Burst-suppression (BS) is a deep anesthesia pattern characterized by alternating periods of near-isoelectric suppression and high-amplitude bursts, leading to nonstationary EEG dynamics. In this regime, conventional EEG metrics become unreliable or undefined, limiting continuous physiological and pharmacodynamic modeling across anesthetic states.We introduce a continuous and interpretable representation of suppression-related EEG state transitions using Gaussian Mixture Model (GMM) decomposition of alpha-band (8-13 Hz) amplitudes.We analyzed 175 EEG recordings from Lariboisière Hospital (Paris, France) and 1418 EEG recordings from the VitalDB database. Alpha-band amplitudes were extracted from 30-second epochs and decomposed with two-component GMMs, yielding latent parameters (means, variances, weights) describing high- and low-amplitude activity and their proportions. These parameters revealed smooth transitions during burst suppression, with the lower-mean component decreasing and its proportion increasing as suppression deepened. Higher GMM means were associated with lower risk of mortality and cognitive decline, with logistic models achieving AUROCs up to 0.89 and 0.80, respectively. Dynamic Time Warping (DTW) analysis revealed significant temporal alignment between arterial blood pressure and GMM-derived latent parameters.By reconstructing the microarchitecture of the alpha band, GMM decomposition provides an interpretable characterization of brain dynamics across moderate and deep anesthesia states. These findings suggest that alpha-band envelope structure encodes physiologically meaningful information beyond conventional EEG markers and may provide a continuous observation variable for pharmacodynamic modeling of the brain during general anesthesia.

Although digital subtraction angiography (DSA) remains the reference standard for post-treatment follow-up of intracranial dural arteriovenous fistulas (DAVFs), it is an invasive procedure associated with procedural risks and may not be justified for the follow-up of all DAVFs. This study aimed to evaluate the diagnostic performance of 3D time-of-flight (3D TOF) and contrast-enhanced 3D T1-weighted gradient-echo (3D T1 Gd) magnetic resonance imaging (MRI) sequences for monitoring embolized intracranial DAVFs. In this retrospective single-center study, consecutive patients with embolized DAVFs between 2004 and 2023, who underwent MRI and arteriography during follow-up, were evaluated. 3D TOF sequence images were independently reviewed by two readers to assess treatment completeness. In cases of residual fistula, cortical venous drainage (CVD) was evaluated. Patency of the fistulous or proximal venous sinus was assessed on contrast-enhanced 3D T1-weighted GRE imaging. The median follow-up duration was 3.6 months (interquartile range [IQR], 3.0–8.4 months). Imaging findings were systematically compared with DSA as the reference standard. Seventy-six patients (mean age, 56 ± 12,8 years; 46 men) with 78 embolized DAVFs were included. The positive predictive value, negative predictive value, and diagnostic accuracy of 3D TOF sequence for the detection of residual fistulas were 79

BACKGROUND : Microcirculatory dysfunction is common in critical care, but has been primarily described in severely ill patients. While its prognostic significance is well established in septic shock, it might be associated with poor outcome in other critical conditions. The tissue-to-arterial CO₂ gradient (PatCO₂) provides a straightforward, non-invasive and dynamic approach to microcirculatory assessment, but its relevance beyond acute circulatory failure remains unclear. We aimed to determine whether the evolution of PatCO₂ over the first 48 hours predicts 28-day mortality in a broad intensive care unit (ICU) population. METHODS : This prospective, descriptive study included 94 adult patients between November 2022 and September 2023, within 24 hours of admission to a mixed surgical ICU, regardless of admission diagnosis. PatCO₂ was measured using a transcutaneous CO₂ sensor and arterial blood gas analysis at regular intervals during the first 48 hours. The primary endpoint was 28-day mortality. RESULTS : Mean age was 61±16 years, mean SOFA score at 24 hours was 5.7±4. Admission diagnoses included acute brain injury (42%), sepsis/septic shock (33%), non-septic shock (16%), and acute respiratory failure (9%). Admission PatCO₂ did not differ between survivors and non survivors (17.0±9 mmHg vs. 20.4±13 mmHg, p = 0.31). In contrast, its evolution between day 1 and day 2 (∆ (d2-d1) PatCO₂) was associated with mortality, independently from macrohemodynamics. Microcirculatory dysfunction improved in survivors (∆ (d2-d1) PatCO₂: – 4.6±8.0 mmHg), whereas it worsened in nonsurvivors (+ 3.6±14.2 mmHg, p < 0.05), with higher PatCO₂ on day 2 in nonsurvivors (23.1±18.3 mmHg vs. 12.7 ±5.4 mmHg, p < 0.05). Based on these findings, we designed a simple prognostic score—SkinScore—based on the average 48-hour and day 2 PatCO₂. SkinScore effectively stratified mortality risk and independently predicted death (AUC 0.90 [0.82–0.96]). Integrating Skinscore into SOFA significantly improved prognostic performance (AUC 0.90 [0.80–0.97] vs. 0.81 [0.68–0.91], p < 0.05). CONCLUSION : Early and dynamic microcirculatory monitoring via tissue capnometry predicts outcome in a diverse and moderately ill ICU population. Our findings indicate that many ICU patients may exhibit microperfusion abnormalities associated with prognosis, supporting broader use of this non-invasive, continuous method as a microcirculatory marker.

