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Journal articles on the topic 'Risk-adjusted analysis'

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Published: 10 December 2022
Last updated: 29 January 2023

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1

Longley-Cook, Alastair G. "Risk-Adjusted Economic Value Analysis." North American Actuarial Journal 2, no. 1 (January 1998): 87–98. http://dx.doi.org/10.1080/10920277.1998.10595678.

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2

Fisher, Jeffrey D., and Joseph D’Alessandro. "Risk-Adjusted Attribution Analysis of Real Estate Portfolios." Journal of Portfolio Management 45, no. 7 (August 23, 2019): 80–94. http://dx.doi.org/10.3905/jpm.2019.1.102.

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3

Melnikov, A., and D. Vyachkileva. "Performance Analysis Based on Adequate Risk-Adjusted Measures." Review of Business and Economics Studies 6, no. 3 (September 30, 2018): 5–18. http://dx.doi.org/10.26794/2308-944x-2018-6-2-5-18.

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There are many potential investment options for investors and they should be able to compare them on a risk-adjusted basis. If investors rely only on pure return they can be exposed to a high risk. Therefore, many investors rely on adequate performance measures to evaluate potential investment opportunities. In this paper, we describe widely used risk-adjusted performance measures and add correlation through the M3 measure. We apply described measures to real financial data in order to rank managers and compare rankings between measures. We also look at the following year measures to compare the results with predictions.
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4

Burzoni, Matteo, Marco Frittelli, and Federico Zorzi. "Short Communication: Robust Market-Adjusted Systemic Risk Measures." SIAM Journal on Financial Mathematics 12, no. 3 (January 2021): SC70—SC82. http://dx.doi.org/10.1137/21m1401723.

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5

Arugaslan, Onur, Ajay Samant, and Devrim Yaman. "Portfolio Spiking with Cryptocurrency: A Risk-Adjusted Performance Analysis." Australian Journal of Business and Management Research 07, no. 01 (September 1, 2022): 36–44. http://dx.doi.org/10.52283/nswrca.ajbmr.20220701a03.

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The objective of this study is to provide empirical documentation on the risk-adjusted performance of portfolios formed by investing in a Cryptocurrency such as Bitcoin and a risk-free asset. The study evaluates the performance of these Bitcoin-spiked portfolios using statistical measures grounded in modern portfolio theory. Market returns are adjusted for the degree of total risk, systematic risk, and downside risk inherent in each portfolio, and the securities are then ranked on the basis of risk-adjusted performance. In addition to standard Sharpe, Jensen, and Treynor performance measures, two newer evaluation metrics, the Modigliani and Sortino measures, are used for ranking the portfolios. We report that these portfolios have varying levels of risk and return. Our key finding is that these portfolios’ risk-adjusted returns are not only quite impressive but also exceed that of S&P 500, our benchmark market portfolio. The implication of our results is that investors with higher risk tolerance could earn substantially higher returns by including a larger percentage of Bitcoin in their portfolios. Our results should be informative to individual and institutional investors contemplating investing in cryptocurrencies but aware of their high risk.
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6

Reilly, Frank K., and David J. Wright. "Analysis of Risk-Adjusted Performance of Global Market Assets." Journal of Portfolio Management 30, no. 3 (April 30, 2004): 63–77. http://dx.doi.org/10.3905/jpm.2004.412321.

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7

Sackley, William H. "Analysis of Risk-Adjusted Performance of Global Market Assets." CFA Digest 34, no. 4 (November 2004): 90. http://dx.doi.org/10.2469/dig.v34.n4.1586.

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8

Kim, Hyunjoon, and Zheng Gu. "Risk-Adjusted Performance: A Sector Analysis of Restaurant Firms." Journal of Hospitality & Tourism Research 27, no. 2 (May 2003): 200–216. http://dx.doi.org/10.1177/1096348003027002004.

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9

Cho, Seong, Liang Fu, and Yin Yu. "New risk analysis tools with accounting changes: adjusted Z-score." Journal of Credit Risk 8, no. 1 (March 2012): 89–108. http://dx.doi.org/10.21314/jcr.2012.137.

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10

Creswell, David L. "“Risk-Adjusted Economic Value Analysis,” Alastair Longley-Cook, January 1998." North American Actuarial Journal 2, no. 2 (April 1998): 111–13. http://dx.doi.org/10.1080/10920277.1998.10595710.

