Search Results (139)

Background: Electroencephalography (EEG) signals are widely used for monitoring anesthesia depth during surgery. Current commercial indicators are largely closed-source and may reflect dynamic changes with some delay. Methods: This study proposes a multitask deep learning model for continuous Bispectral Index (BIS) estimation, binary anesthesia-state classification, and prediction of transitions toward light anesthesia at different time intervals. Dual-channel EEG signals from 5471 surgical cases in the VitalDB dataset were divided into 60 s windows. Short-Time Fourier Transform (STFT) captured instantaneous frequency changes to transform the signal into a two-dimensional map. A ResNet-SE architecture incorporating Squeeze-and-Excitation blocks was used to identify EEG features associated with anesthesia depth. Results: A Mean Absolute Error of 3.27 and a Root Mean Square Error of 5.48 were obtained in anesthesia depth estimation. Light anesthesia classification achieved an AUC of 0.99 on the internal test set. Conclusions: The proposed multitask model enables the assessment of anesthesia depth and transitions toward light anesthesia using EEG signals. Full article

Considerable efforts have been devoted to accurately monitoring the depth of anesthesia to ensure patient safety during surgery. Traditional approaches typically rely on electroencephalogram (EEG)-based indices, such as the Bispectral Index (BIS), which require specialized equipment. In contrast, electrocardiogram (ECG) signals are widely available in clinical settings and can be conveniently acquired via wearable devices, while also exhibiting strong responsiveness to anesthetic agents. Inspired by biomimetic physiological regulation mechanisms, this study proposes a wearable-compatible ECG-based framework for depth-of-anesthesia detection that leverages autonomic nervous system characteristics and a knowledge graph-enhanced graph convolutional network (GCN). ECG recordings from 110 patients were preprocessed, and 20 anesthesia-related features were extracted, spanning morphological, statistical, spectral, heart rate variability (HRV), and entropy-based descriptors; feature selection methods identified 13 discriminative features. A patient-level knowledge graph was first constructed using the 88 training patients (1760 nodes), and test patient nodes were incorporated only after training was complete for inductive inference. Experimental results demonstrate that the proposed deep knowledge GCN achieves a test accuracy of 98.18% in distinguishing between awake and deep sleep anesthesia states, indicating that biomimetic, wearable-compatible ECG analysis combined with knowledge graph learning holds strong potential as a cost-effective alternative to traditional EEG-based anesthesia monitoring systems. Full article

Background/Objectives: Sedation is a fundamental component of gastrointestinal endoscopy, improving patient comfort, procedural quality, and overall satisfaction. However, traditional drug-centered sedation models are increasingly challenged by rising procedural volumes, aging populations, and limited anesthesiology resources. The aim of this narrative review is to provide an integrated overview of evolving pharmacological agents, monitoring strategies, organizational models, and future directions toward personalized, technology-supported sedation pathways. Methods: A structured literature search was conducted across PubMed/MEDLINE, Scopus, and Web of Science for studies published between January 2010 and December 2025. Relevant guidelines, randomized controlled trials, meta-analyses, and large observational studies were included. Evidence was synthesized qualitatively, emphasizing clinical applicability and real-world relevance. Results: Propofol remains the most widely used sedative agent due to its rapid onset and recovery profile, although its narrow therapeutic window and lack of antagonist limit its safety in high-risk patients. Emerging agents such as remimazolam and ciprofol demonstrate comparable efficacy with improved respiratory and hemodynamic safety profiles, particularly in elderly populations. Adjunctive strategies, including procedure-specific approaches such as spinal anesthesia, may further optimize sedation. Advanced monitoring tools, such as capnography, bispectral index, and high-flow nasal cannula, show potential in enhancing safety, especially in selected high-risk groups. Structured training programs and standardized discharge criteria are essential for ensuring quality and safety. Conclusions: Sedation in gastrointestinal endoscopy is transitioning from a standardized, drug-centered approach to a personalized, risk-adapted, and technology-supported model. Integration of novel pharmacological agents, advanced monitoring, and structured training will be key to improving patient safety, procedural efficiency, and healthcare sustainability. Full article

