Accidental Pilgrims

Author(s):  
Karin Vélez
Keyword(s):  

This chapter describes how some Catholic pilgrims tried to reconcile the Jesuit official advice of mental self-discipline with their first intense encounters with the Madonna of Loreto. The pilgrims' stories involve both contemplative quests for spiritual improvement and transformative run-ins with the material manifestations of Catholicism. Yet they flip the order recommended by Richeòme of contemplation first and real world next. The first pilgrims considered are the Jesuits who loom large behind the good-pilgrimage rubrics of this time period. Then, the Jesuit template for pilgrimage is tested against the reported experiences of two non-Jesuit travelers to Loreto, Nicolà Albani and Pierre Chaumonot.

2002 ◽  
Vol 17 (4) ◽  
pp. 431-445
Author(s):  
Jerry G. Kreuze ◽  
Jack M. Ruhl

This case uses the concepts of earnings quality and earnings management to illustrate the inherent ambiguity in the earnings measurement process. Accounting students are often uncomfortable with ambiguity. Students want faculty to provide them with a single correct answer, such as the precise earnings for a given time period. Accounting textbooks rarely address this perception; we have yet to find a textbook that illustrates a range of acceptable amounts. This case demonstrates that earnings can be, and often are, ambiguous in the real world.


Author(s):  
Nisha Ratti ◽  
Parminder Kaur

Software evolution is the essential characteristic of the real world software as the user requirements changes software needs to change otherwise it becomes less useful. In order to be used for longer time period, software needs to evolve. The software evolution can be a result of software maintenance. In this chapter, a study has been conducted on 10 versions of GLE (Graphics Layout Engine) and FGS (Flight Gear Simulator) evolved over the period of eight years. An effort is made to find the applicability of Lehman Laws on different releases of two softwares developed in C++ using Object Oriented metrics. The laws of continuous change, growth and complexity are found applicable according to data collected.


2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Ikuko Tanaka ◽  
Masayo Sato ◽  
Tomoko Sugihara ◽  
Douglas E. Faries ◽  
Shuko Nojiri ◽  
...  

Adherence and persistence with osteoporosis treatments are essential for reducing fracture risk. Once-daily teriparatide is available in Japan for treating osteoporosis in patients with a high risk of fracture. The study objective was to describe real-world adherence and persistence with once-daily teriparatide 20 μg during the first year of treatment for patients who started treatment during the first eight months of availability in Japan. This prescription database study involved patients with an index date (first claim) between October 2010 and May 2011, a preindex period ≥6 months, and a postindex period ≥12 months and who were aged >45 years. Adherence (medication possession ratio (MPR)) and persistence (time from the start of treatment to discontinuation; a 60-day gap in supply) were calculated. A total of 287 patients started treatment during the specified time period; 123 (42.9%) were eligible for inclusion. Overall mean (standard deviation) adherence was 0.702 (0.366), with 61.0% of patients having high adherence (MPR > 0.8). The percentage of patients remaining on treatment was 65.9% at 180 days and 61.0% at 365 days. Our findings suggest that real-world adherence and persistence with once-daily teriparatide in Japan are similar to that with once-daily teriparatide in other countries and with other osteoporosis medications.


2021 ◽  
Vol 9 ◽  
pp. 78-86
Author(s):  
Arnav Saini ◽  
Nipun Gauba ◽  
Hardik Chawla ◽  
Jabir Ali

Model predictive contrTraffic Collisions are one of the major sources of deaths, injuries & property damage every year. Road accidents are one of the most difficult real world problems to tackle with, due to its high order of unpredictability. The persistence as well as existence of this problem may be prevalent to a different degree for each & every place. The consequences of this may result in loss of human life & capital. To avoid this, every place needs to tackle the problem with a customized approach depending on the causes that are responsible for the accidents. Even in today's world, where the mass operation of autonomous vehicles is still grim or out of sight, the possibility of predicting a road accident before it takes place, is practically impossible. The only idea or approach that can help to decrease the number of road accidents, is to analyze the reasons that lead to these accidents. The concepts of Data Analysis, Data Visualization & Machine Learning help to tackle real world problems, by exploring & deriving valuable insights, which in turn help in taking measures to solve the targeted problem & drive business growth. In this research study, the dataset pertaining to road mishaps that occurred in UK over time period 2005 - 2015 will be analyzed using these concepts. The defined approach can help the concerned authorities & respective government, to take every possible step & amendment, & hence mitigate the identified causes & scenarios that lead to road accidents.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3079-3079
Author(s):  
Christopher M Hillis ◽  
Lambert Busque ◽  
Julie Stakiw ◽  
Donna L. Forrest

