Perceived Age as a Mortality and Comorbidity Predictor: A Systematic Review

Vascular ageing in relation to chronological and self-perceived age in the general Swedish population

Background. Aortic stiffness is a marker of vascular ageing. Non-conventional risk markers reflecting vascular ageing are largely unexplored. We aimed to investigate the relationship between self-perceived age (SPA) and self-rated health (SRH) with aortic stiffness in the general population. Methods. Cross-sectional assessment of 3760 participants from two Swedish population-based cohorts (mean age 43.5 ± 14.5 years, 53.4% women). Participants completed two self-administered questions about SPA (SPA-self referring to SPA perceived by oneself, and SPA-others referring to SPA perceived by others) graded as: younger, no difference, or older than same-aged/sex peers. SRH was graded as poor versus good. Aortic stiffness (vascular ageing) was assessed by carotid-femoral pulse wave velocity (PWV). Linear regression was performed stratified by the median age of 45 years. Results. Chronologically younger men and women ≤45 years with older SPA-others had unexpectedly lower PWV (β - 0.39, p < .001 and β - 0.40, p < .001, respectively), independently of cardiovascular risk factors and social health determinants, compared with subjects with younger SPA-others. Lower PWV was also observed in women ≤45 years with older SPA-self (β - 0.24 m/s, p = .005) compared with younger SPA-self, but not in men. A similar pattern between SPA-self, SPA-others and PWV was found in chronologically younger subjects ≤45 years reporting good SRH. On the contrary, chronologically older subjects >45 years reporting poor SRH, with older SPA-others had increased vascular ageing (PWV β 2.57, p = .03). Conclusions. Self-perceived age is a subjective cognitive variable inversely associated with vascular ageing particularly among chronologically younger adults ≤45 years.

Facial aging, cognitive impairment, and dementia risk

BACKGROUND

Facial aging, cognitive impairment, and dementia are all age-related conditions. However, the temporal relation between facial age and future risk of dementia was not systematically examined.

OBJECTIVES

To investigate the relationship between facial age (both subjective/perceived and objective) and cognitive impairment and/or dementia risk.

METHODS

The study included 195,329 participants (age ≥ 60 y) from the UK Biobank (UKB) with self-perceived facial age and 612 participants from the Nutrition and Health of Aging Population in China Project (NHAPC) study (age ≥ 56 y) with objective assessment of facial age. Cox proportional hazards model was used to prospectively examine the hazard ratios (HRs) and their 95% confidence intervals (CIs) of self-perceived facial age and dementia risk in the UKB, adjusting for age, sex, education, APOE ε4 allele, and other potential confounders. Linear and logistic regressions were performed to examine the cross-sectional association between facial age (perceived and objective) and cognitive impairment in the UKB and NHAPC, with potential confounders adjusted.

RESULTS

During a median follow-up of 12.3 years, 5659 dementia cases were identified in the UKB. The fully-adjusted HRs comparing high vs. low perceived facial age were 1.61 (95% CI, 1.33 ~ 1.96) for dementia (P-trend ≤ 0.001). Subjective facial age and cognitive impairment was also observed in the UKB. In the NHAPC, facial age, as assessed by three objective wrinkle parameters, was associated with higher odds of cognitive impairment (P-trend < 0.05). Specifically, the fully-adjusted OR for cognitive impairment comparing the highest versus the lowest quartiles of crow's feet wrinkles number was 2.48 (95% CI, 1.06 ~ 5.78).

CONCLUSIONS

High facial age was associated with cognitive impairment, dementia and its subtypes after adjusting for conventional risk factors for dementia. Facial aging may be an indicator of cognitive decline and dementia risk in older adults, which can aid in the early diagnosis and management of age-related conditions.

Association Between Social Isolation With Age-Gap Determined by Artificial Intelligence-Enabled Electrocardiography

Background

Loneliness and social isolation are associated with poor health outcomes such as an increased risk of cardiovascular diseases.

Objectives

The authors aimed to explore the association between social isolation with biological aging which was determined by artificial intelligence-enabled electrocardiography (AI-ECG) as well as the risk of all-cause mortality.

