Emergence of Complex Dynamics in a Simple Model of Signaling Networks

A variety of physical, social and biological systems generate complex fluctuations with correlations across multiple time scales. In physiologic systems, these long-range correlations are altered with disease and aging. Such correlated fluctuations in living systems have been attributed to the interaction of multiple control systems; however, the mechanisms underlying this behavior remain unknown. Here, we show that a number of distinct classes of dynamical behaviors, including correlated fluctuations characterized by $1/f$-scaling of their power spectra, can emerge in networks of simple signaling units. We find that under general conditions, complex dynamics can be generated by systems fulfilling two requirements: i) a ``small-world'' topology and ii) the presence of noise. Our findings support two notable conclusions: first, complex physiologic-like signals can be modeled with a minimal set of components; and second, systems fulfilling conditions (i) and (ii) are robust to some degree of degradation, i.e., they will still be able to generate $1/f$-dynamics

Sex differences in circumstances and consequences of outdoor and indoor falls in older adults in the MOBILIZE Boston cohort study

Background: Despite extensive research on risk factors associated with falling in older adults, and current fall prevention interventions focusing on modifiable risk factors, there is a lack of detailed accounts of sex differences in risk factors, circumstances and consequences of falls in the literature. We examined the circumstances, consequences and resulting injuries of indoor and outdoor falls according to sex in a population study of older adults. Methods: Men and women 65 years and older (N = 743) were followed for fall events from the Maintenance of Balance, Independent Living, Intellect, and Zest in the Elderly (MOBILIZE) Boston prospective cohort study. Baseline measurements were collected by comprehensive clinical assessments, home visits and questionnaires. During the follow-up (median = 2.9 years), participants recorded daily fall occurrences on a monthly calendar, and fall circumstances were determined by a telephone interview. Falls were categorized by activity and place of falling. Circumstance-specific annualized fall rates were calculated and compared between men and women using negative binomial regression models. Results: Women had lower rates of outdoor falls overall (Crude Rate Ratio (RR): 0.72, 95% Confidence Interval (CI): 0.56-0.92), in locations of recreation (RR: 0.34, 95% CI: 0.17-0.70), during vigorous activity (RR: 0.38, 95% CI: 0.18-0.81) and on snowy or icy surfaces (RR: 0.55, 95% CI: 0.36-0.86) compared to men. Women and men did not differ significantly in their rates of falls outdoors on sidewalks, streets, and curbs, and during walking. Compared to men, women had greater fall rates in the kitchen (RR: 1.88, 95% CI: 1.04-3.40) and while performing household activities (RR: 3.68, 95% CI: 1.50-8.98). The injurious outdoor fall rates were equivalent in both sexes. Women’s overall rate of injurious indoor falls was nearly twice that of men’s (RR: 1.98, 95% CI: 1.44-2.72), especially in the kitchen (RR: 6.83, 95% CI: 2.05-22.79), their own home (RR: 1.84, 95% CI: 1.30-2.59) and another residential home (RR: 4.65, 95% CI: 1.05-20.66) or other buildings (RR: 2.29, 95% CI: 1.18-4.44). Conclusions: Significant sex differences exist in the circumstances and injury potential when older adults fall indoors and outdoors, highlighting a need for focused prevention strategies for men and women

Fall Risk is Not Black and White

Objective: To determine whether previously reported racial differences in fall rates between White and Black/African American is explained by differences in health status and neighborhood characteristics. Design: Prospective cohort Setting: Community Participants: The study included 550 White and 116 Black older adults in the Greater Boston area (mean age: 78 years; 36% men) who were English-speaking, able to walk across a room, and without severe cognitive impairment. Measurements: Falls were prospectively reported using monthly fall calendars. The location of each fall and fall-related injuries were asked during telephone interviews. At baseline, we assessed risk factors for falls, including sociodemographic characteristics, physiologic risk factors, physical activity, and community-level characteristics. Results: Over the mean follow-up of 1,048 days, 1,539 falls occurred (incidence: 806/1,000 person-years). Whites were more likely than Blacks to experience any falls (867 versus 504 falls per 1,000 person-years; RR [95% CI]: 1.77 [1.33, 2.36]), outdoor falls (418 versus 178 falls per 1,000 person-years; 1.78 [1.08, 2.92]), indoor falls (434 versus 320 falls per 1,000 person-years; 1.44 [1.02, 2.05]), and injurious falls (367 versus 205 falls per 1,000 person-years; 1.79 [1.30, 2.46]). With exception of injurious falls, higher fall rates in Whites than Blacks were substantially attenuated with adjustment for risk factors and community-level characteristics: any fall (1.24 [0.81, 1.89]), outdoor fall (1.57 [0.86, 2.88]), indoor fall (1.08 [0.64, 1.81]), and injurious fall (1.77 [1.14, 2.74]). Conclusion: Our findings suggest that the racial differences in fall rates may be largely due to confounding by individual-level and community-level characteristics

