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The decompensation trajectory check is a basic step to assess the clinical course and to plan future therapy in hospitalized patients with acute decompensated heart failure (ADHF). Due to the atypical presentation and clinical complexity, trajectory checks can be challenging in older patients with acute HF. Point-of-care ultrasound (POCUS) has proved to be helpful in the clinical decision-making of patients with dyspnea; however, to date, no study has attempted to verify its role in predicting determinants of ADHF in-hospital worsening. In this single-center, cross-sectional study, we consecutively enrolled patients aged 75 or older hospitalized with ADHF in a tertiary care hospital. All of the patients underwent a complete clinical examination, blood tests, and POCUS, including Lung Ultrasound and Focused Cardiac Ultrasound. Out of 184 patients hospitalized with ADHF, 60 experienced ADHF in-hospital worsening. By multivariable logistic analysis, total Pleural Effusion Score (PEFs) [aO.R.: 1.15 (CI95% 1.02–1.33), p = 0.043] and IVC collapsibility [aO.R.: 0.90 (CI95% 0.83–0.95), p = 0.039] emerged as independent predictors of acute HF worsening after extensive adjustment for potential confounders. In conclusion, POCUS holds promise for enhancing risk assessment, tailoring diuretic treatment, and optimizing discharge timing for older patients with ADHF.

Background. Cytokine dysregulation plays a critical role in COVID-19, and its timely recognition is pivotal for a favourable outcome, typically in the oldest patient. Lung ultrasound (LUS) has been proven to be an easy-to-perform, accurate tool for detecting COVID-19 pneumonia. The current study aimed to evaluate the relationship between inflammatory markers and pulmonary injury assessed by LUS in older patients with COVID-19. Methods. We consecutively evaluated older patients (age ≥ 65 years) hospitalized for COVID-19 pneumonia in our tertiary care hospital. All the patients underwent LUS, physical examination, and blood tests. LUS score for monitoring aeration, based on the number of B-lines for each scanned zone was assessed. Kendall’s Correlation was calculat-ed to verify the relationship between LUS and inflammation markers. A 7.5 mg/dl Hs-CRP cut-off was set to define the “hyper-inflammation” state. Finally, a receiver operating curve (ROC) was evaluated to define a cytokine storm – LUS-defined cut-off. Results. Overall, 65 older patients [mean (SD), 82.0 (6.9) years] were included in the analysis. LUS score was related inversely to PaO2/FiO2 ratio at admission (tau-0.29, p < 0.01) and nadir (tau-0.21, p < 0.01), and positively to Hs-CRP (tau 0.35, p < 0.001). An indexed LUS score higher than 0.8 was highly predictive of cytokine storm (AUROC 0.78, p < 0.001; Sensitivity 86%, Specificity 68%). Conclusions. Lung involvement evaluated by LUS correlates direct-ly with inflammatory markers and inversely with PaO2/ FiO2 ratio. LUS values qualified as an independent predictor of cytokine storm, and a score greater than 0.8 is the most predictive cut-off.

Loop diuretics (LDs) represent the cornerstone treatment for relieving pulmonary congestion in patients with heart failure (HF). Their benefit is well-recognized in the short term because of their ability to eliminate fluid retention. However, long term, they could adversely influence prognosis due to activation of the neurohumoral mechanism, particularly in older, frail patients. Moreover, the advent of new drugs capable of improving outcomes and reducing pulmonary and systemic congestion signs in HF emphasizes the possibility of a progressive reduction and discontinuation of LD treatment. Nevertheless, few studies were aimed at investigating the safety of LDs withdrawal in older patients with chronic stable HF. This current review aims to approach current evidence regarding the safety and effectiveness of LDs discontinuation in patients with chronic stable HF, and is based on the material obtained via the PubMed and Scopus databases from January 2000 to November 2022. Our search yielded five relevant studies, including two randomized controlled trials. All participants presented stable HF at the time of study enrolment. Apart from one study, all the investigations were conducted in patients with HF with reduced ejection fraction. The most common outcomes examined were the need for diuretic resumption or the event of death and rehospitalization after diuretic withdrawal. As a whole, although based on a few investigations with a low grade of evidence, diuretic therapy discontinuation might be a safe strategy that deserves consideration for patients with stable HF. However, extensive investigations in older adults, accounting for frailty status, are warranted to confirm these data in this peculiar class of patients.

