Association Between Awake Tracheal Intubation and Peri-Intubation Events in Critically Ill Patients: A Single-Center Retrospective Cohort Study

Association Between Awake Tracheal Intubation and Peri-Intubation Events in Critically Ill Patients: A Single-Center Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association Between Awake Tracheal Intubation and Peri-Intubation Events in Critically Ill Patients: A Single-Center Retrospective Cohort Study Takahiro Masuda, Mayu Saigo, Ryo Kitabayashi, Akihiro Hirakawa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7942044/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Tracheal intubation in critically ill adults often precipitates peri-intubation events including severe cardiovascular instability, severe hypoxemia, and cardiac arrest. Awake tracheal intubation (ATI) may mitigate these risks, yet evidence from intensive care units (ICUs) remains limited. We evaluated whether ATI is associated with fewer peri-intubation events than induction of general anesthesia (GA). Methods We performed a retrospective, single-center cohort study of consecutive adults undergoing ICU tracheal intubation from April 2018 through March 2023. The exposure was ATI versus GA. The primary outcome was a composite peri-intubation event within 30 minutes of procedure start, comprising cardiovascular instability, severe hypoxemia, or cardiac arrest. Secondary outcomes were the composite components and 28-day all-cause mortality. The primary analysis estimated adjusted marginal risks using g-computation with multivariable logistic regression and marginal standardization. Uncertainty was quantified with nonparametric bootstrap. Robustness was examined with modified Poisson regression, 1:1 propensity score matching (targeting ATT), and entropy balancing (targeting ATE). Results Of 553 screened episodes, 342 met criteria. The composite occurred in 172 of 342 patients (50.2%) overall (ATI 9 of 48 [18.8%] vs GA 163 of 294 [55.4%]). After adjustment, the estimated risk of the composite was 0.170 (95% CI, 0.069–0.296) with ATI and 0.558 (0.498–0.617) with GA, yielding an adjusted risk difference of − 0.388 (− 0.508 to − 0.251) and a risk ratio of 0.305 (0.120–0.534). Component analyses suggested lower adjusted risks of cardiovascular instability and severe hypoxemia with ATI. Findings were directionally consistent in propensity score-matched and entropy-balanced analyses. 28-day mortality did not differ significantly (adjusted risk 0.301 with ATI vs 0.181 with GA; risk difference + 0.119, 95% CI − 0.008 to + 0.252). Cardiac arrest was rare (1 event per group). No ATI-attributable safety signals were identified. Conclusions In this single-center ICU cohort, ATI was associated with substantially fewer peri-intubation events than GA, with convergent estimates across complementary analytic approaches. These hypothesis-generating data support considering ATI for physiologically fragile patients and motivate pragmatic trials to define patient selection and implementation strategies. awake tracheal intubation airway management critical illness peri-intubation complications. Figures Figure 1 Background Tracheal intubation in critically ill adults is one of the most frequent and high-risk procedures in intensive care and emergency settings. A large proportion of cases undergo life-threatening complications in peri-intubation phase. The international INTUBE study 1 reported high rates of peri-intubation event including severe hypotension, severe hypoxemia, and cardiac arrest within 30 minutes of intubation. These events are closely linked to pre-existing physiological instability, including shock and hypoxemia. Rapid sequence induction, which involves the rapid and sequential administration of general anesthetic agents and neuromuscular blocking agents, is widely regarded as the standard technique for tracheal intubation in critically ill adults. 2 The 2018 joint guidelines 3 of the Difficult Airway Society and the Intensive Care Society recommend this approach and emphasize the importance of preparation, team coordination, and pharmacological optimization to reduce risk. Despite these measures, induction of general anesthesia and neuromuscular paralysis can depress cardiovascular function 4 and suppress spontaneous ventilation. 5 Patients with physiological derangements may therefore experience worsening hypotension or hypoxemia at the time of induction. Awake tracheal intubation (ATI), performed under topical anesthesia with optional minimal sedation while maintaining patient responsiveness and without the use of neuromuscular blockade before tracheal tube placement, has traditionally been used for anatomically difficult airways. The 2020 Difficult Airway Society guidelines 6 provide detailed recommendations for technique, topicalization, minimal sedation, and use of video laryngoscopy. There is growing interest in applying ATI to physiologically difficult airways such as critically ill patients, 7 where avoidance of induction may preserve hemodynamic stability and spontaneous breathing. However, clinical evidence in critically ill patients remains limited. A recent single-center retrospective cohort suggested that awake tracheal intubation is feasible in the ICU and may offer safety advantages when compared with conventional general anesthesia strategies. 8 That study did not provide extensive adjustment for illness severity or explore the hemodynamic implications of different strategies in depth. We conducted a retrospective cohort study to evaluate the association between ATI and peri-intubation events within 30 minutes of intubation in the ICU to generate estimates that can inform the design of future trials. Methods Study design and setting We conducted a retrospective, single-center cohort study at a 743-bed academic tertiary hospital in Tokyo, Japan. Adult patients aged 18 years or older who underwent tracheal intubation in the intensive care unit (ICU) between 1 April 2018 and 31 March 2023 were eligible. Intubations performed during cardiac arrest were excluded. Two investigators (TM and MS) independently abstracted data from the electronic health record and time-stamped medication administration records using a pre-specified codebook. Discrepancies between the two abstractions were identified and resolved by consensus after repeat verification against the original source records. The institutional review board approved the study [M2023-109] and waived individual consent because risk was minimal. An opt-out mechanism was provided via notices in clinical areas and on the hospital website. Reporting follows the STROBE statement. 9 Exposure Procedures were classified into two mutually exclusive exposure categories. ATI was defined as tracheal intubation performed with airway topicalization while preserving purposeful responsiveness to verbal command. Minimal systemic sedation was permitted using low-dose opioid analgesia only, at the operator’s discretion provided that loss of responsiveness was not intended. Neither general anesthetic agents nor neuromuscular blocking agents were administered before tracheal tube placement in awake tracheal intubation. Any administration of a general anesthetic agent or neuromuscular blocking agent before tube placement led to classification as general anesthesia (GA). Outcomes The primary outcome was the occurrence of peri-intubation events within 30 minutes of the start of the intubation procedure, operationalized in accordance with the INTUBE study. 