Corrigendum: Frailty index and risk of delirium in hospitalized patients: a two-sample Mendelian randomization study.

[This corrects the article DOI: 10.3389/fmed.2024.1361437.].

A Novel Scale System Based on the Frailty Index and Laboratory Indicators for the Short-Term Prognosis of Patients with Acute Myocardial Infarction: A Retrospective Cohort Study.

Objective: Current scoring systems for short-term prognosis in patients with acute myocardial infarction (AMI) lack coverage of risk factors and have limitations in risk stratification. The aim of this study was to develop a novel assessment system based on laboratory indicators and frailty quantification to better infer short-term prognosis and risk indication in patients with AMI. Methods: A total of 365 patients with MI from January 2022 to June 2023 in Northern Jiangsu Province Hospital were included. The primary endpoint was all-cause mortality and major adverse cardiac events (MACE) during follow-up. A novel scoring model ranging from 0 to 12 was constructed, and the predictive ability of this scoring system was evaluated using the area under the receiver operating characteristic curve (AUC). Results: During follow-up, 68 patients experienced MACE. Five scoring indicators were selected through multivariate logistic regression analysis, resulting in a composite score with an AUC of 0.925, demonstrating good prognostic accuracy. Conclusion: The novel prognostic assessment system, which integrates age, Stress Hyperglycemia Ratio (SHR), Neutrophil to Lymphocyte Ratio (NLR), lactate, and frailty score, exhibits good predictive value for short-term MACE in patients with acute myocardial infarction and may enable more accurate risk classification for future use in MI patient risk management.

Enhancing the convenience of frailty index assessment for elderly Chinese people with machine learning methods.

Frailty is a state that is closely associated with adverse health outcomes in the aging process. The frailty index (FI), which measures frailty in terms of cumulative deficits, has been widely used for frailty assessment in elderly people, and its advantage of self-reported information collection makes it applicable to a broader group of elderly people. Our study aims to simplify the Frailty Index Assessment Scale, while maintaining its reliability and accuracy, to easily and quickly assess frailty in elderly people. In this study, participants (age ≥ 65 years) from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which had 13,339, 372 and 1214 participants in 2008, 2011, and 2014, respectively, were used. The 2008 dataset was split into 80% for training and 20% for internal validation, and the data from 2011 to 2014 as external validation. In order to obtain effective predictors, we used Lasso regression, Boruta algorithm and random forest classifier score for feature selection. We used six models for predictive model construction and evaluated the models in the validation dataset. Model performance was measured by area under the curve (AUC), accuracy and F1 score. Logistic regression was found to be the best performing and most interpretable algorithm with AUC, accuracy and F1 of 0.974, 0.932 and 0.880 for the validation dataset, respectively. The AUCs for the external independent validation dataset were 0.963 and 0.977, respectively. Subgroup analysis showed that the model had good predictive power in both males and females. The predictive power was stronger among the elderly people over 80 years old, with AUC, accuracy and F1 of 0.973,0.914, and 0.893, respectively. The model also obtained good predictive power in the case of FI measured by different indicators. The model showed good robustness in the follow-up assessment of frailty status in elderly people, with the AUC remaining above 0.95 and accuracy above 0.9 over the long-term follow-up. Using machine learning techniques, we have successfully developed a simple frailty assessment prediction model based on 10 key features to shorten the frailty assessment scale with near full-scale accuracy. A user-friendly website was created to facilitate the application of this prediction model ( https://healthy-aging.shinyapps.io/Frailty_Assessment/ ).

Frailty; Time for Global Action : Commentary on "Frailty and its Association with Long-Term Mortality among Community-Dwelling older adults aged 75 years and Over".

This commentary examines the study "Frailty and Its Association with Long-Term Mortality Among Community-Dwelling Older Adults Aged 75 Years and Over" by Lewis et al. The retrospective cohort study utilized data from a primary healthcare provider in Israel to investigate frailty using the Frailty Index (FI) and its correlation with long-term mortality. Nearly half of the older adult cohort was identified as frail, with a strong association between higher frailty levels and increased mortality risk. The commentary emphasizes the importance of routine frailty screening in clinical practice and health policy. Integrating FI calculations into electronic health records can facilitate timely care for high-risk individuals. However, presenting frailty data must be managed carefully and in conjunction with patients' preferences to avoid stigmatizing and negatively influencing clinical decisions. While the FI is a valuable tool, it should complement, not replace, other assessments that provide a more holistic view of the patient's health. Furthermore, the commentary strongly advocates for a more comprehensive approach to patient care, emphasizing that non-geriatricians must also be proficient in recognizing and managing frailty. Effectively addressing frailty can lead to significant cost savings for healthcare systems, reduced burden on healthcare facilities, and decreased need for long-term care.