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11

Copeland, G. P., P. Sagar, J. Brennan, G. Roberts, J. Ward, P. Cornford, A. Millar, and C. Harris. "Risk-adjusted analysis of surgeon performance: A 1-year study." British Journal of Surgery 82, no. 3 (March 1995): 408–11. http://dx.doi.org/10.1002/bjs.1800820344.

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12

Gibbs, A. C. C., and G. P. Copeland. "Risk-adjusted analysis of surgeon performance: A 1-year study." British Journal of Surgery 83, no. 1 (January 1996): 136. http://dx.doi.org/10.1002/bjs.1800830154.

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13

Gibbs, A. C. C. "Risk-adjusted analysis of surgeon performance: A 1-year study." British Journal of Surgery 83, no. 6 (June 1996): 869. http://dx.doi.org/10.1002/bjs.1800830645.

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14

Vilija, Alekneviciene, Stareviciute Birute, and Alekneviciute Egle. "Evaluation of the efficiency of European Union farms: a risk-adjusted return approach." Agricultural Economics (Zemědělská ekonomika) 64, No. 6 (June 15, 2018): 241–55. http://dx.doi.org/10.17221/272/2016-agricecon.

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The aim of this study was to assess the efficiency of EU member-state farms using a risk-adjusted return approach and to determine the impact of subsidies on the efficiency of EU farms. Farm efficiency was analysed by the member-state and by the type of farming and was based on the calculation of Sharpe and Treynor ratios. Systemic risk was expressed by standard deviation in order to estimate the share of systemic risk in the total risk. The change in Sharpe ratios was assessed to determine the impact of subsidies on EU farm efficiency. The results of the risk-adjusted return analysis reveal that farms in the EU-15 were more efficient than farms in the EU-12 in 2004–2013, possibly due to being more experienced in risk management. Nevertheless, the EU-15 did not undertake a bigger share of systemic risk when compared to the EU-12 farms. The impact of financial support on the efficiency of the EU-12 farms was also not stronger when compared to the EU-15 farms.
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15

Vannucchi, A., N. Pemmaraju, B. Scott, M. Savona, S. Oh, F. Palandri, H. K. Al-Ali, et al. "P1068: RISK-ADJUSTED SAFETY ANALYSIS OF PACRITINIB IN PATIENTS WITH MYELOFIBROSIS." HemaSphere 6 (June 2022): 958–59. http://dx.doi.org/10.1097/01.hs9.0000847140.81310.7b.

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16

Williams, Jeffery R., Andrew T. Saffert, G. Art Barnaby, Richard V. Llewelyn, and Michael R. Langemeier. "A Risk Analysis of Adjusted Gross Revenue-Lite on Beef Farms." Journal of Agricultural and Applied Economics 46, no. 2 (May 2014): 227–44. http://dx.doi.org/10.1017/s1074070800000754.

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This study evaluates the Adjusted Gross Revenue-Lite (AGR-Lite) whole-farm adjusted gross revenue insurance program on net farm income risk using panel data from 49 southeast Kansas beef farms. On average for the group, but not each individual farm, AGR-Lite reduces the mean and standard deviation of net farm income, raises the average minimum, and lowers the average maximum observations of the net income distribution. Thirty-four farms (69%) received at least one indemnity payment. Stochastic efficiency with respect to a function reveals that AGR-Lite is preferred by 18 of the farm managers (37%) when an upper bound on the risk-aversion coefficient is used.
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17

Roberts, Keith, James Hodson, Robert Sutcliffe, Ravi Marudanayagam, and Darius Mirza. "Assessing surgeons performance using CUSUM analysis of risk adjusted POPF occurrence." Pancreatology 16, no. 3 (June 2016): S113. http://dx.doi.org/10.1016/j.pan.2016.05.380.

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18

Roberts, K., R. Marudanayagam, R. Sutcliffe, and D. Mirza. "Assessing surgeons performance using CUSUM analysis of risk adjusted POPF occurrence." HPB 21 (2019): S683. http://dx.doi.org/10.1016/j.hpb.2019.10.515.

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19

Callery, Mark P. "Risk-Adjusted Outcomes Analysis: Leveling the Field in Health Care Quality." Gastroenterology 134, no. 2 (February 2008): 632–34. http://dx.doi.org/10.1053/j.gastro.2007.12.029.

