Reverse Triggering Research Articles

Does patient-ventilator asynchrony really matter?

Past observational studies have reported the association between patient-ventilator asynchronies and poor clinical outcomes, namely longer duration of mechanical ventilation and higher mortality. But causality has remained undetermined. During the era of lung and diaphragm protective ventilation, should we revolutionize our clinical practice to detect and treat dyssynchrony? Clinicians' ability to recognize asynchronies is typically low. Automatized softwares based on artificial intelligence have been trained to largely outperform human eyesight and are close to be implemented at the bedside. There is growing evidence that in susceptible patients, dyssynchrony may lead to ventilation-induced lung injury (or patient self-inflicted lung injury) and that clusters of such dyssynchronous events have the highest association with poor outcomes. Dyssynchrony may also be associated with harm indirectly when it reflects over-assistance or over-sedation. However, the occurrence of reverse triggering by means of low inspiratory efforts during passive ventilation may prevent diaphragm dysfunction and atrophy and be beneficial. Most recent evidence on the topic suggests that synchrony between the patient and the mechanical ventilator is a critical element for protecting lung and diaphragm during the time of invasive mechanical ventilation or may reflect inadequate settings or sedation. Therefore, it is a complex situation, and clinical trials are still needed to test the effectiveness of keeping patient-ventilator interaction synchronous on clinical outcomes.

Post-insufflation diaphragm contractions in patients receiving various modes of mechanical ventilation

BackgroundDuring mechanical ventilation, post-insufflation diaphragm contractions (PIDCs) are non-physiologic and could be injurious. PIDCs could be frequent during reverse-triggering, where diaphragm contractions follow the ventilator rhythm. Whether PIDCs happens with different modes of assisted ventilation is unknown. In mechanically ventilated patients with hypoxemic respiratory failure, we aimed to examine whether PIDCs are associated with ventilator settings, patients’ characteristics or both.MethodsOne-hour recordings of diaphragm electromyography (EAdi), airway pressure and flow were collected once per day for up to five days from intubation until full recovery of diaphragm activity or death. Each breath was classified as mandatory (without-reverse-triggering), reverse-triggering, or patient triggered. Reverse triggering was further subclassified according to EAdi timing relative to ventilator cycle or reverse triggering leading to breath-stacking. EAdi timing (onset, offset), peak and neural inspiratory time (Tineuro) were measured breath-by-breath and compared to the ventilator expiratory time. A multivariable logistic regression model was used to investigate factors independently associated with PIDCs, including EAdi timing, amplitude, Tineuro, ventilator settings and APACHE II.ResultsForty-seven patients (median[25%-75%IQR] age: 63[52–77] years, BMI: 24.9[22.9–33.7] kg/m2, 49% male, APACHE II: 21[19–28]) contributed 2 ± 1 recordings each, totaling 183,962 breaths. PIDCs occurred in 74% of reverse-triggering, 27% of pressure support breaths, 21% of assist-control breaths, 5% of Neurally Adjusted Ventilatory Assist (NAVA) breaths. PIDCs were associated with higher EAdi peak (odds ratio [OR][95%CI] 1.01[1.01;1.01], longer Tineuro (OR 37.59[34.50;40.98]), shorter ventilator inspiratory time (OR 0.27[0.24;0.30]), high peak inspiratory flow (OR 0.22[0.20;0.26]), and small tidal volumes (OR 0.31[0.25;0.37]) (all P ≤ 0.008). NAVA was associated with absence of PIDCs (OR 0.03[0.02;0.03]; P < 0.001). Reverse triggering was characterized by lower EAdi peak than breaths triggered under pressure support and associated with small tidal volume and shorter set inspiratory time than breaths triggered under assist-control (all P < 0.05). Reverse triggering leading to breath stacking was characterized by higher peak EAdi and longer Tineuro and associated with small tidal volumes compared to all other reverse-triggering phenotypes (all P < 0.05).ConclusionsIn critically ill mechanically ventilated patients, PIDCs and reverse triggering phenotypes were associated with potentially modifiable factors, including ventilator settings. Proportional modes like NAVA represent a solution abolishing PIDCs.