Monitored anesthesia care (MAC) with continuous sedation for awake craniotomy allows rapid recovery but increases risks of hypoventilation and hypoxemia. In April 2019, our center replaced propofol-based sedation with dexmedetomidine-based protocols to improve respiratory safety. We evaluated the impact of this protocol change on respiratory and hemodynamic outcomes. This single-center retrospective before-after observational study analyzed all adult patients undergoing awake craniotomy between April 2017 and July 2021. The propofol group (April 2017-March 2019) received propofol-remifentanil sedation; the dexmedetomidine group (April 2019-July 2021) received dexmedetomidine-based sedation with supplemental low-dose propofol. Primary endpoints were hypoxemia (SpO2 < 92

Introduction De nos jours, une anesthésie doit être la moins invasive possible permettant de maintenir un confort optimal pour le patient mais aussi pour le chirurgien. La sédation-analgésie procédurale (SAP), en constante évolution, repose sur des agents pharmacologiques dont le choix influence directement la sécurité et le confort du patient. La dexmédétomidine est de plus en plus utilisée lors des SAP, notamment grâce au maintien de la ventilation spontanée, mais son utilisation en France reste faible. Problématique État des lieux de l’utilisation et des connaissances de la dexmédétomidine (DXM) en France. Méthode Enquête nationale menée par questionnaire électronique diffusé sur un mois auprès de professionnels exerçant en anesthésie. Résultats Sur 1007 questionnaires analysés, seuls 13 % des répondants ne connaissaient pas la DXM et 54 % des connaisseurs déclaraient ne pas l’utiliser. Parmi les utilisateurs, la molécule est majoritairement employée dans les protocoles d’anesthésie sans opioïdes, plus rarement en SAP. Le bénéfice le plus cité est le maintien d’une ventilation spontanée. Les principaux freins sont le manque de formation et la politique des structures. Trois « super répondants », tous médecins formés et utilisateurs, ont obtenu un score complet au test de connaissances. Conclusion Cette enquête révèle une sous-utilisation de la DXM en SAP en France malgré une bonne connaissance générale de la molécule. Le rôle central de la formation par les pairs, mais aussi la nécessité d’approches pédagogiques plus structurées, apparaissent comme des leviers essentiels pour favoriser son intégration dans les pratiques.

INTRODUCTION:Modern intensive care units (ICU) and operating rooms (OR) generate vast quantities of physiological data, yet this information is often underused due to architectural barriers and lack of interoperability, a failure to integrate data from multiple devices. While imaging data has achieved global standardisation, continuous physiological time series remain fragmented and inaccessible for scientific use, limiting multicentric collaboration and the development of robust artificial intelligence (AI) models. METHODS:We developed an open, interoperable peri-operative data platform compliant with General Data Protection Regulation. The platform integrates data from multiple sources, including patient monitors, syringe pumps, ventilators, EEG systems, and laboratory values, using Apache Kafka for real-time data streaming and a hybrid long-term storage architecture. Data governance was ensured through on-premise storage, anonymisation protocols, and ethical approvals. RESULTS:Since March 2019, the platform has recorded data from 118 915 patients across 77 OR and ICU beds, encompassing waveform and numeric channels. The database includes data from various clinical specialties, such as bowel surgery, otolaryngology, neurosurgery, gynaecology, interventional neuroradiology, and orthopaedics. It encompasses cardiac output monitoring (3458 patients), ventilation data (56 212 patients), advanced ECG analysis (78 091 patients), and EEG recordings (9862 patients). Syringe pump data, collected since February 2023, includes 7096 cases. DISCUSSION:The platform demonstrates the feasibility of creating a scalable, vendor-neutral infrastructure for peri-operative data, enabling both real-time clinical applications and long-term research. By adhering to open standards, it supports secure, cross-institutional collaboration while preserving data integrity. However, challenges remain in standardising data quality and expanding data volume to improve model generalisability. CONCLUSIONS:This work provides a reproducible blueprint for building interoperable peri-operative data platforms, enabling both real-time clinical decision support and large-scale research. By combining real-time acquisition with durable storage and open standards, the platform transforms fragmented physiological data into a shared resource for precision medicine and clinical equity.

