Dynamical Resilience Indicators in Time Series of Self-Rated Health Correspond to Frailty Levels in Older Adults

Assessing dynamical resilience indicators in older adults: a prospective feasibility cohort study

PURPOSE

Measuring dynamical resilience indicators based on time series data may improve the prediction of health deterioration in older adults after hospital discharge. We examined the feasibility of an intensive prospective cohort study examining dynamical resilience indicators based on time series data of symptoms and physical activity in acutely ill older adults who visited the Emergency Department (ED).

METHODS

This is a prospective cohort study with time series data from symptom questionnaires and activity trackers. Thirty older adults (aged 75.9 ± 5.5 years, 37% female) who were discharged from the ED of a tertiary hospital in the Netherlands were included in the study. We monitored self-reported symptoms using a daily online questionnaire, and physical activity using an activity tracker for 30 days. Descriptive data on participant eligibility and adherence to and acceptability of the assessments were collected.

RESULTS

Of 134 older patients visiting the ED, 109/134 (81%) were eligible for inclusion and 30/109 (28%) were included. Twenty-eight (93%) of the included participants completed follow-up. Regarding the adherence rate, 78% of participants filled in the questionnaire and 80% wore the activity tracker. Three (10%) participants completed fewer than three questionnaires. Most participants rated the measurements as acceptable and seven (23%) participants experienced an adverse outcome in the 30 days after discharge.

CONCLUSION

Such an intensive prospective cohort study examining dynamical resilience indicators in older adults was feasible. The quality of the collected data was sufficient, some adjustments to the measurement protocol are recommended. This study is an important first step to study resilience in older adults.

The vulnerability of aging states: A survival analysis across premodern societies

How states and great powers rise and fall is an intriguing enigma of human history. Are there any patterns? Do polities become more vulnerable over time as they age? We analyze longevity in hundreds of premodern states using survival analysis to help provide initial insights into these questions. This approach is commonly used to study the risk of death in biological organisms or failure in mechanical systems. The results reveal that the risk of state termination increased steeply over approximately the first two centuries after formation and stabilized thereafter. This provides the first quantitative support for the hypothesis that the resilience of political states decreases over time. Potential mechanisms that could drive such declining resilience include environmental degradation, increasing complexity, growing inequality, and extractive institutions. While the cases are from premodern times, such dynamics and drivers of vulnerability may remain relevant today.

Association between Muscle Fatigability, Self-Perceived Fatigue and C-Reactive Protein at Admission in Hospitalized Geriatric Patients

Background: The capacity to perceived vitality (CPV) ratio is a novel measure for intrinsic capacity or resilience based on grip work and self-perceived fatigue. CPV has been associated with pre-frailty in older adults and post-surgery inflammation in adults. To better understand the utility of this measure in a frail population, we examined the association between CPV and inflammation in geriatric inpatients. Methods: Data were obtained from 104 hospitalized geriatric patients. The average age of participants was 83.3 ± 7.5 years, and 55.8% of participants were women. In the cross-sectional analyses, associations between C-reactive protein (CRP), grip work (GW), self-perceived fatigue (SPF) and the CPV ratio (higher values indicate better capacity) were examined using linear regression adjusted for confounders. Results: The adjusted association between CRP (abnormal vs. normal) and the CPV ratio was not statistically significant (B = -0.33, 95% CI = -4.00 to 3.34). Associations between CRP and GW (B = 25.53, 95% CI = -478.23 to 529.30) and SPF (B = 0.57, 95% CI = -0.64 to 1.77) were also not statistically significant. Similar results were found in unadjusted models and analyses of cases with complete data. Conclusions: In this frail group of geriatric inpatients, inflammation, routinely assessed with CRP, was not associated with CPV or its components, GW and SPF. Further research is needed to explore whether CPV is a useful indicator of frailty or recovery capacity in hospitalized geriatric patients.

Predicting mortality risk after a fall in older adults using health care spending patterns: a population-based cohort study

OBJECTIVE

To develop a prognostic model of 1-year mortality for individuals aged 65+ presenting at the emergency department (ED) with a fall based on health care spending patterns to guide clinical decision-making.

DESIGN

Population-based cohort study (n = 35,997) included with a fall in 2013 and followed 1 year.

METHODS

Health care spending indicators (dynamical indicators of resilience, DIORs) 2 years before admission were evaluated as potential predictors, along with age, sex and other clinical and sociodemographic covariates. Multivariable logistic regression models were developed and internally validated (10-fold cross-validation). Performance was assessed via discrimination (area under the receiver operating characteristic curve, AUC), Brier scores, calibration and decision curve analysis.

RESULTS

The AUC of age and sex for mortality was 72.5% [95% confidence interval 71.8 to 73.2]. The best model included age, sex, number of medications and health care spending DIORs. It exhibited high discrimination (AUC: 81.1 [80.5 to 81.6]), good calibration and potential clinical benefit for various threshold probabilities. Overall, health care spending patterns improved predictive accuracy the most while also exhibiting superior performance and clinical benefit.

CONCLUSIONS

Patterns of health care spending have the potential to significantly improve assessments on who is at high risk of dying following admission to the ED with a fall. The proposed methodology can assist in predicting the prognosis of fallers, emphasising the added predictive value of longitudinal health-related information next to clinical and sociodemographic predictors.

Measurements of damage and repair of binary health attributes in aging mice and humans reveal that robustness and resilience decrease with age, operate over broad timescales, and are affected differently by interventions

As an organism ages, its health-state is determined by a balance between the processes of damage and repair. Measuring these processes requires longitudinal data. We extract damage and repair transition rates from repeated observations of binary health attributes in mice and humans to explore robustness and resilience, which respectively represent resisting or recovering from damage. We assess differences in robustness and resilience using changes in damage rates and repair rates of binary health attributes. We find a conserved decline with age in robustness and resilience in mice and humans, implying that both contribute to worsening aging health - as assessed by the frailty index (FI). A decline in robustness, however, has a greater effect than a decline in resilience on the accelerated increase of the FI with age, and a greater association with reduced survival. We also find that deficits are damaged and repaired over a wide range of timescales ranging from the shortest measurement scales toward organismal lifetime timescales. We explore the effect of systemic interventions that have been shown to improve health, including the angiotensin-converting enzyme inhibitor enalapril and voluntary exercise for mice. We have also explored the correlations with household wealth for humans. We find that these interventions and factors affect both damage and repair rates, and hence robustness and resilience, in age and sex-dependent manners.

Self-perceived health and functional status of older people: Telephone-based lifestyle survey of older adults in Tehran province

Background: The prevalence study of health conditions can help policy makers to document base policymaking. This study aimed to reveal the health status, including the prevalence of geriatric syndrome health conditions such as activity of daily livings, pain, and physical and mental health of older adults in Tehran province.

Methods: This cross-sectional study was a telephone survey with older people ≥60 years old using a systematic random sampling of telephone numbers in Tehran province. The Persian version of the Katz’ activity of daily living (ADL) and the Lawton’s instrumental activity of daily living (IADL) questionnaires were used to evaluate the functional status. Pain, history of chronic diseases, continence, hospital admission, sensory problems, and self-perceived health (SPH) were asked by trained nurses or gerontologists thorough telephone interviews.