FI-lab in the emergency department and adverse outcomes among acutely hospitalized older adults.

BACKGROUND: The emergency department is treating a growing number of older patients with frailty, which has been linked to poorer outcomes. Urgency is generally emphasized in the emergency department based on indicators such as triage scores and early warning scores for decision-making. However, this approach may not be sufficient for frail older people. The Frailty Index-laboratory (FI-lab) has been used as a simple assessment tool for frailty, but it may also reflect disease severity and predict adverse outcomes in the emergency care setting. Therefore, we aimed to evaluate the association between FI-lab in the emergency room and adverse outcomes during hospitalization through comparison with assessments using triage and early warning scores. METHODS: This was a retrospective cohort study conducted in a tertiary hospital. The study included patients aged 65 years or older who were admitted to the general internal medicine ward after being initially evaluated in the emergency department. FI-lab was calculated using 24 laboratory parameters from blood tests. The National Early Warning Score (NEWS), the Japan Triage and Acuity Scale (JTAS), and the modified JTAS were also used as prognostic indicators, and their association with adverse outcomes was compared with that of FI-lab. RESULTS: In total, 872 patients (mean age, 80.9 years; male, 52.6 %) were analyzed. Patients who died during hospitalization had a higher FI-lab than those who survived. In multiple regression analysis, FI-lab, NEWS, and the modified JTAS were significantly associated with in-hospital death and prolonged length of hospital stay. In contrast, none of these indices were associated with in-hospital falls. The FI-lab was independently associated with the likelihood of discharge to home. CONCLUSIONS: FI-lab evaluated in the emergency department reflected the severity of illness in acutely hospitalized older adults, similarly to NEWS and JTAS, and was a useful indicator for predicting adverse outcomes. These results may indicate the value of FI-lab for older adults in the acute care setting.

Evaluation of Five Screening Tools in Detecting Physical Frailty in Cirrhosis and Their Prognostic Role.

Background: Physical frailty (PF) is a syndrome of decreased physical function and reserves, preventing patients from coping with stressful events. PF screening tools in patients with liver cirrhosis (LC) can help evaluate the risk of complications and death. The aim of this study was to assess the performance of five screening tools in detecting PF and their ability to predict 18-month mortality in LC. Methods: The Short Physical Performance Battery (SPPB), Fried frailty phenotype (FFP), Clinical Frailty Scale (CFS) and 6-Minute Walk Test (6MWT) were compared with the Liver Frailty Index (LFI) as the method of reference. Patients with an LFI ≥ 4.5, SPPB ≤ 8, FFP ≥ 3, CFS ≥ 6 points, and those walking <250 m, were considered frail. Results: A total of 109 consecutive patients with stable LC were included [63.3% male, median age 62 years, (IQR 52-70), MELD 9 (7-14.5), 46.8% with decompensated LC (DC)]. PF was present in 23.9%, 27.5%, 41.3%, 13.8%, and 28.4% as assessed by the LFI, SPPB, FFP, CFS, and 6MWT, respectively. Cohen's kappa measurement of agreement of four of the tools with LFI was 0.568, 0.334, 0.439, and 0.502, respectively (p < 0.001 for each). Kaplan-Meier survival curves at 18 months showed higher mortality in frail patients compared to non-frail patients by any method (log rank p < 0.05). In the multivariate models, PF defined by any method emerged as an independent prognostic factor of 18-month mortality after adjustment for age, gender, and MELD-score. Conclusions: Patients characterized as frail by five screening tools were not identical. However, PF defined by either method was proven to be an independent poor prognostic factor for long-term mortality after adjustment for covariates.

Effectiveness of the frailty index in predicting short-term and long-term mortality risk in patients with chronic heart failure.

