A Real-World Assessment of Stage I Lung Cancer Through Electronic Nose Technology.

INTRODUCTION: Electronic nose (E-nose) technology has reported excellent sensitivity and specificity in the setting of lung cancer screening. However, the performance of E-nose specifically for early-stage tumors remains unclear. Therefore, the aim of our study was to assess the diagnostic performance of E-nose technology in clinical stage I lung cancer. METHODS: This phase IIc trial (NCT04734145) included patients diagnosed with a single greater than or equal to 50% solid stage I nodule. Exhalates were prospectively collected from January 2020 to August 2023. Blinded bioengineers analyzed the exhalates, using E-nose technology to determine the probability of malignancy. Patients were stratified into three risk groups (low-risk, [<0.2]; moderate-risk, [≥0.2-0.7]; high-risk, [≥0.7]). The primary outcome was the diagnostic performance of E-nose versus histopathology (accuracy and F1 score). The secondary outcome was the clinical performance of the E-nose versus clinicoradiological prediction models. RESULTS: Based on the predefined cutoff (<0.20), E-nose agreed with histopathologic results in 86% of cases, achieving an F1 score of 92.5%, based on 86 true positives, two false negatives, and 12 false positives (n = 100). E-nose would refer fewer patients with malignant nodules to observation (low-risk: 2 versus 9 and 11, respectively; p = 0.028 and p = 0.011) than would the Swensen and Brock models and more patients with malignant nodules to treatment without biopsy (high-risk: 27 versus 19 and 6, respectively; p = 0.057 and p < 0.001). CONCLUSIONS: In the setting of clinical stage I lung cancer, E-nose agrees well with histopathology. Accordingly, E-nose technology can be used in addition to imaging or as part of a "multiomics" platform.

Use of Sensor Array Analysis to Detect Ovarian Cancer through Breath, Urine, and Blood: A Case-Control Study.

Ovarian cancer (OC) is the eighth most common cancer in women. Since screening programs do not exist, it is often diagnosed in advanced stages. Today, the detection of OC is based on clinical examination, transvaginal ultrasound (US), and serum biomarker (Carbohydrate Antigen 125 (CA 125) and Human Epididymis Protein 4 (HE4)) dosage, with a sensitivity of 88% and 95%, respectively, and a specificity of 84% for US and 76% for biomarkers. These methods are clearly not enough, and OC in its early stages is often missed. Many scientists have recently focused their attention on volatile organic compounds (VOCs). These are gaseous molecules, found in the breath, that could provide interesting information on several diseases, including solid tumors. To detect VOCs, an electronic nose was invented by a group of researchers. A similar device, the e-tongue, was later created to detect specific molecules in liquids. For the first time in the literature, we investigated the potential use of the electronic nose and the electronic tongue to detect ovarian cancer not just from breath but also from urine, blood, and plasma samples.

Diaphragmatic ultrasound evaluation in acute heart failure: clinical and functional associations.

Heart failure patients often experience respiratory symptoms due to diaphragmatic involvement, but the diaphragmatic motion in heart failure remains understudied. This research aimed to investigate the correlation between ultrasonographically assessed diaphragmatic motion and thickness with cardiac performance indexes in an emergency setting. Seventy-two acutely decompensated heart failure patients and 100 non-heart failure individuals were enrolled. Diaphragmatic motion and thickness were assessed via ultrasound. Cardiac and respiratory parameters were recorded, and regression analysis was performed. Heart failure patients exhibited reduced diaphragmatic motion at total lung capacity compared to controls, and an inverse association was found between motion and heart failure severity (NYHA stage). Diaphragmatic thickness was also higher in heart failure patients at tidal volume and total lung capacity. Notably, diaphragmatic motion inversely correlated with systolic pulmonary artery pressure. The study highlights diaphragmatic dysfunction in acutely decompensated heart failure, with reduced motion and increased thickness. These changes were associated with cardio-respiratory parameters, specifically systolic pulmonary artery pressure. Monitoring diaphragmatic motion via ultrasound may aid in evaluating heart failure severity and prognosis in emergency settings. Additionally, interventions targeting diaphragmatic function could improve heart failure management. Further research is warranted to enhance heart failure management and patient outcomes.