Objectives: Oocyte pick-up (OPU) is commonly performed under propofol-based sedation during in vitro fertilization (IVF). However, considerable interindividual variability in propofol requirement has been observed. Controlled ovarian hyperstimulation results in supraphysiological levels of ovarian steroid hormones, which may influence anesthetic sensitivity. This study aimed to evaluate the relationship between preprocedural serum estradiol and progesterone levels and propofol requirement during OPU performed under bispectral index (BIS)-guided sedation. Methods: In this prospective observational study, 96 women undergoing OPU were included. Serum estradiol and progesterone levels measured on the day of the procedure were recorded. Sedation was performed using a standardized protocol with midazolam, fentanyl, and propofol titrated to maintain BIS values between 40 and 60. Propofol consumption was normalized to body weight (mg/kg) and procedure duration (μg/kg/min). Correlation analyses and multivariable linear regression models were used to evaluate associations. Results: Mean propofol consumption was 157.3 ± 53.1 mg (2.41 ± 0.83 mg/kg), corresponding to an infusion rate of 125.7 ± 69.6 μg/kg/min. In multivariable analysis, estradiol levels were independently associated with propofol requirement (β = 0.238, p = 0.014), whereas progesterone levels were not significantly associated with anesthetic dosing after adjustment. BMI (β = −0.305, p = 0.002) and procedure duration (β = 0.224, p = 0.021) were also identified as independent predictors. Conclusions: Estradiol levels were associated with propofol requirement during OPU performed under BIS-guided sedation. However, given the observational design and the modest magnitude of the observed associations, these findings should be interpreted cautiously. BMI and procedure duration appeared to be more consistent predictors of propofol administration. Full article

Background and Objectives: Remimazolam and remifentanil are ultra-short-acting agents that are used for sedation and analgesia, respectively. Their combined effect on respiratory function is unclear. We evaluated whether co-administration produced dose-dependent respiratory depression and loss of consciousness (LOC) preceded oxygen desaturation. Materials and Methods: A randomized, double-blind trial was conducted from May to July 2024. Female patients (20–65 years; n = 108; American Society of Anesthesiologists physical status I–II) undergoing elective gynecological surgery were selected. Patients received remifentanil via target-controlled infusion (TCI) at effect-site concentrations (C_e) of 1.0, 1.5, or 2.0 ng/mL (Groups 1.0, 1.5, and 2.0) combined with a fixed C_e of 500 ng/mL remimazolam. Respiratory variables, timing of LOC, bispectral index, and adverse events were recorded. Results: Respiratory depression increased in a dose-dependent manner. Jaw thrust was required in 52.8% of Group 1.0 and 91.7% of Group 2.0 (p < 0.001). The need for 100% oxygen increased from 30.6% to 69.4% (p = 0.001). Minute ventilation decreased only in Group 2.0 (p = 0.008). Involuntary movements were frequent in Group 1.0 (p = 0.005). Conclusions: Remimazolam–remifentanil co-administration via TCI induced dose-dependent respiratory depression and pre-LOC desaturation. Therefore, continuous monitoring and careful titration are essential. Full article

Cropland parcels are fundamental units in agricultural production, and their precise delineation is critical for cadastral management and precision agriculture. However, heterogeneous agricultural landscapes with fragmented patches, complex land cover, and indistinct boundaries pose significant challenges for automated parcel delineation. Unmanned aerial systems (UASs) offer flexible, high-resolution multi-temporal spectral and elevation data, providing potential opportunities for mapping patched parcels. This study proposed an automated method for mapping patched cropland parcels using centimeter-level digital surface models (DSMs) and digital orthophoto maps (DOMs), validated at three typical sites in the Sichuan Basin. The method integrates (1) threshold segmentation of topographic relief to distinguish field surfaces from borders; (2) vegetation removal using a visible-band difference vegetation index (VDVI) mask; and (3) morphological refinement to produce high-precision vectorized field polygons. Results show that integrating bi-temporal UAS elevation and spectral data enables accurate, automated field extraction. Area-based mapping accuracy reached 98.1%, with an overall accuracy (OA) of 96.1% and a Kappa coefficient (KC) of 0.92. Field-count correctness was 93.3%, and the relative error of boundary length was 4.55%. Notably, parcels with regular shapes achieved even higher accuracy, with OA of 99.1% and KC of 0.98. By leveraging UAS-based elevation and spectral data, the proposed method can offer an alternative way to precise delineation of patched field boundary and provides reliable technical support for cadastral mapping and cropland surveys in agricultural regions. Full article