Patient-ventilator asynchrony classification in mechanically ventilated patients: Model-based or machine learning method?

Background and objectivePatient-ventilator asynchrony (PVA) is associated with poor clinical outcomes and remains under-monitored. Automated PVA detection would enable complete monitoring standard observational methods do not allow. While model-based and machine learning PVA approaches exist, they have variable performance and can miss specific PVA events. This study compares a model and rule-based algorithm with a machine learning PVA method by retrospectively validating both methods using an independent patient cohort. MethodsHysteresis loop analysis (HLA) which is a rule-based method (RBM) and a tri-input convolutional neural network (TCNN) machine learning model are used to classify 7 different types of PVA, including: 1) flow asynchrony; 2) reverse triggering; 3) premature cycling; 4) double triggering; 5) delayed cycling; 6) ineffective efforts; and 7) auto triggering. Class activation mapping (CAM) heatmaps visualise sections of respiratory waveforms the TCNN model uses for decision making, improving result interpretability. Both PVA classification methods were used to classify incidence in an independent retrospective clinical cohort of 11 mechanically ventilated patients for validation and performance comparison. ResultsSelf-validation with the training dataset shows overall better HLA performance (accuracy, sensitivity, specificity: 97.5 %, 96.6 %, 98.1 %) compared to the TCNN model (accuracy, sensitivity, specificity: 89.5 %, 98.3 %, 83.9 %). In this study, the TCNN model demonstrates higher sensitivity in detecting PVA, but HLA was better at identifying non-PVA breathing cycles due to its rule-based nature. While the overall AI identified by both classification methods are very similar, the intra-patient distribution of each PVA type varies between HLA and TCNN. ConclusionThe collective findings underscore the efficacy of both HLA and TCNN in PVA detection, indicating the potential for real-time continuous monitoring of PVA. While ML methods such as TCNN demonstrate good PVA identification performance, it is essential to ensure optimal model architecture and diversity in training data before widespread uptake as standard care. Moving forward, further validation and adoption of RBM methods, such as HLA, offers an effective approach to PVA detection while providing clear distinction into the underlying patterns of PVA, better aligning with clinical needs for transparency, explicability, adaptability and reliability of these emerging tools for clinical care.

Application of a cloud platform that identifies patient-ventilator asynchrony and enables continuous monitoring of mechanical ventilation in intensive care unit

BackgroundPatient-ventilator asynchrony (PVA) frequently occurs in mechanically ventilated patients within the ICU and has the potential for harm. Depending solely on the health care team cannot accurately and promptly identify PVA. To address this issue, our team has developed a cloud-based platform for monitoring mechanical ventilation (MV), comprising the PVA-RemoteMonitor system and the 24-h MV analysis report. We conducted a survey to evaluate physicians' satisfaction and acceptance of the platform in 14 ICUs. MethodsData from medical records, clinical information systems, and ventilators were uploaded to the cloud platform and underwent data processing. The data were analyzed to monitor PVA and displayed in the front-end. The 24-h analysis report for MV was generated for clinical reference. Critical care physicians in 14 hospitals' ICUs that involved in the platform participated in a questionnaire survey, among whom 10 physicians were interviewed to investigate physicians’ acceptance and opinions of this system. ResultsThe PVA-RemoteMonitor system exhibited a high level of specificity in detecting flow insufficiency, premature cycle, delayed cycle, reverse trigger, auto trigger, and overshoot, with sensitivities of 90.31 %, 98.76 %, 99.75 %, 99.97 %, 100 %, and 99.69 %, respectively. The 24-h analysis report supplied essential data about PVA and respiratory mechanics. 86.2 % (75/87) of physicians supported the application of this platform. ConclusionsThe PVA-RemoteMonitor system accurately identified PVA, and the MV analysis report provided guidance in controlling PVA. Our platform can effectively assist ICU physicians in the management of ventilated patients.