Frailty in the chronic respiratory patient: association with mortality and clinical features in obstructive, restrictive, and mixed spirometric patterns.

BACKGROUND: Frailty associates with increased vulnerability to adverse health outcomes and reduced tolerance to medical interventions. Its impact on patients with chronic respiratory diseases, particularly beyond chronic obstructive pulmonary disease (COPD), remains poorly understood. AIMS: To evaluate the association between frailty index and 5-year mortality across different "spirometric" patterns and the variation in their occurring frailty determinants. METHODS: This study analyzed data from the SARA study, which enrolled 1968 older adults, to evaluate the association between frailty and 5-year mortality across different spirometric patterns. Frailty was assessed using the frailty index (FI), and spirometry was performed to determine lung function patterns. Hazard ratios (HRs) were calculated using Cox regression models, adjusting for age and sex. RESULTS: Among the study participants, 16% were classified as frail. Frailty was associated with a significantly increased risk of mortality across all spirometric patterns. The 5-year mortality rates were 34.3% in subjects with normal spirometry, 45.1% in those with obstructive defects, 55% in those with restrictive defects, and 42.6% in those with mixed airflow defects. The unadjusted HRs for mortality were 2.64 (95% CI 2.10-3.32) for the overall cohort, 2.24 (95% CI 1.48-3.40) for obstructive defects, 2.45 (95% CI 1.12-5.36) for restrictive defects, and 2.79 (95% CI 1.41-3.17) for mixed airflow defects. After adjusting for age and sex, the HRs remained statistically significant: 2.25 (95% CI 1.37-2.84) for the overall cohort, 2.08 (95% CI 1.37-3.18) for obstructive defects, 2.27 (95% CI 1.04-1.17) for restrictive defects, and 2.21 (95% CI 1.20-3.08) for mixed airflow defects. CONCLUSION: Frailty is a common syndrome and is associated with a significantly increased risk of mortality. The FI provides valuable information for risk profiling and personalized interventions beyond age and lung function parameters. Including frailty assessment in clinical evaluations can aid in resource allocation and improve patient care in respiratory diseases.

Handgrip Strength Test and Bioelectrical Impedance Analysis in SARS-CoV-2 Patients Admitted to Sub-Intensive Unit.

Hospitalized patients with respiratory failure due to SARS-CoV-2 pneumonia are at increased risk of malnutrition and related mortality. The predictive value of the Mini-Nutritional Assessment short form (MNA-sf®), hand-grip strength (HGS), and bioelectrical impedance analysis (BIA) was determined with respect to in-hospital mortality or endotracheal intubation. The study included 101 patients admitted to a sub-intensive care unit from November 2021 to April 2022. The discriminative capacity of MNA-sf, HGS, and body composition parameters (skeletal mass index and phase angle) was assessed computing the area under the receiver operating characteristic curves (AUC). Analyses were stratified by age groups (<70/70+ years). The MNA-sf alone or in combination with HGS or BIA was not able to reliably predict our outcome. In younger participants, HGS showed a sensitivity of 0.87 and a specificity of 0.54 (AUC: 0.77). In older participants, phase angle (AUC: 0.72) was the best predictor and MNA-sf in combination with HGS had an AUC of 0.66. In our sample, MNA- sf alone, or in combination with HGS and BIA was not useful to predict our outcome in patients with COVID-19 pneumonia. Phase angle and HGS may be useful tools to predict worse outcomes in older and younger patients, respectively.

Incidence and Outcome of Pneumomediastinum in Non-ICU Hospitalized COVID-19 Patients.