CONTEXT AND IMPORTANCE:With over 300 million surgeries performed under general anaesthesia annually, optimising perioperative brain health has become a critical public health priority. Electroencephalogram (EEG) monitoring, initially conceived to prevent awareness during anaesthesia, is now emerging as a tool for assessing cognitive vulnerability and predicting neurocognitive outcomes. OBJECTIVES:This narrative review synthesises the evolution of intraoperative EEG monitoring across three conceptual stages: from a depth-of-anaesthesia measure to a tool for optimising anaesthetic exposure, and to an emerging biomarker of brain frailty and long-term perioperative risk. KEY FINDINGS:We review the technical foundations of EEG signal analysis and the distinctive patterns produced by GABAergic anaesthetics, characterised by frontal alpha anteriorization and slow-wave oscillations. EEG-guided anaesthetic titration reduces drug consumption, accelerates recovery, and minimises environmental impact, while maintaining equivalent safety. Specific intraoperative EEG patterns, including burst suppression and diminished alpha power, are robustly associated with postoperative delirium and cognitive decline, especially in vulnerable populations. However, trials targeting these patterns have not consistently prevented delirium, revealing that baseline cognitive impairment mediates most of the risk. Age-dependent EEG changes under anaesthesia, including reduced oscillatory power and altered spectral characteristics, may serve as markers of latent brain vulnerability. CLINICAL IMPLICATIONS:Intraoperative EEG monitoring should be viewed not merely as a tool for titrating hypnotic agents, but as a window into perioperative brain health. Future integration of machine learning algorithms and longitudinal cognitive follow-up may enable EEG-based preoperative risk stratification and individualised perioperative management strategies, transforming perioperative care for cognitively vulnerable patients.

BACKGROUND:This study investigated the impact of cerebral blood flow (CBF) on electroencephalography (EEG) during general anesthesia (GA) in neuroradiology procedures and described the pressure-flow relationship during increasing and decreasing mean arterial pressure changes (mAP) challenges. METHODS:Data were collected from 63 patients (aged 45 [32-53] years, 73 % women) who had EEG, mAP, and CBF monitored during stabilized GA. CBF was approximated by the mean blood velocity in the mean cerebral artery (MCAvmean), measured by transcranial Doppler. We analyzed the alpha-delta ratio (ADR) to validate that the EEG signal under general anesthesia is influenced by CBF by demonstrating a significant association between MCAvmean changes caused by an mAP challenge and intraoperative EEG parameters. Secondary objectives include (1) an evaluation of response delays between CBF and ADR correlation; (2) characterizing the relationship between CBFv and mAP by comparing linear regression coefficients between increasing and decreasing mAP challenges. RESULTS:mAP challenges lasted for a median duration of 410[220-585] seconds. We found a significant linear relationship between MCAvmean changes and alpha-delta ratio, with the strongest association found for a time delay between 4' and 9'30 s (permutation test). Our results show directional sensitivity of the cerebral pressure-flow relationship, with asymmetric responses to positive and negative mAP challenges across the cohort (0.28 [0.12-0.37] and 0.38 [0.25-0.74] respectively, p = 0.004). CONCLUSION:The ADR appears to be a delayed marker for studying the relationship between CBF and intraoperative EEG. We observed asymmetry in the cerebral pressure-flow relationship during increasing and decreasing mAP challenges.