Results: In this study, 1251 older adults with the mean age of 67.03±7.51 years have been recruited. About 64.50% (95% CI: 64.4-64.6) of them were totally independent according to ADL (female=60.02% and male=68.50%), and about 40.50% (95% CI: 40.4-40.5) were independent based on IADL domains (female=39.41% and male=41.80). The dependency rates in ADL increased with the aging of population. Joint pain was the most prevalent type of pains and near to 26.00% (95% CI: 64.4-64.6) of the participants suffered moderate joint pains. About 71.5% (95% CI: 71.4-71.5) of the participants were urinary continent (female=67.66% and male=76.06%), and 91.9% (95% CI: 91.9-92.0) had bowel control (female=91.47% and male=92.94%) and the prevalence of incontinence increased by advancing age. Only 26.70% (95% CI: 26.6-26.8) of the participants reported excellent and good levels of perceived health status (female=21.98% and male=31.48%) and about 26.2% (95% CI: 26.1-26.2) of them reported some degree of visual impairment.

Conclusion: The results of the present study can provide a good view about the health profile of older adults, including pain, functional status, sphincter control, chronic diseases, sensory status, and SPH. Future studies should prioritize SPH as an important predictor of mortality rates.

A complex systems approach to aging biology

Having made substantial progress understanding molecules, cells, genes and pathways, aging biology research is now moving toward integration of these parts, attempting to understand how their joint dynamics may contribute to aging. Such a shift of perspective requires the adoption of a formal complex systems framework, a transition being facilitated by large-scale data collection and new analytical tools. Here, we provide a theoretical framework to orient researchers around key concepts for this transition, notably emergence, interaction networks and resilience. Drawing on evolutionary theory, network theory and principles of homeostasis, we propose that organismal function is accomplished by the integration of regulatory mechanisms at multiple hierarchical scales, and that the disruption of this ensemble causes the phenotypic and functional manifestations of aging. We present key examples at scales ranging from sub-organismal biology to clinical geriatrics, outlining how this approach can potentially enrich our understanding of aging.

Synchrony of biomarker variability indicates a critical transition: Application to mortality prediction in hemodialysis

Critical transition theory suggests that complex systems should experience increased temporal variability just before abrupt state changes. We tested this hypothesis in 763 patients on long-term hemodialysis, using 11 biomarkers collected every two weeks and all-cause mortality as a proxy for critical transitions. We find that variability-measured by coefficients of variation (CVs)-increases before death for all 11 clinical biomarkers, and is strikingly synchronized across all biomarkers: the first axis of a principal component analysis on all CVs explains 49% of the variance. This axis then generates powerful predictions of mortality (HR95 = 9.7, p < 0.0001, where HR95 is a scale-invariant metric of hazard ratio; AUC up to 0.82) and starts to increase markedly ∼3 months prior to death. Our results provide an early warning sign of physiological collapse and, more broadly, a quantification of joint system dynamics that opens questions of how system modularity may break down before critical transitions.

Dynamical indicators in time series of healthcare expenditures predict mortality risk of older adults following spousal bereavement

BACKGROUND

The process of aging renders older people susceptible for adverse outcomes upon stress. Various indicators derived from complex systems theory have been proposed for quantifying resilience in living organisms, including humans. We investigated the ability of system-based indicators in capturing the dynamics of resilience in humans who suffer the adversity of spousal bereavement and tested their predictive power in mortality as a finite health transition.

METHODS

Using longitudinal register data on weekly healthcare consumption of all Danish citizens over the age of 65 from January 1st, 2011, throughout December 31st, 2016, we performed statistical comparisons of the indicators 'average', 'slope', 'mean squared error', and 'lag-1 autocorrelation' one year before and after spousal bereavement, stratified for age and sex. The relation between levels of these indicators before bereavement and mortality hazards thereafter was determined by time to event analysis. We assessed the added value for mortality prediction via the time dependent area (AUC) under the receiver operating characteristic curve.

RESULTS

The study included 934,003 citizens of whom 51,890 experienced spousal bereavement and 2862 died in the first year thereafter. Healthcare consumption is increased, more volatile and accelerating with aging and in men compared to women (all p-values < 0.001). All dynamic indicators before bereavement were positively related with mortality hazards thereafter (all p-values < 0.001). The average discriminative performance for the 1-year mortality risk of the model with only age as a predictor (AUC: 68.9% and 70.2%) was significantly increased with the addition of dynamical indicators (78.5% and 82.4%) for males and females, respectively.

CONCLUSIONS

Dynamic indicators in time series of health care expenditures are strong predictors of mortality risk and could be part of predictive models for prognosis after life stressors, such as bereavement.

Resilience in sports: a multidisciplinary, dynamic, and personalized perspective

Athletes are exposed to various psychological and physiological stressors, such as losing matches and high training loads. Understanding and improving the resilience of athletes is therefore crucial to prevent performance decrements and psychological or physical problems. In this review, resilience is conceptualized as a dynamic process of bouncing back to normal functioning following stressors. This process has been of wide interest in psychology, but also in the physiology and sports science literature (e.g. load and recovery). To improve our understanding of the process of resilience, we argue for a collaborative synthesis of knowledge from the domains of psychology, physiology, sports science, and data science. Accordingly, we propose a multidisciplinary, dynamic, and personalized research agenda on resilience. We explain how new technologies and data science applications are important future trends (1) to detect warning signals for resilience losses in (combinations of) psychological and physiological changes, and (2) to provide athletes and their coaches with personalized feedback about athletes' resilience.

The hanging chin sign as a mortality predictor in geriatric patients at the emergency department: a retrospective cohort study

Background

At the emergency department, there is a need for an instrument which is quick and easy to use to identify geriatric patients with the highest risk of mortality. The so- called ‘hanging chin sign’, meaning that the mandibula projects over one or more ribs on the chest X-ray, could be such an instrument. This study aims to investigate if the hanging chin sign is a predictor of mortality in geriatric patients admitted through the emergency department.

Methods

We performed an observational retrospective cohort study in a Dutch teaching hospital. Patients of ≥65 years who were admitted to the geriatric ward following an emergency department visit were included. The primary outcome of this study was mortality. Secondary outcomes included the length of admission, discharge destination and the reliability compared to patient-related variables and the APOP screener.

Results

Three hundred ninety-six patients were included in the analysis. Mean follow up was 300 days; 207 patients (52%) died during follow up. The hanging chin sign was present in 85 patients (21%). Patients with the hanging chin sign have a significantly higher mortality risk during admission (OR 2.94 (1.61 to 5.39), p < 0.001), within 30 days (OR 2.49 (1.44 to 4.31), p = 0.001), within 90 days (OR 2.16 (1.31 to 3.56), p = 0.002) and within end of follow up (OR 2.87 (1.70 to 4.84),p < 0.001). A chest X-ray without a PA view or lateral view was also associated with mortality. This technical detail of the chest x-ray and the hanging chin sign both showed a stronger association with mortality than patient-related variables or the APOP screener.

Conclusions

The hanging chin sign and other details of the chest x-ray were strong predictors of mortality in geriatric patients presenting at the emergency department and admitted to the geriatric ward. Compared to other known predictors, they seem to do even better in predicting mortality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02780-7.

Physical Resilience in Daily Functioning Among Acutely Ill Hospitalized Older Adults: The Hospital-ADL Study

OBJECTIVES

Insight into older adults' physical resilience is needed to predict functional recovery after hospitalization. We assessed functional trajectories in response to acute illness and subsequent hospitalization and investigated baseline variables and dynamic variables associated with these trajectories.