1 A peri-intubation event was recorded if any of the following occurred: cardiovascular instability, severe hypoxemia, or cardiac arrest. Cardiovascular instability was defined as systolic arterial pressure less than 65 mmHg recorded at least once, or systolic arterial pressure less than 90 mmHg for more than 30 minutes, or a new or increased vasopressor requirement, or an intravenous fluid bolus greater than 15 mL per kilogram. Severe hypoxemia was defined as peripheral oxygen saturation less than 80 percent. Secondary outcomes were the individual components of the primary composite and 28-day all-cause mortality. Physiological variables were extracted from ICU bedside monitor archives, where signals are recorded at 1-minute intervals. The start of the intubation procedure defined time zero. When multiple values were present within the 30-minute window after time zero, the worst value was used. Initiation or escalation of vasopressors around the time of intubation was recorded when available. Covariates Covariates were specified a priori based on clinical relevance. These included age, sex, body mass index (BMI), indication for tracheal intubation categorized as respiratory failure, shock, or airway protection including concerns for occlusion with tumor, systolic blood pressure, heart rate, and peripheral oxygen saturation at time zero, and severity of illness measured by Sequential Organ Failure Assessment (SOFA) 10 and Acute Physiology and Chronic Health Evaluation (APACHE) II 11 scores. Drug information was also abstracted, doses of systemic opioids, induction agents, and neuromuscular blocking agents. Drug doses are reported as mg·kg⁻¹ where feasible. No formal sample size calculation was undertaken because all eligible cases within the study period were included. Baseline characteristics are presented as counts and percentages for categorical variables and as medians with interquartile ranges for continuous variables. Statistical analysis Primary estimand and outcome model The primary estimand was the average treatment effect (ATE) of ATI compared with GA on the risk of peri-intubation events within 30 minutes. We used g-computation 12 , 13 with marginal standardization. For each binary outcome we fitted a multivariable logistic regression with exposure and prespecified covariates: age, sex, BMI, SOFA score, APACHE II score, the indication of tracheal intubation (e.g., respiratory failure, and shock). After model fitting, we predicted each patient’s outcome probability twice, once setting exposure to awake for all patients and once setting exposure to general anesthesia for all patients, while keeping covariates at observed values. Averaging these predicted probabilities yielded the adjusted risk under each strategy. From these marginal risks we derived the adjusted risk difference as the primary contrast and also reported the risk ratio and the number needed to treat or harm, calculated as 1 divided by the absolute value of the risk difference with the sign indicating benefit or harm. When the confidence interval for the risk difference crossed zero, we did not present NNT or NNH. Uncertainty was quantified with nonparametric bootstrap at the patient level. At each replicate we refitted the outcome model and recomputed all marginal quantities. We used 1,000 replicates and percentile 95% confidence intervals. The random seed was fixed. We focused on effect sizes and intervals rather than p-values. To examine model dependence on the risk-ratio scale we fitted a modified Poisson regression with a log link and robust (sandwich) standard errors and reported the adjusted risk ratio. 14 Sensitivity analyses addressing confounding by indication To assess sensitivity to residual confounding we performed propensity score matching 15 – 17 and entropy balancing. 18 , 19 For propensity score matching, we estimated the score with logistic regression that included the same covariates as the outcome model, then applied 1:1 nearest-neighbor matching without replacement using a caliper equal to 0.25 of the standard deviation of the logit of the propensity score. We evaluated covariate balance with absolute standardized mean differences and used 0.10 or less as a practical target. On the matched sample we estimated marginal risks, risk differences, and risk ratios using the matching weights, and we obtained confidence intervals by repeating the entire matching procedure within each bootstrap replicate. This analysis targets the average treatment effect in the treated population. We also reported the effective sample size for the matched sample. For entropy balancing, we constructed weights that enforced exact mean balance on all prespecified covariates and then estimated weighted marginal risks, risk differences, and risk ratios. Confidence intervals were obtained by repeating the reweighting within each bootstrap replicate. This analysis targets the average treatment effect in the full cohort. As diagnostics we summarized the distribution of weights, documented extreme values and any capping if applied, and reported the effective sample size. Rare outcomes For very rare outcomes such as cardiac arrest, we reported group-specific risks with exact Clopper-Pearson intervals and risk differences with Newcombe score intervals. When applicable, we considered Firth logistic regression as a supplementary analysis and reported results in the supplement. Analyses were conducted using SAS version 9.4 (SAS Institute, Cary, NC, USA) and R version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria). Results Patient selection and data quality During the study period, 553 ICU tracheal intubation episodes were screened; 342 met all inclusion and no exclusion criteria and were analyzed (Figure 1). There were no missing data in exposure, outcomes, or prespecified covariates. Awake tracheal intubation (ATI) accounted for 48/342 episodes (14.0%). Propensity-score matching (1:1) yielded a matched subset of 92 episodes (46 per group) that we used only for sensitivity analyses. Baseline characteristics in the full cohort are shown in Table 1. Figure 1. Patient flow for the ICU intubation cohort. Of 553 intubations screened, 342 met eligibility for analysis. Exposure groups were awake tracheal intubation (ATI) in 48 patients and general anesthesia in 294. The propensity score–matched cohort included 92 patients (46 per group). Table 1. Baseline characteristics by exposure (with standard mean difference) Notes: Continuous variables are shown as median [IQR], and categorical variables as n (%). Standardized mean differences (SMD) were computed as the difference in means divided by the pooled SD for continuous variables, and as the difference in proportions divided by √{p(1−p)} for binary variables. SOFA and APACHE II were assessed within 24 hours from ICU admission. Exposure verification and baseline profile In the ATI group, no episode received a general anesthetic (e.g., propofol, midazolam) or a neuromuscular blocker before tracheal tube placement; when present, systemic sedation consisted of low-dose fentanyl only (Table 1). Compared with GA, ATI episodes were generally younger, had lower BMI, higher SOFA and APACHE II scores, and more frequent shock with lower systolic blood pressure and lower SpO₂ at time zero (Table 1). The main indication for intubation was respiratory failure (296/342, 86.6%), followed by shock (33/342, 9.6%) and airway protection (21/342, 6.1%). Primary outcome: peri-intubation composite The crude incidence of the composite peri-intubation event within 30 min was 50.2% (172/342) overall, 18.8% (9/48) with ATI vs 55.4% (163/294) with GA. In the primary analysis using g-computation (marginal standardization of a multivariable logistic model), the adjusted risk of the composite was 0.170 (95% CI, 0.069–0.296) with ATI and 0.558 (95% CI, 0.498–0.617) with GA, yielding an adjusted risk difference −0.388 (95% CI, −0.508 to −0.251), an adjusted risk ratio 0.305 (95% CI, 0.120–0.534), and a number needed to treat 2.58. Table 2. Adjusted risks and effect estimates using g-computation analysis. Notes. Adjusted risks estimated via g-computation (logistic regression with marginal standardization). Covariates: age, sex, BMI, SOFA, APACHE II, and indication (respiratory failure, shock). RD (ATI−GA) is in percentage points; negative values favor ATI. 95% CIs from nonparametric patient-level bootstrap (1,000 replicates; percentile method). NNT/NNH is 1/|RD| and shown only when the CI does not cross 0. Outcomes assessed within 30 minutes from intubation start. Abbreviations: ATI=awake tracheal intubation; GA=general anesthesia; RD=risk difference; RR=risk ratio; CI=confidence interval; NNT/NNH=number needed to treat/harm. Secondary outcomes: components of peri-intubation events For cardiovascular instability, adjusted risks were 0.165 (95% CI, 0.065–0.285) with ATI and 0.470 (95% CI, 0.414–0.529) with GA; RD −0.305 (95% CI, −0.426 to −0.180), RR 0.352 (95% CI, 0.136–0.614), NNT 3.28. For severe hypoxemia, adjusted risks were 0.023 (95% CI, 0–0.060) with ATI and 0.168 (95% CI, 0.127–0.213) with GA; RD −0.144 (95% CI, −0.202 to −0.091), RR 0.139 (95% CI, 0–0.381), NNT 6.93. All adjusted estimates appear in Table 2. Mortality and peri-intubation cardiac arrest Twenty-eight–day all-cause mortality was 18.4% (63/342). Adjusted risks were 0.301 (95% CI, 0.176–0.427) with ATI and 0.181 (95% CI, 0.139–0.224) with GA; RD +0.119 (95% CI, −0.008 to +0.252), RR 1.66 (95% CI, 0.957–2.56). Thus, mortality did not differ statistically and may be influenced by confounding by indication. Peri-intubation cardiac arrest occurred once in each group (2/342, 0.6% overall); given rarity, group-specific risks with exact Clopper-Pearson CIs and the Newcombe CI for the risk difference are reported in Table S5. Sensitivity analyses Findings were directionally consistent across sensitivity analyses. Modified Poisson regression with robust variance produced risk ratios similar in magnitude and direction to the g-computation estimates (Table S4). Propensity-score matching (ATT target) and entropy balancing (ATE target) yielded comparable risk differences and ratios (Tables S2–S3); propensity-score overlap was limited, especially for GA at low scores (Figure S1). Assessment of unmeasured confounding E-values 20 indicated that relatively strong unmeasured confounding would be required to fully explain the protective association of ATI for the composite and its components. For the composite (g-computation), the E-value for the point estimate RR 0.305 was 6.01, and 3.15 for the confidence limit closest to the null. For cardiovascular instability, the corresponding E-values were 5.13 and 2.64; for severe hypoxemia, 13.91 and 4.69. For 28-day mortality (RR 1.66), the E-value was 2.71 and 1.00 for the CI limit, consistent with the CI spanning the null (Table S6). Discussion Among critically ill adults undergoing emergent tracheal intubation in the ICU, awake tracheal intubation (ATI) was associated with a substantially lower risk of peri-intubation events within 30 minutes compared with general anesthesia. After g-computation (standardized risks), the estimated risk was 0.170 with ATI versus 0.558 with general anesthesia, corresponding to an adjusted risk difference of − 0.388 (95% CI − 0.508 to − 0.251) and a risk ratio of 0.305 (95% CI 0.120–0.534), yielding an NNT of ~ 3. Results were directionally consistent across sensitivity analyses using propensity-score matching (ATT) and entropy balancing (ATE). The primary association was moderately robust to unmeasured confounding: the E-value for the point estimate was 6.0 (and 3.1 for the confidence limit closest to the null). Reductions were evident for both cardiovascular instability and severe hypoxemia. On the other hand, 28-day mortality did not differ significantly between groups, and peri-intubation cardiac arrest was rare (1 event per group), limiting precision for those outcomes. We used a prespecified causal framework with marginal standardization to estimate risk differences and risk ratios on the probability scale. The primary analysis relied on g-computation with nonparametric bootstrap confidence intervals. We then targeted complementary estimands: the average treatment effect on the treated (ATT) through propensity score matching, and the average treatment effect (ATE) through entropy balancing. Modified Poisson regression with robust variance offered an independent check of the relative risk. For rare outcomes we reported exact interval estimates. We verified exposure fidelity and reported component outcomes separately. We assessed overlap, effective sample sizes, and weight distributions to detect instability. There were no missing data in exposures, outcomes, or covariates, which reduced the need for imputation. E-value analyses indicated that an unmeasured confounder would need to be strong and similarly associated with exposure and outcome to move the estimates to the null. Together, these steps support internal validity and reduce model and design dependence. The existing literature has established that emergency tracheal intubation in the critically ill patients carries a high risk of peri-intubation life-threatening complications. Large multicenter cohorts 1 , 21 , 22 have reported that roughly half of critically ill patients experience at least one adverse event during or shortly after intubation, and that cardiac arrest, while uncommon, is not rare. Multiple randomized controlled trials have attempted to reduce these events by optimizing precautious fluid bolus administration, 23,24 precautious inotropic support, 25 and pre-oxygenation strategy including high-flow nasal cannula 26 within a rapid sequence induction paradigm. These trials have largely failed to produce consistent or clinically meaningful reductions in severe hypoxemia or hemodynamic instability. As a result, the field knows a great deal about how often complications occur, but far less about whether a different physiologic strategy could reduce the burden of harm. This gap motivates a focused clinical question. Rapid sequence induction couples a bolus of induction agents that depress myocardial contractility 27 – 31 with neuromuscular blockade that abolishes respiratory effort. In physiologically unstable patients, this combination can lower cardiac output and remove the patient’s own spontaneous breathing effort at the precise moment airway instrumentation occurs. Awake tracheal intubation represents a contrasting strategy. It preserves spontaneous ventilation, allows stepwise topical anesthesia and titrated analgesia, and can be conducted without the abrupt hemodynamic shifts that follow induction. Despite being codified for difficult airway management, 4 awake tracheal intubation techniques have rarely been evaluated in critically ill populations, and the few available reports are single-center and retrospective. 8 The clinical question is whether, in real practice, awake tracheal intubation is associated with fewer peri-intubation events than general anesthesia. 32 , 33 Our findings address this question directly and show large, directionally consistent reductions in the composite and its components across analytic approaches. We also observed no clear difference in 28-day mortality. The present study contributes three advances that address the gap and support future trial design. First, we move beyond device-oriented comparisons inside rapid sequence induction and instead contrast two competing clinical strategies. We verify exposure fidelity and describe drug use patterns, which clarifies what “awake” and “general anesthesia” meant at the bedside. Second, we estimate effects on the probability scale using g-computation with marginal standardization as the primary analysis, and we probe robustness with propensity score matching for the treated population and entropy balancing for the average population. This approach yields adjusted absolute risks, risk differences, and risk ratios for the composite outcome and its components, along with numbers needed to treat. Third, we provide diagnostics that matter for translation. We assess covariate balance, overlap, effective sample sizes, and weight distributions, and we quantify the strength of unmeasured confounding needed to explain away the findings using E-values. Together these elements supply the control event rates, effect size ranges, and feasibility signals needed to power a pragmatic trial that compares awake intubation with rapid sequence induction in the ICU. In summary, the novelty of this work is conceptual and practical. Conceptually, it reframes airway management for the critically ill from marginal tweaks within rapid sequence induction to a choice between physiologic strategies. Practically, it delivers the epidemiologic inputs and robustness checks required to advance from observational insight to a definitive randomized trial. This study has several limitations. First, it was a retrospective single-center cohort restricted to ICU intubations, so causal relationships cannot be inferred and generalizability to emergency departments, wards, or other institutions may be limited. Second, confounding by indication may persist despite multivariable adjustment including propensity score matching and entropy balancing, unmeasured factors such as operator judgement, airway difficulty, and periprocedural strategy could still influence both exposure and outcomes. Third, although data abstraction was performed independently by two investigators using a pre-specified codebook and discrepancies were resolved against source records, retrospective chart review is susceptible to information bias and lack of blinding. Fourth, several procedural variables were unavailable, including number of