The yield of head CT in syncope: a pilot study

Although head CT is often routinely performed in emergency department (ED) patients with syncope, few studies have assessed its value

Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study

Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model. Methods: Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Multivariate missing data were imposed on four covariates using four different mechanisms; missing completely at random (MCAR), missing at random (MAR), missing not at random (MNAR) and a combination of all three mechanisms. Five amounts of incomplete cases from 5% to 75% were considered. Complete case analysis (CC), single imputation (SI) and five multiple imputation (MI) techniques available within the R statistical software were investigated: a) data augmentation (DA) approach assuming a multivariate normal distribution, b) DA assuming a general location model, c) regression switching imputation, d) regression switching with predictive mean matching (MICE-PMM) and e) flexible additive imputation models. A Cox proportional hazards model was fitted and appropriate estimates for the regression coefficients and model performance measures were obtained. Results: Performing a CC analysis produced unbiased regression estimates, but inflated standard errors, which affected the significance of the covariates in the model with 25% or more missingness. Using SI, underestimated the variability; resulting in poor coverage even with 10% missingness. Of the MI approaches, applying MICE-PMM produced, in general, the least biased estimates and better coverage for the incomplete covariates and better model performance for all mechanisms. However, this MI approach still produced biased regression coefficient estimates for the incomplete skewed continuous covariates when 50% or more cases had missing data imposed with a MCAR, MAR or combined mechanism. When the missingness depended on the incomplete covariates, i.e. MNAR, estimates were biased with more than 10% incomplete cases for all MI approaches. Conclusion: The results from this simulation study suggest that performing MICE-PMM may be the preferred MI approach provided that less than 50% of the cases have missing data and the missing data are not MNAR

Racial Disparities in Emergency General Surgery: Do Differences in Outcomes Persist Among Universally Insured Military Patients?

Research Objective: Described as one of the most serious health problems affecting the nation, racial disparities are estimated to account for \u3e83,000 deaths, \u3e$57 billion per year. They have been identified in multiple surgical settings, including differences in outcomes by race among emergency general surgery(EGS) patients. As many minority patients are uninsured, increasing access to care is thought to be a viable solution to mitigate inequities. The objectives of this study were to determine whether racial disparities in 30/90/180day outcomes exist within a universally-insured population of military/civilian-dependent EGS patients and whether differences in outcomes differentially persist in care received at military-vs-civilian hospitals and among sponsors who are enlisted-service members-vs-officers. It also considered longer-term outcomes of care. Study Design: Risk-adjusted survival analyses using Cox proportional-hazards models assessed race-based differences in mortality, major morbidity, and readmission from index-hospital admission (discharge for readmission) through 30/90/180days. Models accounted for hospital clustering and possible biases associated with missing race (reweighted-estimating equations). Sub-analyses considered effects restricted to operative interventions, stratified by 24 EGS-diagnostic categories defined by the American Association for the Surgery of Trauma(AAST), and effect modification related to rank (SES-proxy: officers-vs-enlisted-sponsors) and military-vs-civilian-hospital care. Population Studied: Five years of national TRICARE Prime/Prime-plus data, which provides insurance to active/reserve/retired members of the US Armed Services and dependents, were queried for adults (≥18y) with primary EGS conditions, defined by the AAST. Patients who did not have an index admission between 01/01/2006-01/07/2010 (minimum 180days follow-up) or who were not continuously enrolled in TRICARE for 180days were excluded. Non-surviving patients were retained while they survived. Principal Findings: A total of 101,011 patients were included: 73.5% White, 14.5% Black, 4.4% Asian, 7.7% other. Risk-adjusted analyses reported equivalent-or-better mortality and readmission outcomes among minority patients at 30/90/180days—even when restricted to civilian hospitals where studies suggest that EGS disparities are found. Readmissions within military hospitals were lower among minority patients. Major morbidity was higher among Black versus White patients (HR[95%CI]): 30day-1.23[1.13-1.35], 90day-1.18[1.09-1.28], 180day-1.15[1.07-1.24]—a finding driven by appendiceal disorders (HR:1.69-1.70). No other diagnostic category-based HR was significant. When considered by rank, significant effects were isolated to enlisted-service members. However, given the relatively small number of patients who were (dependents of) officers, it is difficult to determine whether rank-based findings are a result of social determinants or influenced by the limited number of minority patients. Conclusions: The first of its kind to examine racial disparities in longer-term outcomes of EGS care, this longitudinal analysis of military patients demonstrated apparent mitigation of racial disparities within a universally-insured health system when compared to the overall US health system. Efforts to explain findings based on consideration of care provided in military-vs-civilian hospitals, among specific EGS-diagnostic categories, and based on sponsor rank revealed modification of the association between race and outcomes to some extent for all three. Implications for Policy or Practice: The contrast between results for universally-insured military/civilian-dependent patients and reported disparities among all US civilian patients merits consideration. The data speak to the importance of insurance-coverage in the development of disparities interventions nationwide and will help to inform policy within the DoD

