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The new noninvasive finger sensor system NICCI (Getinge; Gothenburg, Sweden) allows continuous cardiac output monitoring. We aimed to investigate its cardiac output measurement performance.To investigate the NICCI system's cardiac output measurement performance.Prospective method comparison study.University Medical Center Hamburg-Eppendorf, Hamburg, Germany.Fifty-one patients after cardiac surgery.We performed a method comparison study in 51 patients after cardiac surgery to compare NICCI cardiac output (CO NICCI ) and NICCI cardiac output calibrated to pulmonary artery thermodilution cardiac output measurement (CO NICCI-CAL ) with pulmonary artery thermodilution cardiac output (CO PAT ). As a secondary analysis we also compared CNAP cardiac output (CO CNAP ) and externally calibrated CNAP cardiac output (CO CNAP-CAL ) with CO PAT .We analysed 299 cardiac output measurement pairs. The mean of the differences (95% limits of agreement) between CO NICCI and CO PAT was 0.6 (-1.8 to 3.1) l min -1 with a percentage error of 48%. The mean of the differences between CO NICCI-CAL and CO PAT was -0.4 (-1.9 to 1.1) l min -1 with a percentage error of 29%. The mean of the differences between CO CNAP and CO PAT was 1.0 (-1.8 to 3.8) l min -1 with a percentage error of 53%. The mean of the differences between CO CNAP-CAL and CO PAT was -0.2 (-2.0 to 1.6) l min -1 with a percentage error of 35%.The agreement between CO NICCI and CO PAT is not clinically acceptable.The study was registered in the German Clinical Trial Register (DRKS00023189) after inclusion of the first patient on October 2, 2020.

Perioperative hemodynamic management aims to optimize organ perfusion pressure and blood flow-assuming this ensures that oxygen delivery meets cellular metabolic needs. Cellular metabolic needs are reflected by energy expenditure. A better understanding of energy expenditure under general anesthesia could help tailor perioperative hemodynamic management to actual demands. We thus sought to assess energy expenditure under general anesthesia. Our primary hypothesis was that energy expenditure under general anesthesia is lower than preoperative awake resting energy expenditure.We conducted an observational study on patients having elective noncardiac surgery at the University Medical Center Hamburg-Eppendorf (Germany) between September 2019 and March 2020. We assessed preoperative awake resting energy expenditure, energy expenditure under general anesthesia, and energy expenditure after surgery using indirect calorimetry. We compared energy expenditure under general anesthesia at incision to preoperative awake resting energy expenditure using a Wilcoxon signed-rank test for paired measurements.We analyzed 60 patients. Median (95% confidence interval [CI]) preoperative awake resting energy expenditure was 953 (95% CI, 906-962) kcal d-1 m-2. Median energy expenditure under general anesthesia was 680 (95% CI, 642-711) kcal d-1 m-2-and thus 263 (95% CI, 223-307) kcal d-1 m-2 or 27% (95% CI, 23%-30%) lower than preoperative awake resting energy expenditure (P.001).Median energy expenditure under general anesthesia is about one-quarter lower than preoperative awake resting energy expenditure in patients having noncardiac surgery.

The finger-cuff system CNAP (CNSystems Medizintechnik, Graz, Austria) allows non-invasive automated measurement of pulse pressure variation (PPVCNAP). We sought to validate the PPVCNAP-algorithm and investigate the agreement between PPVCNAP and arterial catheter-derived manually calculated pulse pressure variation (PPVINV). This was a prospective method comparison study in patients having neurosurgery. PPVINV was the reference method. We applied the PPVCNAP-algorithm to arterial catheter-derived blood pressure waveforms (PPVINV−CNAP) and to CNAP finger-cuff-derived blood pressure waveforms (PPVCNAP). To validate the PPVCNAP-algorithm, we compared PPVINV−CNAP to PPVINV. To investigate the clinical performance of PPVCNAP, we compared PPVCNAP to PPVINV. We used Bland–Altman analysis (absolute agreement), Deming regression, concordance, and Cohen's kappa (predictive agreement for three pulse pressure variation categories). We analyzed 360 measurements from 36 patients. The mean of the differences between PPVINV−CNAP and PPVINV was −0.1% (95% limits of agreement (95%-LoA) −2.5 to 2.3%). Deming regression showed a slope of 0.99 (95% confidence interval (95%-CI) 0.91 to 1.06) and intercept of −0.02 (95%-CI −0.52 to 0.47). The predictive agreement between PPVINV−CNAP and PPVINV was 92% and Cohen’s kappa was 0.79. The mean of the differences between PPVCNAP and PPVINV was −1.0% (95%-LoA−6.3 to 4.3%). Deming regression showed a slope of 0.85 (95%-CI 0.78 to 0.91) and intercept of 0.10 (95%-CI −0.34 to 0.55). The predictive agreement between PPVCNAP and PPVINV was 82% and Cohen’s kappa was 0.48. The PPVCNAP-algorithm reliably calculates pulse pressure variation compared to manual offline pulse pressure variation calculation when applied on the same arterial blood pressure waveform. The absolute and predictive agreement between PPVCNAP and PPVINV are moderate.