OBJECTIVE: This study explored the effectiveness of a newly constructed frailty index (FI) for predicting short-term and long-term mortality in patients with chronic heart failure (HF). MATERIALS AND METHODS: This retrospective study included inpatients aged ≥60 years diagnosed with chronic HF at a teaching hospital in western China. General data on the patients were collected from the electronic medical record system between January 1, 2017, and July 7, 2022, and death information was obtained from follow-up calls made from July 31, 2022, to August 1, 2022. Receiver operating characteristic (ROC) curves were used to analyze the accuracy of the FI in predicting death in patients with chronic HF. Logistic regression (during hospitalization and within 30 days after discharge) and Cox regression (within 180 days after discharge and one year after discharge) analyses were used to assess associations between frailty and mortality risk in elderly patients with chronic HF. RESULTS: A total of 432 patients with chronic HF were included in the study. The non-frail group had FI values <0.3, while the FI values in the frail group were ≥0.3. Overall, 130 patients (30.09 %) were diagnosed with frailty, 66 (15.28 %) died during hospitalization or within 30 days after discharge, 55 (12.73 %) died within 180 days after discharge, and 68 (15.74 %) died within one year after discharge. The in-hospital and 30-day mortality rates, the 180-day mortality rates, and the 1-year mortality rates were higher in frail patients than in non-frail patients (in-hospital and 30-day mortality rates, 37.69 % vs. 5.63 %, P < 0.001; within 180 days, 30.61 % vs. 8.45 %, P < 0.001; within 1 year, 34.69 % vs. 11.49 %, P < 0.001). The area under the curve (AUC) values of FI for predicting in-hospital and 30-day mortality after discharge were 0.804, with values of 0.721 for 180-day mortality after discharge and 0.720 for 1-year mortality after discharge. Logistic regression analysis with adjustment for potential confounders indicated that frail HF patients had a higher risk of death during hospitalization and within 30 days than non-frail patients (odds ratio [OR] = 4.98, 95 % confidence interval [CI]: 2.46-10.09). Cox regression analysis with adjustment for potential confounders showed that frail HF patients had a higher risk of death within 180 days (hazard ratio [HR] = 2.63, 95 %CI: 1.47-4.72) and within 1 year (HR = 2.01, 95 %CI: 1.19-3.38). CONCLUSION: The results of this study showed that the new FI constructed according to the established construction rules could predict the in-hospital mortality and the risk of death within 30 days after discharge, 180 days after discharge, and 1 year after discharge in patients with chronic HF.

Association between frailty index and cognitive dysfunction in older adults: insights from the 2011-2014 NHANES data.

Background: As the population ages, the occurrence of cognitive decline and dementia is continuously increasing. Frailty is a prevalent problem among older adults. Epidemiologic studies have shown a comorbidity between frailty and cognitive impairment. However, their relationship remains unclear. The frailty index is an important indicator for measuring frailty. This study aims to investigate the relationship between frailty index and cognitive dysfunction in older adults aged 60 years and older in the United States from the 2011-2014 National Health and Nutrition Examination Survey (NHANES). Methods: Community-dwelling older adults aged 60 years or older from 2011 to 2014 were extracted from the NHANES database. The frailty index was calculated using the formula: frailty index = total number of deficits present/total number of deficits measured. The Animal Fluency (AF), the Digit Symbol Substitution Test (DSST), the Consortium to Establish a Registry for Alzheimer's disease Delayed Recall (CERAD-DR), and Word Learning (CERAD-WL) were used to evaluate cognitive dysfunction. Firstly, weighted logistic regression analysis was used to explore the relationship between frailty index and cognitive dysfunction. Secondly, the influence of covariates on the frailty index was evaluated by subgroup analysis and interaction. Finally, the non-linear relationship is discussed by using the restricted cubic spline regression model. Results: Our study included a total of 2,574 patients, weighted logistic regression analysis, after adjusting for all covariates, showed that the frailty index was associated with every test score. The interaction showed that covariates had no significant effect on this association in AF. The association between the frailty index and AF in the restricted cubic spline regression model is non-linear. As the frailty index increased, the risk of AF reduction increased, suggesting a higher risk of cognitive dysfunction. Conclusion: In general, a high frailty index appears to be associated with an increased risk of cognitive dysfunction in the elderly. Consequently, protecting against cognitive decline necessitates making geriatric frailty prevention and treatment top priorities.