DESIGN

Prospective observational cohort study (Hospitalization-Associated Disability and impact on daily Life Study).

SETTING AND PARTICIPANTS

This study included 207 older adults (aged 79.8 ± 6.9 years, 49% female, 57% frail) acutely hospitalized in 6 Dutch hospitals.

METHODS

Functional disability was assessed using the 15-item modified activities of daily living index retrospectively 2 weeks before admission, and prospectively from admission up to 3 months after discharge. Baseline variables including frailty, somatic, physical, and psychosocial factors were assessed at admission. Dynamic variables (step count, pain, fatigue, and fear of falling) were continuously or repeatedly assessed during hospitalization. We performed individual spline modeling using random effects. Baseline variables and within-person mean levels and variability in the dynamic variables were assessed as predictors of functional trajectories.

RESULTS

Functional disability significantly increased before admission and decreased from admission to 3 months post discharge. Frail participants had a significantly higher increase in functional disability before admission compared with nonfrail participants. Lower step count, higher pain scores, and higher within-person variability in fear of falling were significantly associated with higher increase in functional disability before admission. Higher within-person variability in fear of falling was associated with more recovery.

CONCLUSIONS AND IMPLICATIONS

Older adults increase in functional disability before hospitalization and start to recover from admission onward. Frailty and dynamic variables are associated with a higher increase in functional disability after acute illness. Our findings give more insight into older adults' physical resilience, which may improve the prediction of functional recovery and may improve therapeutic decision-making and rehabilitation strategies to improve functional recovery after acute hospitalization.

Self-rated health trajectory and frailty among community-dwelling older adults: evidence from the Taiwan Longitudinal Study on Aging (TLSA)

OBJECTIVES

Self-rated health (SRH) is an assessment and predictor of health based on an individual's general condition; however, evidence of the value of SRH for predicting frailty remains scarce for older Asian adults. This study aimed to evaluate the relationship between SRH score trajectory and frailty among older individuals in Taiwan.

DESIGN

An 8-year retrospective cohort study.

SETTING

Data were retrieved from the Taiwan Longitudinal Study on Aging from 1999 to 2007.

PARTICIPANTS

Respondents aged 53-69 years old who were not frail or disabled in 1999 (n=1956).

PRIMARY AND SECONDARY OUTCOME MEASURES

Frailty was defined using the Fried criteria. The group-based trajectory modelling technique was used to estimate SRH trajectories. Logistic regression analysis was used to examine the associations between changes in SRH and frailty.

RESULTS

Four SRH trajectory classes were identified across the 8-year follow-up: 232 participants (11.9%) were classified into the constantly poor SRH group, 1123 (57.4%) into the constantly fair SRH group, 335 (17.1%) into the constantly good SRH group and 266 (13.6%) into the good-to-fair SRH group. After adjusting for gender, age, level of education, income, social participation, health behaviours and major comorbidities, it was found that age, poor income satisfaction, without job and constantly poor SRH were associated with increased risk of frailty, while constantly good SRH (OR 0.04, 95% CI (0.01 to 0.32)) and good-to-fair SRH (OR 0.19, 95% CI (0.06 to 0.63)) were associated with reduced risks of frailty.

CONCLUSIONS

Constantly poor SRH was associated with an increased risk of frailty in older age. SRH in older adults should be recognised as a predictive tool for future frailty. Diet and exercise interventions may help to prevent frailty among high-risk older individuals with constantly low SRH.

Dynamical indicators of resilience from physiological time series in geriatric inpatients: Lessons learned

The concept of physical resilience may help geriatric medicine objectively assess patients' ability to 'bounce back' from future health challenges. Indicators putatively forecasting resilience have been developed under two paradigms with different perspectives: Critical Slowing Down and Loss of Complexity. This study explored whether these indicators validly reflect the construct of resilience in geriatric inpatients. Geriatric patients (n = 121, 60% female) had their heart rate and physical activity continuously monitored using a chest-worn sensor. Indicators from both paradigms were extracted from both physiological signals. Measures of health functioning, concomitant with low resilience, were obtained by questionnaire at admission. The relationships among indicators and their associations with health functioning were assessed by correlation and linear regression analyses, respectively. Greater complexity and higher variance in physical activity were associated with lower frailty (β = -0.28, p = .004 and β = -0.37, p < .001, respectively) and better ADL function (β = 0.23, p = .022 and β = 0.38, p < .001). The associations of physical activity variance with health functioning were not in the expected direction based on Critical Slowing Down. In retrospect, these observations stress the importance of matching the resilience paradigm's assumptions to the homeostatic role of the variable monitored. We present several lessons learned.

Potentially preventable hospitalizations-The 'pre-hospital syndrome': Retrospective observations from the MonashWatch self-reported health journey study in Victoria, Australia

RATIONALE, AIMS, AND OBJECTIVES

HealthLinks: Chronic Care is a state-wide public hospital initiative designed to improve care for cohorts at-risk of potentially preventable hospitalizations at no extra cost. MonashWatch (MW) is an hospital outreach service designed to optimize admissions in an at-risk cohort. Telehealth operators make regular phone calls (≥weekly) using the Patient Journey Record System (PaJR). PaJR generates flags based on patient self-report, alerting to a risk of admission or emergency department attendance. 'Total flags' of global health represent concerns about self-reported general health, medication, and wellness. 'Red flags' represent significant disease/symptoms concerns, likely to lead to hospitalization.

METHODS

A time series analysis of PaJR phone calls to MW patients with ≥1 acute non-surgical admissions in a 20-day time window (10 days pre-admission and 10 days post-discharge) between 23 December 2016 and 11 October 2017. Pettitt's hypothesis-testing homogeneity measure was deployed to analyse Victorian Admitted Episode/Emergency Minimum Datasets and PaJR data.

FINDINGS

A MW cohort of 103 patients (mean age 74 ± 15 years; with 59% males) had 263 admissions was identified. Bed days ranged from <1 to 37.3 (mean 5.8 ± 5.8; median 4.1). The MW cohort had 7.6 calls on average in the 20-day pre- and post-hospital period. Most patients reported significantly increased flags 'pre-hospital' admission: medication issues increased on day 7.0 to 8.5; total flags day 3, worse general health days 2.5 to 1.8; and red flags of disease symptoms increased on day 1. These flags persisted following discharge.

DISCUSSION/CONCLUSION

This study identified a 'pre-hospital syndrome' similar to a post-hospital phase aka the well-documented 'post-hospital syndrome'. There is evidence of a 10-day 'pre-hospital' window for interventions to possibly prevent or shorten an acute admission in this MW cohort. Further validation in a larger diverse sample is needed.