Pulse pressure variation (PPV) is a dynamic cardiac preload variable used to predict fluid responsiveness. PPV can be measured non-invasively using innovative finger-cuff systems allowing for continuous arterial pressure waveform recording, e.g., the Nexfin system [BMEYE B.V., Amsterdam, The Netherlands; now Clearsight (Edwards Lifesciences, Irvine, CA, USA)] (PPVFinger). However, the agreement between PPVFinger and PPV derived from an arterial catheter (PPVART) in obese patients having laparoscopic bariatric surgery is unknown. We compared PPVFinger and PPVART at 6 time points in 60 obese patients having laparoscopic bariatric surgery in a secondary analysis of a prospective method comparison study. We used Bland–Altman analysis to assess absolute agreement between PPVFinger and PPVART. The predictive agreement for fluid responsiveness between PPVFinger and PPVART was evaluated across three PPV categories (PPV 13%) as concordance rate of paired measurements and Cohen’s kappa. The overall mean of the differences between PPVFinger and PPVART was 0.5 ± 4.6% (95%-LoA − 8.6 to 9.6%) and the overall predictive agreement was 72.4% with a Cohen’s kappa of 0.53. The mean of the differences was − 0.7 ± 3.8% (95%-LoA − 8.1 to 6.7%) without pneumoperitoneum in horizontal position and 1.1 ± 4.8% (95%-LoA − 8.4 to 10.5%) during pneumoperitoneum in reverse-Trendelenburg position. The absolute agreement and predictive agreement between PPVFinger and PPVART are moderate in obese patients having laparoscopic bariatric surgery.

BACKGROUND Cardiac output is an important hemodynamic variable and determines oxygen delivery. In contrast to blood pressure, cardiac output is rarely measured even in high-risk surgical patients, suggesting that clinicians consider blood pressure to be a reasonable indicator of systemic blood flow. However, the relationship depends on constant vascular tone and volume, both of which routinely vary during anesthesia and surgery. We therefore tested the hypothesis that there is no clinically meaningful correlation between mean arterial pressure and cardiac index in major abdominal surgery patients. METHODS In this prospective observational study, we assessed the relationship between mean arterial pressure and cardiac index in 100 patients having major abdominal surgery under general anesthesia. RESULTS The pooled within-patient correlation coefficient calculated using meta-analysis methods was r = 0.34 (95% confidence interval, 0.28-0.40). Linear regression using a linear mixed effects model of cardiac index on mean arterial pressure revealed that cardiac index increases by 0.014 L·min-1·m-2 for each 1 mm Hg increase in mean arterial pressure. The 95% Wald confidence interval of this slope was 0.011 to 0.018 L·min-1·m-2·mm Hg-1 and thus within predefined equivalence margins of -0.03 and 0.03 L·min-1·m-2·mm Hg-1, thereby demonstrating lack of clinically meaningful association between mean arterial pressure and cardiac index. CONCLUSIONS There is no clinically meaningful correlation between mean arterial pressure and cardiac index in patients having major abdominal surgery. Intraoperative blood pressure is thus a poor surrogate for cardiac index.

