Decomposition can harm the accuracy of behavioural frequency reports

In survey research, the use of decomposition can lead to pronounced reporting errors as seen by overreporting and overall reporting error. A total of 87 subjects answered either decomposed or undecomposed questions concerning telephone calls made by them while at work. The questionnaire conditions varied the length of the reference period (1 week or 6 months), and the type of call (local or long-distance). Decomposition conditions introduced either spatial or temporal cues. In all comparisons, decomposed questions increased overreporting bias relative to undecomposed questions. In addition, undecomposed questions with a 1-week reference period led to increased overreporting bias in comparison to undecomposed/6-month questions. Results are consistent with a category split estimation model in which smaller categories are predicted to lead to overreporting, and larger categories to underreporting. Decomposition is not recommended for gaining retrospective reports of non-distinctive, frequent events. Copyright © 2000 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/35010/1/646_ftp.pd

Static and dynamic single leg postural control performance during dual-task paradigms

ABSTRACTCombining dynamic postural control assessments and cognitive tasks may give clinicians a more accurate indication of postural control under sport-like conditions compared to single-task assessments. We examined postural control, cognitive and squatting performance of healthy individuals during static and dynamic postural control assessments in single- and dual-task paradigms. Thirty participants (female = 22, male = 8; age = 20.8 ± 1.6 years, height = 157.9 ± 13.0 cm, mass = 67.8 ± 20.6 kg) completed single-leg stance and single-leg squat assessments on a force plate individually (single-task) and concurrently (dual-task) with two cognitive assessments, a modified Stroop test and the Brooks Spatial Memory Test. Outcomes included centre of pressure speed, 95% confidence ellipse, squat depth and speed and cognitive test measures (percentage of correct answers and reaction time). Postural control performance varied between postural control assessments and testing paradigms. Participants did not squat..

Derivation and validation of an algorithm to predict transitions from community to residential long-term care among persons with dementia—A retrospective cohort study

Objectives: To develop and validate a model to predict time-to-LTC admissions among individuals with dementia. Design: Population-based retrospective cohort study using health administrative data. Setting and participants: Community-dwelling older adults (65+) in Ontario living with dementia and assessed with the Resident Assessment Instrument for Home Care (RAI-HC) between April 1, 2010 and March 31, 2017. Methods: Individuals in the derivation cohort (n = 95,813; assessed before March 31, 2015) were followed for up to 360 days after the index RAI-HC assessment for admission into LTC. We used a multivariable Fine Gray sub-distribution hazard model to predict the cumulative incidence of LTC entry while accounting for all-cause mortality as a competing risk. The model was validated in 34,038 older adults with dementia with an index RAI-HC assessment between April 1, 2015 and March 31, 2017. Results: Within one year of a RAI-HC assessment, 35,513 (37.1%) individuals in the derivation cohort and 10,735 (31.5%) in the validation cohort entered LTC. Our algorithm was well-calibrated (Emax = 0.119, ICIavg = 0.057) and achieved a c-statistic of 0.707 (95% confidence interval: 0.703–0.712) in the validation cohort. Conclusions and implications: We developed an algorithm to predict time to LTC entry among individuals living with dementia. This tool can inform care planning for individuals with dementia and their family caregivers

Variation in Access to Specialist Care and Risk of Surgery in Patients with Inflammatory Bowel Disease: A Population-Based Cohort Study

Introduction Inflammatory bowel disease (IBD; subtypes: Crohn’s disease (CD) and ulcerative colitis (UC)) is a chronic disease of the gastrointestinal tract with rising prevalence among people ≥65y. Rural residents, especially those ≥65y, have decreased access to specialist care. Specialist care is associated with lower risk of hospitalization and surgery. Objectives and Approach We evaluated variation across physician networks in access to specialist care and surgery among incident patients ≥65y in Ontario health administrative data. Access to specialist care was defined as: ≥1 outpatient visit to gastroenterologists or the majority of IBD-specific outpatient care by gastroenterologists. Variation was assessed with multilevel logistic regression and median odds ratios (MOR), adjusting for age, sex, distance from IBD physician, comorbidities, neighbourhood income, and rural/urban. Models evaluating surgical risk also adjusted for specialist care use, emergency department visits, and hospitalization at diagnosis. Network-level variables included rurality (RIO score), population colonoscopy and gastroenterologist supply. Results There was significant variation in having ≥1 gastroenterologist visit (CD p=0.0001, MOR 3.3; UC p<0.0001, MOR 3.1) and gastroenterologist providing the majority of care (CD p=0.0001, MOR 3.0; UC p<0.0001, MOR 3.7) within 12 months of diagnosis. Variation remained significant after accounting for network-level characteristics (≥1 gastroenterologist visit: CD p=0.0002, MOR 2.6, UC p<0.0001, MOR 2.2; majority of care: CD p=0.0002, MOR 2.4; UC p<0.0001, MOR 2.4). In CD, there was no variation in the five-year risk of surgery (p=0.07, MOR 1.3) and was unchanged by network-level factors (p=0.13, MOR 1.3). Variation in the risk of colectomy exists for patients with UC (p=0.016, MOR 1.3) and was not reduced when accounting for network-level characteristics (p=0.019, MOR 1.3). Conclusion/Implications Access to specialist care among patients with elderly-onset IBD is varies greatly between networks but this variation cannot be explained by differing provision of gastroenterological services across physician networks. Further research is needed to understand the factors that influence access to care and outcomes in elderly patients with IBD