Sedation and anesthesia are integral components of modern gastrointestinal endoscopy, enhancing patient comfort and procedural success while adding risks such as respiratory and cardiovascular complications. Accurate monitoring of sedation depth is essential to balance safety and procedural efficacy. This narrative literature review synthesizes current evidence on monitoring depth of anesthesia during endoscopic procedures, including clinical assessment scales, capnography, and processed electroencephalogram (pEEG)-based technologies. The effects of commonly used sedative agents on monitoring parameters and the impact of different monitoring strategies on clinical outcomes are also discussed. Current evidence indicates that clinical assessment remains the cornerstone of monitoring during moderate sedation, while capnography improves early detection of respiratory compromise during deep sedation. pEEG-based monitoring may provide additional value in selected high-risk or prolonged procedures but should complement, not replace, clinical evaluation. A multimodal monitoring approach tailored to sedation depth and patient risk profile is likely to be the most effective strategy for optimizing patient safety. Future research should focus on standardizing monitoring protocols and identifying populations most likely to benefit from advanced monitoring techniques. Full article

Background: This study aims to conduct an analysis of the literature on low-flow anesthesia published over the past 30 years, identifying the most productive countries, institutions, authors, and journals; uncovering the intellectual structure of the field through the most influential publications, authors, and journals; and visualizing thematic clusters and evolving research trends based on keyword analyses. Methods: This retrospective bibliometric study analyzed scientific publications on low-flow anesthesia indexed in the Science Citation Index Expanded (SCIE) of the Web of Science Core Collection (WoSCC) between 1993 and 2024. Articles were classified by countries, institutions, journals, and researchers, and the number of studies and citations were determined. Co-citation analysis and keyword co-occurrence analysis were performed to map thematic clusters and intellectual structures. Results: A total of 260 articles met the inclusion criteria. The United States led with 39 publications, followed by Turkey (33) and Japan (27). The most productive institution was Northwestern University (USA), and the most published journal was Anesthesia & Analgesia. The most prolific authors were André M. De Wolf and Jan F. A. Hendrickx, while co-citation analysis identified Edmund I. Eger II and Hiromichi Bito as the most influential authors based on centrality metrics. MDS and trend topic analyses revealed prominent keywords including “closed loop”, “remifentanil”, “sevoflurane”, “bispectral index”, “EEG analysis”, “pharmacokinetics”, “absorbent”, “performance”, and “FGF” (fresh gas flow). Conclusions: The United States leads the field of low-flow anesthesia in both publication count and citations. Trending terms such as “closed loop,” “performance,” “remifentanil,” “sevoflurane,” “bispectral index,” “EEG analysis,” “FGF,” and “absorbent” reflect the current research directions in this field. Full article