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20

Roberts, Kenneth S. "“Risk-Adjusted Economic Value Analysis”, Alastair G. Longley-Cook, January 1998." North American Actuarial Journal 2, no. 1 (January 1998): 99. http://dx.doi.org/10.1080/10920277.1998.10595679.

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21

Wurzburger, Benjamin W. "“Risk-Adjusted Economic Value Analysis,” Alastair G. Longley-Cook, January 1998." North American Actuarial Journal 3, no. 1 (January 1999): 142–46. http://dx.doi.org/10.1080/10920277.1999.10595786.

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22

Roberts, K., R. Marudanayagam, R. Sutcliffe, and D. Mirza. "Assessing surgeons performance using CUSUM analysis of risk adjusted POPF occurrence." HPB 21 (2019): S914. http://dx.doi.org/10.1016/j.hpb.2019.10.1094.

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23

Farkas, Walter, Fulvia Fringuellotti, and Radu Tunaru. "A cost-benefit analysis of capital requirements adjusted for model risk." Journal of Corporate Finance 65 (December 2020): 101753. http://dx.doi.org/10.1016/j.jcorpfin.2020.101753.

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24

McCloskey, Carol A., Mark A. Wilson, Steven J. Hughes, and George M. Eid. "Laparoscopic colorectal surgery is safe in the high-risk patient: A NSQIP risk-adjusted analysis." Surgery 142, no. 4 (October 2007): 594–97. http://dx.doi.org/10.1016/j.surg.2007.07.020.

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25

Hosseini, M., and J. Ramazani. "The Cardiac Anesthesia Risk Evaluation (CARE) score for risk-adjusted morbidity analysis in cardiac surgery." Journal of North Khorasan University of Medical Sciences 4, no. 4 (March 1, 2013): 695–99. http://dx.doi.org/10.29252/jnkums.4.4.695.

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26

Rehmani, Amir. "An empirical analysis of equity mutual funds using risk-adjusted performance measures." Asian Journal of Research in Banking and Finance 12, no. 4 (2022): 55–64. http://dx.doi.org/10.5958/2249-7323.2022.00023.2.

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27

Nitcheva, Daniela K., Walter W. Piegorsch, R. Webster West, and Ralph L. Kodell. "Multiplicity-Adjusted Inferences in Risk Assessment: Benchmark Analysis with Quantal Response Data." Biometrics 61, no. 1 (March 2005): 277–86. http://dx.doi.org/10.1111/j.0006-341x.2005.031211.x.

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28

Ernst, Armin, Michael Simoff, David Ost, Yaron Goldman, and Felix J. F. Herth. "Prospective Risk-Adjusted Morbidity and Mortality Outcome Analysis After Therapeutic Bronchoscopic Procedures." Chest 134, no. 3 (September 2008): 514–19. http://dx.doi.org/10.1378/chest.08-0580.

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29

Harris, Jeremy R., Thomas L. Forbes, Stefan H. Steiner, D. Kirk Lawlor, Guy DeRose, and Kenneth A. Harris. "Risk-adjusted analysis of early mortality after ruptured abdominal aortic aneurysm repair." Journal of Vascular Surgery 42, no. 3 (September 2005): 387.e1–387.e6. http://dx.doi.org/10.1016/j.jvs.2005.05.042.

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30

Jongsoon Koo. "Analysis on the Risk-Adjusted Performance of Ship Investment Companies in Korea." Journal of Shipping and Logistics 29, no. 1 (March 2013): 83–103. http://dx.doi.org/10.37059/tjosal.2013.29.1.83.

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31

Longley-Cook, Alastair G. "Author’s Reply: Risk-Adjusted Economic Value Analysis - Discussion by Kenneth S. Roberts." North American Actuarial Journal 2, no. 1 (January 1998): 99–100. http://dx.doi.org/10.1080/10920277.1998.10595680.

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32

Longley-Cook, Alastair G. "Author’s Reply: Risk-Adjusted Economic Value Analysis - Discussion by David L. Creswell." North American Actuarial Journal 2, no. 2 (April 1998): 113–14. http://dx.doi.org/10.1080/10920277.1998.10595711.