attempts, duration of the procedure, formal airway assessments, and operator experience, all of which may affect outcomes. Fifth, event counts for cardiac arrest were very low, which necessitated Firth’s penalized regression and resulted in imprecise estimates for that component and for 28-day mortality; the study was not powered to detect differences in these endpoints. Finally, outcomes followed INTUBE definitions within a 30-minute window and were derived from the worst recorded values. Although ICU monitoring at 1-minute resolution reduces misclassification, different outcome definitions or windows might yield different estimates. Conclusion In this retrospective single-center ICU cohort, awake tracheal intubation was associated with a lower incidence of peri-intubation events, chiefly cardiovascular instability. These findings are hypothesis generating and warrant prospective evaluation in clearly defined high-risk groups. Abbreviations APACHE II Acute Physiology and Chronic Health Evaluation II ATE Average treatment effect ATT Average treatment effect on the treated ATI Awake tracheal intubation BMI Body mass index CI Confidence interval EB Entropy balancing EHR Electronic health record ESS Effective sample size GA General anesthesia HR Heart rate ICU Intensive care unit IQR Interquartile range IRB Institutional review board NNT / NNH Number needed to treat / Number needed to harm PS Propensity score PSM Propensity score matching RD Risk difference RR Risk ratio RSI Rapid sequence induction SBP Systolic blood pressure SOFA Sequential Organ Failure Assessment SpO₂ Peripheral oxygen saturation STROBE Strengthening the Reporting of Observational Studies in Epidemiology Declarations Ethics approval and consent to participate The present study was approved by the Tokyo Medical and Dental University Institutional Review Board (approval M2023-109). Because this was a retrospective chart review using de-identified data, the IRB waived the requirement for informed consent. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Authors’ information Not applicable. Funding Not applicable. Author Contribution TM and MS contributed equally to this work. They conceived and planned the study, collected the data, and drafted the manuscript. TM and RK performed the data analyses and contributed to manuscript revision. AH supervised the study and critically revised the manuscript. All authors reviewed and interpreted the results, approved the final version, and agree to be accountable for all aspects of the work. Acknowledgement We wish to thank Kenji Wakabayashi, the director of the intensive care unit of Institute of Science Tokyo Hospital for providing constructive comments and supervision on this study. 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J Crit Care 2023;77:154317. https://doi.org/10.1016/j.jcrc.2023.154317 . Greer A, Hewitt M, Khazaneh PT, et al. Ketamine Versus Etomidate for Rapid Sequence Intubation: A Systematic Review and Meta-Analysis of Randomized Trials. Crit Care Med 2025;53(2):e374-e383. https://doi.org/10.1097/CCM.0000000000006515 . Russotto V, Tassistro E, Myatra SN, et al. Peri-intubation Cardiovascular Collapse in Patients Who Are Critically Ill: Insights from the INTUBE Study. Am J Respir Crit Care Med 2022;206(4):449–458. https://doi.org/10.1164/rccm.202111-2575OC . Lapinsky SE. Tracheal intubation in the critically ill: just say no to drugs. Br J Anaesth 2012;109(2):287; author reply 287-8. https://doi.org/10.1093/bja/aes238 . Masuda T, Nosaka N, Nagashima M. Intubation Practices and Adverse Peri-intubation Events in Critically Ill Patients. JAMA 2021;326(6):568–569. https://doi.org/10.1001/jama.2021.8529 . Tables Table 1 and 2 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1BaselinewithSMD.docx Table2ClinicalOutcomeforGcomputation.docx TableS1SMDsunadjPSMEB.docx TableS3EBdiagnostics.docx TableS4mPoisson.docx TableS6Evalues.docx TableS5RareEvents.docx TableS2PSMdiagnostics.docx FigureS1LovePSM.tif FigureS2LoveEB.tif Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7942044","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":541885848,"identity":"c7d677d1-1886-476a-8631-2047d209ad4f","order_by":0,"name":"Takahiro 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16:16:18","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":18081,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2PSMdiagnostics.docx","url":"https://assets-eu.researchsquare.com/files/rs-7942044/v1/fe1a0b59a016804c9cbc5cdf.docx"},{"id":95565520,"identity":"644f9310-490d-47ce-9e9a-38276c6b4951","added_by":"auto","created_at":"2025-11-10 16:16:30","extension":"tif","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":158634,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1LovePSM.tif","url":"https://assets-eu.researchsquare.com/files/rs-7942044/v1/47cbfdf8dea7b611f4f52650.tif"},{"id":95655534,"identity":"df75be00-5644-4c4d-bee1-54aa23db6442","added_by":"auto","created_at":"2025-11-11 16:16:25","extension":"tif","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":157170,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS2LoveEB.tif","url":"https://assets-eu.researchsquare.com/files/rs-7942044/v1/cde779c67dcfbdc8385fd2ad.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Awake Tracheal Intubation and Peri-Intubation Events in Critically Ill Patients: A Single-Center Retrospective Cohort Study","fulltext":[{"header":"Background","content":"\u003cp\u003eTracheal intubation in critically ill adults is one of the most frequent and high-risk procedures in intensive care and emergency settings. A large proportion of cases undergo life-threatening complications in peri-intubation phase. The international INTUBE study\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e reported high rates of peri-intubation event including severe hypotension, severe hypoxemia, and cardiac arrest within 30 minutes of intubation. These events are closely linked to pre-existing physiological instability, including shock and hypoxemia.\u003c/p\u003e\u003cp\u003eRapid sequence induction, which involves the rapid and sequential administration of general anesthetic agents and neuromuscular blocking agents, is widely regarded as the standard technique for tracheal intubation in critically ill adults.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e The 2018 joint guidelines\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e of the Difficult Airway Society and the Intensive Care Society recommend this approach and emphasize the importance of preparation, team coordination, and pharmacological optimization to reduce risk. Despite these measures, induction of general anesthesia and neuromuscular paralysis can depress cardiovascular function\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e and suppress spontaneous ventilation.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e Patients with physiological derangements may therefore experience worsening hypotension or hypoxemia at the time of induction.\u003c/p\u003e\u003cp\u003eAwake tracheal intubation (ATI), performed under topical anesthesia with optional minimal sedation while maintaining patient responsiveness and without the use of neuromuscular blockade before tracheal tube placement, has traditionally been used for anatomically difficult airways. The 2020 Difficult Airway Society guidelines\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e provide detailed recommendations for technique, topicalization, minimal sedation, and use of video laryngoscopy. There is growing interest in applying ATI to physiologically difficult airways such as critically ill patients,\u003csup\u003e7\u003c/sup\u003e where avoidance of induction may preserve hemodynamic stability and spontaneous breathing.\u003c/p\u003e\u003cp\u003eHowever, clinical evidence in critically ill patients remains limited. A recent single-center retrospective cohort suggested that awake tracheal intubation is feasible in the ICU and may offer safety advantages when compared with conventional general anesthesia strategies.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e That study did not provide extensive adjustment for illness severity or explore the hemodynamic implications of different strategies in depth.\u003c/p\u003e\u003cp\u003eWe conducted a retrospective cohort study to evaluate the association between ATI and peri-intubation events within 30 minutes of intubation in the ICU to generate estimates that can inform the design of future trials.