Methods

The study included adults aged ≥18 years seen at Mayo Clinic from 2019 to 2022 who respond to a survey for social isolation assessment and had a 12-lead ECG within 1 year of completing the questionnaire. Biological age was determined from ECGs using a previously developed and validated convolutional neural network (AI-ECG age). Age-Gap was defined as AI-ECG age minus chronological age, where positive values reflect an older-than-expected age. The status of social isolation was measured by the previously validated multiple-choice questions based on Social Network Index (SNI) with score ranges between 0 (most isolated) and 4 (least isolated).

Results

A total of 280,324 subjects were included (chronological age 59.8 ± 16.4 years, 50.9% female). The mean Age-Gap was -0.2 ± 9.16 years. A higher SNI was associated with a lower Age-Gap (β of SNI = 4 was -0.11; 95% CI: -0.22 to -0.01; P < 0.001, adjusted to covariates). Cox proportional hazard analysis revealed the association between social connection and all-cause mortality (HR for SNI = 4, 0.47; 95% CI: 0.43-0.5; P < 0.001).

Conclusions

Social isolation is associated with accelerating biological aging and all-cause mortality independent of conventional cardiovascular risk factors. This observation underscores the need to address social connection as a health care determinant.

Risk factors for 30-day readmission following shoulder arthroscopy: a systematic review

BACKGROUND

Recently, there has been a rapid shift from open shoulder surgery to arthroscopic shoulder procedures for treating several shoulder pathologies. This shift is mainly due to reduced postoperative complications and 30-day readmission. Although the 30-day readmission rate is low, the risk still exists. One way to minimize the risk factors is to analyze all the risk factors contributing to the 30-day readmission following shoulder arthroscopy.

METHODS

Electronic databases such as PubMed, Google Scholar, and Cochrane library were searched. Studies were selected based on predefined inclusion and exclusion criteria. Newcastle-Ottawa score was used for the quality assessment of individual studies. Two reviewers extracted data from the selected studies. Results were evaluated through narrative analysis and presented as an odds ratio with 95% confidence interval. A meta-analysis was not possible due to the heterogeneity in the available data.

RESULTS

A total of 12 studies evaluating 494,038 patients were selected in our review. All the studies have a low risk of bias (median = 8). Significant factors predicting readmission included age, gender, COPD (chronic obstructive pulmonary disorder), steroid use, smoking, preoperative opioid use, higher American Society of Anesthesiologists (ASA) score (3 or higher), and general and regional anesthesia vs. regional anesthesia alone.

CONCLUSION

Through our systematic review, we tried to identify risk factors that can predict 30-day readmission following shoulder arthroscopy. These include age > 65 years, COPD, steroid use, opioid use, and OR time > 90 mins. These high-risk patients could be triaged earlier by identifying these parameters, and effective pre and post-operative surveillance could minimize 30-day readmission risk following shoulder arthroscopy.

Early Drug Prescription Patterns as Predictors of Final Workers Compensation Claim Costs and Closure: An Updated Analysis on an Expanded Cohort

OBJECTIVE

The aim of the study is to determine the associations of workers' compensation claim costs and return to work with drugs prescribed for early symptom management.

METHODS

Claims filed from 1998 to 2007 were followed for 10 years from the injury date. Drugs analyzed included gabapentin, pregabalin, antipsychotics, antidepressants, sedatives, benzodiazepines, carisoprodol, and opioids, controlling for initial reserve, sex, age, physical therapy, attorney involvement, and surgery.

RESULTS

Gabapentin, antipsychotics, antidepressants, and sedatives used in the first 3 months after injury were significantly associated with higher claim cost (≥$100,000). All opioid morphine equivalent doses greater than or equal to 5 mg/d for the first 6 months was significantly associated with higher cost (≥$100,000) and not being released to work at end of third year after injury with dose-response relationships.

CONCLUSIONS

Prescription patterns in the first 3 months or first 6 months of workers' compensation claim development may be used as predictors of claim outcomes.