The association between use of proton pump inhibitors and frailty index among middle-aged and older adults.

AIMS: This study aimed to investigate the association between use of proton pump inhibitors (PPI) and frailty index (FI), and to assess the causality relationship using Mendelian randomization (MR). METHODS: A total of 9756 middle-aged and older adults from the National Health and Nutrition Examination Survey were included. The FI was evaluated using a previously validated 49-item deficit model to assess frailty status, which is one of the common approaches to measure overall health burden. We performed weighted multivariable-adjusted linear regression to assess the association between PPI use and FI, and conducted a two-sample MR to evaluate causality, employing various sensitivity analyses for robustness. The inverse variance weighted (IVW) method was used as the primary analysis. RESULTS: Multiple linear regression analysis revealed a positive association between PPI use and FI (ß = 0.048, 95% confidence interval [CI]: 0.042-0.054, P < .001). This association was observed in both short-term (≤ 1 year) and long-term (> 1 year) PPI users (P for trend < 0.001). The MR study also revealed a positive association between PPI use and FI based on the IVW method (ß = 1.183, 95% CI: 0.474-1.892, P = .001). CONCLUSIONS: While our findings suggest a potential link between PPI use and FI, they should be interpreted with caution due to the study's limitations. Although the MR analysis suggests a causal relationship, further research, particularly longitudinal studies, is needed to confirm these findings and better establish temporality.

Disentangling the relationship between biological age and frailty in community-dwelling older Mexican adults.

OBJECTIVE: Older adults have heterogeneous aging rates. Here, we explored the impact of biological age (BA) and accelerated aging on frailty in community-dwelling older adults. METHODS: We assessed 735 community-dwelling older adults from the Coyocan Cohort. BA was measured using AnthropoAge, accelerated aging with AnthropoAgeAccel, and frailty using both Fried's phenotype and the frailty index. We explored the association of BA and accelerated aging (AnthropoAgeAccel ≥0) with frailty at baseline and characterized the impact of both on body composition and physical function. We also explored accelerated aging as a risk factor for frailty progression after 3-years of follow-up. RESULTS: Older adults with accelerated aging have higher frailty prevalence and indices, lower handgrip strength and gait speed. AnthropoAgeAccel was associated with higher frailty indices (ß=0.0053, 95%CI 0.0027-0.0079), and increased odds of frailty at baseline (OR 1.16, 95%CI 1.09-1.25). We observed a sexual dimorphism in body composition and physical function linked to accelerated aging in non-frail participants; however, this dimorphism was absent in pre-frail/frail participants. Accelerated aging at baseline was associated with higher risk of frailty progression over time (OR 1.74, 95%CI 1.11-2.75). CONCLUSIONS: Despite being intertwined, biological accelerated aging is largely independent of frailty in community-dwelling older adults.

Prevalence and future estimates of frailty and pre-frailty in a population-based sample of people 70 years and older in Norway: the HUNT study.

BACKGROUND: Frailty in older people is a rising global health concern; therefore, monitoring prevalence estimates and presenting projections of future frailty are important for healthcare planning. AIM: To present current prevalence estimates of frailty and pre-frailty and future projections according to both dominant frailty models in a large population-based observational study including adults ≥ 70 years in Norway. METHODS: In this population-based observational study, we included 9956 participants from the HUNT4 70 + study, conducting assessments at field stations, homes, and nursing homes. Frailty was assessed using Fried criteria and a 35-item frailty index (HUNT4-FI). Inverse probability weighting and calibration using post-stratification weights and aggregated register data for Norway according to age, sex, and education ensured representativeness, and population projection models were used to estimate future prevalence. RESULTS: According to Fried criteria, the current prevalence rates of frailty and pre-frailty in people ≥ 70 years were 10.6% and 41.9%, respectively, and for HUNT4-FI 35.8% and 33.2%, respectively. Compared to previous European estimates we identified higher overall frailty prevalence, but lower prevalence in younger age groups. Projections suggest the number of Norwegian older adults living with frailty will close to double by 2040. CONCLUSION: Frailty in older people in Norway is more prevalent than previous European estimates, emphasising the imperative for effective interventions aimed to delay and postpone frailty and ensure healthcare system sustainability in an ageing population. Future planning should consider the great heterogeneity in health and functioning within the 70 + population.