Postinduction and intraoperative hypotension are associated with organ injury in non-cardiac surgery patients. Automated ambulatory blood pressure monitoring can identify chronic arterial hypertension and nocturnal blood pressure non-dipping. We tested the hypotheses that: a) chronic arterial hypertension and nocturnal non-dipping are independent risk factors for postinduction and intraoperative hypotension; and b) adding information on chronic arterial hypertension and nocturnal non-dipping improves hypotension prediction models based on readily available preoperative clinical information.Prediction model development based on a secondary analysis of a prospective observational study.German university medical center.366 non-cardiac surgery patients who had preoperative automated ambulatory blood pressure monitoring.Multivariable analyses to identify risk factors for postinduction and intraoperative hypotension. Area under receiver operating characteristics curves (AUROC) and likelihood-ratio tests to test whether adding information on chronic arterial hypertension and nocturnal non-dipping improves hypotension prediction models based on readily available preoperative clinical information.Risk factors for postinduction hypotension were age in years (odds ratio: 1.06 (95% confidence interval: 1.03 to 1.10), P = 0.001), American Society of Anesthesiologists physical status class (1.85 (1.02 to 3.35), P = 0.043), preoperative use of angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (15.19 (1.76 to 131.46), P = 0.013), chronic arterial hypertension (2.54 (1.49 to 4.34), P = 0.001), and nocturnal non-dipping (3.61 (2.09 to 6.23), P 0.001). The model's AUROC was 0.76 (95% confidence interval: 0.71 to 0.81) with and 0.67 (0.62 to 0.73) without information on chronic arterial hypertension and nocturnal non-dipping (P 0.001). Risk factors for intraoperative hypotension were male sex (1.73 (1.07 to 2.80), P = 0.025), chronic arterial hypertension (4.35 (2.33 to 8.14), P 0.001), and nocturnal non-dipping (3.56 (2.07 to 6.11), P 0.001). The model's AUROC was 0.76 (0.70 to 0.81) with and 0.63 (0.57 to 0.69) without information on chronic arterial hypertension and nocturnal non-dipping (P 0.001).Chronic arterial hypertension and nocturnal non-dipping are independent risk factors for postinduction and intraoperative hypotension in non-cardiac surgery patients. Adding information on chronic arterial hypertension and nocturnal non-dipping moderately improved hypotension prediction models based on preoperative clinical information.

It remains unknown what constitutes physiologically relevant intraoperative bradycardia. Intraoperative bradycardia is usually defined using absolute heart rate thresholds, ignoring preoperative baseline heart rates. In contrast, we considered defining intraoperative bradycardia relative to preoperative ambulatory nighttime heart rate. Specifically, we hypothesized that the individual mean intraoperative heart rate is lower than the mean preoperative ambulatory nighttime heart rate. We, therefore, sought to investigate the relationship between the intraoperative and preoperative ambulatory nighttime heart rates in adults having noncardiac surgery with general anesthesia. Additionally, we sought to investigate the incidence of intraoperative bradycardia using relative versus absolute heart rate thresholds.We conducted a secondary analysis of a database from a prospective study including preoperative ambulatory and intraoperative heart rates in 363 patients having noncardiac surgery with general anesthesia.The mean intraoperative heart rate was lower than the mean nighttime heart rate (mean difference, -9 bpm; 95% confidence interval [CI], -10 to -8 bpm; P.001). The mean intraoperative heart rate was lower than the mean nighttime heart rate in 319 of 363 patients (88%; 95% CI, 84%-91%). The incidence of intraoperative bradycardia was 42% (95% CI, 38%-47%) when it was defined as intraoperative heart rate30% lower than mean nighttime heart rate and 43% (95% CI, 38%-49%) when it was defined as intraoperative heart rate45 bpm.The mean intraoperative heart rate is lower than the mean nighttime heart rate in about 9 of 10 patients. Intraoperative bradycardia might thus be physiologically and clinically important. Future research needs to investigate whether there is an association between intraoperative bradycardia and postoperative outcomes.

Blood pressure is the main determinant of organ perfusion. Hypotension is common in patients having surgery and in critically ill patients. The severity and duration of hypotension are associated with hypoperfusion and organ dysfunction. Hypotension is mostly treated reactively after low blood pressure values have already occurred. However, prediction of hypotension before it becomes clinically apparent would allow the clinician to treat hypotension pre-emptively, thereby reducing the severity and duration of hypotension. Hypotension cannowbepredictedminutes before it actually occurs from the blood pressure waveform using machine-learning algorithms that can be trained to detect subtle changes in cardiovascular dynamics preceding clinically apparent hypotension. However, analyzing the complex cardiovascular system is a challenge because cardiovascular physiology is highly interdependent, works within complicated networks, and is influenced by compensatory mechanisms. Improved hemodynamic data collection and integration will be a key to improve current models and develop new hypotension prediction models. (C) 2019 Elsevier Ltd. All rights reserved.