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33

Wu, Yuping, Walter W. Piegorsch, R. Webster West, Dengfang Tang, Maureen O. Petkewich, and Wei Pan. "Multiplicity-adjusted Inferences in Risk Assessment: Benchmark Analysis with Continuous Response Data." Environmental and Ecological Statistics 13, no. 1 (March 2006): 125–41. http://dx.doi.org/10.1007/s10651-005-5695-x.

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34

Bertolaccini, Luca, Roberto Crisci, Duilio Divisi, Benedetta Bedetti, Lidia Libretti, Davide Patrini, Fabrizio Minervini, and Marco Scarci. "Risk-Adjusted Costs Analysis of a Multicenter Video-Assisted Thoracoscopic Lobectomy Activity." Journal of the American College of Surgeons 227, no. 4 (October 2018): e99. http://dx.doi.org/10.1016/j.jamcollsurg.2018.08.267.

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35

Forbes, Thomas L., Stefan H. Steiner, D. Kirk Lawlor, Guy DeRose, and Kenneth A. Harris. "Risk-Adjusted Analysis of Outcomes Following Elective Open Abdominal Aortic Aneurysm Repair." Annals of Vascular Surgery 19, no. 2 (March 2005): 142–48. http://dx.doi.org/10.1007/s10016-004-0158-7.

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36

Sutton, R., S. Bann, M. Brooks, and S. Sarin. "The surgical risk scale as an improved tool for risk-adjusted analysis in comparative surgical audit." British Journal of Surgery 89, no. 6 (June 2002): 763–68. http://dx.doi.org/10.1046/j.1365-2168.2002.02080.x.

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37

Temkin-Greener, Helena, Mark R. Meiners, and Leonard Gruenberg. "PACE and the Medicare+Choice Risk-Adjusted Payment Model." INQUIRY: The Journal of Health Care Organization, Provision, and Financing 38, no. 1 (February 2001): 60–72. http://dx.doi.org/10.5034/inquiryjrnl_38.1.60.

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This paper investigates the impact of the Medicare principal inpatient diagnostic cost group (PIP-DCG) payment model on the Program of All-Inclusive Care for the Elderly (PACE). Currently, more than 6,000 Medicare beneficiaries who are nursing home certifiable receive care from PACE, a program poised for expansion under the Balanced Budget Act of 1997. Overall, our analysis suggests that the application of the PIP-DCG model to the PACE program would reduce Medicare payments to PACE, on average, by 38%. The PIP-DCG payment model bases its risk adjustment on inpatient diagnoses and does not capture adequately the risk of caring for a population with functional impairments.
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38

Pemmaraju, Naveen, Bart L. Scott, Michael R. Savona, Stephen T. Oh, Claire Harrison, Alessandro M. Vannucchi, Francesca Palandri, et al. "Risk-adjusted safety analysis of pacritinib (PAC) in patients (pts) with myelofibrosis (MF)." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): 7058. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.7058.

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7058 Background: PAC is a novel JAK2/IRAK1 inhibitor that has shown significant activity in pts with MF, including those with platelet (plt) counts <50×109/L. Recently, JAK inhibitors have come under increased scrutiny due to specific, emerging toxicities with drugs in this class. This safety analysis focuses on these toxicities of interest for pts treated with PAC 200 mg BID and best available therapy (BAT), including ruxolitinib (RUX), on the Phase 3 PERSIST-2 and Phase 2 PAC203 studies. Data are presented as risk-adjusted incidences to account for differential time at risk for adverse events (AEs) between arms due to cross-over. Methods: Pts treated with PAC 200 mg BID on PERSIST-2 and PAC203, and those treated with BAT on PERSIST-2, were included. Risk-adjusted AEs, representing event rate per 100 patient-years (pt-yrs), were calculated for overall and fatal AEs, bleeding AEs (determined by Standardized Medical Dictionary for Regulatory Activities Query [SMQ]), cardiac AEs (by SMQ), major cardiac events (per major adverse cardiovascular events [MACE] classification), infections, thromboses, and secondary malignancies. Results: A total of 160 pts were analyzed as the pooled PAC group (n=106 in PERSIST-2; n=54 in PAC203) and 98 pts in the BAT group (44 on RUX). At baseline, median plt count was 57×109/L; 61% had prior JAK2 inhibitor therapy. The rate of AEs was higher on PAC versus BAT, while the rate of fatal AEs was lower (Table). Both bleeding and cardiac events occurred at slightly lower rates on PAC compared to BAT. There were no MACE events on PAC, whereas there were on BAT. Malignant neoplasms occurred at similar rates on PAC and BAT, though rate of non-melanoma skin cancers was lower in pooled PAC (3/100 pt-yrs) versus BAT (7/100 pt-yrs), including RUX (11/100 pt-yrs). Infection occurred more frequently on PAC, though fungal and viral infections occurred less frequently, as did herpes zoster reactivation (pooled PAC: 0/100 pt-yrs vs BAT: 2.4/100 pt-yrs, including RUX: 5.5/100 pt-yrs). Thrombosis occurred at similar rates on PAC and BAT. Conclusions: Risk-adjusted analysis demonstrates that the safety profile of PAC 200 mg BID is comparable or superior to BAT, including RUX. PAC 200 mg BID may represent a full-dose therapeutic option for pts with MF, including those with thrombocytopenia. Clinical trial information: NCT02055781; NCT04884191. [Table: see text]
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39

