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AbstractIn contrast to red blood cells, platelets float rather than sediment when a column of blood is placed in the gravitational field. By the analogy of erythrocyte sedimentation (ESR), it can be expressed with the platelet antisedimentation rate (PAR), which quantitates the difference in platelet count between the upper and lower halves of the blood column after 1 h of 1 g sedimentation. Venous blood samples from 21 healthy subjects were analyzed for PAR. After a 1-h sedimentation, the upper and lower fractions of blood samples were analyzed for platelet count, mean platelet volume (MPV), immature platelet fraction (IPF), and high-fluorescence IPF (H-IPF). The mechanisms behind platelet flotation were explored by further partitioning of the blood column, time-dependent measurements of platelet count and comparison with ESR. The structure and function of the platelets were assessed by electron microscopy (EM) and atomic force microscopy (AFM), and platelet aggregometry, respectively. Platelet antisedimentation is driven by density differences and facilitated by a size-exclusion mechanism caused by progressive erythrocyte sedimentation. The area under the curve (AUC) of the whole blood adenosine diphosphate (ADP) aggregation curves showed significant differences between the upper and lower samples (p

Abstract Background The concept of frailty provides an age-independent, easy-to-use tool for risk stratification. We aimed to summarize the evidence on the efficacy of frailty tools in risk assessment in COVID-19 patients. Methods The protocol was registered (CRD42021241544). Studies reporting on frailty in COVID-19 patients were eligible. The main outcomes were mortality, length of hospital stay (LOH) and intensive care unit (ICU) admission in frail and non-frail COVID-19 patients. Frailty was also compared in survivors and non-survivors. Five databases were searched up to 24th September 2021. The QUIPS tool was used for the risk of bias assessment. Odds ratios (OR) and weighted mean differences (WMD) were calculated with 95% confidence intervals (CI) using a random effect model. Heterogeneity was assessed using the I 2 and χ 2 tests. Results From 3640 records identified, 54 were included in the qualitative and 42 in the quantitative synthesis. Clinical Frailty Scale (CFS) was used in 46 studies, the Hospital Frailty Risk Score (HFRS) by 4, the Multidimensional Prognostic Index (MPI) by 3 and three studies used other scores. We found that patients with frailty (CFS 4–9 or HFRS ≥ 5) have a higher risk of mortality (CFS: OR: 3.12; CI 2.56–3.81; HFRS OR: 1.98; CI 1.89–2.07). Patients with frailty (CFS 4–9) were less likely to be admitted to ICU (OR 0.28, CI 0.12–0.64). Quantitative synthesis for LOH was not feasible. Most studies carried a high risk of bias. Conclusions As determined by CFS, frailty is strongly associated with mortality; hence, frailty-based patient management should be included in international COVID-19 treatment guidelines. Future studies investigating the role of frailty assessment on deciding ICU admission are strongly warranted.

Introduction: Exploration of novel and effective antiplatelet strategies for the secondary prevention of ischemic stroke is utmost. Some platelet derived microparticles (PMVs) in convalescent stroke subjects were found to be predictive for the next vascular event. Patients with high-on-treatment platelet reactivity (HTPR) had a significantly higher risk for ischemic stroke. Here, we aimed to explore associations among circulating microparticles and responsivness to antiplatelet (clopidogrel) therapy. Methods: A total of 18 patients on clopidogrel therapy due to secondary stroke prevention were rospectively recruited into this study. Twenty age-matched healthy subjects served as controls. Flow cytometric measurements of microparicles (MVs) and data analysis were performed on Beckman-Coulter FC-500 cytometer with CXP software. Besides, platelet aggregometry data were revealed. Both measurements were performed in whole blood and from the lower and upper blood fractions separated after 1-hour gravity sedimentation by the analogy with erythrocyte sedimentation rate. Results: The total number of circulating MVs, and particularly the platelet derived CD42+ and PAC-1+ were significantly higher in post-stroke patients (p < 0.001). The platelet aggregation in the whole blood (area under the curve, AUC) showed a significant negative correlation with the total number of MPs in the lower blood sample after 1-hour gravity sedimentation (r = –0.650, p = 0.005). Next, we analyzed associations among MPs and aggregometry data obtained from clopidogrel responders and non-responders. Both, area under the curve (AUC) and velocity in the whole blood showed opposite correlation with the total number of MVs in the lower blood sample after 1-hour gravity sedimentation. Importantly, a significant negative correlation was observed for the velocity (r = –0.801, p = 0.005), but not for the AUC in responders. Platelet derived CD42+ and PAC-1+ MVs showed positive correlations with neutrophils in the lower blood sample (p = 0.008 and p = 0.006 respectively). Conclusions: Circulating MVs may allow to monitor the response to antiplatelet therapy in post-stroke patients. In addition, the link between platelet derived MVs and neutrophil granulocytes might become therapeutic targets in the future.