OBJECTIVES: Pneumomediastinum (PNM) is a rare complication of mechanical ventilation, but its reported occurrence in patients with acute respiratory distress syndrome secondary to COVID-19 is significant. The objective is to determine the incidence, risk factors, and outcome of PNM in non-ICU hospitalized patients with severe-to-critical COVID-19 pneumonia. DESIGN: Retrospective observational study. SETTING: Population-based, single-setting, tertiary-care level COVID treatment center. PATIENTS: Individuals hospitalized with a diagnosis of COVID-19 pneumonia and severe to critical illness were included. Those hospitalized without respiratory failure, observed for less than 24 hours, or admitted from an ICU were excluded. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: All patients underwent a complete clinical assessment and chest CT scan, and were followed up from hospitalization to discharge or death. The outcome was the number of cases of PNM, defined as the presence of free air in the mediastinal tissues diagnosed by chest CT scan, in non-ICU hospitalized patients and the subsequent risk of intubation and mortality. PNM occurred in 48 out of 331 participants. The incidence was 14.5% (95% CI, 10.9-18.8%). A CT-Scan Severity score greater than 15 was positively associated with PNM (odds ratio [OR], 4.09; p = 0.002) and was observed in 35.2% of the participants (95% CI, 26.2-44.9%). Noninvasive ventilation was also positively associated with PNM (OR, 4.46; p = 0.005), but there was no positive association with airway pressures. Fifty patients (15%) were intubated, and 88 (27%) died. Both the risk for intubation and mortality were higher in patients with PNM, with a hazard ratio of 3.72 ( p < 0.001) and 3.27 ( p < 0.001), respectively. CONCLUSIONS: Non-ICU hospitalized patients with COVID-19 have a high incidence of PNM, increasing the risk for intubation and mortality three- to four-fold, particularly in those with extensive lung damage. These findings help define the risk and outcome of PNM in severe-to-critical COVID-19 pneumonia in a non-ICU setting.

The Role of Gut Bacteriome in Asthma, Chronic Obstructive Pulmonary Disease and Obstructive Sleep Apnoea.

The human body contains a very complex and dynamic ecosystem of bacteria. The bacteriome interacts with the host bi-directionally, and changes in either factor impact the entire system. It has long been known that chronic airway diseases are associated with disturbances in the lung bacteriome. However, less is known about the role of gut bacteriome in the most common respiratory diseases. Here, we aim to summarise the evidence concerning the role of the intestinal bacteriome in the pathogenesis and disease course of bronchial asthma, chronic obstructive pulmonary disease, and obstructive sleep apnea. Furthermore, we discuss the consequences of an altered gut bacteriome on the most common comorbidities of these lung diseases. Lastly, we also reflect on the therapeutic potential of influencing the gut microbiome to improve disease outcomes.

Predictors of undernutrition in COPD patients.

BACKGROUND & AIMS: Chronic obstructive pulmonary disease (COPD) is a chronic disease characterized by persistent respiratory symptoms and airflow limitation. The Global Initiative for Chronic Obstructive Lung Disease (GOLD) report recommends smoking cessation, pharmacological therapy and pulmonary rehabilitation, but this clinical course can be negatively influenced by undernutrition, a condition documented in about 20% of COPD patients. An altered energy balance characterized by an insufficient intake of energy and nutrients is the primary cause of undernutrition, therefore the aim of this study is to investigate whether clinical and instrumental variables collected during a routine respiratory assessment associate with an altered energy balance in order to identify COPD patients at higher risk of undernutrition worth of further assessment. METHODS: A total of forty-nine participants with a diagnosis of stable COPD were included in this mono-center and longitudinal study. Subjects underwent a multidimensional assessment including evaluation of medical history, evaluation of pulmonary function, evaluation of nutritional status, evaluation of energy intake and resting energy expenditure (REE) using EPIC questionnaire and indirect-calorimetry (IC), respectively, evaluation of physical impairment and mood status. RESULTS: The 24% of participants was at risk of undernutrition with a mean energy intake, total protein intake and lipid intake significantly lower than not at risk subjects, while REE was significantly higher. Age, sex, multimorbidity, disability and depression, and pulmonary function tests were not associated with a negative energy balance, with the exception of the Cumulative Illness Rating Scale (CIRS) severity index, which showed a significant association. CONCLUSION: Clinical evaluation and pulmonary function tests are unable to reliably predict undernutrition in COPD patients, so a nutritional screening should always be forecast in this population based on an accurate evaluation of energy intake and expenditure and body composition.