Background Pulmonary artery thermodilution is the clinical reference method for cardiac output monitoring. Because both continuous and intermittent pulmonary artery thermodilution are used in clinical practice it is important to know whether cardiac output measurements by the two methods are clinically interchangeable. Methods We performed a systematic review and meta-analysis of clinical studies comparing cardiac output measurements assessed using continuous and intermittent pulmonary artery thermodilution in adult surgical and critically ill patients. 54 studies with 1522 patients were included in the analysis. Results The heterogeneity across the studies was high. The overall random effects model-derived pooled estimate of the mean of the differences was 0.08 (95%-confidence interval 0.01 to 0.16) L/min with pooled 95%-limits of agreement of − 1.68 to 1.85 L/min and a pooled percentage error of 29.7 (95%-confidence interval 20.5 to 38.9)%. Conclusion The heterogeneity across clinical studies comparing continuous and intermittent pulmonary artery thermodilution in adult surgical and critically ill patients is high. The overall trueness/accuracy of continuous pulmonary artery thermodilution in comparison with intermittent pulmonary artery thermodilution is good (indicated by a pooled mean of the differences PROSPERO registration number CRD42020159730.

It remains unclear whether reduced myocardial contractility, venous dilation with decreased venous return, or arterial dilation with reduced systemic vascular resistance contribute most to hypotension after induction of general anesthesia. We sought to assess the relative contribution of various hemodynamic mechanisms to hypotension after induction of general anesthesia with sufentanil, propofol, and rocuronium. In this prospective observational study, we continuously recorded hemodynamic variables during anesthetic induction using a finger-cuff method in 92 non-cardiac surgery patients. After sufentanil administration, there was no clinically important change in arterial pressure, but heart rate increased from baseline by 11 (99.89% confidence interval: 7 to 16) bpm (P −5*m2 (P values

Pulse pressure variation (PPV) and cardiac output (CO) can guide perioperative fluid management. Capstesia (Galenic App, Vitoria-Gasteiz, Spain) is a mobile application for snapshot pulse wave analysis (PWAsnap) and estimates PPV and CO using pulse wave analysis of a snapshot of the arterial blood pressure waveform displayed on any patient monitor. We evaluated the PPV and CO measurement performance of PWAsnap in adults having major abdominal surgery. In a prospective study, we simultaneously measured PPV and CO using PWAsnap installed on a tablet computer (PPVPWAsnap, COPWAsnap) and using invasive internally calibrated pulse wave analysis (ProAQT; Pulsion Medical Systems, Feldkirchen, Germany; PPVProAQT, COProAQT). We determined the diagnostic accuracy of PPVPWAsnap in comparison to PPVProAQT according to three predefined PPV categories and by computing Cohen’s kappa coefficient. We compared COProAQT and COPWAsnap using Bland-Altman analysis, the percentage error, and four quadrant plot/concordance rate analysis to determine trending ability. We analyzed 190 paired PPV and CO measurements from 38 patients. The overall diagnostic agreement between PPVPWAsnap and PPVProAQT across the three predefined PPV categories was 64.7% with a Cohen’s kappa coefficient of 0.45. The mean (± standard deviation) of the differences between COPWAsnap and COProAQT was 0.6 ± 1.3 L min− 1 (95% limits of agreement 3.1 to − 1.9 L min− 1) with a percentage error of 48.7% and a concordance rate of 45.1%. In adults having major abdominal surgery, PPVPWAsnap moderately agrees with PPVProAQT. The absolute and trending agreement between COPWAsnap with COProAQT is poor. Technical improvements are needed before PWAsnap can be recommended for hemodynamic monitoring.

Background: Finger cuff technologies allow continuous noninvasive arterial blood pressure (AP) and cardiac output/index (CO/CI) monitoring. Methods: We performed a meta-analysis of studies comparing finger cuff-derived AP and CO/CI measurements with invasive measurements in surgical or critically ill patients. We calculated overall random effects model-derived pooled estimates of the mean of the differences and of the percentage error (PE; CO/CI studies) with 95%-confidence intervals (95%-CI), pooled 95%-limits of agreement (95%-LOA), Cochran's Q and I2 (for heterogeneity). Results: The pooled mean of the differences (95%-CI) was 4.2 (2.8 to 5.62) mm Hg with pooled 95%-LOA of –14.0 to 22.5 mm Hg for mean AP (Q=230.4 [P