Effectiveness of the frailty index in predicting recurrent pneumonia and death in long-term hospitalized patients with vascular cognitive impairment.

OBJECTIVE: The aim was to predict the effectiveness of using frailty, defined by the frailty index (FI), for predicting recurrent pneumonia and death in patients 50 years and older with vascular cognitive impairment (VCI) during long-term hospitalization. MEASUREMENTS: This retrospective cohort study was conducted at a teaching hospital in western China and included VCI patients aged ≥50 years undergoing long-term hospitalization. The relevant data were collected from the electronic medical record system. The FI was based on 31 parameters and groups were defined using a cutoff value (0.2) as robust (FI < 0.2) and FRAIL (≥0.2). The definition of recurrent pneumonia was a minimum of two episodes within a year, with the symptoms, signs, and imaging results of pneumonia disappearing completely between episodes, and a minimum interval between episodes of seven days. Death was recorded by the hospital as the result of cardiac and respiratory arrest and survival was defined as the interval between hospital admission and confirmed death. Logistic regression models were used to assess the association between FI and recurrent pneumonia, while associations between FI and death were assessed by Cox proportional hazards models. RESULTS: A total of 252 long-term hospitalized VCI patients ≥50 years old were enrolled, of whom 115 were male (45.6 %). Ninety-seven patients (38.5 %) were defined as FRAIL. The median length of stay for hospitalized patients was 37 months. Overall, 215 patients developed pneumonia during hospitalization, which occurred an average of 14.5 months after admission, while 151 (59.9 %) had recurrent pneumonia, and 155 (61.5 %) died. Of these, 143 died in the hospital and 12 died after discharge. No significant differences were seen in the incidence of recurrent pneumonia between FRAIL and robust long-term hospitalized VCI patients (FRAIL vs. robust: 66.0 % vs. 56.1 %, P = 0.121) while FRAIL patients had a higher mortality rate than robust patients (FRAIL vs. robust: 71.1 % vs. 55.5 %, P = 0.013). After further Cox regression analysis and adjustment for possible confounders found to be significant in the univariate analysis (including age, sex, smoking history, and activities of daily living (ADL) score), FRAIL patients had a higher risk of death than healthy patients (HR = 1.595, 95 % CI: 1.149-2.213). In addition, based on Model 2, confounding variables that were not statistically significant in the univariate analysis but may have had an impact on the results (including marital status, educational level, drinking history, comorbidity and rehabilitation treatment) were incorporated into Model 3 for further correction. The result remained unchanged, namely, that compared with robust patients, FRAIL patients had a higher risk of death (HR = 1.771, 95 % CI: 1.228-2.554). CONCLUSIONS AND IMPLICATIONS: Frailty defined by the FI was effective for predicting the risk of mortality but not that of recurrent pneumonia in long-term hospitalized VCI patients aged 50 or older.

The association of frailty with morbidity and mortality following major mucosal head and neck surgery.

OBJECTIVES: Frailty refers to a state of reduced physiological reserve and functional decline. We sought to analyse whether frailty, assessed using the 5-item modified frailty index (5mFI), was associated with increased morbidity and mortality following major mucosal head and neck surgery. MATERIALS AND METHODS: We performed a retrospective study of patients undergoing major mucosal head and neck surgical resection over a 2-year period. Potential confounding variables were controlled by way of multivariable regression analysis. RESULTS: There were 310 patients included with 77 (24.8 %) classified as frail. Most patients were male (219/310, 70.7 %), had a history of smoking (246/310, 79.4 %) and 151 patients (48.7 %) were older than 65 at time of surgery. Most surgeries related to oral cavity or oropharyngeal subsites (227/310, 73.2 %) and 150 patients (48.4 %) underwent microvascular free tissue reconstruction. On multivariable analysis, frail patients were more likely to suffer adverse outcomes such as a return to theatre (OR 3.47, 95 % CI 1.82-6.62, p < 0.001), a Clavien-Dindo grade IV complication (OR 6.23, 95 % CI 2.55-15.20, p < 0.001) or medical complications, such as respiratory complications (OR 2.61, 95 % CI 1.45-4.69; p = 0.001) or delirium (OR 5.05, 95 % CI 2.46-10.33; p < 0.001). Additionally, hospital length of stay was increased among frail patients (ß 16.46 days, 95 % CI 9.85-23.07 days; p < 0.001). Neither 90-day nor 1-year post-operative mortality was increased in frail patients. CONCLUSION: Frailty assessed using the 5mFI was associated with greater post-operative morbidity, but not mortality following major mucosal head and neck surgery.