Intraoperative stress is common to patients undergoing carotid endarterectomy (CEA); thus, impaired oxygen and metabolic balance may appear. In this study, we aimed to identify new markers of intraoperative cerebral ischemia, with predictive value on postoperative complications during CEA, performed in regional anesthesia. A total of 54 patients with significant carotid stenosis were recruited and submitted to CEA. Jugular and arterial blood samples were taken four times during operation, to measure the jugulo-arterial carbon dioxide partial pressure difference (P(j-a)CO2), and cortisol, S100B, L-arginine, and lactate levels. A positive correlation was found between preoperative cortisol levels and all S100B concentrations. In addition, they are positively correlated with P(j-a)CO2 values. Conversely, postoperative cortisol inversely correlates with P(j-a)CO2 and postoperative S100B values. A negative correlation was observed between maximum systolic and pulse pressures and P(j-a)CO2 after carotid clamp and before the release of clamp. Our data suggest that preoperative cortisol, S100B, L-arginine reflect patients’ frailty, while these parameters postoperatively are influenced by intraoperative stress and injury. As a novelty, P(j-a)CO2 might be an emerging indicator of cerebral blood flow during CEA.

High rates of thrombosis are present in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Deeper insight into the prothrombotic state is essential to provide the best thromboprophylaxis care. Here, we aimed to explore associations among platelet indices, conventional hemostasis parameters, and viscoelastometry data. This pilot study included patients with severe COVID-19 (n = 21) and age-matched controls (n = 21). Each patient received 100 mg aspirin therapy at the time of blood sampling. Total platelet count, high immature platelet fraction (H-IPF), fibrinogen, D-dimer, Activated Partial Thromboplastin Time, von Willebrand factor antigen and von Willebrand factor ristocetin cofactor activity, plasminogen, and alpha2-antiplasmin were measured. To monitor the aspirin therapy, a platelet function test from hirudin anticoagulated whole blood was performed using the ASPI test by Multiplate analyser. High on-aspirin platelet reactivity (n = 8) was defined with an AUC > 40 cut-off value by ASPI tests. In addition, in vitro viscoelastometric tests were carried out using a ClotPro analyser in COVID-associated thromboembolic events (n = 8) (p = 0.071) nor the survival rate (p = 0.854) showed associations with high on-aspirin platelet reactivity status. The platelet count (p = 0.03), all subjects. COVID-19 patients presented with higher levels of inflammatory markers, compared with the controls, along with evidence of hypercoagulability by ClotPro. H-IPF (%) was significantly higher among non-survivors (n = 18) compared to survivors (p = 0.011), and a negative correlation (p = 0.002) was found between H-IPF and plasminogen level in the total population. The platelet count was significantly higher among patients with high on-aspirin platelet reactivity (p = 0.03). Neither the ECA-A10 (p = 0.008), and ECA-MCF (p = 0.016) were significantly higher, while the tPA-CFT (p < 0.001) was significantly lower among patients with high on-aspirin platelet reactivity. However, only fibrinogen proved to be an independent predictor of hypofibrinolysis in severe COVID-19 patients. In conclusion, a faster developing, more solid clot formation was observed in aspirin ‘non-responder’ COVID-19 patients. Therefore, an individually tailored thromboprophylaxis is needed to prevent thrombotic complications, particularly in the hypofibrinolytic cluster.

Copyright of Hungarian Journal of Anesthesiolog & Intensive Therapy / Aneszteziológia és Intenzív Terápia is the property of Hungarian Society of Anaesthesiology & Intensive Therapy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hungarian Journal of Anesthesiolog & Intensive Therapy / Aneszteziológia és Intenzív Terápia is the property of Hungarian Society of Anaesthesiology & Intensive Therapy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)