Prediction of Mortality in Hemodialysis Patients Using Moving Multivariate Distance

There is an increasingly widespread use of biomarkers in network physiology to evaluate an organism’s physiological state. A recent study showed that albumin variability increases before death in chronic hemodialysis patients. We hypothesized that a multivariate statistical approach would better allow us to capture signals of impending physiological collapse/death. We proposed a Moving Multivariate Distance (MMD), based on the Mahalanobis distance, to quantify the variability of the multivariate biomarker profile as a whole from one visit to the next. Biomarker profiles from a visit were used as the reference to calculate MMD at the subsequent visit. We selected 16 biomarkers (of which 11 are measured every 2 weeks) from blood samples of 763 chronic kidney disease patients hemodialyzed at the CHUS hospital in Quebec, who visited the hospital regularly (∼every 2 weeks) to perform routine blood tests. MMD tended to increase markedly preceding death, indicating an increasing intraindividual multivariate variability presaging a critical transition. In survival analysis, the hazard ratio between the 97.5th percentile and the 2.5th percentile of MMD reached as high as 21.1 [95% CI: 14.3, 31.2], showing that higher variability indicates substantially higher mortality risk. Multivariate approaches to early warning signs of critical transitions hold substantial clinical promise to identify early signs of critical transitions, such as risk of death in hemodialysis patients; future work should also explore whether the MMD approach works in other complex systems (i.e., ecosystems, economies), and should compare it to other multivariate approaches to quantify system variability.

Quantifying and Classifying Physical Resilience Among Older Adults: The Health, Aging, and Body Composition Study

BACKGROUND

The concept of resilience has gained increasing attention in aging research; however, current literature lacks consensus on how to measure resilience. We constructed a novel resilience measure based on the degree of mismatch between persons' frailty level and disease burden and examined its predictive validity. We also sought to explore the physiological correlates of resilience.

METHODS

Participants were 2,457 older adults from the Health, Aging, and Body Composition Study. We constructed the resilience measure as the residual taken from the linear model regressing frailty on age, sex, race/ethnicity, 14 diseases, self-reported health, and number of medications. Participants were classified into three groups-adapters, expected agers, and premature frailers-based on residuals (less than, within, or above one standard deviation of the mean). Validation outcomes included years of able life (YAL), years of healthy life (YHL), years of healthy and able life (YHAL), disability, hospitalization, and survival.

RESULTS

The average YHAL was 5.1, 7.7, and 9.1 years among premature frailers, expected agers, and adapters, respectively. Compared with premature frailers and expected agers, adapters had significantly lower rates of disability, hospitalization, and mortality and higher proportion surviving to 90 years. The likelihood of surviving to 90 years was 20.4%, 30.6%, and 39.7% among premature frailers, expected agers, and adapters.

CONCLUSIONS

We developed and validated a novel approach for quantifying and classifying physical resilience in a cohort of well-functioning white and black older adults. Persons with high physical resilience level had longer healthy life span and lower rates of adverse outcomes.

The physical frailty syndrome as a transition from homeostatic symphony to cacophony

Frailty in aging marks a state of decreased reserves resulting in increased vulnerability to adverse outcomes when exposed to stressors. This Perspective synthesizes the evidence on the aging-related pathophysiology underpinning the clinical presentation of physical frailty as a phenotype of a clinical syndrome that is distinct from the cumulative-deficit-based frailty index. We focus on integrating the converging evidence on the conceptualization of physical frailty as a state, largely independent of chronic diseases, that emerges when the dysregulation of multiple interconnected physiological and biological systems crosses a threshold to critical dysfunction, severely compromising homeostasis. Our exegesis posits that the physiology underlying frailty is a critically dysregulated complex dynamical system. This conceptual framework implies that interventions such as physical activity that have multisystem effects are more promising to remedy frailty than interventions targeted at replenishing single systems. We then consider how this framework can drive future research to further understanding, prevention and treatment of frailty, which will likely preserve health and resilience in aging populations.

Differential haptoglobin responsiveness to a Mannheimia haemolytica challenge altered immunologic, physiologic, and behavior responses in beef steers

Indicator traits associated with disease resiliency would be useful to improve the health and welfare of feedlot cattle. A post hoc analysis of data collected previously (Kayser et al., 2019a) was conducted to investigate differences in immunologic, physiologic, and behavioral responses of steers (N = 36, initial BW = 386 ± 24 kg) that had differential haptoglobin (HPT) responses to an experimentally induced challenge with Mannheimia haemolytica (MH). Rumen temperature, DMI, and feeding behavior data were collected continuously, and serial blood samples were collected following the MH challenge. Retrospectively, it was determined that 9 of the 18 MH-challenged steers mounted a minimal HPT response, despite having similar leukocyte and temperature responses to other MH-challenged steers with a greater HPT response. Our objective was to examine differences in behavioral and physiological responses between MH-challenged HPT responsive (RES; n = 9), MH-challenged HPT nonresponsive (NON; n = 9), and phosphate-buffered saline-inoculated controls (CON; n = 18). Additionally, 1H NMR analysis was conducted to determine whether the HPT-responsive phenotype affected serum metabolite profiles. The RES steers had lesser (P < 0.05) cortisol concentrations than NON and CON steers. The magnitude of the increases in neutrophil concentrations and rumen temperature, and the reduction in DMI following the MH challenge were greatest (P < 0.05) in RES steers. Univariate analysis of serum metabolites indicated differences between RES, NON, and CON steers following the MH challenge; however, multivariate analysis revealed no difference between HPT-responsive phenotypes. Prior to the MH challenge, RES steers had longer (P < 0.05) head down and bunk visit durations, slower eating rates (P < 0.01) and greater (P < 0.05) daily variances in bunk visit frequency and head down duration compared with NON steers, suggesting that feeding behavior patterns were associated with the HPT-responsive phenotype. During the 28-d postchallenge period, RES steers had decreased (P < 0.05) final BW, tended (P = 0.06) to have lesser DMI, and had greater (P < 0.05) daily variances in head down and bunk visit durations compared with NON steers, which may have been attributed to their greater acute-phase protein response to the MH challenge. These results indicate that the HPT-responsive phenotype affected feeding behavior patterns and may be associated with disease resiliency in beef cattle.

Psychological contributors to the frail phenotype: The association between resilience and frailty in patients with cirrhosis

We examined whether a key psychological trait-resilience, defined as one's ability to recover quickly from difficulties-contributes to the frail phenotype in patients with cirrhosis. Included were 300 adult patients with cirrhosis who underwent outpatient physical frailty testing using the Liver Frailty Index and resilience testing using the Connor-Davidson Resilience Scale (CD-RISC). The Liver Frailty Index was categorized as robust, prefrail-robust, prefrail-frail, and frail; CD-RISC was categorized using population norms as: least, less, more, and most resilient. Linear regression was used to assess factors associated with frailty (by the Liver Frailty Index per 0.1 unit change). Among the most resilient, only 10% were frail; among the least resilient, 29% were frail. In univariable analysis, resilience was strongly associated with the Liver Frailty Index (coef = -0.13 per point increase; 95% confidence interval [CI], -0.20 to -0.60; P < .001) and remained significantly associated with frailty in multivariable adjustment (coef = -0.13, 95% CI -0.19 to -0.07; P < .001). Low resilience is strongly associated with the frail phenotype in patients with cirrhosis. Given that resilience is modifiable, our data suggest that effective interventions to mitigate frailty should include strategies to build resilience in patients with low baseline resilience.