Causal associations between frailty and low back pain: a bidirectional two-sample mendelian randomization study.

BACKGROUND: Previous observational studies have revealed a potentially robust bidirectional relationship between frailty and low back pain (LBP). However, the precise causal relationship remains unclear. METHODS: To examine the potential causal association between frailty and LBP, we conducted bidirectional two-sample Mendelian randomization analysis (MR) study. Genetic data on frailty index (FI) and LBP were acquired from publicly available genome-wide association studies (GWAS). Various MR methodologies were utilized, such as inverse variance weighting (IVW), weighted median, and MR-Egger, to evaluate causality. Additionally, sensitivity analyses were conducted to evaluate the robustness of the findings. RESULTS: Genetically predicted higher FI (IVW, odds ratio [OR] = 1.66, 95% CI 1.17-2.36, p = 4.92E-03) was associated with a higher risk of LBP. As for the reverse direction, genetic liability to LBP showed consistent associations with a higher FI (IVW, OR = 1.13, 95% CI 1.07-1.19, p = 2.67E-05). The outcomes from various MR techniques and sensitivity analyses indicate the robustness of our findings. CONCLUSION: Our research findings provide additional evidence bolstering the bidirectional causal relationship between frailty and LBP.

Genetic liability to higher frailty index may increase the risk of ophthalmic disease.

PURPOSE: Frailty and age-related eye diseases are common in older people; however, whether there is a causal link remains unknown. We aimed to explore the causal associations between the frailty index (FI) and ophthalmic traits and identify modifiable mediators. METHODS: Linkage disequilibrium score regression and two-sample Mendelian randomization were applied to identify genetic correlations and causal associations between FI and ophthalmic traits. Summary data for FI was obtained from a genome-wide association study that included 175,226 individuals of European ancestry. Summary-level statistics for ophthalmic traits were obtained from relative GWASs. Summary-level data for cardiovascular risk factors, inflammatory biomarkers, and the central nervous system were used to identify the possible mediators. RESULTS: FI had a significant genetic correlation with 10 ophthalmic traits. Per SD increment of FI, the odds ratio was 1.329 (95% CI, 1.123, 1.573; P = 9.5 × 10-4) for cataracts, 1.825 (95% CI, 1.115, 2.986; P = 0.016) for keratitis, 1.798 (95% CI, 1.039, 3.11; P = 0.036) for disorders of vitreous body and 1.478 (95% CI, 1.005, 2.173; P = 0.046) for disorders of sclera, cornea, iris and ciliary body. The MR effect estimates of FI on ophthalmic traits were attenuated after adjusting for mental disorders, type 2 diabetes, triglyceride, and interleukin-8 (IL-8) levels. CONCLUSION: This study reports a genetic correlation and causal association between FI and ophthalmic traits, in which mental disorders, type 2 diabetes, triglycerides, and IL-8 may play a mediating role. These findings highlight a possible method to reduce the risk of FI-related ophthalmic diseases.

Frailty and Long-Term Mortality Following Emergency Laparotomy: A Comparison Between the 11-Item and 5-Item Modified Frailty Indices.