Abstract Background: Registry data in chronic myeloid leukemia (CML) complement clinical trial data, and can help determine how closely real world clinical practice adheres to guidelines. Several reports addressing this issue have suggested adherence to monitoring guidelines varies. However, no Canadian data on this topic has been published to date. To provide insight into this issue, we present data from the British Columbia (BC), Saskatchewan (SK), Ontario (ON) and Quebec (QC) CML registries. Methods: Data on cytogenetic and molecular monitoring were analyzed for CML patients treated with first-line imatinib from 2001-2015 in the BC registry, 2009-2014 in the SK registry and 2001-2014 in the ON registry. From 2006, clinicians in BC and SK were advised to follow the European LeukemiaNet (ELN) monitoring recommendations. Molecular monitoring of BCR-ABL for these provinces was conducted at the BC Cancer Agency Molecular Genetics Laboratory according to standard practices. In ON, clinicians were not advised to follow any particular guidelines and molecular and cytogenetic tests were conducted by the Hamilton Regional Laboratory Medicine Program using contemporary standards. In QC, province-specific guidelines were in place beginning in 2012 (see www.gqr-lmc-nmp.ca for specific guidance). Treatment patterns for patients treated with first-line imatinib from BC, SK and QC were analyzed for the 2001-2015, 2001-2014 and 2002-2012 time periods, respectively. Results: Monitoring data were collected for 234, 58 and 104 patients from BC, SK and ON, respectively. As shown in table 1, adherence to monitoring recommendations in Canada was 70% to 80% at 12 months. Treatment data were available for 234 BC patients, 73 SK patients, and 223 QC patients. Data on adherence to treatment recommendations were available for 58 SK patients diagnosed with CML and treated with first-line imatinib between 2009 and 2014. Of these 58 patients, over a quarter (n=15) experienced treatment failure or failed to meet ELN milestones without a change in therapy. Smaller proportions of patients receiving first-line imatinib therapy in BC and QC remained on imatinib therapy (see table 2). Discussion and Conclusions: These data suggest there is room for improvement with regards to adherence to CML monitoring and treatment recommendations in Canada. However, assessment of adherence to recommendations and inter-provincial comparisons are limited by the fact that monitoring and treatment guidelines have evolved over the data collection time period, as well as by differences in data collection strategies. For instance, in the ON registry, monitoring at the 3-month time point may be lower as testing was not typically conducted at 3 months in ON during the early 2000s. The opposite pattern observed in BC (with higher testing rates at 3 months dropping off by 18 months) may be attributable to the strict time period definition, with more patients receiving testing outside of the 4-week window after 1 year or more on treatment. In spite of these limitations, data collection through these registries continues to improve our understanding of real world CML populations and its management in Canada, as well as to spur initiatives aimed at improving CML care. This study was sponsored by Bristol-Myers Squibb. Professional medical writing and editorial assistance was provided by MedPlan Communications Inc. and was funded by Bristol-Myers Squibb. Disclosures Hillis: Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; BMS: Honoraria; Celgene: Consultancy. Busque:Novartis: Honoraria, Research Funding, Speakers Bureau; BMS: Honoraria, Speakers Bureau; Pfizer: Honoraria, Speakers Bureau. Stakiw:Roche: Research Funding; BMS: Honoraria; Novartis: Honoraria, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Celgene: Honoraria, Speakers Bureau; Jansen: Honoraria, Speakers Bureau. Forrest:BMS: Consultancy, Research Funding; Ariad: Honoraria, Speakers Bureau.


Author(s):  
Kaitlin Rainwater-Lovett ◽  
John T Redd ◽  
Miles A Stewart ◽  
Natalia Elías Calles ◽  
Tyler Cluff ◽  
...  

Abstract Background Monoclonal antibodies (mAbs) against SARS-CoV-2 are a promising treatment for limiting the progression of COVID-19 and decreasing strain on hospitals. Their use, however, remains limited, particularly in disadvantaged populations. Methods Electronic health records were reviewed from SARS-CoV-2 patients at a single medical center in the United States that initiated mAb infusions in January 2021 with the support of the U.S. Department of Health and Human Services’ National Disaster Medical System. Patients who received mAbs were compared to untreated patients from the time period before mAb availability who met eligibility criteria for mAb treatment. We used logistic regression to measure the effect of mAb treatment on the risk of hospitalization or emergency department (E.D.) visit within 30 days of laboratory-confirmed COVID-19. Results Of 598 COVID-19 patients, 270 (45%) received bamlanivimab and 328 (55%) were untreated. Two hundred and thirty-one patients (39%) were Hispanic. Among treated patients, 5/270 (1.9%) presented to the E.D. or required hospitalization within 30 days of a positive SARS-CoV-2 test, compared to 39/328 (12%) untreated patients (p<0.001). After adjusting for age, gender, and comorbidities, the risk of E.D. visit or hospitalization was 82% lower in mAb-treated patients compared to untreated patients (95% confidence interval [CI]: 56%-94%). Conclusions In this diverse, real-world COVID-19 patient population, mAb treatment significantly decreased the risk of subsequent E.D. visit or hospitalization. Broader treatment with mAbs, including in disadvantaged patient populations, can decrease the burden on hospitals and should be facilitated in all populations in the United States to ensure health equity.