BACKGROUND AND PURPOSE:The optimal timing for mobilizing patients during the acute phase of ischemic stroke remains unclear. Prior research has produced conflicting results, often neglecting the impact of upstream arterial stenosis on cerebral blood flow. This study aimed to determine whether early transition to a seated position in the acute phase of ischemic stroke influences intracranial hemodynamics, particularly in patients with significant carotid stenosis. METHODS:In a prospective, bi-centric, 1:1 case-control observational study (NCT04180826), we continuously and non-invasively monitored cerebral and systemic hemodynamics during the first authorized transition from supine to a sitting position in patients with ischemic stroke of the carotid territory. Cases were defined as those with homolateral carotid stenosis >50% by NASCET criteria. The primary outcome was a >10% reduction in mean flow velocity (MFV) in the homolateral middle cerebral artery (MCA). RESULTS:Of 42 screened patients, 36 were included (19 controls, 17 cases). A significant (>10%) MFV drop occurred in 9/17 cases (53%) versus 1/19 controls (5%; p = 0.012). Notably, cases with an MFV drop showed no compensatory systemic response (no rise in blood pressure or heart rate). Multivariate analysis revealed that a shorter time from stroke onset to sitting (coefficient = -2.793, p = 0.016) and being a case (coefficient = -6.283, p = 0.004) independently predicted an MFV decrease >10%. Additional factors associated with significant MFV decline in cases included the absence of a blood pressure increase after verticalization, lower hemoglobin (p = 0.007), and higher BNP levels (p = 0.024). CONCLUSIONS:Early sitting in the acute phase of ischemic stroke is more frequently associated with marked MFV reductions in patients with carotid stenosis, potentially due to impaired systemic hemodynamic adaptation. These findings underscore the importance of individualized mobilization strategies based on vascular and systemic factors.

This proof of concept study demonstrates the capabilities of a virtually automatically generated digital twin framework for enhancing hemodynamic monitoring in critical care. By combining a deterministic cardiovascular model with patient-specific data through data assimilation techniques, the digital twin can act as a data denoiser, reconstruct physiological waveforms that are typically unavailable in critical care settings and generate clinically relevant biomarkers. Validation was performed using real data from patients under general anesthesia. The proposed framework efficient calibration and ability to follow the patient's state over time supports the possibility of real-time bedside applications.

Monitoring mean arterial pressure (MAP) is essential for ensuring safe general anesthesia. Current practices rely either on non-invasive cuff measurements, which suffer from poor temporal resolution, or invasive arterial lines, which provide excellent accuracy and resolution but carry a significant risk of complications. Therefore, identifying alternatives to arterial lines in the operating rooms is a pressing need. Despite the importance of this issue in the community, clinically viable non-invasive MAP monitoring methods have yet to emerge. Existing approaches often encounter reproducibility issues, notably on large, open-source databases, and are not always optimized for real-time predictions. To address these limitations, this study introduces AnesthNet, a deep learning architecture designed for MAP estimation, using data exclusively from non-invasive and routine sensors such as photoplethysmography, ECG, and cuff oscillometer. AnesthNet was evaluated against the best-performing state-of-the-art deep learning architectures, using international standards to assess their performance on two of the largest datasets to date: VitalDB (2,833 patients) and LaribDB (5,060 patients). AnesthNet achieved superior performances, reaching an MAE of 4.6 (± 4.7) mmHg on VitalDB and 3.8 (± 5.7) mmHg on LaribDB. Our model also outperformed other architectures for different delays in cuff values and yielded no significant latency during inference, meeting clinical real-time requirements.

This study explores the feasibility of continuous pulse wave velocity (PWV) monitoring during general anaesthesia (GA), particularly in response to blood pressure fluctuations. Our aim is to evaluate whether dynamic PWV can provide new insight to detect cardiovascular risks. From December 2022 to February 2023, continuous carotid and femoral Doppler monitoring was performed on patients scheduled for surgery with GA, to collect PWV data at awakening (PWVAW) and during GA (PWVGA). The study investigated PWV’s response to MAP fluctuations using the α-angle, a dynamic stiffness parameter. We evaluated PWV and α-angle efficacy in discriminating between low (CVR-) and high (CVR+) cardiovascular risk patients. Among 43 patients, 41 (95