Resilience in older persons: A systematic review of the conceptual literature

Although ageing research increasingly incorporates resilience, a common notion on what resilience means is lacking. We aimed to give a comprehensive overview of the conceptual literature on resilience in older persons, identifying areas of consensus and variation/debate. A systematic search of eight databases from different disciplines led to the inclusion of 36 texts. Across the conceptual literature of resilience in older persons, three common features of descriptions of resilience were identified: a stressor, a response and a mechanism. Based on differences in their interpretation of how resilience is expressed we distinguished two perspectives. The first, classical and most widely applied perspective, describes the expression of resilience as a positive response to a high intensity stressor. The second, newer perspective, describes resilience in the context of responses relative to equilibrium, following low intensity stressors. Almost all descriptions across the two perspectives describe the resilience mechanism to be dynamic and emphasize the importance of the context in achieving resilience. This review provides clarity on the current conceptual status of resilience in older persons, an important step towards a higher level of consistency in the future use of resilience in ageing.

The role of illness acuity on the association between frailty and mortality in emergency department patients referred to internal medicine

BACKGROUND

we investigated whether two frailty tools predicted mortality among emergency department (ED) patients referred to internal medicine and how the level of illness acuity influenced any association between frailty and mortality.

METHODS

two tools, embedded in a Comprehensive Geriatric Assessment (CGA), were the clinical frailty scale (CFS) and a 57-item deficit accumulation frailty index (FI-CGA). Illness acuity was assessed using the Canadian Triage and Acuity Scale (CTAS). We examined all-cause 30-day and 6-month mortality and time to death.

RESULTS

in 808 ED patients (mean age ± SD 80.8 ± 8.8, 54.4% female), the mean FI-CGA score was 0.44 ± 0.14, and the CFS was 5.6 ± 1.6. A minority (307; 38%) were classified as having high acuity (CTAS: 1-2). The 30-day mortality rate was 17%; this increased to 34% at 6 months. Compared to well patients with low acuity, the risk of 30-day mortality was 22.5 times (95% CI: 9.35-62.12) higher for severely frail patients with high acuity; 53% of people with very severe frailty (CFS = 8) and high acuity died within 30 days. When acuity was low, the risk for 30-day mortality was significantly higher only among those with very high levels of frailty (CFS 7-9, FI-CGA > 0.5). When acuity was high, even lower levels of frailty (CFS 5-6, FI-CGA 0.4-0.5) were associated with higher 30-day mortality.

CONCLUSIONS

across levels of frailty, higher acuity increased mortality risk. When acuity was low, the risk was significant only when the degree of frailty was high, whereas when acuity was high, even lower levels of frailty were associated with greater mortality risk.

Evidence from two cohorts for the frailty syndrome as an emergent state of parallel dysregulation in multiple physiological systems

Frailty is a clinical syndrome often present in older adults and characterized by a heightened vulnerability to stressors. The biological antecedents and etiology of frailty are unclear despite decades of research: frailty is associated with dysregulation in a wide range of physiological systems, but no specific cause has been identified. Here, we test predictions stemming from the hypothesis that there is no specific cause: that frailty is an emergent property arising from the complex systems dynamics of the broad loss of organismal homeostasis. Specifically, we use dysregulation of six physiological systems using the Mahalanobis distance approach in two cohorts of older adults to test the breadth, diffuseness, and nonlinearity of associations between frailty and system-specific dysregulation. We find clear support for the breadth of associations between frailty and physiological dysregulation: positive associations of all systems with frailty in at least some analyses. We find partial support for diffuseness: the number of systems or total amount of dysregulation is more important than the identity of the systems dysregulated, but results only partially replicate across cohorts. We find partial support for nonlinearity: trends are exponential but not always significantly so, and power is limited for groups with very high levels of dysregulation. Overall, results are consistent with-but not definitive proof of-frailty as an emergent property of complex systems dynamics. Substantial work remains to understand how frailty relates to underlying physiological dynamics across systems.

Psychological Resilience as an Emergent Characteristic for Well-Being: A Pragmatic View

Currently, there is no clear agreement on the definition and conceptualization for psychological resilience (PR) in old age. Adopting a pragmatic view, this article elucidates the definition and conceptualization of PR by (1) extracting existing PR concepts that are relevant to aging, and (2) elucidating the contributing and delimiting factors for developing and sustaining PR as guided by the biopsychosocial framework. In addition, a comprehensive review of the tools used to measure PR was conducted to examine how scholars have conceptualized PR. Consequently, the renewed understanding defines PR as an emergent construct which is malleable, enduring, and can be developed and sustained by a dynamic interplay of biological, psychological, spiritual, and social factors. Correlates in terms of physical and mental well-being in the context of aging are identified.

The Application of the Concept of Resilience in Aging Research and Older Adult Care: A Focus Group Study

Introduction: Research incorporating resilience, a concept featuring a positive outcome despite some type of stressor, has the potential to identify possibilities for promotion of the well-being of older people. This study aims to gain insight into the value and potential applications of resilience in both research and care practice from the perspective of researchers and care professionals. Specifically, the value of two scientific approaches, the a priori (i.e., based on a priori definition of a stressor and outcome) and dynamical systems approaches (i.e., based on mathematically modeled patterns in the real-time response to perturbations), was explored. Methods: Focus groups were performed to explore the thoughts of academic researchers from different disciplines in the fields of aging and care and care professionals on the application of the concept of resilience, including the a priori and dynamical systems approaches. Analysis of these focus groups was based on the framework method. Results: Five focus groups were held with a total of nine researchers from different disciplines (e.g., epidemiology, sociology) and 15 older adult care professionals from different professions (e.g., elderly care physician, physiotherapist). The participants described resilience as a concept with value for both aging research and care through its positive connotation and comprehensiveness. Continued research was thought to play an important role in clearing up some of the existing ambiguity surrounding resilience. The importance of resilience in the context of both high- and low-intensity stressors was underscored. The a priori and dynamical systems approaches were considered to have their specific advantages and disadvantages on both conceptual and feasibility levels. Therefore, the use of both approaches, side by side and in combination, was suggested. Conclusion: This qualitative exploration among researchers and care professionals confirms that the concept of resilience, including the a priori and dynamical systems approaches, is valuable. However, more work is necessary before can be delivered on the potential of resilience in aging research and older adult care practice. Greater conceptual and operational clarity can be achieved through more qualitative studies on the concept that take the perspective of older people into account and through empirical studies that work with both approaches simultaneously and/or in combination.

Estimation of homeostatic dysregulation and frailty using biomarker variability: a principal component analysis of hemodialysis patients

Increased intraindividual variability in several biological parameters is associated with aspects of frailty and may reflect impaired physiological regulation. As frailty involves a cumulative decline in multiple physiological systems, we aimed to estimate the overall regulatory capacity by applying a principal component analysis to such variability. The variability of 20 blood-based parameters was evaluated as the log-transformed coefficient of variation (LCV) for one year’s worth of data from 580 hemodialysis patients. All the LCVs were positively correlated with each other and shared common characteristics. In a principal component analysis of 19 LCVs, the first principal component (PC1) explained 27.7% of the total variance, and the PC1 score exhibited consistent correlations with diverse negative health indicators, including diabetes, hypoalbuminemia, hyponatremia, and relative hypocreatininemia. The relationship between the PC1 score and frailty was subsequently examined in a subset of the subjects. The PC1 score was associated with the prevalence of frailty and was an independent predictor for frailty (odds ratio per SD: 2.31, P = 0.01) using a multivariate logistic regression model, which showed good discrimination (c-statistic: 0.85). Therefore, the PC1 score represents principal information shared by biomarker variabilities and is a reasonable measure of homeostatic dysregulation and frailty.