Author(s):  
Benjamin Y Andrew ◽  
Matthew E Ehrlich ◽  
Colleen M Stack ◽  
Julian P Yang ◽  
Jodi A Dodds

Background: The benefit of tissue plasminogen activator (tPA) in the treatment of acute ischemic stroke is time-dependent. AHA/ASA guidelines recommend a goal door-to-needle (DTN) time of 60 minutes or less. In practice, medically complicated patients can pose challenges leading to prolonged treatment times that skew institutional mean DTN values. We aimed to produce a simple statistical tool to calculate individualized DTN targets while accounting for outliers to help institutions achieve a mean DTN < 60 minutes. Methods: An IRB approved, single-center, retrospective analysis of consecutive acute stroke code case data from Duke University Hospital (Durham, NC) between January 2014 and July 2016 was conducted. We devised a formula (Figure 1) to calculate the goal DTN time (t g ) necessary to achieve an overall mean DTN of < 60 minutes while adjusting for the frequency and magnitude of outliers. This formula was created as a modifiable tool using an individual institution’s outlier definition, current outlier frequency (f m ), and outlier DTN average (t m ) over a pre-defined time period. As proof of concept, the formula was tested using an outlier definition of ≥100 minutes. The formula was modeled using both real-world institutional data and a simulated sample of 200 patients. Results: In 1069 consecutive stroke codes, tPA was administered in 135 cases with mean DTN 68.2 minutes (range 15-205). Of these, 18 cases (13.3%) met our definition of outlier, with t m of 134 minutes. Using the developed formula with institutional data resulted in a target DTN of 48.6 minutes for non-outlier cases to achieve overall mean DTN < 60 minutes. Using the simulated dataset, our tool similarly calculated a goal DTN of 49 minutes. Conclusions: This simple statistical tool is a novel solution for generating an institution-specific goal DTN based on unique organizational data, experiences, and nuances in order to meet the recommended mean DTN. Additionally, these individualized goals may further motivate stroke teams to carry out more efficient clinical care rather than consistently aiming for DTN values < 60 minutes. The tool presented here is easily adaptable to future changes in recommended target goals and can be seamlessly incorporated into institution-wide systems planning.


2012 ◽  
Vol 39 (4) ◽  
pp. 448-459 ◽  
Author(s):  
Hyunho Chang ◽  
Dongjoo Park ◽  
Younginn Lee ◽  
Byoungjo Yoon

The objective of this study is to introduce an effective and practical model, based on non-parametric regression, to instantaneously estimate multivariate imputations replacing multiple missing variables during multiple time periods. The developed model was essentially designed for system-oriented, real-world applications. In an empirical study with real-world data, the proposed model, on the whole, outperformed the seasonal auto-regressive integrated moving average (ARIMA). The analysis of the results indicates that the introduced model was more applicable to multivariate imputation during multiple time intervals than that of ARIMA. In addition, it was revealed that ARIMA could somewhat deform the relationship between the volume (q) and speed (s), whereas the developed model reproduced the q–s relationship more similarly than ARIMA. Moreover, the proposed model is very simple and does not require system operators to input or recalibrate any external parameters because it was developed for applications of real data management systems.


2021 ◽  
Author(s):  
Kaitlin Rainwater-Lovett ◽  
John T. Redd ◽  
Miles A. Stewart ◽  
Natalia Elias Calles ◽  
Tyler Cluff ◽  
...  

Background: Monoclonal antibodies (mAbs) against SARS-CoV-2 are a promising treatment for limiting the progression of COVID-19 and decreasing strain on hospitals. Their use, however, remains limited, particularly in disadvantaged populations. Methods: Electronic health records were reviewed from SARS-CoV-2 patients at a single medical center in the United States that initiated mAb infusions in January 2021 with the support of the U.S. Department of Health and Human Services' National Disaster Medical System. Patients who received mAbs were compared to untreated patients from the time period before mAb availability who met eligibility criteria for mAb treatment. We used logistic regression to measure the effect of mAb treatment on the risk of hospitalization or emergency department (E.D.) visit within 30 days of laboratory-confirmed COVID-19. Results: Of 598 COVID-19 patients, 270 (45%) received bamlanivimab and 328 (55%) were untreated. Two hundred and thirty-one patients (39%) were Hispanic. Among treated patients, 5/270 (1.9%) presented to the E.D. or required hospitalization within 30 days of a positive SARS-CoV-2 test, compared to 39/328 (12%) untreated patients (p<0.001). After adjusting for age, gender, and comorbidities, the risk of E.D. visit or hospitalization was 82% lower in mAb-treated patients compared to untreated patients (95% confidence interval [CI]: 66%-94%). Conclusions: In this diverse, real-world COVID-19 patient population, mAb treatment significantly decreased the risk of subsequent E.D. visit or hospitalization. Broader treatment with mAbs, including in disadvantaged patient populations, can decrease the burden on hospitals and should be facilitated in all populations in the United States to ensure health equity.


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