Camilleri, Silvio John, and Ritienne Farrugia. "The Risk-Adjusted Performance of Alternative Investment Funds and UCITS: A Comparative Analysis." International Journal of Economics and Finance 10, no. 7 (May 28, 2018): 23. http://dx.doi.org/10.5539/ijef.v10n7p23.

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This study evaluates the performance of a selection of Alternative Investment Funds (AIFs), and Undertakings for Collective Investment in Transferable Securities Funds (UCITS) which followed a global geographic focus strategy during the period 2010-2016. These two fund structures are governed by different regulatory frameworks, which have evolved and re-shaped over the years. Various yardsticks are employed to evaluate the risk-adjusted performance of the sampled funds, and Monte-Carlo simulations are used to gauge the possible out-of-sample returns. Most of the sampled funds underperformed the benchmark index in terms of their Sharpe and Treynor ratios. Whilst UCITS registered a better overall performance, AIFs outperformed UCITS towards the end of the sample period. This suggests that investors should not assume that one fund structure is inherently superior to the other, since the relative performance may vary over time.
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40

Kim, Sun-Hee, and Kwang-Soo Lee. "Comparing Risk-adjusted In-hospital Mortality for Craniotomies : Logistic Regression versus Multilevel Analysis." Korean Journal of Health Service Management 9, no. 2 (June 30, 2015): 81–88. http://dx.doi.org/10.12811/kshsm.2015.9.2.081.

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41

Cavallo, Eduardo A., and Patricio Valenzuela. "The Determinants of Corporate Risk in Emerging Markets: An Option-Adjusted Spread Analysis." IMF Working Papers 07, no. 228 (2007): 1. http://dx.doi.org/10.5089/9781451867923.001.

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42

Bordag, L. A. "Study of the risk-adjusted pricing methodology model with methods of geometrical analysis." Stochastics 83, no. 4-6 (September 13, 2010): 333–45. http://dx.doi.org/10.1080/17442508.2010.489642.

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43

Touijer, K., K. Kuroiwa, J. Eastham, A. Vickers, V. Reuter, P. Scardino, and B. Guillonneau. "RISK-ADJUSTED ANALYSIS OF POSITIVE SURGICAL MARGINS FOLLOWING LAPAROSCOPIC AND RETROPUBIC RADICAL PROSTATECTOMY." European Urology Supplements 5, no. 2 (April 2006): 322. http://dx.doi.org/10.1016/s1569-9056(06)61203-7.

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44

Reed, James F., and Stephen A. Olenchock. "Comparative analysis of risk-adjusted bypass surgery stratification models in a community hospital." Heart & Lung 32, no. 6 (November 2003): 383–90. http://dx.doi.org/10.1016/j.hrtlng.2003.08.001.

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45

Janssens, Pim M. W., Anja Scholten, Harm De Waard, Natascha Tiemens, Monique Van Uum, Everlien Schrijver, Brigitte Roozenburg, et al. "Prospective risk analysis adjusted to the reality of clinical and fertility laboratory processes." Diagnosis 2, no. 4 (December 1, 2015): 235–43. http://dx.doi.org/10.1515/dx-2015-0027.