The present study focuses on the identification of the gene expression profile of neonatal rat cardiomyocytes (NRVCMs) after dynamic mechanical stretch through microarrays of RNA isolated from cells stretched for 2, 6 or 24 h. In this analysis, myeloid leukemia factor-1 (MLF1) was found to be significantly downregulated during the course of stretch. We found that MLF1 is highly expressed in the heart, however, its cardiac function is unknown yet. In line with microarray data, MLF1 was profoundly downregulated in in vivo mouse models of cardiomyopathy, and also significantly reduced in the hearts of human patients with dilated cardiomyopathy. Our data indicates that the overexpression of MLF1 in NRVCMs inhibited cell proliferation while augmenting apoptosis. Conversely, knockdown of MLF1 protected NRVCMs from apoptosis and promoted cell proliferation. Moreover, we found that knockdown of MLF1 protected NRVCMs from hypoxia-induced cell death. The observed accelerated apoptosis is attributed to the activation of caspase-3/-7/PARP-dependent apoptotic signaling and upregulation of p53. Most interestingly, MLF1 knockdown significantly upregulated the expression of D cyclins suggesting its possible role in cyclin-dependent cell proliferation. Taken together, we, for the first time, identified an important role for MLF1 in NRVCM proliferation.

Automated continuous noninvasive ward monitoring may enable subtle changes in vital signs to be recognized. There is already some evidence that automated ward monitoring can improve patient outcome. Before automated continuous noninvasive ward monitoring can be implemented in clinical routine, several challenges and problems need to be considered and resolved; these include the meticulous validation of the monitoring systems with regard to their measurement performance, minimization of artifacts and false alarms, integration and combined analysis of massive amounts of data including various vital signs, and technical problems regarding the connectivity of the systems.

Intraoperative hypotension (IOH) i.e., low arterial blood pressure (AP) during surgery is common in patients having non-cardiac surgery under general anaesthesia. It has a multifactorial aetiology, and is associated with major postoperative complications including acute kidney injury, myocardial injury and death. Therefore, IOH may be a modifiable risk factor for postoperative complications. However, there is no uniform definition for IOH. IOH not only occurs during surgery but also after the induction of general anaesthesia before surgical incision. However, the optimal therapeutic approach to IOH remains elusive. There is evidence from one small randomised controlled trial that individualising AP targets may reduce the risk of postoperative organ dysfunction compared with standard care. More research is needed to define individual AP harm thresholds, to develop therapeutic strategies to treat and avoid IOH, and to integrate new technologies for continuous AP monitoring.

Postoperative mortality is a major healthcare problem. In order to decrease postoperative mortality, avoiding postoperative complications is key. In turn, to avoid postoperative complications, modifiable risk factors independently associated with these complications need to be identified and avoided. One of the modifiable risk factors for postoperative complications may be perioperative hypotension— i.e., low blood pressure in the perioperative period. In this review, we discuss perioperative hypotension that includes intraoperative hypotension (IOH) and postoperative hypotension (POH), and its impact on postoperative patient outcomes, challenges related to its diagnosis, and potential therapeutic approaches. IOH is common in patients having non-cardiac surgery under general anesthesia and is associated with acute kidney injury, myocardial injury, and death. The relationship between IOH and serious postoperative complications is supported by many observational analyses and one randomized trial that suggests that individualized blood pressure management reduces the risk of postoperative organ dysfunction compared with usual care. More randomized controlled trials are needed before recommendations can be given on how to individualize intraoperative blood pressure targets in clinical routine. POH refers to hypotension occurring on the remaining day of surgery and during the first days after surgery. Available data suggest that POH after non-cardiac surgery is common, profound, and largely undetected by current vital sign monitoring on the general care ward. There is evidence that POH is associated with adverse postoperative outcomes, especially myocardial injury, acute kidney injury, and death. However, there is a need for more data on the pathophysiology, impact, and management of POH. Continuous ward monitoring might enable POH to be detected and treated in a timely manner. However, strategies to prevent or treat POH based on continuous ward monitoring need to be tested for their effectiveness to improve quality of care or patient- centered outcomes in large-scale interventional trials.