Reverse triggering ? a novel or previously missed phenomenon?

Reverse triggering (RT) was described in 2013 as a form of patient-ventilator asynchrony, where patient's respiratory effort follows mechanical insufflation. Diagnosis requires esophageal pressure (Pes) or diaphragmatic electrical activity (EAdi), but RT can also be diagnosed using standard ventilator waveforms. We wondered (1) how frequently RT would be present but undetected in the figures from literature, especially before 2013; (2) whether it would be more prevalent in the era of small tidal volumes after 2000. We searched PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials, from 1950 to 2017, with key words related to asynchrony to identify papers with figures including ventilator waveforms expected to display RT if present. Experts labelled waveforms. 'Definite' RT was identified when Pes or EAdi were in the tracing, and 'possible' RT when only flow and pressure waveforms were present. Expert assessment was compared to the author's descriptions of waveforms. We found 65 appropriate papers published from 1977 to now, containing 181 ventilator waveforms. 21 cases of 'possible' RT and 25 cases of 'definite' RT were identified by the experts. 18.8% of waveforms prior to 2013 had evidence of RT. Most cases were published after 2000 (1 before vs. 45 after, p = 0.03). 54% of RT cases were attributed to different phenomena. A few cases of identified RT were already described prior to 2013 using different terminology (earliest in 1997). While RT cases attributed to different phenomena decreased after 2013, 60% of 'possible' RT remained missed. RT has been present in the literature as early as 1997, but most cases were found after the introduction of low tidal volume ventilation in 2000. Following 2013, the number of undetected cases decreased, but RT are still commonly missed. Reverse Triggering, A Missed Phenomenon in the Literature. Critical Care Canada Forum 2019 Abstracts. Can J Anesth/J Can Anesth67 (Suppl 1), 1-162 (2020). https://doi-org.myaccess.library.utoronto.ca/ https://doi.org/10.1007/s12630-019-01552-z .

ECMO for drug-refractory electrical storm without a reversible trigger: a retrospective multicentric observational study.

Drug-refractory electrical storm (ES) is a life-threatening medical emergency. We describe the use of venoarterial extracorporeal membrane oxygenation (VA-ECMO) in drug-refractory ES without a reversible trigger, for which specific guideline recommendations are still lacking. Retrospective observational study in four Iberian centres on the indications, treatment, complications, and outcome of drug-refractory ES not associated with acute coronary syndromes, decompensated heart failure, drug toxicity, electrolyte disturbances, endocrine emergencies, concomitant acute illness with fever, or poor compliance with anti-arrhythmic drugs, requiring VA-ECMO for circulatory support. Thirty-four (6%) out of 552 patients with VA-ECMO for cardiogenic shock were included [71% men; 57 (44-62) years], 65% underwent cardiopulmonary resuscitation before VA-ECMO implantation, and 26% during cannulation. Left ventricular unloading during VA-ECMO was used in 8 (24%) patients: 3 (9%) with intraaortic balloon pump, 3 (9%) with LV vent, and 2 (6%) with Impella. Thirty (88%) had structural heart disease and 8 (24%) had an implantable cardioverter-defibrillator. The drug-refractory ES was mostly due to monomorphic ventricular tachycardia (VT) and ventricular fibrillation (VF) (59%), isolated monomorphic VT (26%), polymorphic VT (9%), or VF (6%). Thirty-one (91%) required deep sedation, 44% overdrive pacing, 36% catheter ablation, and 26% acute autonomic modulation. The main complications were nosocomial infection (47%), bleeding (24%), and limb ischaemia (21%). Eighteen (53%) were weaned from VA-ECMO, and 29% had heart transplantation. Twenty-seven (79%) survived to hospital discharge (48 (33-82) days). Non-survivors were older [62 (58-67) vs. 54 (43-58); P<0.01] and had a higher first rhythm disorder-to-ECMO interval [0 (0-2) vs. 2 (1-11) days; P=0.02]. Seven (20%) had rehospitalization during follow-up [29 (12-48) months], with ES recurrence in 6%. VA-ECMO bridged drug-refractory ES without a reversible trigger with a high success rate. This required prolonged hospital stays and coordination between the ECMO centre, the electrophysiology laboratory, and the heart transplant programme.