INTRODUCTION: Emergency laparotomy (EL) is a high-risk operation which is increasingly performed on an aging patient population. Objective frailty assessment using a validated index has the potential to improve preoperative risk stratification. This study aimed to assess the correlation between frailty and long-term mortality and morbidity outcomes for older EL patients. Secondary aims were to compare the 11-item and shortened five-item modified frailty indices (mFIs) in terms of value and predictive validity. METHODS: A prospective multicenter observational study of patients aged ≥55 y undergoing EL was conducted across five hospitals in New Zealand between 2017 and 2022. Frailty was measured using the 11-item and abbreviated five-item mFIs. Multivariable logistic regression was used to determine whether frailty was independently associated with one-year postoperative mortality and other morbidity outcomes. Correlation between the two frailty indices were assessed with the Spearman's correlation coefficient (P). RESULTS: Frailty assessments were performed in 861 participants, with the prevalence being 18.7% and 29.8% using the 11-item and five-item mFIs, respectively. Both frailty indices demonstrated similar associations with one-year mortality (two-fold increased risk), major complications, admission to intensive care unit, rehabilitation, and 30-d readmission. The 11-item mFI demonstrated a greater association with early mortality (four-fold increased risk), reoperations, and increased length of stay compared with the five-item frailty index. Spearman P was 0.6 (P < 0.001). CONCLUSIONS: Frailty, as identified by the 11-item and five-item mFIs, was associated with one-year mortality and other important morbidity outcomes for older EL patients. These forms of frailty assessment provide important information that may aid in risk assessment and patient-centered decision-making.

Spinal alignment and surgical correction in the aging spine and osteoporotic patient.

Background: The aging spine often presents multifaceted surgical challenges for the surgeon because it can directly and indirectly impact a patient's spinal alignment and quality of life. Elderly and osteoporotic patients are predisposed to progressive spinal deformities and potential neurologic compromise and surgical management can be difficult because these patients often present with greater frailty. Methods: This was a literature review of spinal alignment changes, preoperative considerations, and spinal alignment considerations for surgical strategies. Results: Many factors impact spinal alignment as we age including lumbar lordosis flexibility, hip flexion, deformity, and osteoporosis. Preoperative considerations are required to assess the patient's overall health, bone mineral density, and osteoporosis medications. Careful radiographic assessment of the spinopelvic parameters using various classification/scoring systems provide the surgeon with goals for surgical treatment. An individualized surgical strategy can be planned for the patient including extent of surgery, surgical approach, extent of the constructs, fixation techniques, vertebral augmentation, ligamentous augmentation, and staging surgery. Conclusions: Surgical treatment should only be considered after a thorough assessment of the patient's health, deformity, bone quality and corresponding age matched alignment goals. An individualized treatment approach is often required to tackle the deformity and minimize the risk of hardware related complications and pseudarthrosis. Anabolic agents offer a promising benefit in this patient population by directly addressing and improving their bone quality and mineral density preoperatively and postoperatively.

Predicting outcomes in head and neck surgery with modified frailty index and surgical apgar scores.

OBJECTIVE: To compare the efficacy of the Modified Frailty Index and Modified Surgical Apgar scores in predicting postoperative outcomes in head and neck cancer patients. METHODS: We retrospectively reviewed patients who underwent major head and neck surgery between 2012 and 2015. Modified Surgical Apgar, and Frailty Index, scores were calculated on 723 patients. The primary outcome was 30-day complication and/or mortality. RESULTS: The mean Modified Frailty Index was 0.11 ± 0.12, and mean Modified Surgical Apgar score was 6.15 ± 1.67. Both scores were significantly associated with 30-day complication (P<0.05). The Modified Surgical Apgar score was superior to the Modified Frailty Index in predicting complications (Area Under the Curve (AUC) = 0.76; 95 % Confidence Interval (CI), 0.722-0.793; and AUC=0.59; 95 % CI, 0.548-0.633, respectively). Concurrent use of both scoring systems (AUC=0.77) was not superior to individual use. An increase in the mFI from 0.27 to 0.36 was associated with an increase in the risk of complication postoperatively (Odds Ratio (OR) = 3.67; 95 % CI, 1.30-10.34, P=.014). A reduction in the mSAS from 7 to 6 increased the risk of complication following surgery (OR=2.64; 95 % CI, 1.45-4.80; P=.002). CONCLUSION: Both scores are useful in risk stratifying head and neck cancer patients. The Modified Surgical Apgar score was superior at predicting complications; concurrent use of both scores added minimal benefit.

Modified 5-Item Frailty Index (mFI-5) may predict postoperative outcomes after pancreatoduodenectomy for pancreatic Cancer.