Background: Machine-learning techniques have been recently utilized to predict the probability of unfavorable outcomes among elderly patients suffering from heart failure (HF); yet none has integrated an assessment for frailty and comorbidity. This research seeks to determine which machine-learning-based phenogroups that incorporate frailty and comorbidity are most strongly correlated with death or readmission at hospital for HF within six months following discharge from hospital. Methods: In this single-center, prospective study of a tertiary care center, we included all patients aged 65 and older discharged for acute decompensated heart failure. Random forest analysis and a Cox multivariable regression were performed to determine the predictors of the composite endpoint. By k-means and hierarchical clustering, those predictors were utilized to phenomapping the cohort in four different clusters. Results: A total of 571 patients were included in the study. Cluster analysis identified four different clusters according to frailty, burden of comorbidities and BNP. As compared with Cluster 4, we found an increased 6-month risk of poor outcomes patients in Cluster 1 (very frail and comorbid; HR 3.53 [95% CI 2.30–5.39]), Cluster 2 (pre-frail with low levels of BNP; HR 2.59 [95% CI 1.66–4.07], and in Cluster 3 (pre-frail and comorbid with high levels of BNP; HR 3.75 [95% CI 2.25–6.27])). Conclusions: In older patients discharged for ADHF, the cluster analysis identified four distinct phenotypes according to frailty degree, comorbidity, and BNP levels. Further studies are warranted to validate these phenogroups and to guide an appropriate selection of personalized, model of care.

Background: Direct oral anticoagulants (DOACs) pharmacokinetics depends on estimated glomerular filtration rate (eGFR), whose estimation is crucial for optimal risk/benefit balance. Aims: To assess the concordance among different eGFR formulas and the potential impact on DOACs prescription appropriateness and bleeding risk in oldest hospitalized patients. Methods: Post hoc analysis of a single-centre prospective cohort study. eGFR was calculated by creatinine-based (MDRD, CKD-EPICr, BIS1) and creatinine–cystatin-C-based (CKD-EPIComb and BIS2) formulas. Patients were stratified according to eGFR [severely depressed (SD) 15–29; moderately depressed (MD) 30–49; preserved/mildly depressed (PMD): ≥ 50 ml/min/1.73 m2]. Concordance between the different equations was assessed by Cohen’s kappa coefficient. Results: Among AF patients, 841 (59.2% women, mean age 85.9 ± 6.5 years) received DOACs. By CKD-EPICr equation, 135 patients were allocated in the SD, 255 in the MD and 451 in the PMD group. The concordance was excellent only between BIS 2 and CKD-EPIComb and MDRD and CKD-EPICr, while was worse (from good to poor) between the other formulas. Indeed, by adding cystatin-C almost over 1/3 of the patients were reallocated to a worse eGFR class. Bleeding prevalence increased by 2–3% in patients with discordant eGFR between formulas, reallocated to a worse chronic kidney disease (CKD) stage, although without reaching statistical significance. CKD-EPIComb resulted the best predictor of bleeding events (AUROC 0.71, p = 0.03). Discussion: This study highlights the variability in CKD staging according to different eGFR formulas, potentially determining inappropriate DOACs dosing. Although the cystatin-C derived CKDEPIComb equation is the most accurate for stratifying patients, BIS1 may represent a reliable alternative.