Quantifying Individual Response to PRRSV Using Dynamic Indicators of Resilience Based on Activity

Pigs are faced with various perturbations throughout their lives, some of which are induced by management practices, others by natural causes. Resilience is described as the ability to recover from or cope with a perturbation. Using these data, activity patterns of an individual, as well as deviations from these patterns, can potentially be used to quantify resilience. Dynamic indicators of resilience (DIORs) may measure resilience on a different dimension by calculating variation, autocorrelation and skewness of activity from the absolute activity data. The aim of this study was to investigate the potential of using DIORs of activity, such as average, root mean square error (RMSE), autocorrelation or skewness as indicators of resilience to infection with the Porcine Reproductive and Respiratory Syndrome Virus (PRRSV). For this study, individual activity was obtained from 232 pigs equipped with ear tag accelerometers and inoculated with PRRSV between seven and 9 weeks of age. Clinical scores were assigned to each individual at 13 days post-challenge and used to distinguish between a resilient and non-resilient group. Mortality post-challenge was also recorded. Average, RMSE, autocorrelation and skewness of activity were calculated for the pre- and post-challenge phases, as well as the change in activity level pre- vs. post-challenge (i.e., delta). DIORs pre-challenge were expected to predict resilience to PRRSV in the absence of PRRSV infection, whereas DIORs post-challenge and delta were expected to reflect the effect of the PRRSV challenge. None of the pre-challenge DIORs predicted morbidity or mortality post-challenge. However, a higher RMSE in the 3 days post-challenge and larger change in level and RMSE of activity from pre- to post-challenge tended to increase the probability of clinical signs at day 13 post-infection (poor resilience). A higher skewness post-challenge (tendency) and a larger change in skewness from pre- to post-challenge increased the probability of mortality. A decrease in skewness post-challenge lowered the risk of mortality. The post-challenge DIOR autocorrelation was neither linked to morbidity nor to mortality. In conclusion, results from this study showed that post-challenge DIORs of activity can be used to quantify resilience to PRRSV challenge.

Measuring resilience prospectively as the speed of affect recovery in daily life: a complex systems perspective on mental health

INTRODUCTION

There is growing evidence that mental disorders behave like complex dynamic systems. Complex dynamic systems theory states that a slower recovery from small perturbations indicates a loss of resilience of a system. This study is the first to test whether the speed of recovery of affect states from small daily life perturbations predicts changes in psychopathological symptoms over 1 year in a group of adolescents at increased risk for mental disorders.

METHODS

We used data from 157 adolescents from the TWINSSCAN study. Course of psychopathology was operationalized as the 1-year change in the Symptom Checklist-90 sum score. Two groups were defined: one with stable and one with increasing symptom levels. Time-series data on momentary daily affect and daily unpleasant events were collected 10 times a day for 6 days at baseline. We modeled the time-lagged effect of daily unpleasant events on negative and positive affect after each unpleasant event experienced, to examine at which time point the impact of the events is no longer detectable.

RESULTS

There was a significant difference between groups in the effect of unpleasant events on negative affect 90 min after the events were reported. Stratified by group, in the Increase group, the effect of unpleasant events on both negative (B = 0.05, p < 0.01) and positive affect (B = - 0. 08, p < 0.01) was still detectable 90 min after the events, whereas in the Stable group this was not the case.

CONCLUSION

Findings cautiously suggest that adolescents who develop more symptoms in the following year may display a slower affect recovery from daily perturbations at baseline. This supports the notion that mental health may behave according to the laws of a complex dynamic system. Future research needs to examine whether these dynamic indicators of system resilience may prove valuable for personalized risk assessment in this field.

Measurement of Dynamical Resilience Indicators Improves the Prediction of Recovery Following Hospitalization in Older Adults

OBJECTIVES

Acute illnesses and subsequent hospital admissions present large health stressors to older adults, after which their recovery is variable. The concept of physical resilience offers opportunities to develop dynamical tools to predict an individual's recovery potential. This study aimed to investigate if dynamical resilience indicators based on repeated physical and mental measurements in acutely hospitalized geriatric patients have added value over single baseline measurements in predicting favorable recovery.

DESIGN

Intensive longitudinal study.

SETTING AND PARTICIPANTS

121 patients (aged 84.3 ± 6.2 years, 60% female) admitted to the geriatric ward for acute illness.

MEASUREMENTS

In addition to preadmission characteristics (frailty, multimorbidity), in-hospital heart rate and physical activity were continuously monitored with a wearable sensor. Momentary well-being (life satisfaction, anxiety, discomfort) was measured by experience sampling 4 times per day. The added value of dynamical indicators of resilience was investigated for predicting recovery at hospital discharge and 3 months later.

RESULTS

31% of participants satisfied the criteria of good recovery at hospital discharge and 50% after 3 months. A combination of a frailty index, multimorbidity, Clinical Frailty Scale, and or gait speed predicted good recovery reasonably well on the short term [area under the receiver operating characteristic curve (AUC) = 0.79], but only moderately after 3 months (AUC = 0.70). On addition of dynamical resilience indicators, the AUC for predicting good 3-month recovery increased to 0.79 (P = .03). Variability in life satisfaction and anxiety during the hospital stay were independent predictors of good 3-month recovery [odds ratio (OR) = 0.24, P = .01, and OR = 0.54, P = .04, respectively].

CONCLUSIONS AND IMPLICATIONS

These results highlight that measurements capturing the dynamic functioning of multiple physiological systems have added value in assessing physical resilience in clinical practice, especially those monitoring mental responses. Improved monitoring and prediction of physical resilience could help target intensive treatment options and subsequent geriatric rehabilitation to patients who will most likely benefit from them.

Resilience in Clinical Care: Getting a Grip on the Recovery Potential of Older Adults

Background

Geriatricians are often confronted with unexpected health outcomes in older adults with complex multimorbidity. Aging researchers have recently called for a focus on physical resilience as a new approach to explaining such outcomes. Physical resilience, defined as the ability to resist functional decline or recover health following a stressor, is an emerging construct.

Methods

Based on an outline of the state‐of‐the‐art in research on the measurement of physical resilience, this article describes what tests to predict resilience can already be used in clinical practice and which innovations are to be expected soon.

Results

An older adult's recovery potential is currently predicted by static tests of physiological reserves. Although geriatric medicine typically adopts a multidisciplinary view of the patient and implicitly performs resilience management to a certain extent, clinical management of older adults can benefit from explicitly applying the dynamical concept of resilience. Two crucial leads for advancing our capacity to measure and manage the resilience of individual patients are advocated: first, performing multiple repeated measurements around a stressor can provide insight about the patient's dynamic responses to stressors; and, second, linking psychological and physiological subsystems, as proposed by network studies on resilience, can provide insight into dynamic interactions involved in a resilient response.

