Could self-reported physical performance help predict individuals at the highest risk of mortality and hospital admission events in clinical practice? Findings from the Hertfordshire Cohort Study.

AIM: To consider how self-reported physical function measures relate to adverse clinical outcomes measured over 20 years of follow-up in a community-dwelling cohort (aged 59-73 at baseline) as compared with hand grip strength, a well-validated predictor of adverse events. BACKGROUND: Recent evidence has emphasized the significant association of physical activity, physical performance, and muscle strength with hospital admissions in older people. However, physical performance tests require staff availability, training, specialized equipment, and space to perform them, often not feasible or realistic in the context of a busy clinical setting. METHODS: In total, 2997 men and women were analyzed. Baseline predictors were measured grip strength (Jamar dynamometer) and the following self-reported measures: physical activity (Dallosso questionnaire); physical function score (SF-36 Health Survey); and walking speed. Participants were followed up from baseline (1998-2004) until December 2018 using UK Hospital Episode Statistics and mortality data, which report clinical outcomes using ICD-10 coding. Predictors in relation to the risk of mortality and hospital admission events were examined using Cox regression with and without adjustment for sociodemographic and lifestyle characteristics. FINDINGS: The mean age at baseline was 65.7 and 66.6 years among men and women, respectively. Over follow-up, 36% of men and 26% of women died, while 93% of men and 92% of women were admitted to hospital at least once. Physical activity, grip strength, SF-36 physical function, and walking speed were all strongly associated with adverse health outcomes in both sex- and fully adjusted analyses; poorer values for each of the predictors were related to greater risk of mortality (all-cause, cardiovascular-related) and any, neurological, cardiovascular, respiratory, any fracture, and falls admissions. SF-36 physical function and grip strength were similarly associated with the adverse health outcomes considered.

Lifecourse correlates of self-rated health and associations with subsequent mortality: findings from the Hertfordshire Cohort Study.

Background: Poor self-rated health (SRH) has been shown to predict adverse health outcomes among older people, however these associations have traditionally only been considered at one point in the lifecourse, usually midlife or later. Here we examined lifecourse correlates of SRH in early, mid and later life, relating these to subsequent risk of mortality in a community-dwelling cohort. Methods: 2989 men and women from the Hertfordshire Cohort Study (HCS) were included in this study. The HCS was initially retrospective and linked contemporary health outcome data to early life data available from health ledgers but investigations from baseline (1998-2004, aged 59-73) onwards have been prospective. At baseline, participants completed an initial clinic visit, which included questionnaire assessment of SRH, reported as 'excellent', 'very good', 'good', 'fair', or 'poor'. Socioeconomic, lifestyle, mental health and demographic information was also collected. Deaths were recorded from baseline to 31/12/2018. Baseline characteristics in relation to SRH were examined using sex-stratified ordinal logistic regression; these factors were examined in relation to mortality using sex-stratified Cox regression. Statistically significant exposures were then included in sex-stratified mutually-adjusted models. Results: In mutually-adjusted analysis, numerous contemporaneous correlates of poorer SRH in the seventh decade were identified and included obesity, lower physical activity, greater comorbidity and higher levels of depression among men and women. For example, odds ratios for being in a lower category of SRH were as follows: obese (BMI≥30) vs underweight/healthy (BMI<25) (men 1.60 (1.21, 2.11), women 1.65 (1.25, 2.17)) and per additional system medicated (men 1.62 (1.47, 1.77), women 1.53 (1.41, 1.66)). By contrast, factors earlier in the lifecourse (early growth, age left full-time education) were not associated with SRH in late adulthood. 36% of men and 26% of women died during follow-up. Hazard ratios (95% CI) for mortality per lower category of SRH were 1.22 (1.10,1.36) among men and 1.17 (1.01,1.35) among women after adjustment for age, BMI, smoking, physical activity, diet quality, education, home ownership status, comorbidity level and depression levels, suggesting residual confounding by other unrecorded factors that are related to SRH. Conclusions: Poorer SRH in the seventh decade was a risk factor for mortality. Importantly modifiable adverse health behaviours in the seventh decade, such as low physical activity, were associated with poorer SRH and later mortality after adjustment for socioeconomic factors and comorbidity level. By contrast early growth and education were not related to later SRH. These data suggest that attention to lifestyle in late midlife may be associated with better SRH and subsequent health outcomes, highlighting the value of intervention at this stage of the lifecourse.