Respiratory entrainment related reverse triggering in mechanically ventilated children

BackgroundThe underlying pathophysiological pathways how reverse triggering is being caused are not fully understood. Respiratory entrainment may be one of these mechanisms, but both terms are used interchangeably. We sought to characterize reverse triggering and the relationship with respiratory entrainment among mechanically ventilated children with and without acute lung injury.MethodsWe performed a secondary phyiology analysis of two previously published data sets of invasively mechanically ventilated children < 18 years with and without lung injury mechanically ventilated in a continuous or intermittent mandatory ventilation mode. Ventilator waveforms, electrical activity of the diaphragm measured with surface electromyography and oesophageal tracings were analyzed for entrained and non-entrained reverse triggered breaths.ResultsIn total 102 measurements (3110 min) from 67 patients (median age 4.9 [1.8 ; 19,1] months) were analyzed. Entrained RT was identified in 12 (12%) and non-entrained RT in 39 (38%) recordings. Breathing variability for entrained RT breaths was lower compared to non-entrained RT breaths. We did not observe breath stacking during entrained RT. Double triggering often occurred during non-entrained RT and led to an increased tidal volume. Patients with respiratory entrainment related RT had a shorter duration of MV and length of PICU stay.ConclusionsReverse triggering is not one entity but a clinical spectrum with different mechanisms and consequences.Trial registrationNot applicable.

Pendelluft in patients with acute respiratory distress syndrome during trigger and reverse triggering breaths

Pendelluft, the shift of air from non-dependent to dependent lung regions, is known to occur during active breathing in ventilated patients. However, information about pendelluft in ARDS patients under assisted mechanical ventilation is limited. In this prospectively collected and retrospectively analyzed study, we combined electrical impedance tomography and respiratory mechanics monitoring to quantitatively examine pendelluft in trigger and reverse triggering breaths in 20 mechanically ventilated patients with ARDS during the transition from controlled to active breaths under volume-cycled ventilation. Besides the 10 resting breaths in each patient, 20% of the counted active breaths were selected based on three levels of esophageal pressure swing (∆Pes): low (< 5 cm H2O, breaths = 471), moderate (≥ 5, < 10 cm H2O, breaths = 906), and high effort (≥ 10 cm H2O, breaths = 565). The pendelluft response to breathing efforts was significantly greater in trigger breaths than in reverse triggering breaths (p < 0.0001). Based on the pendelluft-∆Pes slope (ml/cmH2O), there were two distinct patterns of effort-related pendelluft (high vs. low pendelluft group). For trigger breaths, the high pendelluft group (n = 9, slope 0.7–2.4 ml/cmH2O) was significantly associated with lower peak airway/plateau pressure and lower respiratory system/lung elastance than the low pendelluft group (n = 11, slope − 0.1 to 0.3 ml/cmH2O). However, there was no difference in respiratory mechanics between high and low pendelluft groups for reverse triggering breathes. The use of ∆Pes to predict pendelluft was found to have a low positive predictive value.