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and setting\u003c/h2\u003e\u003cp\u003eWe conducted a retrospective, single-center cohort study at a 743-bed academic tertiary hospital in Tokyo, Japan. Adult patients aged 18 years or older who underwent tracheal intubation in the intensive care unit (ICU) between 1 April 2018 and 31 March 2023 were eligible. Intubations performed during cardiac arrest were excluded. Two investigators (TM and MS) independently abstracted data from the electronic health record and time-stamped medication administration records using a pre-specified codebook. Discrepancies between the two abstractions were identified and resolved by consensus after repeat verification against the original source records. The institutional review board approved the study [M2023-109] and waived individual consent because risk was minimal. An opt-out mechanism was provided via notices in clinical areas and on the hospital website. Reporting follows the STROBE statement.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eExposure\u003c/h3\u003e\n\u003cp\u003eProcedures were classified into two mutually exclusive exposure categories. ATI was defined as tracheal intubation performed with airway topicalization while preserving purposeful responsiveness to verbal command. Minimal systemic sedation was permitted using low-dose opioid analgesia only, at the operator\u0026rsquo;s discretion provided that loss of responsiveness was not intended. Neither general anesthetic agents nor neuromuscular blocking agents were administered before tracheal tube placement in awake tracheal intubation. Any administration of a general anesthetic agent or neuromuscular blocking agent before tube placement led to classification as general anesthesia (GA).\u003c/p\u003e"},{"header":"Outcomes","content":"\u003cp\u003eThe primary outcome was the occurrence of peri-intubation events within 30 minutes of the start of the intubation procedure, operationalized in accordance with the INTUBE study.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e A peri-intubation event was recorded if any of the following occurred: cardiovascular instability, severe hypoxemia, or cardiac arrest. Cardiovascular instability was defined as systolic arterial pressure less than 65 mmHg recorded at least once, or systolic arterial pressure less than 90 mmHg for more than 30 minutes, or a new or increased vasopressor requirement, or an intravenous fluid bolus greater than 15 mL per kilogram. Severe hypoxemia was defined as peripheral oxygen saturation less than 80 percent. Secondary outcomes were the individual components of the primary composite and 28-day all-cause mortality.\u003c/p\u003e\u003cp\u003ePhysiological variables were extracted from ICU bedside monitor archives, where signals are recorded at 1-minute intervals. The start of the intubation procedure defined time zero. When multiple values were present within the 30-minute window after time zero, the worst value was used. Initiation or escalation of vasopressors around the time of intubation was recorded when available.\u003c/p\u003e\n\u003ch3\u003eCovariates\u003c/h3\u003e\n\u003cp\u003eCovariates were specified a priori based on clinical relevance. These included age, sex, body mass index (BMI), indication for tracheal intubation categorized as respiratory failure, shock, or airway protection including concerns for occlusion with tumor, systolic blood pressure, heart rate, and peripheral oxygen saturation at time zero, and severity of illness measured by Sequential Organ Failure Assessment (SOFA)\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e and Acute Physiology and Chronic Health Evaluation (APACHE) II\u003csup\u003e11\u003c/sup\u003e scores. Drug information was also abstracted, doses of systemic opioids, induction agents, and neuromuscular blocking agents. Drug doses are reported as mg\u0026middot;kg⁻\u0026sup1; where feasible.\u003c/p\u003e\u003cp\u003eNo formal sample size calculation was undertaken because all eligible cases within the study period were included. Baseline characteristics are presented as counts and percentages for categorical variables and as medians with interquartile ranges for continuous variables.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003ePrimary estimand and outcome model\u003c/h2\u003e\u003cp\u003eThe primary estimand was the average treatment effect (ATE) of ATI compared with GA on the risk of peri-intubation events within 30 minutes. We used g-computation\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e with marginal standardization. For each binary outcome we fitted a multivariable logistic regression with exposure and prespecified covariates: age, sex, BMI, SOFA score, APACHE II score, the indication of tracheal intubation (e.g., respiratory failure, and shock). After model fitting, we predicted each patient\u0026rsquo;s outcome probability twice, once setting exposure to awake for all patients and once setting exposure to general anesthesia for all patients, while keeping covariates at observed values. Averaging these predicted probabilities yielded the adjusted risk under each strategy. From these marginal risks we derived the adjusted risk difference as the primary contrast and also reported the risk ratio and the number needed to treat or harm, calculated as 1 divided by the absolute value of the risk difference with the sign indicating benefit or harm. When the confidence interval for the risk difference crossed zero, we did not present NNT or NNH.\u003c/p\u003e\u003cp\u003eUncertainty was quantified with nonparametric bootstrap at the patient level. At each replicate we refitted the outcome model and recomputed all marginal quantities. We used 1,000 replicates and percentile 95% confidence intervals. The random seed was fixed. We focused on effect sizes and intervals rather than p-values. To examine model dependence on the risk-ratio scale we fitted a modified Poisson regression with a log link and robust (sandwich) standard errors and reported the adjusted risk ratio.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eSensitivity analyses addressing confounding by indication\u003c/h3\u003e\n\u003cp\u003eTo assess sensitivity to residual confounding we performed propensity score matching\u003csup\u003e\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e and entropy balancing.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e For propensity score matching, we estimated the score with logistic regression that included the same covariates as the outcome model, then applied 1:1 nearest-neighbor matching without replacement using a caliper equal to 0.25 of the standard deviation of the logit of the propensity score. We evaluated covariate balance with absolute standardized mean differences and used 0.10 or less as a practical target. On the matched sample we estimated marginal risks, risk differences, and risk ratios using the matching weights, and we obtained confidence intervals by repeating the entire matching procedure within each bootstrap replicate. This analysis targets the average treatment effect in the treated population. We also reported the effective sample size for the matched sample.\u003c/p\u003e\u003cp\u003eFor entropy balancing, we constructed weights that enforced exact mean balance on all prespecified covariates and then estimated weighted marginal risks, risk differences, and risk ratios. Confidence intervals were obtained by repeating the reweighting within each bootstrap replicate. This analysis targets the average treatment effect in the full cohort. As diagnostics we summarized the distribution of weights, documented extreme values and any capping if applied, and reported the effective sample size.\u003c/p\u003e\n\u003ch3\u003eRare outcomes\u003c/h3\u003e\n\u003cp\u003eFor very rare outcomes such as cardiac arrest, we reported group-specific risks with exact Clopper-Pearson intervals and risk differences with Newcombe score intervals. When applicable, we considered Firth logistic regression as a supplementary analysis and reported results in the supplement.