Conclusion

A big challenge still lies ahead in translating the dynamical concept of resilience into clinical tools and guidelines. As a first step in bridging this gap, this article outlines what opportunities clinicians and researchers can already exploit to improve prediction, understanding, and management of resilience of older adults. J Am Geriatr Soc 67:2650–2657, 2019

Critical Transitions in Intensive Care Units: A Sepsis Case Study

The progression of complex human diseases is associated with critical transitions across dynamical regimes. These transitions often spawn early-warning signals and provide insights into the underlying disease-driving mechanisms. In this paper, we propose a computational method based on surprise loss (SL) to discover data-driven indicators of such transitions in a multivariate time series dataset of septic shock and non-sepsis patient cohorts (MIMIC-III database). The core idea of SL is to train a mathematical model on time series in an unsupervised fashion and to quantify the deterioration of the model’s forecast (out-of-sample) performance relative to its past (in-sample) performance. Considering the highest value of the moving average of SL as a critical transition, our retrospective analysis revealed that critical transitions occurred at a median of over 35 hours before the onset of septic shock, which suggests the applicability of our method as an early-warning indicator. Furthermore, we show that clinical variables at critical-transition regions are significantly different between septic shock and non-sepsis cohorts. Therefore, our paper contributes a critical-transition-based data-sampling strategy that can be utilized for further analysis, such as patient classification. Moreover, our method outperformed other indicators of critical transition in complex systems, such as temporal autocorrelation and variance.

Recurrent Measurement of Frailty Is Important for Mortality Prediction: Findings from the North West Adelaide Health Study

OBJECTIVES

Frailty places individuals at greater risk of adverse health outcomes. However, it is a dynamic condition and may not always lead to decline. Our objective was to determine the relationship between frailty status (at baseline and follow-up) and mortality using both the frailty phenotype (FP) and frailty index (FI).

DESIGN

Population-based cohort.

SETTING

Community-dwelling older adults.

PARTICIPANTS

A total of 909 individuals aged 65 years or older (55% female), mean age 74.4 (SD 6.2) years, had frailty measurement at baseline. Overall, 549 participants had frailty measurement at two time points.

MEASUREMENTS

Frailty was measured using the FP and FI, with a mean 4.5 years between baseline and follow-up. Mortality was matched to official death records with a minimum of 10 years of follow-up.

RESULTS

For both measures, baseline frailty was a significant predictor of mortality up to 10 years, with initially good predictive ability (area under the curve [AUC] = .8-.9) decreasing over time. Repeated measurement at follow-up resulted in good prediction compared with lower (AUC = .6-.7) discrimination of equivalent baseline frailty status. In a multivariable model, frailty measurement at follow-up was a stronger predictor of mortality compared with baseline. Frailty change for the Continuous FI was a significant predictor of decreased or increased mortality risk based on corresponding improvement or worsening of score (hazard ratio = 1.04; 95% confidence interval = 1.02-1.07; P = .001).

CONCLUSIONS

Frailty measurement is a good predictor of mortality up to 10 years; however, recency of frailty measurement is important for improved prediction. A regular review of frailty status is required in older adults. J Am Geriatr Soc 67:2311-2317, 2019.

Rerouting Geriatric Medicine by Complementing Static Frailty Measures With Dynamic Resilience Indicators of Recovery Potential

Medicine is still very inadequate in forecasting recovery of tipping points in health and disease, especially in older adults. However, increasingly, diseases and invasive treatments unexpectedly push older patients with low resilience over their tipping points (TPs). These TPs are the points in human physiology that separate more healthy conditions from disease conditions or malfunctioning of the older human’s subsystems or organs, such as delirium, syncope and falls in old age, which threaten the functioning of the older person as a whole. Either the person may recover from the perturbation induced by such a subsystem TP and the balance of the whole system is restored, or the TP may set in motion a cascade of events driving the system down to a state of more decline, ultimately leading to death. A main unanswered question here is how to predict whether these older persons will recover or not. To improve this TP-recovery-forecasting, intriguing findings on measures of resilience found in other complex biological systems may be translated to humans. New dynamic resilience biomarkers for resilience can enrich clinical prediction for pathophysiological recovery and could test interventions for their effectiveness in improving resilience. Therefore, we hypothesize that dynamic, stimulus-response measures of recovery rate over time, observed after having received a minor stressor in a healthy condition, can be used to quantify recovery potential following subsystem TPs in disease and following invasive treatments in humans and thus the person’s resilience. Current static frailty prognostics can predict risks for death, institutionalization, delirium, falls, and other TP transitions, but it has not been proven that they can predict recovery. Our hypothesis on dynamic indicators of recovery is logical and timely, as it can now be studied with sensor technology to create a fundamentally different approach of variables that may be validated to forecast recovery potential. By generating dynamic measures of systemic resilience over various organ systems, we may subsequently model resilience generically across many chronic diseases, affecting different organ systems. Next, quantifying systemic resilience may reroute scientific and clinical pathways by predicting and preventing irreversible tipping points and by improving recovery by older adults.

Health and Disease-Emergent States Resulting From Adaptive Social and Biological Network Interactions

Health is an adaptive state unique to each person. This subjective state must be distinguished from the objective state of disease. The experience of health and illness (or poor health) can occur both in the absence and presence of objective disease. Given that the subjective experience of health, as well as the finding of objective disease in the community, follow a Pareto distribution, the following questions arise: What are the processes that allow the emergence of four observable states-(1) subjective health in the absence of objective disease, (2) subjective health in the presence of objective disease, (3) illness in the absence of objective disease, and (4) illness in the presence of objective disease? If we consider each individual as a unique biological system, these four health states must emerge from physiological network structures and personal behaviors. The underlying physiological mechanisms primarily arise from the dynamics of external environmental and internal patho/physiological stimuli, which activate regulatory systems including the hypothalamic-pituitary-adrenal axis and autonomic nervous system. Together with other systems, they enable feedback interactions between all of the person's system domains and impact on his system's entropy. These interactions affect individual behaviors, emotional, and cognitive responses, as well as molecular, cellular, and organ system level functions. This paper explores the hypothesis that health is an emergent state that arises from hierarchical network interactions between a person's external environment and internal physiology. As a result, the concept of health synthesizes available qualitative and quantitative evidence of interdependencies and constraints that indicate its top-down and bottom-up causative mechanisms. Thus, to provide effective care, we must use strategies that combine person-centeredness with the scientific approaches that address the molecular network physiology, which together underpin health and disease. Moreover, we propose that good health can also be promoted by strengthening resilience and self-efficacy at the personal and social level, and via cohesion at the population level. Understanding health as a state that is both individualized and that emerges from multi-scale interdependencies between microlevel physiological mechanisms of health and disease and macrolevel societal domains may provide the basis for a new public discourse for health service and health system redesign.

Opportunities to Improve Resilience in Animal Breeding Programs

Resilience is the capacity of an animal to be minimally affected by disturbances or to rapidly return to the state pertained before exposure to a disturbance. However, indicators for general resilience to environmental disturbances have not yet been defined, and perhaps therefore resilience is not yet included in breeding goals. The current developments on big data collection give opportunities to determine new resilience indicators based on longitudinal data, which can aid to incorporate resilience in animal breeding goals. The objectives of this paper were: (1) to define resilience indicator traits based on big data, (2) to define economic values for resilience, and (3) to show the potential to improve resilience of livestock through inclusion of resilience in breeding goals. Resilience might be measured based on deviations from expected production levels over a period of time. Suitable resilience indicators could be the variance of deviations, the autocorrelation of deviations, the skewness of deviations, and the slope of a reaction norm. These (new) resilience indicators provide opportunity to include resilience in breeding programs. Economic values of resilience indicators in the selection index can be calculated based on reduced costs due to labor and treatments. For example, when labor time is restricted, the economic value of resilience increases with an increasing number of animals per farm, and can become as large as the economic value of production. This shows the importance of including resilience in breeding goals. Two scenarios were described to show the additional benefit of including resilience in breeding programs. These examples showed that it is hard to improve resilience with only production traits in the selection index, but that it is possible to greatly improve resilience by including resilience indicators in the selection index. However, when health-related traits are already present in the selection index, the effect is smaller. Nevertheless, inclusion of resilience indicators in the selection index increases the response in the breeding goal and resilience, which results in less labor-demanding, and thus easier-to-manage livestock. Current developments on massive collection of data, and new phenotypes based on these data, offer exciting opportunities to breed for improved resilience of livestock.