BACKGROUND:Perioperative renal and myocardial protection primarily depends on preoperative prediction tools, along with intraoperative optimization of cardiac output (CO) and mean arterial pressure (MAP). We hypothesise that monitoring the intraoperative global afterload angle (GALA), a proxy of ventricular afterload derived from the velocity pressure (VP) loop, could better predict changes in postoperative biomarkers than the recommended traditional MAP and CO. METHOD:This retrospective monocentric study included patients programmed for neurosurgery with continuous VP loop monitoring. Patients with hemodynamic instability were excluded. Those presenting a 1-day post-surgery increase in creatinine, B-type natriuretic peptide, or troponin Ic us were labelled Bio+, Bio- otherwise. Demographics, intra-operative data, and comorbidities were considered as covariates. The study aimed to determine if intraoperative GALA monitoring could predict early postoperative biomarker disruption. RESULT:From November 2018 to November 2020, 86 patients were analysed (Bio+/Bio- = 47/39). Bio+ patients were significantly older (62 [54-69] vs. 42 [34-57] years, p <  0.0001), More often hypertensive (25% vs. 9%, p = 0.009), and more frequently treated with antihypertensive drugs (31.9% vs. 7.7%, p = 0.013). GALA was significantly larger in Bio+ patients (40 [31-56] vs. 23 [19-29] °, p < 0.0001), while CO, MAP, and cumulative time spent <65mmHg were similar between groups. GALA exhibited strong predictive performances for postoperative biological deterioration (AUC = 0.88 [0.80-0.95]), significantly outperforming MAP (MAP AUC = 0.55 [0.43-0.68], p < 0.0001). CONCLUSION:GALA under general anaesthesia prove more effective in detecting patients at risk of early cardiac or renal biological deterioration, compared to classical hemodynamic parameters.

Objective Pulse wave velocity (PWV), a measure of arterial stiffness, varies with mean arterial pressure (MAP). As general anesthesia (GA) causes significant variations in MAP, we proposed to study the feasibility of measuring PWV under GA and to investigate its relationship with MAP. Methods From December 2022 to February 2023, continuous carotid and femoral Doppler monitoring was performed on patients scheduled for surgery with GA, to collect PWV data at awakening (PWVAW) and during GA (PWVGA). The study investigated PWV's response to MAP fluctuations using the α-angle, a dynamic stiffness parameter. We evaluated PWV and α-angle efficacy in discriminating between low (CVR-) and high (CVR+) cardiovascular risk patients. Results Among 43 patients, 41 (95%) had successful PWV measurements. PWVAW was significantly higher than PWVGA (8.1 vs 7.4 m.s-1, p < 0.0001). This difference vanished after matching MAP levels. A strong correlation was found between PWVAW and PWVGA (r = 0.88, and r = 0.97 at the same MAP levels). PWVGA, α-angle and their product (α x PWVGA) were significantly higher in CVR + patients (8.1 vs 6.9 m.s-1, p < 0.01; 2.6 vs 1.3 degrees, p < 0.001; 21.8 vs 8.1 degrees.m.s-1, p < 0.001, respectively), with AUC values indicating good predictive capabilities for cardiovascular risk (PWVGA: AUC [95%CI] = 0.80 [0.65–0.95]; α-angle: 0.83 [0.69–0.96]; product: 0.86 [0.74–0.97]). Conclusion Measuring PWV using carotid and femoral Doppler under GA is viable and can discriminate between varying levels of cardiovascular risk. The α-angle offers a promising approach to refining the assessment of arterial stiffness.

Aims Intraoperative hypotension is a risk factor for kidney, heart and cognitive postoperative complications. Literature suggests that the use of low‐dose peripheral norepinephrine (NOR) reduces organ dysfunction, yet its administration remains unstandardized. In this work we develop a pharmacokinetic (PK)/pharmacodynamic (PD) model of NOR and its effect on mean arterial pressure (MAP). Methods From June 2018 to December 2021, we included patients scheduled for elective neurosurgery and requiring vasopressors for intraoperative hypotension management at Lariboisière Hospital, Paris. Low doses of NOR were administered peripherally, and successive arterial blood samples were collected to track its plasmatic concentration. We used a compartmental modelling approach for NOR PK. We developed and compared 2 models for NOR PD on MAP. Model comparison was done using Bayes information criteria. The resulting PK/PD model parameters were fitted over the entire population and linked to age, weight, height and sex. Results We included 29 patients (age 52 [46–64] years, 69% female). NOR median time to peak effect on MAP was 74 [53–94] s. After bolus administration, MAP increased by 24% (15–31%). A 2‐comparment model with depot best captured NOR PK. NOR PD effect on MAP was well represented by both Emax and Windkessel models, with better results for the former. We found that age, height and weight as well as history of smoking and hypertension were correlated with model parameters. Conclusion We have developed a PK/PD model to accurately track norepinephrine plasma concentration and its effect on MAP over time, which could serve for target‐controlled infusion.