Background: Cardiopulmonary bypass (CPB) is an essential technique for cardiac surgery but significantly increases the risk of perioperative neurological complications. Electroencephalography (EEG) enables real-time monitoring of brain function and provides sensitive biomarkers for early detection of cerebral injury. However, a systematic synthesis of how CPB-related physiological, pharmacological, and technical factors influence EEG signals, and how these insights can be integrated into clinical decision-making, is still lacking. Objective: To systematically review the effects of temperature management, mean arterial pressure (MAP), hemodilution, anesthetic agents, embolization, and systemic inflammatory response during CPB on EEG parameters (including frequency bands, Bispectral Index (BIS), quantitative EEG metrics such as burst suppression ratio (BSR), spectral edge frequency (SEF), etc.), and to evaluate the associations between EEG changes and postoperative delirium (POD) and stroke. Methods: Following the PRISMA 2020 guidelines, we searched PubMed, Web of Science, and related databases for original English-language articles published between February 1974 and September 2025. Inclusion criteria: adult patients (≥18 years) undergoing cardiac surgery with CPB and intraoperative EEG monitoring (raw or processed). Exclusion criteria: reviews, case reports, animal studies, pediatric populations, and articles with inaccessible full texts. Two reviewers independently screened the literature and extracted data; a narrative synthesis was performed. Results: Fifty-one studies were included. Main findings: (1) Hypothermia: BIS decreases linearly with temperature (≈1.12 units/°C); electrocerebral silence occurs during deep hypothermic circulatory arrest; EEG recovery dynamics during rewarming predict POD. (2) MAP and cerebral perfusion: The rate of MAP decline (≥0.66 mmHg/s) is a stronger predictor of EEG abnormalities than the absolute MAP value; under fixed pump flow, some patients exhibit coexisting cerebral overperfusion and metabolic suppression. (3) Hemodilution: Maintaining hemoglobin ≥9.4 g/dL prevents EEG slowing; a drop below 9.2 g/dL significantly increases the risk of slowing. A ≥10% decrease in regional cerebral oxygen saturation (rSO₂) is associated with a 1.5-fold increased risk of burst suppression. (4) Anesthetic agents: Propofol maintains flow-metabolism coupling, and BSR reflects deep anesthesia better than BIS; sevoflurane and isoflurane impair autoregulation and suppress EEG. (5) Embolization and inflammation: EEG epileptiform discharges increase the risk of POD five-fold; a decrease in LIR predicts stroke (AUC 0.771) and POD (AUC 0.779); persistent EEG changes increase the risk of POD 2.65-fold. Conclusions: CPB-related factors affect EEG signals through distinct mechanisms, and specific EEG patterns (slowing, burst suppression, asymmetry, epileptiform discharges) are significantly associated with postoperative neurological complications. Multimodal monitoring (EEG + cerebral oximetry + hemodynamics) with clear intervention thresholds facilitates individualized brain protection. Future interventional studies using real-time EEG feedback are needed to confirm improvements in long-term neurological outcomes. Full article

Background/Objectives: Volatile anesthetic dosing during cardiopulmonary bypass (CPB) is poorly standardized. We estimated the end-tidal sevoflurane (ETsevo) concentration required to maintain adequate anesthesia during CPB and investigated the effects of age and body temperature. Methods: This study is a PRISMA-compliant, PROSPERO-registered meta-analysis. PubMed, Embase, and the Cochrane Library were searched. Prospective studies of adults who underwent cardiac surgery with CPB and receiving sevoflurane were included. Primary outcome was mean ETsevo concentration when bispectral index (BIS) was 40–60. Three-level random-effects meta-analytic models with robust variance estimation were used to pool repeated measurements within studies. Age and body temperature were then examined as study-level moderators. Risk of bias was determined using ROBINS-I. Results: Five studies (n = 129) fulfilled the criteria. Pooled ETsevo during CPB was 0.88 vol% (95% confidence interval [CI] 0.29 to 1.46; p = 0.02) with substantial heterogeneity (I² = 87.6%). Body temperature was not a significant moderator (difference 0.26 vol%; 95% CI −1.12 to 1.64; p = 0.27). Higher mean age was associated with lower ETsevo, evidenced by the finding that patients with a mean age of >62.0 years required 0.45 vol% less ETsevo (95% CI −0.78 to −0.13; p = 0.01), and sensitivity analysis revealed a 0.05 vol% decrease per additional year. Conclusions: To maintain BIS at 40–60 during CPB, the estimated ETsevo requirement is 0.88 vol% (minimum alveolar concentration 0.53–0.58 in patients in their 60s). Requirements decreased with age, and body temperature exerted no detectable effect. Full article

