Morphologic Mapping of the Sublingual Microcirculation in Healthy Volunteers

PURPOSE Monitoring the sublingual and oral microcirculation (SM-OM) using hand-held vital microscopes (HVMs) has provided valuable insight into the (patho)physiology of diseases. However, the microvascular anatomy in a healthy population has not been adequately described yet. METHODS Incident dark field-based HVM imaging was used to visualize the SM-OM. First, the SM was divided into four different fields; Field-a (between incisors-lingua), Field-b (between the canine-first premolar-lingua), Field-c (between the first-second premolar-lingua), Field-d (between the second molar-wisdom teeth-lingua). Second, we investigated the buccal area, lower and upper lip. Total/functional vessel density (TVD/FCD), focus depth (FD), small vessel mean diameters (SVMDs), and capillary tortuosity score (CTS) were compared between the areas. RESULTS Fifteen volunteers with a mean age of 29 ± 6 years were enrolled. No statistical difference was found between the sublingual fields in terms of TVD (p = 0.30), FCD (p = 0.38), and FD (p = 0.09). SVMD was similar in Field-a, Field-b, and Field-c (p = 0.20-0.30), and larger in Field-d (p < 0.01, p = 0.015). The CTS of the buccal area was higher than in the lips. CONCLUSION The sublingual area has a homogenous distribution in TVD, FCD, FD, and SVMD. This study can be a description of the normal microvascular anatomy for future researches regarding microcirculatory assessment

Microcirculatory alterations in critically ill COVID-19 patients analyzed using artificial intelligence

Background: The sublingual microcirculation presumably exhibits disease-specific changes in function and morphology. Algorithm-based quantification of functional microcirculatory hemodynamic variables in handheld vital microscopy (HVM) has recently allowed identification of hemodynamic alterations in the microcirculation associated with COVID-19. In the present study we hypothesized that supervised deep machine learning could be used to identify previously unknown microcirculatory alterations, and combination with algorithmically quantified functional variables increases the model's performance to differentiate critically ill COVID-19 patients from healthy volunteers. Methods: Four international, multi-central cohorts of critically ill COVID-19 patients and healthy volunteers (n = 59/n = 40) were used for neuronal network training and internal validation, alongside quantification of functional microcirculatory hemodynamic variables. Independent verification of the models was performed in a second cohort (n = 25/n = 33). Results: Six thousand ninety-two image sequences in 157 individuals were included. Bootstrapped internal validation yielded AUROC(CI) for detection of COVID-19 status of 0.75 (0.69-0.79), 0.74 (0.69-0.79) and 0.84 (0.80-0.89) for the algorithm-based, deep learning-based and combined models. Individual model performance in external validation was 0.73 (0.71-0.76) and 0.61 (0.58-0.63). Combined neuronal network and algorithm-based identification yielded the highest externally validated AUROC of 0.75 (0.73-0.78) (P < 0.0001 versus internal validation and individual models). Conclusions: We successfully trained a deep learning-based model to differentiate critically ill COVID-19 patients from heathy volunteers in sublingual HVM image sequences. Internally validated, deep learning was superior to the algorithmic approach. However, combining the deep learning method with an algorithm-based approach to quantify the functional state of the microcirculation markedly increased the sensitivity and specificity as compared to either approach alone, and enabled successful external validation of the identification of the presence of microcirculatory alterations associated with COVID-19 status. Keywords: Artificial intelligence; COVID-19; Deep learning; Microcirculation; Neuronal network

Favorable resuscitation characteristics in patients undergoing extracorporeal cardiopulmonary resuscitation:A secondary analysis of the INCEPTION-trial

Introduction: Extracorporeal cardiopulmonary resuscitation (ECPR) is increasingly used as a supportive treatment for refractory out-of-hospital cardiac arrest (OHCA). Still, there is a paucity of data evaluating favorable and unfavorable prognostic characteristics in patients considered for ECPR. Methods: We performed a previously unplanned post-hoc analysis of the multicenter randomized controlled INCEPTION-trial. The study group consisted of patients receiving ECPR, irrespective of initial group randomization. The patients were divided into favorable survivors (cerebral performance category [CPC] 1–2) and unfavorable or non-survivors (CPC 3–5).Results: In the initial INCEPTION-trial, 134 patients were randomized. ECPR treatment was started in 46 (66%) of 70 patients in the ECPR treatment arm and 3 (4%) of 74 patients in the conventional treatment arm. No statistically significant differences in baseline characteristics, medical history, or causes of arrest were observed between survivors (n = 5) and non-survivors (n = 44). More patients in the surviving group had a shockable rhythm at the time of cannulation (60% vs. 14%, p = 0.037), underwent more defibrillation attempts (13 vs. 6, p = 0.002), and received higher dosages of amiodarone (450 mg vs 375 mg, p = 0.047) despite similar durations of resuscitation maneuvers. Furthermore, non-survivors more frequently had post-ECPR implantation adverse events. Conclusion: The persistence of ventricular arrhythmia is a favorable prognostic factor in patients with refractory OHCA undergoing an ECPR-based treatment. Future studies are warranted to confirm this finding and to establish additional prognostic factors. Clinical trial Registration: clinicaltrials.gov</p

Health-related quality of life one year after refractory cardiac arrest treated with conventional or extracorporeal CPR: a secondary analysis of the INCEPTION-trial

Background: Prospective, trial-based data comparing health-related quality of life (HRQoL) in patients surviving out-of-hospital cardiac arrest (OHCA) through extracorporeal cardiopulmonary resuscitation (ECPR) or conventional CPR (CCPR) are scarce. We aimed to determine HRQoL during 1-year after refractory OHCA in patients treated with ECPR and CCPR. Methods: We present a secondary analysis of the multicenter INCEPTION-trial, which studied the effectiveness of ECPR versus CCPR in patients with refractory OHCA. HRQoL was prospectively assessed using the EQ-5D-5L questionnaire. Poor HRQoL was pragmatically defined as an EQ-5D-5L health utility index (HUI) &gt; 1 SD below the age-adjusted norm. We used mixed linear models to assess the difference in HRQoL over time and univariable analyses to assess factors potentially associated with poor HRQoL. Results: A total of 134 patients were enrolled, and hospital survival was 20% (27 patients). EQ-5D-5L data were available for 25 patients (5 ECPR and 20 CCPR). One year after OHCA, the estimated mean HUI was 0.73 (0.05) in all patients, 0.84 (0.12) in ECPR survivors, and 0.71 (0.05) in CCPR survivors (p-value 0.31). Eight (32%) survivors had a poor HRQoL. HRQoL was good in 17 (68%) patients, with 100% in ECPR survivors versus 60% in CCPR survivors (p-value 0.14). Conclusion: One year after refractory OHCA, 68% of the survivors had a good HRQoL. We found no statistically significant difference in HRQoL one year after OHCA in patients treated with ECPR compared to CCPR. However, numerical differences may be clinically relevant in favor of ECPR.</p

Drawing: Towards an Intelligence of Seeing

Changes in the microcirculatory parameters in the survivor and non-survivor groups at the following time points: initiation of the VA-ECMO insertion (T1); 48–72 h after VA-ECMO initiation (T2); and 5–6 days after (T3). (DOCX 15 kb

Mixoma en válvula de Eustaquio

a TVD, b PVD and c PPV in small vessels (capillaries < 25 μm) were compared between each patient during weaning attempts at flow time points of 100% ECMO flow (F100) and 50% ECMO flow (F50) are compared between patients successfully and not successfully weaned (SW and NSW, respectively). (TIF 2730 kb