\u003c/p\u003e\u003cp\u003eAnalyses were conducted using SAS version 9.4 (SAS Institute, Cary, NC, USA) and R version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePatient selection and data quality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the study period, 553 ICU tracheal intubation episodes were screened; 342 met all inclusion and no exclusion criteria and were analyzed (Figure 1). There were no missing data in exposure, outcomes, or prespecified covariates. Awake tracheal intubation (ATI) accounted for 48/342 episodes (14.0%). Propensity-score matching (1:1) yielded a matched subset of 92 episodes (46 per group) that we used only for sensitivity analyses. Baseline characteristics in the full cohort are shown in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1.\u0026nbsp;\u003c/strong\u003ePatient flow for the ICU intubation cohort.\u003c/p\u003e\n\u003cp\u003eOf 553 intubations screened, 342 met eligibility for analysis. Exposure groups were awake tracheal intubation (ATI) in 48 patients and general anesthesia in 294. The propensity score\u0026ndash;matched cohort included 92 patients (46 per group).\u003c/p\u003e\n\u003cp\u003eTable 1. Baseline characteristics by exposure (with standard mean difference)\u003c/p\u003e\n\u003cp\u003eNotes: Continuous variables are shown as median [IQR], and categorical variables as n (%). Standardized mean differences (SMD) were computed as the difference in means divided by the pooled SD for continuous variables, and as the difference in proportions divided by \u0026radic;{p(1\u0026minus;p)} for binary variables. SOFA and APACHE II were assessed within 24 hours from ICU admission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExposure verification and baseline profile\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the ATI group, no episode received a general anesthetic (e.g., propofol, midazolam) or a neuromuscular blocker before tracheal tube placement; when present, systemic sedation consisted of low-dose fentanyl only (Table 1). Compared with GA, ATI episodes were generally younger, had lower BMI, higher SOFA and APACHE II scores, and more frequent shock with lower systolic blood pressure and lower SpO₂ at time zero (Table 1). The main indication for intubation was respiratory failure (296/342, 86.6%), followed by shock (33/342, 9.6%) and airway protection (21/342, 6.1%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrimary outcome: peri-intubation composite\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe crude incidence of the composite peri-intubation event within 30 min was 50.2% (172/342) overall, 18.8% (9/48) with ATI vs 55.4% (163/294) with GA.\u003c/p\u003e\n\u003cp\u003eIn the primary analysis using g-computation (marginal standardization of a multivariable logistic model), the adjusted risk of the composite was 0.170 (95% CI, 0.069\u0026ndash;0.296) with ATI and 0.558 (95% CI, 0.498\u0026ndash;0.617) with GA, yielding an adjusted risk difference\u0026nbsp;\u0026minus;0.388 (95% CI,\u0026nbsp;\u0026minus;0.508 to\u0026nbsp;\u0026minus;0.251), an adjusted risk ratio 0.305 (95% CI, 0.120\u0026ndash;0.534), and a number needed to treat 2.58.\u003c/p\u003e\n\u003cp\u003eTable 2. Adjusted risks and effect estimates using g-computation analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNotes.\u0026nbsp;\u003c/strong\u003eAdjusted risks estimated via g-computation (logistic regression with marginal standardization). Covariates: age, sex, BMI, SOFA, APACHE II, and indication (respiratory failure, shock). RD (ATI\u0026minus;GA) is in percentage points; negative values favor ATI. 95% CIs from nonparametric patient-level bootstrap (1,000 replicates; percentile method). NNT/NNH is 1/|RD| and shown only when the CI does not cross 0. Outcomes assessed within 30 minutes from intubation start. Abbreviations: ATI=awake tracheal intubation; GA=general anesthesia; RD=risk difference; RR=risk ratio; CI=confidence interval; NNT/NNH=number needed to treat/harm.\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSecondary outcomes: components of peri-intubation events\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor cardiovascular instability, adjusted risks were 0.165 (95% CI, 0.065\u0026ndash;0.285) with ATI and 0.470 (95% CI, 0.414\u0026ndash;0.529) with GA; RD\u0026nbsp;\u0026minus;0.305 (95% CI,\u0026nbsp;\u0026minus;0.426 to\u0026nbsp;\u0026minus;0.180), RR 0.352 (95% CI, 0.136\u0026ndash;0.614), NNT 3.28. For severe hypoxemia, adjusted risks were 0.023 (95% CI, 0\u0026ndash;0.060) with ATI and 0.168 (95% CI, 0.127\u0026ndash;0.213) with GA; RD\u0026nbsp;\u0026minus;0.144 (95% CI,\u0026nbsp;\u0026minus;0.202 to\u0026nbsp;\u0026minus;0.091), RR 0.139 (95% CI, 0\u0026ndash;0.381), NNT 6.93. All adjusted estimates appear in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMortality and peri-intubation cardiac arrest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwenty-eight\u0026ndash;day all-cause mortality was 18.4% (63/342). Adjusted risks were 0.301 (95% CI, 0.176\u0026ndash;0.427) with ATI and 0.181 (95% CI, 0.139\u0026ndash;0.224) with GA; RD +0.119 (95% CI,\u0026nbsp;\u0026minus;0.008 to +0.252), RR 1.66 (95% CI, 0.957\u0026ndash;2.56). Thus, mortality did not differ statistically and may be influenced by confounding by indication. Peri-intubation cardiac arrest occurred once in each group (2/342, 0.6% overall); given rarity, group-specific risks with exact Clopper-Pearson CIs and the Newcombe CI for the risk difference are reported in Table S5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSensitivity analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFindings were directionally consistent across sensitivity analyses. Modified Poisson regression with robust variance produced risk ratios similar in magnitude and direction to the g-computation estimates (Table S4). Propensity-score matching (ATT target) and entropy balancing (ATE target) yielded comparable risk differences and ratios (Tables S2\u0026ndash;S3); propensity-score overlap was limited, especially for GA at low scores (Figure S1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of unmeasured confounding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eE-values\u003csup\u003e20\u003c/sup\u003e indicated that relatively strong unmeasured confounding would be required to fully explain the protective association of ATI for the composite and its components. For the composite (g-computation), the E-value for the point estimate RR 0.305 was 6.01, and 3.15 for the confidence limit closest to the null. For cardiovascular instability, the corresponding E-values were 5.13 and 2.64; for severe hypoxemia, 13.91 and 4.69. For 28-day mortality (RR 1.66), the E-value was 2.71 and 1.00 for the CI limit, consistent with the CI spanning the null (Table S6).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAmong critically ill adults undergoing emergent tracheal intubation in the ICU, awake tracheal intubation (ATI) was associated with a substantially lower risk of peri-intubation events within 30 minutes compared with general anesthesia. After g-computation (standardized risks), the estimated risk was 0.170 with ATI versus 0.558 with general anesthesia, corresponding to an adjusted risk difference of \u0026minus;\u0026thinsp;0.388 (95% CI \u0026minus;\u0026thinsp;0.508 to \u0026minus;\u0026thinsp;0.251) and a risk ratio of 0.305 (95% CI 0.120\u0026ndash;0.534), yielding an NNT of ~\u0026thinsp;3. Results were directionally consistent across sensitivity analyses using propensity-score matching (ATT) and entropy balancing (ATE). The primary association was moderately robust to unmeasured confounding: the E-value for the point estimate was 6.0 (and 3.1 for the confidence limit closest to the null). Reductions were evident for both cardiovascular instability and severe hypoxemia. On the other hand, 28-day mortality did not differ significantly between groups, and peri-intubation cardiac arrest was rare (1 event per group), limiting precision for those outcomes.\u003c/p\u003e\u003cp\u003eWe used a prespecified causal framework with marginal standardization to estimate risk differences and risk ratios on the probability scale. The primary analysis relied on g-computation with nonparametric bootstrap confidence intervals. We then targeted complementary estimands: the average treatment effect on the treated (ATT) through propensity score matching, and the average treatment effect (ATE) through entropy balancing. Modified Poisson regression with robust variance offered an independent check of the relative risk. For rare outcomes we reported exact interval estimates. We verified exposure fidelity and reported component outcomes separately. We assessed overlap, effective sample sizes, and weight distributions to detect instability. There were no missing data in exposures, outcomes, or covariates, which reduced the need for imputation. E-value analyses indicated that an unmeasured confounder would need to be strong and similarly associated with exposure and outcome to move the estimates to the null. Together, these steps support internal validity and reduce model and design dependence.