BACKGROUND: Pancreatic Ductal Adenocarcinoma (PDAC) primarily affects older individuals with diminished physiological reserves. The Modified 5-Item Frailty Index (mFI-5) is a novel risk stratification tool proposed to predict postoperative morbidity and mortality. This study aimed to validate the mFI-5 for predicting surgical outcomes in patients undergoing pancreatoduodenectomy (PD) for PDAC. METHODS: Our retrospective PDAC database included patients who underwent PD between 2014 and 2023. Patients were stratified by mFI-5 scores (0 best - 5 worst), which assess preoperative CHF, diabetes mellitus, history of COPD or pneumonia, functional health status, and hypertension requiring medication. Associations between mFI-5 scores and outcomes, including postoperative complications and mortality, were analyzed using logistic regression, Cox proportional hazards models, and Kaplan-Meier survival analysis. RESULTS: Among 250 PDAC patients undergoing PD, 142 (56.8%) had mFI-5 scores ≤ 1, and 25 (10%) had scores ≥ 3. No patients had scores > 4. Higher mFI-5 scores correlated with older age (p < 0.001) and tobacco use (p = 0.036). Multivariate analysis identified age (RR 1.02, p = 0.038), ASA class (ASA III; RR 2.61, p < 0.001; ASA IV; RR 2.63, p = 0.026), and moderate alcohol consumption (RR 0.56, p = 0.038) as frailty predictors. An mFI-5 score > 2 independently associated with higher mortality (HR 2.08, p = 0.026). Median overall survival was significantly lower for patients with mFI-5 scores > 2 than for those with scores ≤ 2 (21.3 vs. 42.1 months, p = 0.022). CONCLUSIONS: The mFI-5 is a valuable tool for predicting postoperative morbidity and mortality in PDAC patients undergoing PD. Integrating frailty assessment into preoperative evaluations can enhance patient selection and surgical outcomes. Future research should focus on incorporating frailty assessments into surgical planning and patient management to improve outcomes in this vulnerable population.

Preoperative Modified Frailty Index-11 versus EuroSCORE II in Predicting Postoperative Mortality and Complications in Elderly Patients Who Underwent Elective Open Cardiac Surgery: A Retrospective Cohort Study.

OBJECTIVE: To compare sensitivity, specificity, receiver operating characteristic (ROC), and area under the curve (AUC) values using the modified Frailty Index 11 (mFI-11), EuroSCORE II, and combined mFI-11 and EuroSCORE II to predict in-hospital mortality and composite morbidities. DESIGN: Retrospective cohort study SETTING: Songklanagarind Hospital, a tertiary care center in southern Thailand. PARTICIPANTS: Elderly patients age ≥60 years who underwent elective open-heart surgical procedures on a pump between January 2017 and December 2022 were included. INTERVENTIONS: ROC curves were constructed to evaluate the discriminatory power of EuroSCORE II and mFI-11 for predicting in-hospital mortality and postoperative complications. MEASUREMENTS AND MAIN RESULTS: The actual in-hospital mortality was 2.5% for all patients. The discriminative accuracy of mFI-11, EuroSCORE II, and combined mFI-11 with EuroSCORE II for predicting in-hospital mortality was good, with respective AUC values of 0.733 (95% confidence interval [CI], 0.6157-0.8499), 0.793 (95% CI, 0.6826-0.9026), and 0.78 (95% CI, 0.6686-0.893). The AUC of mFI-11 for predicting postoperative cardiac, respiratory, neurologic, and renal complications was 0.558 (95% CI, 0.5101-0.6063), 0.606 (95% CI, 0.5542-0.6581), 0.543 (95% CI, 0.4533-0.6337), and 0.652 (95% CI, 0.5859-0.7179), respectively, and that of EuroSCORE II was 0.553 (95% CI, 0.5038-0.6013), 0.631 (95% CI, 0.578-0.6836), 0.619 (95% CI, 0.5306-0.7076), and 0.702 (95% CI, 0.6378-0.7657), respectively. CONCLUSIONS: The mFI-11 and EuroSCORE II demonstrated good discrimination in ROC analysis, with EuroSCORE II showing superior predictive accuracy for in-hospital mortality in elderly elective cardiac surgery patients. However, neither score independently predicted mortality in multiple logistic regression, nor did combining them enhance predictive power significantly. Furthermore, both scores were less effective in predicting postoperative complications.