Polysomnographic Assessment of Sleep Disturbances in Cancer Development A Historical Multicenter Clinical Cohort Study

BackgroundMany cellular processes are controlled by sleep. Therefore, alterations in sleep might be expected to stress biological systems that could influence malignancy risk.Research questionWhat is the association between polysomnographic measures of sleep disturbances and incident cancer, and what is the validity of cluster analysis in identifying polysomnography phenotypes?Study design and methodsWe conducted a retrospective multicenter cohort study using linked clinical and provincial health administrative data on consecutive adults free of cancer at baseline with polysomnography data collected between 1994 and 2017 in four academic hospitals in Ontario, Canada. Cancer status was derived from registry records. Polysomnography phenotypes were identified by k-means cluster analysis. A combination of validation statistics and distinguishing polysomnographic features was used to select clusters. Cox cause-specific regressions were used to assess the relationship between identified clusters and incident cancer.ResultsAmong 29,907 individuals, 2,514 (8.4%) received a diagnosis of cancer over a median of 8.0 years (interquartile range, 4.2-13.5 years). Five clusters were identified: mild (mildly abnormal polysomnography findings), poor sleep, severe OSA or sleep fragmentation, severe desaturations, and periodic limb movements of sleep (PLMS). The associations between cancer and all clusters compared with the mild cluster were significant while controlling for clinic and year of polysomnography. When additionally controlling for age and sex, the effect remained significant only for PLMS (adjusted hazard ratio [aHR], 1.26; 95%&nbsp;CI, 1.06-1.50) and severe desaturations (aHR, 1.32; 95%&nbsp;CI, 1.04-1.66). Further controlling for confounders, the effect remained significant for PLMS, but was attenuated for severe desaturations.InterpretationIn a large cohort, we confirmed the importance of polysomnographic phenotypes and highlighted the role that PLMS and oxygenation desaturation may play in cancer. Using this study's findings, we also developed an Excel (Microsoft) spreadsheet (polysomnography cluster classifier) that can be used to validate the identified clusters on new data or to identify which cluster a patient belongs to.Trial registryClinicalTrials.gov; Nos.: NCT03383354 and NCT03834792; URL: www.Clinicaltrialsgov

Using Large Date to Present Uncertainty for Risk Prediction in the Era of Precision Medicine: The RESPECT Algorithm for Predicted Death at End-of-Life

Introduction In Ontario, only 52% of people received palliative care in their last year of life, with only 20\% of those receiving it at home, which can improve the dying experience. Existing algorithms identifying people at end-of-life can potentially improve access to palliative care but are difficult for patients to understand. Objectives and Approach To predict and communicate risk of death for community dwelling older adults using a pre-specified and published approach (Trial registration NCT02779309). All assessments from community-dwelling Ontarians (N = 488,636) who received at least one home care assessment from the residential assessment instrument – home care (RAI HC) from 2007 to 2013 (N=1,331,273) were included. The algorithm used a two-step approach by rank ordering participants into 61 groups based on six-month probability of death (from Cox-proportional hazard models) and generated Kaplan-Meier five-year survival curves for each group. Median Survival time is reported with uncertainties expressed with 25th to 75th percentiles. Results The median predicted probability of death within six-months was 0.1095 (0.1093-0.1097, 95% CI). Risk varied among the 61 groups from 0.0158 (0.0158-0.0159) to 0.9820 (0.9810-0.9830). Median observed survival time varied from 27 days (10 to 81 days, 25th and 75th percentile) in the highest risk group to 10 years (3655 days (2111 to >3655 days)) in the lowest risk group. Discrimination and calibration were satisfactory between the derivation (2007-2012 assessments) and validation (2013 assessments) cohorts, with a C statistics of 0.77 and discrimination plot intercept 0.094, slope 0.914. The Kaplan-Meier five-year survival curves for each of the 61 groups will be visually represented in six different ways displaying the risk and uncertainty, and can be altered to yield information of interest specific to each patient/caregiver. Conclusion/Implications RESPECT is adaptive and personalized, with instantaneous feedback as the user provides a response to each question. We will present RESPECT’s development and implementation processes and set up an interactive presentation of the calculator, demonstrating RESPECT’s ability to deliver patient-comprehensible end-of-life prognoses with uncertainty to patients and their caregivers