Energy expenditure and intake in COPD: The extent of unnoticed unbalance by predicting REE.

Undernourishment is promoted by an unbalance between energy expenditure and intake. Resting energy expenditure (REE) in chronic obstructive pulmonary disease (COPD) is commonly predicted using the Harris-Benedict (HB) and the Angelillo-Moore (AM) formulas, however no study has investigated to which extent COPD patients with an energy unbalance go unnoticed when REE is predicted rather than measured with indirect calorimetry. This study demonstrates that 66% and 25% of negatively unbalanced patients go unnoticed when using HB and AM, respectively, urging to discourage the use of REE predicting formulas in clinical practice, at least in cases at risk of undernourishment.

Computed tomography findings and prognosis in older COVID-19 patients.

BACKGROUND: In older and multimorbid patients, chronic conditions may affect the prognostic validity of computed tomography (CT) findings in COVID-19. This study aims at assessing to which extent CT findings have prognostic implications in COVID-19 older patients. METHODS: Hospitalized COVID-19 patients aged 60 years or more enrolled in the multicenter, observational and longitudinal GeroCovid study who underwent chest CT were included. Patients were stratified by tertiles of age and pneumonia severity to compare CT findings. Hierarchical clustering based on CT findings was performed to identify CT-related classificatory constructs, if any. The hazard ratio (HR) of mortality was calculated for individual CT findings and for clusters, after adjusting for potential confounders. RESULTS: 380 hospitalized COVID-19 patients, with a mean age of 78 (SD:9) years, underwent chest CT scan. Ground glass opacity (GGO), consolidation, and pleural effusion were the three most common CT findings, with GGO prevalence decreasing from younger to older patients and pleural effusion increasing. More severe the pneumonia more prevalent were GGO, consolidation and pleural effusion. HR of mortality was 1.94 (95%CI 1.24-3.06) for pleural effusion and 13 (95%CI 6.41-27) for cluster with a low prevalence of GGO and a high prevalence of pleural effusion ("LH"), respectively. Out of the three CT based clusters, "LH" was the only independent predictor in the multivariable model. CONCLUSIONS: Pleural effusion qualifies as a distinctive prognostic marker in older COVID-19 patients. Research is needed to verify whether pleural effusion reflects COVID-19 severity or a coexisting chronic condition making the patient at special risk of death. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04379440.

The additional value of lung cancer screening program in identifying unrecognized diseases.

BACKGROUND: A systematic examination of low-dose CT (LDCT) scan, beside lung nodules, may disclose the presence of undiagnosed diseases, improving the efficacy and the cost/efficacy of these programs. The study was aimed at evaluating the association between LDCT scan findings and non-oncologic and oncologic diseases. METHODS: The LDCT scan of participants to the "Un Respiro per la vita"® lung cancer screening program were checked and abnormal findings, beside lung nodules, recorded. First admission to the acute care because of cardiovascular (CD), respiratory (RD) and oncological diseases (OD) in the following three years were retrieved. The association of LDCT scan abnormal findings with CD, RD and OD was assessed through univariable and multivariable logistic regression models. RESULTS: Mean age of 746 participants was 62 years (SD:5), 62% were male. 11 (1.5%) received a diagnosis of lung cancer. 16.1% participants were admitted to the acute care in the following three years: 8.6% for CD, 4.3% for RD and 5.2% for OD. Valve calcification (OR 2.02, p:0.02) and mucus plugs (OR 3.37, p:0.04) were positively associated with CD, while sub-pleural fibrosis had a protective role (OR 0.47, p:0.01). Lung nodules > 8 mm (OR 5.54, p: < 0.01), tracheal deviation (OR 6.04, p:0.01) and mucus plugs (OR 4.00, p:0.04) were positively associated with OD admissions. Centrilobular emphysema OR for RD admissions was 1.97 (p:0.06). CONCLUSIONS: The observed association between selected LDCT findings and ensuing CD, RD and OD suggests that the information potential of LCDT goes beyond the screening of lung cancer.