(1) Background: Electroencephalography (EEG) is widely used to monitor the depth of anesthesia; however, conventional Fourier-based analyses are limited in their ability to characterize non-stationary anesthetic-induced EEG dynamics. In this study, we investigated the utility of singular spectrum analysis (SSA) combined with the Hilbert transform for extracting physiologically meaningful EEG features under sevoflurane general anesthesia. (2) Methods: Frontal EEG data from ten patients undergoing sevoflurane anesthesia were analyzed from the maintenance phase through emergence. Using SSA, short EEG segments were decomposed into six intrinsic mode functions (IMFs) without pre-specified basis functions or frequency bands. Hilbert spectral analysis was applied to each IMF to obtain instantaneous frequency and amplitude characteristics. (3) Results: The SSA-based decomposition clearly captured phase-dependent EEG changes, including α spindle activity during maintenance and increasing high-frequency components preceding emergence. Multiple linear regression models incorporating IMF center frequencies and total power demonstrated strong correlations with the bispectral index (BIS), achieving high predictive accuracy (R² = 0.88, MAE < 4). Compared with conventional spectral approaches, SSA provided superior temporal resolution and stable feature extraction for non-stationary EEG signals. (4) Conclusions: These findings indicate that SSA combined with Hilbert analysis is a robust framework for quantitative EEG analysis during general anesthesia and may enhance real-time, individualized assessments of anesthetic depth. Full article

Background: This study aimed to determine whether the duration or the magnitude of intraoperative BIS suppression has a greater impact on postoperative recovery. Methods: In this observational study, 141 patients were monitored for BIS values, suppression ratio (SR), maximum suppression ratio (SRmax), and total suppression time (SRT) during the perioperative period. Recovery phenotypes were assessed using the Richmond Agitation-Sedation Scale (RASS). Statistical analyses evaluated the relationship between BIS suppression parameters (SR, SRmax, SRT) and postoperative sedation or emergence agitation. Optimal thresholds for clinically significant suppression were determined. Results: Patients classified into the sedation group according to RASS scores exhibited significantly higher intraoperative SRmax values (p: 0.038) and prolonged SRT (p: 0.001) compared to the agitated group. An SRT ≥ 7.5 min predicted sedated recovery with 86.7% sensitivity and 39.4% specificity (AUC = 0.651, 95% CI: 0.561–0.742, p: 0.002). Similarly, an SRmax ≥ 19.5 was associated with sedated recovery (85.3% sensitivity, 53.0% specificity; AUC = 0.683, 95% CI: 0.592–0.775, p: 0.001). No significant association was found between BIS suppression and emergence agitation. Conclusions: Prolonged intraoperative BIS suppression and higher SRmax values are comparably predictive of postoperative sedation but not agitation. Monitoring these parameters may aid in anticipating recovery patterns. Full article

Background and Objectives: Scalp nerve block (SNB) is hypothesized to attenuate the physiological response to skull pinning more effectively than local anesthetic (LA) infiltration. This study aimed to compare the two techniques using Bispectral index (BIS) as a primary surrogate measure of cortical arousal. Materials and Methods: In this prospective observational study, patients undergoing elective craniotomy received either bilateral SNB (Group S, n = 53) or LA infiltration (Group LA, n = 35) based on anesthesiologist preference. Depth of anesthesia was monitored via BIS. The primary outcome was the change in BIS after skull pin insertion. A ΔBIS > 20% from baseline triggered rescue medication (remifentanil/propofol). Secondary outcomes included hemodynamic parameters and rescue requirements. Results: There was a significant main effect of time on BIS values (p < 0.001), indicating that BIS values changed significantly across measurement points. Post-hoc examination of parameter estimates revealed that the Group LA showed significantly greater increases in BIS values compared to the Group S at T1 (p = 0.030) and T3 (p = 0.024). No significant between-group differences in BIS changes were observed at T5, T10, or T15 time points (p > 0.05). Hemodynamic responses (mean arterial pressure and heart rate) were also transiently but significantly higher in Group LA at these time points (p < 0.001). The most clinically notable finding was that significantly more patients in Group LA required rescue medication (p < 0.001), indicating a greater frequency of clinically significant physiological trespass. Conclusions: Compared to LA infiltration, SNB was associated with statistically significant reductions in immediate BIS and hemodynamic responses to skull pinning. The key potential clinical implication is the corresponding reduction in the need for rescue anesthetic intervention. These findings support SNB as a technique for enhancing physiological stability, though the direct impact on patient-centered outcomes requires further study. BIS may serve as a useful adjunctive indicator of the cortical response to noxious stimuli. Full article