\u003c/p\u003e\u003cp\u003eThe existing literature has established that emergency tracheal intubation in the critically ill patients carries a high risk of peri-intubation life-threatening complications. Large multicenter cohorts\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e have reported that roughly half of critically ill patients experience at least one adverse event during or shortly after intubation, and that cardiac arrest, while uncommon, is not rare. Multiple randomized controlled trials have attempted to reduce these events by optimizing precautious fluid bolus administration,\u003csup\u003e23,24\u003c/sup\u003e precautious inotropic support,\u003csup\u003e25\u003c/sup\u003e and pre-oxygenation strategy including high-flow nasal cannula\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e within a rapid sequence induction paradigm. These trials have largely failed to produce consistent or clinically meaningful reductions in severe hypoxemia or hemodynamic instability. As a result, the field knows a great deal about how often complications occur, but far less about whether a different physiologic strategy could reduce the burden of harm.\u003c/p\u003e\u003cp\u003eThis gap motivates a focused clinical question. Rapid sequence induction couples a bolus of induction agents that depress myocardial contractility\u003csup\u003e\u003cspan additionalcitationids=\"CR28 CR29 CR30\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e with neuromuscular blockade that abolishes respiratory effort. In physiologically unstable patients, this combination can lower cardiac output and remove the patient\u0026rsquo;s own spontaneous breathing effort at the precise moment airway instrumentation occurs. Awake tracheal intubation represents a contrasting strategy. It preserves spontaneous ventilation, allows stepwise topical anesthesia and titrated analgesia, and can be conducted without the abrupt hemodynamic shifts that follow induction. Despite being codified for difficult airway management,\u003csup\u003e4\u003c/sup\u003e awake tracheal intubation techniques have rarely been evaluated in critically ill populations, and the few available reports are single-center and retrospective.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e The clinical question is whether, in real practice, awake tracheal intubation is associated with fewer peri-intubation events than general anesthesia.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e Our findings address this question directly and show large, directionally consistent reductions in the composite and its components across analytic approaches. We also observed no clear difference in 28-day mortality.\u003c/p\u003e\u003cp\u003eThe present study contributes three advances that address the gap and support future trial design. First, we move beyond device-oriented comparisons inside rapid sequence induction and instead contrast two competing clinical strategies. We verify exposure fidelity and describe drug use patterns, which clarifies what \u0026ldquo;awake\u0026rdquo; and \u0026ldquo;general anesthesia\u0026rdquo; meant at the bedside. Second, we estimate effects on the probability scale using g-computation with marginal standardization as the primary analysis, and we probe robustness with propensity score matching for the treated population and entropy balancing for the average population. This approach yields adjusted absolute risks, risk differences, and risk ratios for the composite outcome and its components, along with numbers needed to treat. Third, we provide diagnostics that matter for translation. We assess covariate balance, overlap, effective sample sizes, and weight distributions, and we quantify the strength of unmeasured confounding needed to explain away the findings using E-values. Together these elements supply the control event rates, effect size ranges, and feasibility signals needed to power a pragmatic trial that compares awake intubation with rapid sequence induction in the ICU.\u003c/p\u003e\u003cp\u003eIn summary, the novelty of this work is conceptual and practical. Conceptually, it reframes airway management for the critically ill from marginal tweaks within rapid sequence induction to a choice between physiologic strategies. Practically, it delivers the epidemiologic inputs and robustness checks required to advance from observational insight to a definitive randomized trial.\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, it was a retrospective single-center cohort restricted to ICU intubations, so causal relationships cannot be inferred and generalizability to emergency departments, wards, or other institutions may be limited. Second, confounding by indication may persist despite multivariable adjustment including propensity score matching and entropy balancing, unmeasured factors such as operator judgement, airway difficulty, and periprocedural strategy could still influence both exposure and outcomes. Third, although data abstraction was performed independently by two investigators using a pre-specified codebook and discrepancies were resolved against source records, retrospective chart review is susceptible to information bias and lack of blinding. Fourth, several procedural variables were unavailable, including number of attempts, duration of the procedure, formal airway assessments, and operator experience, all of which may affect outcomes. Fifth, event counts for cardiac arrest were very low, which necessitated Firth\u0026rsquo;s penalized regression and resulted in imprecise estimates for that component and for 28-day mortality; the study was not powered to detect differences in these endpoints. Finally, outcomes followed INTUBE definitions within a 30-minute window and were derived from the worst recorded values. Although ICU monitoring at 1-minute resolution reduces misclassification, different outcome definitions or windows might yield different estimates.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this retrospective single-center ICU cohort, awake tracheal intubation was associated with a lower incidence of peri-intubation events, chiefly cardiovascular instability. These findings are hypothesis generating and warrant prospective evaluation in clearly defined high-risk groups.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAPACHE II\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAcute Physiology and Chronic Health Evaluation II\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eATE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAverage treatment effect\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eATT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAverage treatment effect on the treated\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eATI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAwake tracheal intubation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBody mass index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEntropy balancing\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEHR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eElectronic health record\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eESS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEffective sample size\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGeneral anesthesia\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHeart rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICU\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eIntensive care unit\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInterquartile range\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIRB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInstitutional review board\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNNT / NNH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNumber needed to treat / Number needed to harm\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePropensity score\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePSM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePropensity score matching\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRisk difference\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRisk ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRSI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRapid sequence induction\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSBP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSystolic blood pressure\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSOFA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSequential Organ Failure Assessment\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSpO₂\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePeripheral oxygen saturation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSTROBE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStrengthening the Reporting of Observational Studies in Epidemiology\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003e The present study was approved by the Tokyo Medical and Dental University Institutional Review Board (approval M2023-109). Because this was a retrospective chart review using de-identified data, the IRB waived the requirement for informed consent.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eAuthors\u0026rsquo; information\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eTM and MS contributed equally to this work. They conceived and planned the study, collected the data, and drafted the manuscript. TM and RK performed the data analyses and contributed to manuscript revision. AH supervised the study and critically revised the manuscript. All authors reviewed and interpreted the results, approved the final version, and agree to be accountable for all aspects of the work.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003e We wish to thank Kenji Wakabayashi, the director of the intensive care unit of Institute of Science Tokyo Hospital for providing constructive comments and supervision on this study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRussotto V, Myatra SN, Laffey JG, et al. Intubation Practices and Adverse Peri-intubation Events in Critically Ill Patients From 29 Countries. 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J Clin Anesth 2022;80:110846. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jclinane.2022.110846\u003c/span\u003e\u003cspan address=\"10.1016/j.jclinane.2022.110846\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmischney NJ, Nicholson WT, Brown DR, et al. Ketamine/propofol admixture vs etomidate for intubation in the critically ill: KEEP PACE Randomized clinical trial. J Trauma Acute Care Surg 2019;87(4):883\u0026ndash;891. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/TA.0000000000002448\u003c/span\u003e\u003cspan address=\"10.1097/TA.0000000000002448\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKotani Y, Piersanti G, Maiucci G, et al. Etomidate as an induction agent for endotracheal intubation in critically ill patients: A meta-analysis of randomized trials. J Crit Care 2023;77:154317. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jcrc.2023.154317\u003c/span\u003e\u003cspan address=\"10.1016/j.jcrc.2023.154317\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGreer A, Hewitt M, Khazaneh PT, et al. Ketamine Versus Etomidate for Rapid Sequence Intubation: A Systematic Review and Meta-Analysis of Randomized Trials. Crit Care Med 2025;53(2):e374-e383. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/CCM.0000000000006515\u003c/span\u003e\u003cspan address=\"10.1097/CCM.0000000000006515\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRussotto V, Tassistro E, Myatra SN, et al. Peri-intubation Cardiovascular Collapse in Patients Who Are Critically Ill: Insights from the INTUBE Study. Am J Respir Crit Care Med 2022;206(4):449\u0026ndash;458. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1164/rccm.202111-2575OC\u003c/span\u003e\u003cspan address=\"10.1164/rccm.202111-2575OC\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLapinsky SE. Tracheal intubation in the critically ill: just say no to drugs. Br J Anaesth 2012;109(2):287; author reply 287-8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bja/aes238\u003c/span\u003e\u003cspan address=\"10.1093/bja/aes238\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMasuda T, Nosaka N, Nagashima M. Intubation Practices and Adverse Peri-intubation Events in Critically Ill Patients. JAMA 2021;326(6):568\u0026ndash;569. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/jama.2021.8529\u003c/span\u003e\u003cspan address=\"10.1001/jama.2021.8529\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 and 2 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"awake tracheal intubation, airway management, critical illness, peri-intubation complications.","lastPublishedDoi":"10.21203/rs.3.rs-7942044/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7942044/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eTracheal intubation in critically ill adults often precipitates peri-intubation events including severe cardiovascular instability, severe hypoxemia, and cardiac arrest. Awake tracheal intubation (ATI) may mitigate these risks, yet evidence from intensive care units (ICUs) remains limited. We evaluated whether ATI is associated with fewer peri-intubation events than induction of general anesthesia (GA).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe performed a retrospective, single-center cohort study of consecutive adults undergoing ICU tracheal intubation from April 2018 through March 2023. The exposure was ATI versus GA. The primary outcome was a composite peri-intubation event within 30 minutes of procedure start, comprising cardiovascular instability, severe hypoxemia, or cardiac arrest. Secondary outcomes were the composite components and 28-day all-cause mortality. The primary analysis estimated adjusted marginal risks using g-computation with multivariable logistic regression and marginal standardization. Uncertainty was quantified with nonparametric bootstrap. Robustness was examined with modified Poisson regression, 1:1 propensity score matching (targeting ATT), and entropy balancing (targeting ATE).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOf 553 screened episodes, 342 met criteria. The composite occurred in 172 of 342 patients (50.2%) overall (ATI 9 of 48 [18.8%] vs GA 163 of 294 [55.4%]). After adjustment, the estimated risk of the composite was 0.170 (95% CI, 0.069\u0026ndash;0.296) with ATI and 0.558 (0.498\u0026ndash;0.617) with GA, yielding an adjusted risk difference of \u0026minus;\u0026thinsp;0.388 (\u0026minus;\u0026thinsp;0.508 to \u0026minus;\u0026thinsp;0.251) and a risk ratio of 0.305 (0.120\u0026ndash;0.534). Component analyses suggested lower adjusted risks of cardiovascular instability and severe hypoxemia with ATI. Findings were directionally consistent in propensity score-matched and entropy-balanced analyses. 28-day mortality did not differ significantly (adjusted risk 0.301 with ATI vs 0.181 with GA; risk difference\u0026thinsp;+\u0026thinsp;0.119, 95% CI \u0026minus;\u0026thinsp;0.008 to +\u0026thinsp;0.252). Cardiac arrest was rare (1 event per group). No ATI-attributable safety signals were identified.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eIn this single-center ICU cohort, ATI was associated with substantially fewer peri-intubation events than GA, with convergent estimates across complementary analytic approaches. These hypothesis-generating data support considering ATI for physiologically fragile patients and motivate pragmatic trials to define patient selection and implementation strategies.\u003c/p\u003e","manuscriptTitle":"Association Between Awake Tracheal Intubation and Peri-Intubation Events in Critically Ill Patients: A Single-Center Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-10 16:16:25","doi":"10.21203/rs.3.rs-7942044/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2aae7364-6d6e-4631-868c-f3652f4367ba","owner":[],"postedDate":"November 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-11T03:38:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-10 16:16:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7942044","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7942044","identity":"rs-7942044","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}