Frailty Impact during and after Pulmonary Rehabilitation.

Frailty is a condition of reduced physiologic reserve common in COPD candidates to pulmonary rehabilitation, however no study has investigated whether frailty impacts the decline that a great part of COPD patients face after the completion of the rehabilitation program. Study objectives are to verify frailty impact on pulmonary rehabilitation outcomes during and after the program. This is a secondary analysis of a longitudinal study. Stable COPD patients GOLD I-III were randomized to a three-month endurance versus endurance and resistance training. Participants performed a multidimensional assessment at baseline, at the end of the rehabilitation program and after six months. Frailty was defined using a two-step approach including PRISMA-7 and Timed "Up and Go" test. Frailty interaction with time was evaluated using generalized least-squared regression models for repeated measures, correcting for potential confounders. Of the 53 participants with a mean age of 73 (SD:8) years 38 (72%) were frail. The mean 6MWD and V'O2peak increased in frail and no frail patients during pulmonary rehabilitation and declined after its completion, while CAT score showed a steep decline during the training, and a mild decline later. Frailty showed a significant interaction with time in terms of 6MWD variation during (ß adj:43.6 meters, p-value:0.01) and after (ß adj:-47 meters, p-value:0.02) pulmonary rehabilitation; no significant interaction was found in terms of V'O2peak and CAT score variation. In conclusion, frail COPD patients have a higher potential to benefit from pulmonary rehabilitation, but a higher risk to have a steeper decline later.Supplemental data for this article is available online at https://doi.org/10.1080/15412555.2021.1967915 .

Association between frailty index, lung function, and major clinical determinants in chronic obstructive pulmonary disease.

BACKGROUND: Airflow limitation alone is unable to capture the complexity of chronic obstructive pulmonary disease (COPD), better explained by comprehensive disease-specific indexes. Frailty is a clinical condition characterized by high vulnerability to internal and external stressors and represents a strong predictor of adverse outcomes. AIMS: Primary objective was to test the association between indexes of lung function and COPD severity with frailty index (FI), and secondary to evaluate the association between FI and comorbidities, cognitive and physical function, BODE index, and mortality. METHODS: 150 stable COPD outpatients were enrolled and followed up to 4 years. At baseline, participants performed a geriatric multidimensional assessment, pulmonary function tests, arterial blood gas analysis, 6-min walking test, and bioimpedance analysis. BODE and FI were calculated. Spearman's ρ was used to assess correlations. Mortality was assessed using Kaplan-Meier curves. RESULTS: Participants were followed up for a median of 39 months. Mean age was 73 years and median frailty index 0.15 (IQR 0.11-0.19). FI was higher in frequent exacerbators (≥ 2/year) (mean 0.18 vs 0.15, p 0.01) and dyspnoeic patients (mMRC ≥ 2) (mean 0.21 vs 0.14, p < 0.01) and correlated with lung volumes, expiratory flows, and pressure of arterial oxygen. FI was positively correlated with the number of comorbidities, depressive symptoms, cognitive decline, and BODE index. Mortality was higher in patients with BODE higher than 3 (HR 3.6, 95% CI 1.2-10.9), and not associated with FI. DISCUSSION: FI positively correlates with all clinical drivers orienting the choice of treatment in COPD. CONCLUSIONS: FI associates with lung function and COPD severity, but does not associate with mortality.