A novel application of spectrograms with machine learning can detect patient ventilator dyssynchrony

Patients in intensive care units are frequently supported by mechanical ventilation. There is increasing awareness of patient-ventilator dyssynchrony (PVD), a mismatch between patient respiratory effort and assistance provided by the ventilator, as a risk factor for infection, narcotic exposure, lung injury, and adverse neurocognitive effects. One of the most injurious consequences of PVD are double cycled (DC) breaths when two breaths are delivered by the ventilator instead of one. Prior efforts to identify PVD have limited efficacy. An automated method to identify PVD, independent of clinician expertise, acumen, or time, would potentially permit early, targeted treatment to avoid further harm. We performed secondary analyses of data from a clinical trial of children with acute respiratory distress syndrome. Waveforms of ventilator flow, airway pressure and esophageal manometry were annotated to identify DC breaths and underlying PVD subtypes. Spectrograms were generated from those waveforms to train Convolutional Neural Network (CNN) models in detecting DC and underlying PVD subtypes: Reverse Trigger (RT) and Inadequate Support (IS). The DC breath detection model yielded AUROC of 0.980, while the multi-target detection model for underlying dyssynchrony yielded AUROC of 0.980 (RT) and 0.976 (IS). When operating at 75% sensitivity, DC breath detection had a number needed to alert (NNA) 1.3 (99% specificity), while underlying PVD had a NNA 1.6 (98.5% specificity) for RT and NNA 4.0 (98.2% specificity) for IS. CNNs using spectrograms of ventilator waveforms can identify DC breaths and detect the underlying PVD for targeted clinical interventions.

Asynchrony Injures Lung and Diaphragm in Acute Respiratory Distress Syndrome.

Patient-ventilator asynchrony is often observed during mechanical ventilation and is associated with higher mortality. We hypothesized that patient-ventilator asynchrony causes lung and diaphragm injury and dysfunction. Prospective randomized animal study. University research laboratory. Eighteen New Zealand White rabbits. Acute respiratory distress syndrome (ARDS) model was established by depleting surfactants. Each group (assist control, breath stacking, and reverse triggering) was simulated by phrenic nerve stimulation. The effects of each group on lung function, lung injury (wet-to-dry lung weight ratio, total protein, and interleukin-6 in bronchoalveolar lavage), diaphragm function (diaphragm force generation curve), and diaphragm injury (cross-sectional area of diaphragm muscle fibers, histology) were measured. Diaphragm RNA sequencing was performed using breath stacking and assist control (n = 2 each). Inspiratory effort generated by phrenic nerve stimulation was small and similar among groups (esophageal pressure swing ≈ -2.5 cm H2O). Breath stacking resulted in the largest tidal volume (>10 mL/kg) and highest inspiratory transpulmonary pressure, leading to worse oxygenation, worse lung compliance, and lung injury. Reverse triggering did not cause lung injury. No asynchrony events were observed in assist control, whereas eccentric contractions occurred in breath stacking and reverse triggering, but more frequently in breath stacking. Breath stacking and reverse triggering significantly reduced diaphragm force generation. Diaphragmatic histology revealed that the area fraction of abnormal muscle was ×2.5 higher in breath stacking (vs assist control) and ×2.1 higher in reverse triggering (vs assist control). Diaphragm RNA sequencing analysis revealed that genes associated with muscle differentiation and contraction were suppressed, whereas cytokine- and chemokine-mediated proinflammatory responses were activated in breath stacking versus assist control. Breath stacking caused lung and diaphragm injury, whereas reverse triggering caused diaphragm injury. Thus, careful monitoring and management of patient-ventilator asynchrony may be important to minimize lung and diaphragm injury from spontaneous breathing in ARDS.

Eccentric Contractions of the Diaphragm During Mechanical Ventilation.