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AbstractProspective risk analysis (PRA) is a valuable instrument in quality assurance. The practical application of PRA in clinical laboratories according to the method we have described elsewhere leaves room for a number of adaptations to make it more applicable to and consistent with actual laboratory processes.We distinguished between more and less critical tests and products in the laboratory processes and scored the consequences of failures at different steps in line with the previously described failure type and effect analysis (FMEA) method. PRA was carried out for two typical laboratory processes: standard clinical laboratory testing and the cryopreservation of semen.Tests in standard clinical laboratory in processes were labeled critical, semi-critical or non-critical. Consequence scoring (C) and assessed risk (R) were significantly higher for processes containing tests considered to be critical (C=6.6±1.5, R=19.3±13.5) as compared to processes containing tests considered semi- or non-critical (C=3.0±1.4, R=8.2±5.3 and C=3.2±1.8, R=8.6±5.9, respectively). There were no differences in the C and R scores for processes with tests considered semi- or non-critical. In the semen cryopreservation process, a distinction between the processes involving private semen and generally accessible semen was made. The C scores for these were significantly different (C=5.9±2.2 and 5.0±2.0, respectively), the R scores did not differ.Introduction of a test criticality classification for the purpose of consequence scoring led to an improved PRA methodology, better reflecting the reality of clinical laboratory practice. We found that two levels of criticality, critical and less critical, were sufficient to achieve this improvement.
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46

Touijer, Karim, Kentaro Kuroiwa, James A. Eastham, Andrew Vickers, Victor E. Reuter, Peter T. Scardino, and Bertrand Guillonneau. "Risk-Adjusted Analysis of Positive Surgical Margins Following Laparoscopic and Retropubic Radical Prostatectomy." European Urology 52, no. 4 (October 2007): 1090–96. http://dx.doi.org/10.1016/j.eururo.2006.12.014.

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47

Eck, Ruben J., Wouter Bult, Jørn Wetterslev, Reinold O. B. Gans, Karina Meijer, Frederik Keus, and Iwan C. C. van der Horst. "Intermediate Dose Low-Molecular-Weight Heparin for Thrombosis Prophylaxis: Systematic Review with Meta-Analysis and Trial Sequential Analysis." Seminars in Thrombosis and Hemostasis 45, no. 08 (October 17, 2019): 810–24. http://dx.doi.org/10.1055/s-0039-1696965.

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AbstractDifferent doses of low-molecular-weight heparin (LMWH) are registered and used for thrombosis prophylaxis. We assessed benefits and harms of thrombosis prophylaxis with a predefined intermediate-dose LMWH compared with placebo or no treatment in patients at risk of venous thromboembolism (VTE). We performed a systematic review with meta-analyses and trial sequential analyses (TSA) following The Cochrane Handbook for Systematic Reviews of Interventions. Medline, Cochrane CENTRAL, Web of Science, and Embase were searched up to December 2018. Trials were evaluated for risk of bias and quality of evidence was assessed following the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Seventy randomized trials with 34,046 patients were included. Eighteen (26%) had overall low risk of bias. There was a small statistically significant effect of LMWH on all-cause mortality (risk ratio [RR]: 0.96; TSA-adjusted confidence interval [TSA-adjusted CI]: 0.94–0.98) which disappeared in sensitivity analyses excluding ambulatory cancer patients (RR: 0.99; TSA-adjusted CI: 0.84–1.16). There was moderate-quality evidence for a statistically significant beneficial effect on symptomatic VTE (odds ratio [OR]: 0.59; TSA-adjusted CI: 0.53–0.67; number needed to treat [NNT]: 76; 95% CI: 60–106) and a statistically significant harmful effect on major bleeding (Peto OR: 1.66; TSA-adjusted CI: 1.31–2.10; number needed to harm [NNH]: 212; 95% CI: 142–393). There were no significant intervention effects on serious adverse events. The use of intermediate-dose LMWH for thrombosis prophylaxis compared with placebo or no treatment was associated with a small statistically significant reduction of all-cause mortality that disappeared in sensitivity analyses excluding trials that evaluated LMWH for anticancer treatment. Intermediate-dose LMWH provides benefits in terms of VTE prevention while it increases major bleeding.
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48

Jawhar, Mohamad, Juliana Schwaab, Iván Álvarez-Twose, Khalid Shoumariyeh, Nicole Naumann, Johannes Lübke, Cecelia Perkins, et al. "MARS: Mutation-Adjusted Risk Score for Advanced Systemic Mastocytosis." Journal of Clinical Oncology 37, no. 31 (November 1, 2019): 2846–56. http://dx.doi.org/10.1200/jco.19.00640.