Effects of intensive blood pressure treatment on orthostatic hypotension a systematic review and individual participant-based meta-analysis

Background: Although intensive blood pressure (BP)-lowering treatment reduces risk for cardiovascular disease, there are concerns that it might cause orthostatic hypotension (OH). Purpose: To examine the effects of intensive BP-lowering treatment on OH in hypertensive adults. Data Sources: MEDLINE, EMBASE, and Cochrane CENTRAL from inception through 7 October 2019, without language restrictions. Study Selection: Randomized trials of BP pharmacologic treatment (more intensive BP goal or active agent) that involved more than 500 adults with hypertension or elevated BP and that were 6 months or longer in duration. Trial comparisons were groups assigned to either less intensive BP goals or placebo, and the outcome was measured OH, defined as a decrease of 20mmHg or more in systolic BP or 10 mm Hg or more in diastolic BP after changing position from seated to standing. Data Extraction: 2 investigators independently abstracted articles and rated risk of bias. Data Synthesis: 5 trials examined BP treatment goals, and 4 examined active agents versus placebo. Trials examining BP treatment goals included 18 466 participants with 127 882 follow-up visits. Trials were open-label, with minimal heterogeneity of effects across trials. Intensive BP treatment lowered risk for OH (odds ratio, 0.93 [95% CI, 0.86 to 0.99]). Effects did not differ by prerandomization OH (P for interaction = 0.80). In sensitivity analyses that included 4 additional placebo-controlled trials, overall and subgroup findings were unchanged. Limitations: Assessments of OH were done while participants were seated (not supine) and did not include the first minute after standing. Data on falls and syncope were not available. Conclusion: Intensive BP-lowering treatment decreases risk for OH. Orthostatic hypotension, before or in the setting of more intensive BP treatment, should not be viewed as a reason to avoid or de-escalate treatment for hypertension

Testing for Fictive Learning in Decision-Making Under Uncertainty

We conduct two experiments where subjects make a sequence of binary choices between risky and ambiguous binary lotteries. Risky lotteries are defined as lotteries where the relative frequencies of outcomes are known. Ambiguous lotteries are lotteries where the relative frequencies of outcomes are not known or may not exist. The trials in each experiment are divided into three phases: pre-treatment, treatment and post-treatment. The trials in the pre-treatment and post-treatment phases are the same. As such, the trials before and after the treatment phase are dependent, clustered matched-pairs, that we analyze with the alternating logistic regression (ALR) package in SAS. In both experiments, we reveal to each subject the outcomes of her actual and counterfactual choices in the treatment phase. The treatments differ in the complexity of the random process used to generate the relative frequencies of the payoffs of the ambiguous lotteries. In the first experiment, the probabilities can be inferred from the converging sample averages of the observed actual and counterfactual outcomes of the ambiguous lotteries. In the second experiment the sample averages do not converge. If we define fictive learning in an experiment as statistically significant changes in the responses of subjects before and after the treatment phase of an experiment, then we expect fictive learning in the first experiment, but no fictive learning in the second experiment. The surprising finding in this paper is the presence of fictive learning in the second experiment. We attribute this counterintuitive result to apophenia: “seeing meaningful patterns in meaningless or random data.” A refinement of this result is the inference from a subsequent Chi-squared test, that the effects of fictive learning in the first experiment are significantly different from the effects of fictive learning in the second experiment