A Data Science Approach to Predictive Analytic Research and Knowledge Translation

Introduction Current approaches to the development and application of predictive studies is inefficient and difficult to reproduce. Thousands of predictive health algorithms have been developed; however, less than 2\% have been assessed outside their original setting and even fewer have been applied and evaluated in practice. Objectives and Approach Objective: To develop a standardized workflow for algorithm development, dissemination and implementation. Existing predictive analytics workflow and open standards were adapted and expanded for health research and health care settings. The approach was designed to work within multidisciplinary teams and to improve research transparency, reproducibility, quality, efficiency and application. Key components include standardized algorithm description files, documentation and code libraries. All libraries and programming packages, which were created for/with open-source software, can be used for a wide range of statistical and machine learning models. Publicly-available repositories contain the algorithms, validation data, R code and other supporting infrastructure. Results Algorithm development involves variable pre-specification and documentation of model variables, followed by creation of data preprocessing code to generate model variables from the study dataset. Preprocessing uses algorithm specification documentation and a function library, building upon and integrating with existing algorithms when possible to preventing code duplication. Models are output as a Predictive Modelling Markup Language (PMML) file, a portable industry standard for describing and scoring predictive models. A separate scoring "engine" is used to implement PMML-described algorithms in a range of settings, including algorithm validation at other research institutions. Algorithm applications currently include the Project Big Life (www.projectbiglife.ca) online calculators, population, health services and public health planning uses and an algorithm visualization tool. An API permits use of the calculator engine by other organizations. Conclusion/Implications Barriers to the implementation of predictive analytics in real-world settings—such as within electronic medical records or decision aid applications—can be mitigated with well described algorithms that are easy to replicate and implement, especially as access to big health data increases and algorithms become increasingly complex

The Lantern Vol. 51, No. 2, Spring 1985

• Electric Pink • Derby Day • Conversation • Seasons of Sonnets • Long After Killing Us • Haunting Memory • Sacrifice • Is This Positive Enough? • My Teddy Bear • A Gentleman of Ten • Hartman Center • Yesterday\u27s Child • Mors Pueris • Momentary Reflections • Children Sleeping • There\u27s No Place Like Home • I Set My Pleasures Adrift • The Beer Can • Fragments of an Epic • Actaeon • She Sleeps • Chicago • Death Light • Tea With Louise • Balance • The Rivers • Chapel • The Hour of Prayer • Une Fille / Une Femme • A One-Way Mirror • Nonconformity • Cada Noche, Lloro • Reflections on an Empty House Down the Street • Evening Melancholy • Abandoned Road • Big Boy • Baby Brothers • Metro Oscuro • Chuchoterhttps://digitalcommons.ursinus.edu/lantern/1126/thumbnail.jp

Long-term survival and costs following extracorporeal membrane oxygenation in critically ill children—a population-based cohort study

Background Extracorporeal membrane oxygenation (ECMO) is used to provide temporary cardiorespiratory support to critically ill children. While short-term outcomes and costs have been evaluated in this population, less is known regarding long-term survival and costs. Methods Population-based cohort study from Ontario, Canada (October 1, 2009 to March 31, 2017), of pediatric patients (< 18 years of age) receiving ECMO, identified through the use of an ECMO procedural code. Outcomes were identified through linkage to provincial health databases. Primary outcome was survival, measured to hospital discharge, as well as at 1 year, 2 years, and 5 years following ECMO initiation. We evaluated total patient costs in the first year following ECMO. Results We analyzed 342 pediatric patients. Mean age at ECMO initiation was 2.9 years (standard deviation [SD] = 5.0). Median time from hospital admission to ECMO initiation was 5 days (interquartile range [IQR] = 1–13 days). Overall survival to hospital discharge was 56.4%. Survival at 1 year, 2 years, and 5 years was 51.5%, 50.0%, and 42.1%, respectively. Among survivors, 99.5% were discharged home. Median total costs among all patients in the year following hospital admission were $147,957 (IQR$70,571–$300,295). Of these costs, the large proportion were attributable to the inpatient cost from the index admission (median$119,197, IQR $57,839–$250,675). Conclusions Children requiring ECMO continue to have a significant in-hospital mortality, but reassuringly, there is little decrease in long-term survival at 1 year. Median costs among all patients were substantial, but largely reflect inpatient hospital costs, rather than post-discharge outpatient costs. This information provides value to providers and health systems, allowing for prognostication of short- and long-term outcomes, as well as long-term healthcare-related expenses for pediatric ECMO survivors