1403–1415Ohlson JA (1980) Financial ratios and the probabilistic prediction of bankruptcy. J Account Res 18:109–131Peel MJ (1987) Timeliness of private firm reports predicting corporate failure. Invest Anal J 83:23–27Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New YorkScapens RW, Ryan RJ, Flecher L (1981) Explaining corporate failure: a catastrophe theory approach. J Bus Finan Account 8:1–26Skogsvik R (1990) Current cost accounting ratios as predictors of business failures: the Swedish case. J Bus Finan Account 17:137–160Slowinski R, Zopounidis C (1995) Application of the rough set approach to evaluation of bankruptcy risk. Int J Intell Syst Account Finan Manage 4:24–41Vranas AS (1992) The significance of financial characteristics in predicting business failure: an analysis in the Greek context. Found Comput Decis Sci 17:257–275Westgaard S, Wijst N (2001) Default probabilities in a corporate bank portfolio: a logistic model approach. Eur J Oper Res 135:338–349Wilson RL, Sharda R (1994) Bankruptcy prediction using neuronal networks. Decis Support Syst 11:545–557Zavgren CV (1985) Assessing the vulnerability to failure of American industrial firms. A logistic analysis. J Bus Financ Account 12:19–45Zmijewski M (1984) Methodological issues related to the estimation of financial distress prediction models. Studies on Current Econometric Issues in Accounting Research. J Account Res 22:59–86Zopounidis C, Doumpos M (2002) Multicriteria classification and sorting methods: a literature review. Eur J Oper Res 138:229–24

Combined clinical and genomic signatures for the prognosis of early stage non-small cell lung cancer based on gene copy number alterations

BACKGROUND: The development of a more refined prognostic methodology for early non-small cell lung cancer (NSCLC) is an unmet clinical need. An accurate prognostic tool might help to select patients at early stages for adjuvant therapies. RESULTS: A new integrated bioinformatics searching strategy, that combines gene copy number alterations and expression, together with clinical parameters was applied to derive two prognostic genomic signatures. The proposed methodology combines data from patients with and without clinical data with a priori information on the ability of a gene to be a prognostic marker. Two initial candidate sets of 513 and 150 genes for lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively, were generated by identifying genes which have both: a) significant correlation between copy number and gene expression, and b) significant prognostic value at the gene expression level in external databases. From these candidates, two panels of 7 (ADC) and 5 (SCC) genes were further identified via semi-supervised learning. These panels, together with clinical data (stage, age and sex), were used to construct the ADC and SCC hazard scores combining clinical and genomic data. The signatures were validated in two independent datasets (n = 73 for ADC, n = 97 for SCC), confirming that the prognostic value of both clinical-genomic models is robust, statistically significant (P = 0.008 for ADC and P = 0.019 for SCC) and outperforms both the clinical models (P = 0.060 for ADC and P = 0.121 for SCC) and the genomic models applied separately (P = 0.350 for ADC and P = 0.269 for SCC). CONCLUSION: The present work provides a methodology to generate a robust signature using copy number data that can be potentially used to any cancer. Using it, we found new prognostic scores based on tumor DNA that, jointly with clinical information, are able to predict overall survival (OS) in patients with early-stage ADC and SCC

Evaluation of iron status in European adolescents through biochemical iron indicators: the HELENA Study

BACKGROUND/OBJECTIVES: To assess the iron status among European adolescents through selected biochemical parameters in a cross-sectional study performed in 10 European cities. SUBJECTS/METHODS: Iron status was defined utilising biochemical indicators. Iron depletion was defined as low serum ferritin (SF8.5 mg/l) plus iron depletion. Iron deficiency anaemia (IDA) was defined as ID with haemoglobin (Hb) below the WHO cutoff for age and sex: 12.0 g/dl for girls and for boys aged 12.5-14.99 years and 13.0 g/dl for boys aged ≥15 years. Enzyme linked immunosorbent assay was used as analytical method for SF, sTfR and C-reactive protein (CRP). Subjects with indication of inflammation (CRP >5 mg/l) were excluded from the analyses. A total of 940 adolescents aged 12.5-17.49 years (438 boys and 502 girls) were involved. RESULTS: The percentage of iron depletion was 17.6%, significantly higher in girls (21.0%) compared with boys (13.8%). The overall percentage of ID and IDA was 4.7 and 1.3%, respectively, with no significant differences between boys and girls. A correlation was observed between log (SF) and Hb (r = 0.36, P < 0.01), and between log (sTfR) and mean corpuscular haemoglobin (r = -0.30, P < 0.01). Iron body stores were estimated on the basis of log (sTfR/SF). A higher percentage of negative values of body iron was recorded in girls (16.5%) with respect to boys (8.3%), and body iron values tended to increase with age in boys, whereas the values remained stable in girls. CONCLUSIONS: To ensure adequate iron stores, specific attention should be given to girls at European level to ensure that their dietary intake of iron is adequate.status: publishe

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Localization and broadband follow-up of the gravitational-wave transient GW150914

A gravitational-wave transient was identified in data recorded by the Advanced LIGO detectors on 2015 September 14. The event candidate, initially designated G184098 and later given the name GW150914, is described in detail elsewhere. By prior arrangement, preliminary estimates of the time, significance, and sky location of the event were shared with 63 teams of observers covering radio, optical, near-infrared, X-ray, and gamma-ray wavelengths with ground- and space-based facilities. In this Letter we describe the low-latency analysis of the gravitational wave data and present the sky localization of the first observed compact binary merger. We summarize the follow-up observations reported by 25 teams via private Gamma-ray Coordinates Network Circulars, giving an overview of the participating facilities, the gravitational wave sky localization coverage, the timeline and depth of the observations. As this event turned out to be a binary black hole merger, there is little expectation of a detectable electromagnetic signature. Nevertheless, this first broadband campaign to search for a counterpart of an Advanced LIGO source represents a milestone and highlights the broad capabilities of the transient astronomy community and the observing strategies that have been developed to pursue neutron star binary merger events. Detailed investigations of the electromagnetic data and results of the electromagnetic follow-up campaign will be disseminated in the papers of the individual teams

One-year cardiovascular outcomes after coronavirus disease 2019: The cardiovascular COVID-19 registry.