Diaphragm dysfunction is a highly prevalent phenomenon in patients receiving mechanical ventilation, mainly due to ventilatory over-assistance and the development of diaphragm disuse atrophy. Promoting diaphragm activation whenever possible and facilitating an adequate interaction between the patient and the ventilator is encouraged at the bedside to avoid myotrauma and further lung injury. Eccentric contractions of the diaphragm are defined as muscle activation while muscle fibers are lengthening within the exhalation phase. There is recent evidence that suggests that eccentric activation of the diaphragm is very frequent and may occur during post-inspiratory activity or under different types of patient-ventilator asynchronies, which include ineffective efforts, premature cycling, and reverse triggering. The consequences of this eccentric contraction of the diaphragm may have opposite effects, depending on the level of breathing effort. For instance, during high or excessive effort, eccentric contractions can result in diaphragm dysfunction and injured muscle fibers. Conversely, when eccentric contractions of the diaphragm occur along with low breathing effort, a preserved diaphragm function, better oxygenation, and more aerated lung tissue are observed. Despite this controversial evidence, evaluating the level of breathing effort at the bedside seems crucial and is highly recommended to optimize ventilatory therapy. The impact of eccentric contractions of the diaphragm on the patient's outcome remains to be elucidated.

Evolution and triggers of defibrillator shocks in patients with arrhythmogenic right ventricular cardiomyopathy

IntroductionImplantable cardioverter-defibrillators (ICDs) can prevent sudden cardiac death due to ventricular arrhythmias in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC). The aim of our study was to assess the cumulative...

Reverse Triggering during Controlled Ventilation: From Physiology to Clinical Management.

Reverse triggering dyssynchrony is a frequent phenomenon recently recognized in sedated critically ill patients under controlled ventilation. It occurs in at least 30-55% of these patients and often occurs in the transition from fully passive to assisted mechanical ventilation. During reverse triggering, patient inspiratory efforts start after the passive insufflation by mechanical breaths. The most often referred mechanism is the entrainment of the patient's intrinsic respiratory rhythm from the brainstem respiratory centers to periodic mechanical insufflations from the ventilator. However, reverse triggering might also occur because of local reflexes without involving the respiratory rhythm generator in the brainstem. Reverse triggering is observed during the acute phase of the disease, when patients may be susceptible to potential deleterious consequences of injurious or asynchronous efforts. Diagnosing reverse triggering might be challenging and can easily be missed. Inspection of ventilator waveforms or more sophisticated methods, such as the electrical activity of the diaphragm or esophageal pressure, can be used for diagnosis. The occurrence of reverse triggering might have clinical consequences. On the basis of physiological data, reverse triggering might be beneficial or injurious for the diaphragm and the lung, depending on the magnitude of the inspiratory effort. Reverse triggering can cause breath-stacking and loss of protective lung ventilation when triggering a second cycle. Little is known about how to manage patients with reverse triggering; however, available evidence can guide management on the basis of physiological principles.

Reverse triggering neural network and rules-based automated detection in acute respiratory distress syndrome.

PurposeDyssynchrony may cause lung injury and is associated with worse outcomes in mechanically ventilated patients. Reverse triggering (RT) is a common type of dyssynchrony presenting with several phenotypes which may directly cause lung injury and be difficult to identify. Due to these challenges, automated software to assist in identification is needed. Materials and methodsThis was a prospective observational study using a training set of 15 patients and a validation dataset of 13 patients. RT events were manually identified and compared with “rules-based” programs (with and without esophageal manometry and reverse triggering with breath stacking), and were used to train a neural network artificial intelligence (AI) program. RT phenotypes were identified using previously defined rules. Performance of the programs was compared via sensitivity, specificity, positive predictive value (PPV) and F1 score. Results33,244 breaths were manually analyzed, with 8718 manually identified as reverse-triggers. The rules-based and AI programs yielded excellent specificity (>95% in all programs) and F1 score (>75% in all programs). RT with breath stacking (24.4%) and mid-cycle RT (37.8%) were the most common phenotypes. ConclusionsAutomated detection of RT demonstrated good performance, with the potential application of these programs for research and clinical care.

Use of ultrasonography of the diaphragm as a reverse trigger detection method

Use of ultrasonography of the diaphragm as a reverse trigger detection method

Reverse triggering

Reverse triggering

Four-Dimensional Computed Tomography of Paradoxical Motion of Eventrated Diaphragm Induced by Reverse Triggering.

Four-Dimensional Computed Tomography of Paradoxical Motion of Eventrated Diaphragm Induced by Reverse Triggering.