Symptom-based clusters in patients with advanced chronic organ failure identify different trajectories of symptom variations.

BACKGROUND: Healthcare needs are complex and heterogeneous in advanced chronic organ failure. However, based on symptom clusters, groups of patients with similar quality of life, care dependency and life-sustaining treatment preferences can be identified. AIMS: To evaluate the stability of symptom-based clusters over time, and whether and to what extent the clusters are able to predict patients' 2-year survival and hospitalization rates. METHODS: This is a secondary analysis of a longitudinal observational study including 95 outpatients with chronic obstructive pulmonary disease (COPD) GOLD stage III-IV, 80 outpatients with chronic heart failure (CHF) NYHA stage III-IV and 80 outpatients with chronic renal failure (CRF) requiring dialysis. Patients were clustered into three groups applying K-means algorithm on baseline symptoms' severity and were then longitudinally evaluated. 2-year survival and hospital admissions during 1 year were estimated using Kaplan-Meier curves and Cox models. 1-year tendencies in symptom variation, using mixed linear models, and clusters comparison over time were performed. RESULTS: The three clusters were unable to predict patients' survival and hospital admissions. Noteworthy, they show different trajectories of symptom variation, with Cluster 1 patients experiencing a worsening of symptoms, associated with an increased care dependency, and Cluster 2 and Cluster 3 patients being stable or having a relief in some symptoms. Although Cluster 1 is becoming more similar to Cluster 2, the three clusters preserve the overall characteristics and differences. DISCUSSION: Symptom-based clusters might help to identify patients with different trajectories of symptom variations. CONCLUSION: Symptom clusters do not predict survival and hospital admissions and are stable over time.

Clustering of patients with end-stage chronic diseases by symptoms: a new approach to identify health needs.

BACKGROUND: End-stage chronic obstructive pulmonary disease (COPD), chronic heart failure (CHF) and chronic renal failure (CRF) are characterized by a high burden of daily symptoms that, irrespective of the primary organ failure, are widely shared. AIMS: To evaluate whether and to which extent symptom-based clusters of patients with end-stage COPD, CHF and CRF associate with patients' health status, mobility, care dependency and life-sustaining treatment preferences. METHODS: 255 outpatients with a diagnosis of advanced COPD (n = 95), advanced CHF (n = 80) or CRF requiring dialysis (n = 80) were visited in their home environment and underwent a multidimensional assessment: clinical characteristics, symptom burden using Visual Analog Scale (VAS), health status questionnaires, timed "Up and Go" test, Care Dependency Scale and willingness to undergo mechanical ventilation or cardiopulmonary resuscitation. Three clusters were obtained applying K-means cluster analysis on symptoms' severity assessed via VAS. Cluster characteristics were compared using non-parametric tests. RESULTS: Cluster 1 patients, with the least symptom burden, had a better quality of life, lower care dependency and were more willing to accept life-sustaining treatments than others. Cluster 2, with a high presence and severity of dyspnea, fatigue, cough, muscle weakness and mood problems, and Cluster 3, with the highest occurrence and severity of symptoms, reported similar care dependency and life-sustaining treatment preferences, while Cluster 3 reported the worst physical health status. DISCUSSION: Symptom-based clusters identify patients with different health needs and might help to develop palliative care programs. CONCLUSION: Clustering by symptoms identifies patients with different health status, care dependency and life-sustaining treatment preferences.

Defining Resilience in Older People: Does a Subjective Definition of Stressor Work?