This paper reports the proceedings of a meeting convened by the Research Group on Thoracic Ultrasound in Older People of the Italian Society of Gerontology and Geriatrics, to discuss the current state-of-the-art of clinical research in the field of geriatric thoracic ultrasound and identify unmet research needs and potential areas of development. In the last decade, point-of-care thoracic ultrasound has entered clinical practice for diagnosis and management of several respiratory illnesses, such as bacterial and viral pneumonia, pleural effusion, acute heart failure, and pneumothorax, especially in the emergency–urgency setting. Very few studies, however, have been specifically focused on older patients with frailty and multi-morbidity, who frequently exhibit complex clinical pictures needing multidimensional evaluation. At the present state of knowledge, there is still uncertainty on the best requirements of ultrasound equipment, methodology of examination, and reporting needed to optimize the advantages of thoracic ultrasound implementation in the care of geriatric patients. Other issues regard differential diagnosis between bacterial and aspiration pneumonia, objective grading of interstitial syndrome severity, quantification and monitoring of pleural effusions and solid pleural lesions, significance of ultrasonographic assessment of post-COVID-19 sequelae, and prognostic value of assessment of diaphragmatic thickness and motility. Finally, application of remote ultrasound diagnostics in the community and nursing home setting is still poorly investigated by the current literature. Overall, the presence of several open questions on geriatric applications of thoracic ultrasound represents a strong call to implement clinical research in this field.

Objective. Dabigatran, a direct inhibitor of thrombin, represents an effective alternative to warfarin. Despite the good tolerance and predictable pharmacokinetic profile, dabigatran may be associated to adverse reactions, including gastrointestinal disorders. Here we report on a case of hepatotoxicity along with an extensive revision of the available literature on dabigatran induced liver injury Methods & results. An 84 years old man attended the Emergency Department after experiencing fatigue for a few days. He suffered from atrial fibrillation and had been initiated on dabigatran (110 mg bid) in the last four weeks. Clinical examination revealed tachycardia, scleral icterus in the absence of signs of chronic hepatic disease. Blood chemistry showed altered liver function tests: AST 809 IU/L, ALT 1629 IU/L, total bilirubin 2.42 mg/dL, gGT 381 IU/L, ALP 388 IU/L, LDH 552 IU/L. Screening laboratory investigations for infectious, autoimmune or metabolic hepatotoxic pathology were unremarkable. The abdominal ultrasound examination excluded vascular causes, revealing non-homogeneous echo-structure consistent with mild hepatic steatosis. At admission to our Geriatric ward dabigatran was discontinued and fondaparinux was introduced. Resolution of the hepatitis and normalization of blood chemistry was observed within two weeks. Few cases are described regarding hepatotoxicity likely caused by the recent onset of treatment with dabigatran. Conclusions. DOACs associated hepatotoxicity is rare but potentially harmful and should be kept in mind, especially in comorbid patients with unexplained liver injury. The mechanism of liver injury during dabigatran therapy is unknown and, not related to cytochrome P450 enzymes since the drug does not affect CYP450 activity.