Resilience and health (care): A dynamic adaptive perspective

This special forum on resilience explores particular worldviews of resilience-clinical, psychosocial, sociological, complexity science, organizational, and political economy through eight papers. This forum aims to open up the wealth of understandings and implications in health care by taking a transdisciplinary overview.

Resilience, health perceptions, (QOL), stressors, and hospital admissions-Observations from the real world of clinical care of unstable health journeys in Monash Watch (MW), Victoria, Australia

RATIONALE, AIMS, AND OBJECTIVES

Monash Watch (MW) aims to reduce potentially preventable hospitalisations in a cohort above a risk "threshold" identified by Health Links Chronic Care (HLCC) algorithms using personal, diagnostic, and service data. MW conducted regular patient monitoring through outbound phone calls using the Patient Journey Record System (PaJR). PaJR alerts are intended to act as a self-reported barometer of stressors, resilience, and health perceptions with more alerts per call indicating greater risk.

AIMS

To describe predictors of PaJR alerts (self-reported from outbound phone calls) and predictors of acute admissions based upon a Theoretical Model for Static and Dynamic Indicators of Acute Admissions.

METHODS

Participants: HLCC cohort with predicted 3+ admissions/year in MW service arm for >40 days; n = 244. Baseline measures-Clinical Frailty Index (CFI); Connor Davis Resilience (CD-RISC): SF-12v2 Health Survey scores Mental (MSC) and Physical (PSC) and ICECAP-O. Dynamic measures: PaJR alerts/call in 10 869 MW records. Acute (non-surgical) admissions from Victorian Admitted Episode database.

ANALYSIS

Logistic regression, correlations, and timeseries homogeneity metrics using XLSTAT.

FINDINGS

Baseline indicators were significantly correlated except SF-12_MCS. SF12-MSC, SF12-PSC and ICECAP-O best predicted PaJR alerts/call (ROC: 0.84). CFI best predicted acute admissions (ROC: 0.66), adding CD-RISC, SF-12_MCS, SF-12_PCS and ICECAP-O with two-way interactions improved model (ROC: 0.70). PaJR alerts were higher ≤10 days preceding acute admissions and significantly correlated with admissions. Patterns in PaJR alerts in four case studies demonstrated dynamic variations signifying risk. Overall, all baseline indicators were explanatory supporting the theoretical model. Timing of PaJR alerts and acute admissions reflecting changing stressors, resilience, and health perceptions were not predicted from baseline indicators but provided a trigger for service interventions.

CONCLUSION

Both static and dynamic indicators representing stressors, resilience, and health perceptions have the potential to inform threshold models of admission risk in ways that could be clinically useful.

Cycles, Arrows and Turbulence: Time Patterns in Renal Disease, a Path from Epidemiology to Personalized Medicine?

Patients with end-stage renal disease (ESRD) experience unique patterns in their lifetime, such as the start of dialysis and renal transplantation. In addition, there is also an intricate link between ESRD and biological time patterns. In terms of cyclic patterns, the circadian blood pressure (BP) rhythm can be flattened, contributing to allostatic load, whereas the circadian temperature rhythm is related to the decline in BP during hemodialysis (HD). Seasonal variations in BP and interdialytic-weight gain have been observed in ESRD patients in addition to a profound relative increase in mortality during the winter period. Moreover, nonphysiological treatment patters are imposed in HD patients, leading to an excess mortality at the end of the long interdialytic interval. Recently, new evidence has emerged on the prognostic impact of trajectories of common clinical and laboratory parameters such as BP, body temperature, and serum albumin, in addition to single point in time measurements. Backward analysis of changes in cardiovascular, nutritional, and inflammatory parameters before the occurrence as hospitalization or death has shown that changes may already occur within months to even 1-2 years before the event, possibly providing a window of opportunity for earlier interventions. Disturbances in physiological variability, such as in heart rate, characterized by a loss of fractal patterns, are associated with increased mortality. In addition, an increase in random variability in different parameters such as BP and sodium is also associated with adverse outcomes. Novel techniques, based on time-dependent analysis of variability and trends and interactions of multiple physiological and laboratory parameters, for which machine-learning -approaches may be necessary, are likely of help to the clinician in the future. However, upcoming research should also evaluate whether dynamic patterns observed in large epidemiological studies have relevance for the individual risk profile of the patient.

Quantifying resilience of humans and other animals

All life requires the capacity to recover from challenges that are as inevitable as they are unpredictable. Understanding this resilience is essential for managing the health of humans and their livestock. It has long been difficult to quantify resilience directly, forcing practitioners to rely on indirect static indicators of health. However, measurements from wearable electronics and other sources now allow us to analyze the dynamics of physiology and behavior with unsurpassed resolution. The resulting flood of data coincides with the emergence of novel analytical tools for estimating resilience from the pattern of microrecoveries observed in natural time series. Such dynamic indicators of resilience may be used to monitor the risk of systemic failure across systems ranging from organs to entire organisms. These tools invite a fundamental rethinking of our approach to the adaptive management of health and resilience.

The fabric of resilience among the elderly and the reinvention of the self despite the difficulties faced

Abstract Objective :To seek an understanding of how frail elderly persons construct resilience. Method: The “signs, meanings and actions” model was used. The population was randomly selected among elderly persons classified as robust or pre-frail in the FIBRA-study, Belo Horizonte, Minas Gerais, Brazil. Thirteen elderly persons (aged 69 to 86) were interviewed. Results: a) the construction of bonds - a healthy relationship with spouses, sons, daughters, grandchildren and great-grandchildren brings meaning to and sustains life and contributes to its organization; b) the reinvention of oneself - when suffering trauma, elderly people seek paths that can give sense to life, even if difficult memories persist; c) religiosity: catholic, evangelical or spiritualist experiences strengthen; cures, protections and so-called miracles are valued, and the religious community represents a space for belonging. Conclusion: Resilience is constructed through the bonds between the elderly person and those close to them, and in the search for solutions, including through the religious experience.

Using Patient Reported Outcomes Measures to Promote Integrated Care

INTRODUCTION

Patient reported outcome measures (PROMs) have been introduced as standardised outcomes, but have not been implemented widely for disease targeted pathways of care, nor for geriatric patients who prefer functional performance and quality of life.

DISCUSSION

We describe innovative multipurpose implementation of PROMs as evidenced by two best practices of PROMs application in geriatric and physiotherapy practice. We show that PROMs can show meaningful outcomes in older subjects' patient journeys, which can at the same time serve individuals and groups of both patients and professionals.

KEY LESSON

PROMs can deliver generic outcomes relevant for older patients, may improve patient-physician relationship, quality of care and prediction of future outcomes in geriatric care, if they are valid, reliable and responsive, but still short and simple. A precondition to make the hard tip from research to practice is that PROMs are carefully positioned in the clinical encounters and in electronic health records.