BACKGROUND: The operational definition of resilience is elusive and resilient people are difficult to identify. We used self-reported "major health event" (srMHE) to identify resilience and evaluate the functional and mortality trajectories associated with this condition. METHOD: We selected from the InCHIANTI study persons aged 65 or older who could perform the Short Physical Performance Battery at baseline and attended the 3 years follow-up visit. We identified 4 groups: Controls: no srMHE and no decline in physical function; Decliners: no srMHE and decline in physical function; Resilient: srMHE and no decline in physical function; and Non-resilient: srMHE and decline in physical function. Linear mixed models and Cox regression were used to analyze changes in activities of daily living (ADL) score over 9- and 10-year mortality across groups, respectively. RESULTS: The 313 participants that reported a srMHE had worse perceived health status and higher number of GP visits and prescribed drugs at baseline. Of these, 78 were Resilient and 235 Non-resilient; of the remaining, 136 were Controls and 277 Decliners. Compared to the Controls, Resilient had similar change of ADL score over time (ß: -.03, p = .92) and mortality (hazard ratio: 1.31, 95% confidence interval: 0.76-2.23), while Decliners and Non-resilient showed significantly higher mortality and, the latter, worsening of ADL score. Additional srMHE during follow-up affected the rate of change of ADL score and mortality more in the Controls group than in the Resilient group. CONCLUSIONS: A srMHE along with repeated evaluation of physical function may be used to identify resilience in older people, and may complement the standard functional evaluation of geriatric patients.

The Role of Electronic Noses in Phenotyping Patients with Chronic Obstructive Pulmonary Disease.

Chronic obstructive pulmonary disease (COPD) is a common progressive disorder of the respiratory system which is currently the third leading cause of death worldwide. Exhaled breath analysis is a non-invasive method to study lung diseases, and electronic noses have been extensively used in breath research. Studies with electronic noses have proved that the pattern of exhaled volatile organic compounds is different in COPD. More recent investigations have reported that electronic noses could potentially distinguish different endotypes (i.e., neutrophilic vs. eosinophilic) and are able to detect microorganisms in the airways responsible for exacerbations. This article will review the published literature on electronic noses and COPD and help in identifying methodological, physiological, and disease-related factors which could affect the results.

Metabolic syndrome is associated with better quality of sleep in the oldest old: results from the "Mugello Study".

BACKGROUND AND AIMS: Reduced sleep quality is common in advanced age. Poor sleep quality is associated with adverse outcomes, chiefly cardiovascular, in young and middle-aged subjects, possibly because of its association with metabolic syndrome (MetS). However, the correlates of sleep quality in oldest populations are unknown. We evaluated the association of sleep quality with MetS in a cohort of subjects aged 90+. METHODS AND RESULTS: We analysed data of 343 subjects aged 90+ living in the Mugello area (Tuscany, Italy). Quality of sleep was assessed using the Pittsburgh Sleep Quality Assessment Index (PSQI). Good quality of sleep was defined by a PSQI score < 5. MetS was diagnosed according to the National Cholesterol Education Program's ATP-III criteria; 83 (24%) participants reported good quality of sleep. MetS was diagnosed in 110 (24%) participants. In linear and logistic models, MetS was inversely associated with PSQI score ((B = - 1.04; 95% CI - 2.06 to - .03; P = .044), with increased probability of good sleep quality (OR = 2.52; 95% CI 1.26-5.02; P = .009), and with a PSQI below the median (OR = 2.11; 95% CI 1.11-3.40, P = .022), after adjusting. None of the single components of MetS were associated with PSQI (all P values > .050). However, an increasing number of MetS components was associated with increasing probability of good quality of sleep (P for trend = .002), and of PSQI below the median (P for trend = .007). Generalized Additive Model analysis documented no smoothing function suggestive of nonlinear association between PSQI and MetS. CONCLUSION: Our results confirm a high prevalence of poor sleep quality in oldest age; however, in these subjects, MetS seems to be associated with better sleep quality. Additional larger, dedicated studies are required to confirm our results, and, if so, to identify the subsystems involved and the potential therapeutic implications of such an association.