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PURPOSE To develop a risk score for patients with advanced systemic mastocytosis (AdvSM) that integrates clinical and mutation characteristics. PATIENTS AND METHODS The study included 383 patients with AdvSM from the German Registry on Disorders of Eosinophils and Mast Cells (training set; n = 231) and several centers for mastocytosis in the United States and Europe, all within the European Competence Network on Mastocytosis (validation set; n = 152). A Cox multivariable model was used to select variables that were predictive of overall survival (OS). RESULTS In multivariable analysis, the following risk factors were identified as being associated with OS: age greater than 60 years, anemia (hemoglobin < 10 g/dL), thrombocytopenia (platelets < 100 × 109/L), presence of one high molecular risk gene mutation (ie, in SRSF2, ASXL1, and/or RUNX1), and presence of two or more high molecular risk gene mutations. By assigning hazard ratio–weighted points to these variables, the following three risk categories were defined: low risk (median OS, not reached), intermediate risk (median OS, 3.9 years; 95% CI, 2.1 to 5.7 years), and high risk (median OS, 1.9 years; 95% CI, 1.3 to 2.6 years; P < .001). The mutation-adjusted risk score (MARS) was independent of the WHO classification and was confirmed in the independent validation set. During a median follow-up time of 2.2 years (range, 0 to 23 years), 63 (16%) of 383 patients experienced a leukemic transformation to secondary mast cell leukemia (32%) or secondary acute myeloid leukemia (68%). The MARS was also predictive for leukemia-free survival ( P < .001). CONCLUSION The MARS is a validated, five-parameter, WHO-independent prognostic score that defines three risk groups among patients with AdvSM and may improve up-front treatment stratification for these rare hematologic neoplasms.
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49

Aditya, Muhammad, Catharina Umbul Wahjuni, and Muhammad Atoillah Isfandiari. "Risk Factor Analysis of Recurrent Acute Coronary Syndrome." Jurnal Berkala Epidemiologi 6, no. 3 (December 31, 2018): 192. http://dx.doi.org/10.20473/jbe.v6i32018.192-199.

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Background: Acute coronary syndrome (ACS) is a form of life-threatening coronary heart disease. Interestingly, this entity has the possibility to recurrence with prevalence reaches 21-30% in a year. Purpose: This study aims to analyse risk factors associated with recurrent ACS incident. Methods: The analytic observation research with the case-control design was applied in this present study. Furthermore, this research was conducted at the Dr. Mohamad Soewandhie General Hospital, Surabaya. This study carried from February to July 2018. The samples used in this study cover 43 cases and 43 controls in the consecutive admission to the ACS patients who came to the cardiac clinic of the Dr. Mohamad Soewandhie General Hospital, Surabaya that meets the research criteria. On the other hand, bivariable analysis was performed using simple logistic regression and multivariable analysis was performed using multiple logistic regression. This study showed that the most influential risk factor for ACS recurrent. Results: incident were including control of Low-Density Lipoprotein Cholesterol (LDL-C) ≥ 100 mg/dL (p= 0.03; adjusted OR= 3.35; 95% CI= 1.16 < OR < 9.68), irregular exercise schedule (p < 0.01; adjusted OR= 9.15; 95% CI= 2.83 <OR <29.58), and smoking history (p= 0.02; adjusted OR= 4.07; 95% CI= 1.29 <OR <12.84). Conclusion: The control of LDL Cholesterol levels below 100 mg/dL, regular exercise, and avoid smoking are beneficial for people with ACS to reduce the risk of recurrent ACS incident.
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Zhang, Ning. "The Modified Mortality Decomposition Model and its Application in the China Longevity Risk Analysis." Advanced Materials Research 756-759 (September 2013): 2912–17. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.2912.

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the paper made an adjustment on the mortality decomposition model which was first proposed by the author. The mortality data can be processed by the classical wavelet and HHT methods. Compared with the classical mortality analyzing method, more information about longevity risk can be captured by the adjusted mortality decomposition. As a new development, the adjusted mortality decomposition is more effective for the short data set like China. Also the paper gave a modified form of longevity risk index which is different from that the author introduced in another paper. The new modified index is more suitable for China. Based on the adjusted decomposition of mortality rate data and modified longevity risk index, the paper gave their application and detailed analysis on China longevity risk. The important result of different provinces is also given.
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