OBJECTIVES: To compare the diagnostic accuracy of lung ultrasound (LUS) and standard chest X-ray (CXR) in older patients admitted to an acute-care geriatric ward for suspected acute pneumonia, and to develop an easy-to-use diagnostic tool, now called Pneumonia Lung Ultrasound Score (PLUS), for early risk stratification. DESIGN: Prospective, single-center, cohort study. SETTING: Acute-care geriatric ward of tertiary care center. PARTICIPANTS: Individuals, aged 65 years and older, with suspected acute pneumonia. MEASUREMENTS: Participants were stratified according to the Multidimensional Prognostic Index. All the patients underwent CXR and LUS, whereas chest computed tomography was performed in case of mismatch between LUS and CXR. Using logistic multivariate regression, we assessed the influence of age, sex, multimorbidity, cognitive impairment, and clinical biomarkers in the misdiagnosis of acute pneumonia. Finally, an easy-to-perform diagnostic tool based on the combination of biomarkers (brain natriuretic peptide, high-sensitivity C-reactive protein, and partial pressure arterial oxygen/fraction of inspired oxygen ratio) and LUS was realized. A receiver operating characteristic curve was used to verify the predictive accuracy of PLUS, CXR, and LUS in pneumonia diagnosis. RESULTS: A total of 132 subjects (69% women; mean age = 85.3 ± 6.9 years) were enrolled in the study. Acute pneumonia was diagnosed in 94 of 132 cases. LUS showed higher diagnostic accuracy compared with CXR (0.91 (95% confidence interval (CI) = 0.85–0.93) vs 0.67 (95% CI = 0.58–0.75)) in detecting pneumonic consolidations. A higher degree of cognitive impairment was associated with both LUS and CXR pneumonia misdiagnosis (odds ratio = 1.30 (95% CI = 1.04–1.65)). PLUS showed higher predictive accuracy in the diagnosis of acute pneumonia compared with LUS (AUC = 0.92 (95% CI = 0.87–0.98) vs 0.86 (95% CI = 0.80–0.96); P =.029). CONCLUSIONS: This study confirms the higher diagnostic accuracy of LUS c

Background: Triple-negative breast cancer (TNBC) is a very heterogeneous disease. Several gene expression and mutation profiling approaches were used to classify it, and all converged to the identification of distinct molecular subtypes, with some overlapping across different approaches. However, a standardised tool to routinely classify TNBC in the clinics and guide personalised treatment is lacking. We aimed at defining a specific gene signature for each of the six TNBC subtypes proposed by Lehman et al. in 2011 (basal-like 1 (BL1); basal-like 2 (BL2); mesenchymal (M); immunomodulatory (IM); mesenchymal stem-like (MSL); and luminal androgen receptor (LAR)), to be able to accurately predict them. Methods: Lehman’s TNBCtype subtyping tool was applied to RNA-sequencing data from 482 TNBC (GSE164458), and a minimal subtype-specific gene signature was defined by combining two class comparison techniques with seven attribute selection methods. Several machine learning algorithms for subtype prediction were used, and the best classifier was applied on microarray data from 72 Italian TNBC and on the TNBC subset of the BRCA-TCGA data set. Results: We identified two signatures with the 120 and 81 top up- and downregulated genes that define the six TNBC subtypes, with prediction accuracy ranging from 88.6 to 89.4%, and even improving after removal of the least important genes. Network analysis was used to identify highly interconnected genes within each subgroup. Two druggable matrix metalloproteinases were found in the BL1 and BL2 subsets, and several druggable targets were complementary to androgen receptor or aromatase in the LAR subset. Several secondary drug–target interactions were found among the upregulated genes in the M, IM and MSL subsets. Conclusions: Our study took full advantage of available TNBC data sets to stratify samples and genes into distinct subtypes, according to gene expression profiles. The development of a data mining approach to acquire a large amo

Background: The aim of this study is to identify miRNAs able to predict the outcomes in breast cancer patients after neoadjuvant chemotherapy (NAC). Patients and methods: We retrospec-tively analyzed 24 patients receiving NAC and not reaching pathologic complete response (pCR). miRNAs were analyzed using an Illumina Next‐Generation‐Sequencing (NGS) system. Results: Event‐free survival (EFS) and overall survival (OS) were significantly higher in patients with up-regulation of let‐7a‐5p (EFS p = 0.006; OS p = 0.0001), mirR‐100‐5p (EFS s p = 0.01; OS p = 0.03), miR‐ 101‐3p (EFS p = 0.05; OS p = 0.01), and miR‐199a‐3p (EFS p = 0.02; OS p = 0.01) in post‐NAC samples, independently from breast cancer subtypes. At multivariate analysis, only let‐7a‐5p was significantly associated with EFS (p = 0.009) and OS (p = 0.0008). Conclusion: Up‐regulation of the above miRNAs could represent biomarkers in breast cancer.