BACKGROUND:Due to their invasiveness, arterial lines are not typically used in routine monitoring, despite their superior responsiveness in hemodynamic monitoring and detecting intraoperative hypotension. To address this issue, noninvasive, continuous arterial pressure monitoring is necessary. We developed a deep-learning model that reconstructs continuous mean arterial pressure (MAP) using the photoplethysmograhy (PPG) signal and compared it to the arterial line gold standard. METHODS:We analyzed high-frequency PPG signals from 117 patients in neuroradiology and digestive surgery with a median of 2201 (interquartile range [IQR], 788-4775) measurements per patient. We compared models with different combinations of convolutional and recurrent layers using as inputs for our neural network high-frequency PPG and derived features including dicrotic notch relative amplitude, perfusion index, and heart rate. Mean absolute error (MAE) was used as performance metrics. Explainability of the deep-learning model was reconstructed with Grad-CAM, a visualization technique using saliency maps to highlight the parts of an input that are significant for a deep-learning model decision-making process. RESULTS:An MAP baseline model, which consisted only of standard cuff measures, reached an MAE of 6.1 (± 14.5) mm Hg. In contrast, the deep-learning model achieved an MAE of 3.5 (± 4.4) mm Hg on the external test set (a 42.6% improvement). This model also achieved the narrowest confidence intervals and met international standards used within the community (grade A). The saliency map revealed that the deep-learning model primarily extracts information near the dicrotic notch region. CONCLUSIONS:Our deep-learning model noninvasively estimates arterial pressure with high accuracy. This model may show potential as a decision-support tool in operating-room settings, particularly in scenarios where invasive blood pressure monitoring is unavailable.

Editor—Reusable flexible bronchoscopes have historically been used for difficult tracheal intubation in the operating theatre, but the use of single-use bronchoscopes is on the rise. Single-use bronchoscopes are assumed to reduce the risks of cross-contamination 1 Terjesen C.L. Kovaleva J. Ehlers L. Early assessment of the likely cost effectiveness of single-use flexible video bronchoscopes. Pharmacoecon Open. 2017; 1: 133-141 Crossref PubMed Scopus (26) Google Scholar and reduce hospital costs. 2 Mouritsen J.M. Ehlers L. Kovaleva J. Ahmad I. El-Boghdadly K. A systematic review and cost effectiveness analysis of reusable vs. single-use flexible bronchoscopes. Anaesthesia. 2020; 75: 529-540 Crossref PubMed Scopus (46) Google Scholar However, their technical reliability for difficult tracheal intubation compared with reusable devices is unclear. 3 Fukada T. Tsuchiya Y. Iwakiri H. Ozaki M. Is the Ambu aScope 3 Slim single-use fiberscope equally efficient compared with a conventional bronchoscope for management of the difficult airway?. J Clin Anesth. 2016; 30: 68-73 Crossref PubMed Scopus (9) Google Scholar ,4 Krugel V. Bathory I. Frascarolo P. Schoettker P. Comparison of the single-use Ambu® aScope™ 2 vs the conventional fibrescope for tracheal intubation in patients with cervical spine immobilisation by a semirigid collar: single-use Ambu® aScope™ 2 vs the conventional fibrescope. Anaesthesia. 2013; 68: 21-26 Crossref PubMed Scopus (25) Google Scholar Moreover, an economic advantage largely depends on the type and number of procedures performed per year as well as study-site specificities. 5 McCahon R.A. Whynes D.K. Cost comparison of re-usable and single-use fibrescopes in a large English teaching hospital. Anaesthesia. 2015; 70: 699-706 Crossref PubMed Scopus (29) Google Scholar ,6 Châteauvieux C. Farah L. Guérot E. et al. Single-use flexible bronchoscopes compared with reusable bronchoscopes: positive organizational impact but a costly solution. J Eval Clin Pract. 2018; 24: 528-535 Crossref PubMed Scopus (23) Google Scholar Finally, the potential environmental consequences of this transition have not been sufficiently assessed. This study marks the first attempt to compare the use of single-use and reusable flexible bronchoscopes for difficult tracheal intubation with a holistic approach, encompassing environmental, economic, and clinician satisfaction assessments.