Hospital admissions and mortality over 20 years in community-dwelling older people: findings from the Hertfordshire Cohort Study.

BACKGROUND: Demographic changes worldwide are leading to pressures on health services, with hospital admissions representing an important contributor. Here, we report admission types experienced by older people and examine baseline risk factors for subsequent admission/death, from the community-based Hertfordshire Cohort Study. METHODS: 2997 participants (1418 women) completed a baseline questionnaire and clinic visit to characterize their health. Participants were followed up from baseline (1998-2004, aged 59-73 years) until December 2018 using UK Hospital Episode Statistics and mortality data, which report clinical outcomes using ICD-10 coding. Baseline characteristics in relation to the risk of admission/death during follow-up were examined using sex-stratified univariate logistic regression. RESULTS: During follow-up, 36% of men and 26% of women died and 93% of men and 92% of women had at least one hospital admission; 6% of men and 7% of women had no admissions and were alive at end of follow-up. The most common types of admission during follow-up were cardiovascular (ever experienced: men 71%, women 68%) and respiratory (men 40%, women 34%). In both sexes, baseline risk factors that were associated (p < 0.05) with admission/death during follow-up were older age, poorer SF-36 physical function, and poorer self-rated health. In men, manual social class and a history of smoking, and in women, higher BMI, not owning one's home, and a minor trauma fracture since age 45, were also risk factors for admission/death. CONCLUSIONS: Sociodemographic factors were related to increased risk of admission/death but a small proportion experienced no admissions during this period, suggesting that healthy ageing is achievable.

Success and challenges of health systems resilience-enhancing strategies for managing Public Health Emergencies of International Concerns (PHEIC): A systematic review protocol.

INTRODUCTION: Health systems resilience is the ability to prepare, manage and learn from a sudden and unpredictable extreme change that impacts health systems. Health systems globally have recently been affected by a number of catastrophic events, including natural disasters and infectious disease epidemics. Understanding health systems resilience has never been more essential until emerging global pandemics. Therefore, the application of resilience-enhancing strategies needs to be assessed to identify the management gaps and give valuable recommendations from the lessons learnt from the global pandemic. METHODS: The systematic review will be reported using the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA-P) protocols guideline. Reporting data on World Health Organization (WHO) health system building blocks and systematic searches on resilience enhancing strategies for the management of Public Health Emergencies of International Concerns (PHEIC) after the establishment of International Health Regulations (IHR) in 2007 will be included. The search will be conducted in PubMed, Scopus, Web of Science and Google Scholar ETHICS AND DISSEMINATION: Ethics approval and safety considerations are not applicable. Pre-print of the protocol is available online, and the screening of the articles will be done using Rayyan software in a transparent manner. The findings will be presented at conferences and the final review's findings will be published in a peer-reviewed international journal and will be disseminated to global communities for the application of successful management strategies for the management of future pandemics. PROSPERO REGISTRATION NUMBER: CRD42022352612; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022352612.

Neutrophil Lymphocyte Ratio as a Marker of In-Hospital Deterioration in COVID-19: Observations From a Resource Constraint Setting.

Introduction and Objectives: The study was conducted to assess the association of neutrophil lymphocyte ratio (NLR) in COVID-19 and to identify the cut-off value that predicts mortality, need of respiratory support and admission to high-dependency or intensive care. Methods: A retrospective observational study was conducted to collect demographic data, clinical variables, the neutrophil-lymphocyte ratio on-admission and the outcome of confirmed COVID-19 patients admitted to a tertiary care center in Sri Lanka. Results: There were 208 patients with a median age of 56 years (IQR 43-67) and 98 (47.1%) males. The median neutrophil count was 4.07 × 103/µL (IQR 2.97-6.79) and the median lymphocyte count was 1.74 × 103/µL (IQR 1.36-4.75). The calculated NLR ranged from 0.12 to 48.28 with a median value of 2.32 (IQR 1.37-4.76). A NLR value >3.6 predicted development of severe disease requiring respiratory support, transfer to a high-dependency or an intensive care unit and/or succumbing to the illness with a sensitivity 80% and specificity 80% (area under the curve 0.8, 95% CI 0.72-0.88, P < .0001). The adjusted odds ratio of NLR > 3.6 on predicting severe disease was 11.1, 95% CI 4.5- 27.0, P < .0001. Conclusions: A NLR > 3.6 is a useful variable to be included in risk prediction scores in Sri Lanka.