Background/Objectives: Drug-induced sleep endoscopy (DISE) is used in obstructive sleep apnea (OSA) to visualize dynamic upper airway collapse, but sedation protocols vary widely with no consensus on the optimal agent or technique. This narrative review aims to clarify current sedation strategies for DISE in OSA and their clinical implications. Methods: We systematically searched PubMed, Scopus, Web of Science, and Cochrane Library for English-language publications on DISE sedation (2000–2025). Relevant clinical studies, guidelines, and reviews were included. Data were qualitatively synthesized due to heterogeneity among studies. Results: Sedation approaches in DISE varied considerably. Propofol, dexmedetomidine, and midazolam were the primary agents identified. Propofol provided rapid, titratable sedation but increased airway collapsibility at higher doses; dexmedetomidine produced a more natural sleep-like state with minimal respiratory depression; midazolam was less favored due to prolonged effects. Use of target-controlled infusion (TCI) and pharmacokinetic–pharmacodynamic (PK–PD) models improved control of propofol sedation. Co-sedative adjuncts (e.g., opioids) reduced the required sedative dose but added risk of respiratory depression. Careful titration to the lowest effective dose-often guided by bispectral index (BIS) monitoring—was emphasized to achieve adequate sedation without artifactual airway collapse. No universal DISE sedation protocol was identified. Conclusions: Optimal DISE sedation balances adequate depth with patient safety to ensure reliable findings. Using the minimum effective dose, guided by objective monitoring (e.g., BIS), is recommended. There is a need for standardized sedation protocols and further research (e.g., in obese patients) to resolve current controversies and improve DISE’s utility in OSA management. Full article

Background: Awake carotid endarterectomy (CEA) under local anesthesia demands an optimal sedation strategy that ensures patient comfort while preserving the ability for real-time neurological assessment. Dexmedetomidine (DEX) and remifentanil (REMI) are widely used agents, but direct comparisons in this setting remain scarce. Methods: Exploratory, retrospective, single-center study of awake CEA (March–July 2019). DEX or REMI infusions were titrated to a Richmond Agitation–Sedation Scale (RASS) of −1 to −2. Outcomes were sedation failure (RASS ≥ +2 despite maximum infusion rate), bradycardia, hypotension, and neurologic events. Statistical analyses used χ² test (categorical variables) and Student’s t-test or Mann–Whitney test (continuous variables). Associations were assessed with Firth’s logistic regression (univariable and bivariate models), reporting odds ratios (OR) with 95% confidence intervals (CI_95%). Trends in the Bispectral Index (BIS), hemodynamic, and respiratory parameters were assessed using two-way repeated-measures Analysis of Variance (ANOVA). A p-value < 0.05 was considered significant. Results: Fifty-two patients were included (DEX = 25; REMI = 27). DEX group showed more frequent sedation failure (32.0% vs. 3.7%; p = 0.020), bradycardia (36.0% vs. 3.7%; p = 0.009), and hypotension (28.0% vs. 0%; p = 0.011). DEX was associated with increased risk in sedation failure (OR 8.58, CI_95% 1.70–85.81), bradycardia (OR 10.17, CI_95% 2.05–101.21), and hypotension (OR 22.30, CI_95% 2.46–2959.60); the direction of associations remained consistent in bivariate models adjusted for baseline confounders. ANOVA showed group-by-time interactions for BIS, heart rate, mean arterial pressure, and end-tidal CO₂. No intraoperative complications or adverse outcomes were observed. Conclusions: In this retrospective cohort of awake CEA, DEX was associated with higher rates of sedation failure and hemodynamic adverse events compared with REMI, without an apparent impact on procedural success. Given non-random allocation and baseline imbalances, these findings are hypothesis-generating and warrant confirmation in larger, robust, and prospective studies. Full article