BackgroundThe long-term cardiovascular (CV) outcomes of COVID-19 have not been fully explored.MethodsThis was an international, multicenter, retrospective cohort study conducted between February and December 2020. Consecutive patients ≥18 years who underwent a real-time reverse transcriptase-polymerase chain reaction (RT-PCR) for SARS-CoV2 were included. Patients were classified into two cohorts depending on the nasopharyngeal swab result and clinical status: confirmed COVID-19 (positive RT-PCR) and control (without suggestive symptoms and negative RT-PCR). Data were obtained from electronic records, and clinical follow-up was performed at 1-year. The primary outcome was CV death at 1-year. Secondary outcomes included arterial thrombotic events (ATE), venous thromboembolism (VTE), and serious cardiac arrhythmias. An independent clinical event committee adjudicated events. A Cox proportional hazards model adjusted for all baseline characteristics was used for comparing outcomes between groups. A prespecified landmark analysis was performed to assess events during the post-acute phase (31-365 days).ResultsA total of 4,427 patients were included: 3,578 (80.8%) in the COVID-19 and 849 (19.2%) control cohorts. At one year, there were no significant differences in the primary endpoint of CV death between the COVID-19 and control cohorts (1.4% vs. 0.8%; HRadj 1.28 [0.56-2.91]; p = 0.555), but there was a higher risk of all-cause death (17.8% vs. 4.0%; HRadj 2.82 [1.99-4.0]; p = 0.001). COVID-19 cohort had higher rates of ATE (2.5% vs. 0.8%, HRadj 2.26 [1.02-4.99]; p = 0.044), VTE (3.7% vs. 0.4%, HRadj 9.33 [2.93-29.70]; p = 0.001), and serious cardiac arrhythmias (2.5% vs. 0.6%, HRadj 3.37 [1.35-8.46]; p = 0.010). During the post-acute phase, there were no significant differences in CV death (0.6% vs. 0.7%; HRadj 0.67 [0.25-1.80]; p = 0.425), but there was a higher risk of deep vein thrombosis (0.6% vs. 0.0%; p = 0.028). Re-hospitalization rate was lower in the COVID-19 cohort compared to the control cohort (13.9% vs. 20.6%; p = 0.001).ConclusionsAt 1-year, patients with COVID-19 experienced an increased risk of all-cause death and adverse CV events, including ATE, VTE, and serious cardiac arrhythmias, but not CV death.Study registrationURL: https://www.clinicaltrials.gov. Unique identifier: NCT04359927

One-year cardiovascular outcomes after coronavirus disease 2019: The cardiovascular COVID-19 registry

Background The long-term cardiovascular (CV) outcomes of COVID-19 have not been fully explored. Methods This was an international, multicenter, retrospective cohort study conducted between February and December 2020. Consecutive patients.18 years who underwent a real-time reverse transcriptase-polymerase chain reaction (RT-PCR) for SARS-CoV2 were included. Patients were classified into two cohorts depending on the nasopharyngeal swab result and clinical status: confirmed COVID-19 (positive RT-PCR) and control (without suggestive symptoms and negative RT-PCR). Data were obtained from electronic records, and clinical follow-up was performed at 1-year. The primary outcome was CV death at 1-year. Secondary outcomes included arterial thrombotic events (ATE), venous thromboembolism (VTE), and serious cardiac arrhythmias. An independent clinical event committee adjudicated events. A Cox proportional hazards model adjusted for all baseline characteristics was used for comparing outcomes between groups. A prespecified landmark analysis was performed to assess events during the post-acute phase (31-365 days). Results A total of 4,427 patients were included: 3,578 (80.8%) in the COVID-19 and 849 (19.2%) control cohorts. At one year, there were no significant differences in the primary endpoint of CV death between the COVID-19 and control cohorts (1.4% vs. 0.8%; HRadj 1.28 [0.562.91]; p = 0.555), but there was a higher risk of all-cause death (17.8% vs. 4.0%; HRadj 2.82 [1.99-4.0]; p = 0.001). COVID-19 cohort had higher rates of ATE (2.5% vs. 0.8%, HRadj 2.26 [1.02-4.99]; p = 0.044), VTE (3.7% vs. 0.4%, HRadj 9.33 [2.93-29.70]; p = 0.001), and serious cardiac arrhythmias (2.5% vs. 0.6%, HRadj 3.37 [1.35-8.46]; p = 0.010). During the post-acute phase, there were no significant differences in CV death (0.6% vs. 0.7%; HRadj 0.67 [0.25-1.80]; p = 0.425), but there was a higher risk of deep vein thrombosis (0.6% vs. 0.0%; p = 0.028). Re-hospitalization rate was lower in the COVID-19 cohort compared to the control cohort (13.9% vs. 20.6%; p = 0.001). Conclusions At 1-year, patients with COVID-19 experienced an increased risk of all-cause death and adverse CV events, including ATE, VTE, and serious cardiac arrhythmias, but not CV death