Reverse Triggering: An Introduction to Diagnosis, Management, and Pharmacologic Implications.

Reverse triggering is an underdiagnosed form of patient-ventilator asynchrony in which a passive ventilator-delivered breath triggers a neural response resulting in involuntary patient effort and diaphragmatic contraction. Reverse triggering may significantly impact patient outcomes, and the unique physiology underscores critical potential implications for drug-device-patient interactions. The purpose of this review is to summarize what is known of reverse triggering and its pharmacotherapeutic consequences, with a particular focus on describing reported cases, physiology, historical context, epidemiology, and management. The PubMed database was searched for publications that reported patients presenting with reverse triggering. The current body of evidence suggests that deep sedation may predispose patients to episodes of reverse triggering; as such, providers may consider decreasing sedation or modifying ventilator settings in patients exhibiting ventilator asynchrony as an initial measure. Increased clinician awareness and research focus are necessary to understand appropriate management of reverse triggering and its association with patient outcomes.

Identifying asynchronies: Reverse trigger

A variety of asynchronies between the patient’s respiratory efforts and the programed ventilatory settings have been categorized. Reverse trigger is described as an inspiratory effort occurring after a ventilator-initiated breath and may represent a form of respiratory entrainment. In other words, the ventilator triggers muscular efforts. It often appears in a repetitive, stereotyped pattern. It occurs often in mechanically ventilated patients at risk of injury, might be underrecognized at the bedside and may has adverse effects on oxygenation and ventilation, as well as potentially increasing lung injury. We can phenotype these events using the Campbell diagram (pressure–volume loop) by differentiating their occurrence during inspiration and expiration. Reverse trigger with sufficient inspiratory effort and duration can result in an additional ventilator-delivered stacked breath, which can cause large tidal volumes and increased transpulmonary pressure. Keywords: Asynchrony, ventilator, reverse trigger, entrainment, lung injury, phenotype.

Metformin does not prevent the alteration of reticulum-mitochondria Ca2+ coupling and the progression towards early diabetic cardiomyopathy with HFpEF in a diet-induced mouse model of T2D

Diabetic cardiomyopathy, as a major complication of type 2 diabetes (T2D), shows a rising prevalence nowadays. Reticulum-mitochondria Ca2+ uncoupling was recently reported as an early but reversible trigger of cardiac dysfunction using a diet-induced murine model of DCM with heart failure and preserved ejection fraction (HFpEF). Metformin is the first-line treatment prescribed to treat T2D patients, with known protective effects against myocardial infarction. We here aimed to determine if metformin could hinder the alteration of the reticulum-mitochondria Ca2+ coupling and the cardiac dysfunction induced by a high-fat high-sucrose diet (HFHSD) in mice. Mice were either fed a HFHSD or a standard diet for 16 weeks. During the last 6 weeks of diet, HFHSD mice received a daily oral gavage with either metformin or vehicle. Reticulum-mitochondria Ca2+ coupling was assessed: 1) structrally by proximity ligation assay between IP3R and VDAC; and 2) functionally by Ca2+ imaging of the mitochondrial Ca2+ sensor, 4mtD3cpv, expressed by intramyocardial adenoviral injection. Echocardiography was perfomed on lightly anesthetized animals to assess systolic function and hypertrophy. Metformin rescued the glucose tolerance and insulinemia in HFHSD mice, but partially for the cardiac insulin resistance. However, in the HFHSD cardiomyocyte, metformin did not preclude the reduction of the proximity between IP3R and VDAC, and of the histamine-driven reticulum-mitochondria Ca2+ transfer through the IP3R-VDAC complex. Echocardiography also revealed no prevention of HFHSD-induced cardiac hypertrophy and strain rate reduction. Our data report that 6 weeks of metformin treatment did not preserve the reticulum-mitochondria Ca2+ coupling in the diabetic heart and did not prevent the progression towards early DCM with HFpEF.