Calsarcin-1 deficient mice develop dilated cardiomyopathy (DCM) phenotype in pure C57BL/6 genetic background (Cs1-ko) despite severe contractile dysfunction and robust activation of fetal gene program. Here we performed a microRNA microarray to identify the molecular causes of this cardiac phenotype that revealed the dysregulation of several microRNAs including miR-301a, which was highly downregulated in Cs1-ko mice compared to the wild-type littermates. Cofilin-2 (Cfl2) was identified as one of the potential targets of miR-301a using prediction databases, which we validated by luciferase assay and mutation of predicted binding sites. Furthermore, expression of miR-301a contrastingly regulated Cfl2 expression levels in neonatal rat ventricular cardiomyocytes (NRVCM). Along these lines, Cfl2 was significantly upregulated in Cs1-ko mice, indicating the physiological association between miR-301a and Cfl2 in vivo. Mechanistically, we found that Cfl2 activated serum response factor response element (SRF-RE) driven luciferase activity in neonatal rat cardiomyocytes and in C2C12 cells. Similarly, knockdown of miR301a activated, whereas, its overexpression inhibited the SRF-RE driven luciferase activity, further strengthening physiological interaction between miR-301a and Cfl2. Interestingly, the expression of SRF and its target genes was strikingly increased in Cs1-ko suggesting a possible in vivo correlation between expression levels of Cfl2/miR-301a and SRF activation, which needs to be independently validated. In summary, our data demonstrates that miR-301a regulates Cofilin-2 in vitro in NRVCM, and in vivo in Cs1-ko mice. Our findings provide an additional and important layer of Cfl2 regulation, which we believe has an extended role in cardiac signal transduction and dilated cardiomyopathy presumably due to the reported involvement of Cfl2 in these mechanisms.

Transcription factor (TF) networks regulate the lineage choice of hematopoietic stem and progenitor cells (HSPCs). Previous studies suggested a functional antagonism between the core hematopoietic TFs PU.1 and GATA1, and their autoregulation as the basis for a cell-intrinsic stochastic switch regulating PU.1 expression in lineage choice of HSPCs. Using long-term quantitative time-lapse imaging of HSCs from the PU.1eYFP/GATA1mCherry reporter mouse line, we previously showed that a random PU.1 and GATA1 switch does not initiate myeloid lineage choice. To further analyze the regulation of PU.1, we generated a novel mouse line with an inducible PU.1-ERT2 allele co-expressed with the PU.1eYFP/GATA1mCherry reporter alleles. Using single-cell reprogramming assays, microfluidics facilitated reversible PU.1 induction by TNF and single-cell quantification in response to transgenic PU.1-ERT2 activation, we quantified PU.1 expression in thousands of single HSPCs to measure the short- and long- term autoregulation dynamics. Surprisingly, we do not observe direct autoregulation of PU.1 at many different stages of hematopoietic differentiation. We find PU.1 autoregulation not to be involved in initiating differentiation, but to be an indirect consequence of it. Finally, to dissect the molecular triad of PU.1, GATA1 and GATA2 in regulating HSC lineage choice, we have generated a novel reporter mouse line for GATA2 protein and continuously quantify its expression dynamics, simultaneous with that of GATA1 in living HSPCs along the megakaryocyte-erythrocyte and granulocyte-monocyte differentiation trajectories. These data disprove several previous assumptions about the regulation of HSPC fate control, identify novel regulators, and demonstrate vacancy for other cell-extrinsic and -intrinsic players in regulating hematopoietic TFs specifically and lineage choice of HSCs in general.

The dilated cardiomyopathy (DCM) is a major cause for heart failure. A causative genetic background is suspected in up to 50% of all DCM cases. However, the underlying molecular pathways remain incompletely understood. Here we analyze a calsarcin-1 deficient (CS1ko) mouse line as a model for DCM. These mice showed strong upregulation of fetal genes (e.g., Nppa, Nppb ) and the calcineurin-dependent gene Rcan1.4. Interestingly, we could not detect any signes of hypertrophy. In addition, there was no increase of fibrosis in CS1ko mice compared to wildtype controls. A screening experiment revealed upregulation of Cofilin2 (Cfl2), an actin depolymerisation factor and member of the ADF/Cofilin family, in Cs1ko mice (2.6-fold, pNppa and Nppb , which could be further increased by co-stimulation with phenylephrine (PE). In contrast to these findings, cell size analysis revealed a Cfl2-mediated decrease in cell size with and without PE, while knockdown of Cfl2 did not influence cellular hypertrophy. Taken together, our data imply a role for Cfl2 in the pathogenesis of DCM. Cs-1ko mice show a dilated phenotype, strong upregulation of the fetal gene program without a change in cell size. This correlates with the findings of overexpression of Cfl2 in NRVCM. Furthermore, increased Cfl2 levels induce SRF activity with potential influence on cardiomyocyte function. Further analyses are required to delineate the involved molecular pathways.