Assessing the Futility of Thrombolysis in Out-of-Hospital Cardiac Arrest. A Retrospective Cohort study.

Assessing the Futility of Thrombolysis in Out-of-Hospital Cardiac Arrest. 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A Retrospective Cohort study. Alan Cowley, Dan Cody, Eleanor Jaquet, Magnus Nelson This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5198608/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 Thrombolysis has been considered a potential intervention to improve outcomes in out-of-hospital cardiac arrest (OHCA). This retrospective cohort study aimed to evaluate whether thrombolysis offers any meaningful survival benefit by assessing 30-day survival and return of spontaneous circulation (ROSC) upon hospital arrival, with a focus on demonstrating futility. Methods Data from a single-centre registry, comprising 2,862 OHCA patients, including 171 who received thrombolysis, were analysed. Logistic regression was employed to calculate unadjusted and adjusted odds ratios (OR) with 95% confidence intervals (CI) for the primary outcome of 30-day survival and the secondary outcome of ROSC. Results The 30-day survival rate in the thrombolysis group was 4%, substantially lower than in the non-thrombolysis group. The unadjusted odds ratio (OR) for survival with thrombolysis was 0.36 (95% CI 0.16–0.81), and after adjusting for confounders, the OR decreased to 0.08 (95% CI 0.04–0.19), indicating a significantly reduced likelihood of survival with thrombolysis. The adjusted OR for achieving return of spontaneous circulation (ROSC) was 0.21 (95% CI 0.14–0.33), suggesting a similarly diminished likelihood of ROSC with thrombolysis. Both models were highly significant for predictors such as shockable rhythm (OR 15.89 for survival, OR 4.14 for ROSC), witnessed bystander CPR (OR 1.99 for survival, OR 2.04 for ROSC). A MacFaddens R-squared value of 0.27 for the primary outcome, represents a moderate model fit at best. Conclusion Thrombolysis administration in OHCA was associated with a significant reduction in both 30-day survival and ROSC rates, demonstrating the futility of thrombolysis in improving outcomes in this context. The poor fit of the regression models underscores the need for further investigation to identify additional factors that may impact survival, and to reevaluate the use of thrombolysis in OHCA management. Thrombolysis Out-of-Hospital Cardiac Arrest Tenecteplase Return of Spontaneous Circulation Survival Outcomes Ambulance Paramedic Figures Figure 1 BACKGROUND Clinical trials have demonstrated the efficacy and safety of thrombolytic medications in certain controlled situations, such as ST-elevation myocardial infarction and massive pulmonary embolism, where international guidance recommends thrombolysis as a first- or second-line therapy [ 1 – 2 ]. However, evidence regarding the use of thrombolysis in out-of-hospital cardiac arrest (OHCA) is limited. While some case studies suggest potential benefits [e.g., 3], the overall body of evidence shows no clear mortality advantage [e.g., 4–5], and a recent study cautiously suggests inferiority [ 6 ]. Previous studies have often been of low quality or marked by heterogeneity in the thrombolytic agents used, as well as variations in dosing strategies. Within the South East Coast Ambulance Service NHS Foundation Trust (SECAmb), thrombolysis is administered by Critical Care Paramedics (CCPs) using Tenecteplase, a tissue-type plasminogen activator. Tenecteplase promotes blood clot breakdown by converting plasminogen into plasmin, the enzyme responsible for clot dissolution. While other thrombolytics are available and commonly used in-hospital, Tenecteplase remains the most pragmatic option for UK paramedics due to its inclusion in Schedule 17 of the Human Medicines Regulations 2012, as well as its simpler dosing regimen compared to alternatives. In SECAmb, Tenecteplase is primarily used by CCPs for suspected thrombo-embolic causes of cardiac arrest and, rarely, for ST-elevation myocardial infarction (STEMI) where timely access to primary percutaneous coronary intervention (PPCI) is unavailable. In the context of out-of-hospital cardiac arrest (OHCA), thrombolysis is used selectively by CCPs when a thromboembolic aetiology is strongly suspected. Specifically, Tenecteplase is administered in cases where pulmonary embolism (PE) is believed to be the precipitating cause of cardiac arrest, based on clinical indicators such as sudden cardiac collapse in a patient with known venous thromboembolism risk factors, absence of other obvious causes, and specific rhythm presentations (e.g., pulseless electrical activity with high suspicion of PE). Additionally, thrombolysis may be considered in rare instances of STEMI-induced cardiac arrest where there is significant delay in access to primary percutaneous coronary intervention (PPCI). However, the decision to administer Tenecteplase is typically made in the absence of definitive diagnostic tools, relying on clinical judgment and prehospital protocols. This retrospective cohort study aims to explore the futility of thrombolysis in the prehospital management of OHCA, focusing on safety, efficacy, and patient outcomes. The standardised use of a single thrombolytic drug in a homogeneous protocol offers an opportunity to assess whether thrombolysis provides any real-world benefit in this context. The study is particularly valuable for several reasons: Real-World Evidence : While clinical trials and in-hospital data provide insights into the safety and efficacy of thrombolytic medications, they often exclude the diverse and complex prehospital patient population encountered in routine clinical practice. This study will contribute real-world evidence on the effectiveness of Tenecteplase in OHCA, focusing on futility in improving survival. Prehospital Protocol Optimisation : Understanding whether thrombolysis improves outcomes in OHCA can help refine prehospital treatment protocols for cardiac emergencies. If thrombolysis is shown to offer no meaningful benefit, this study can inform decisions to avoid unnecessary interventions, redirecting resources to more effective treatments. Patient Outcomes : This study will evaluate the relationship between prehospital thrombolysis and key clinical outcomes, specifically return of spontaneous circulation (ROSC) at hospital arrival and 30-day survival. Demonstrating futility in these outcomes would provide important evidence against the routine use of thrombolysis in OHCA. Decision-Making and Resource Allocation : The findings could help guide policy decisions regarding the allocation of resources, including the use of thrombolytic drugs in prehospital settings. Demonstrating futility would also impact training priorities for paramedics and CCPs, allowing resources to be directed to interventions with proven efficacy. Addressing an Evidence Gap : Despite the widespread use of thrombolysis in prehospital settings for acute cardiac emergencies, there is a paucity of real-world data specifically evaluating its efficacy in OHCA. This study seeks to fill that gap, with a focus on whether thrombolysis should continue to be employed in this context. This study, by evaluating the futility of thrombolysis in improving survival outcomes in OHCA, will provide important insights for clinical practice and decision-making in prehospital emergency care. METHODS Patient Population Due to the low frequency of thrombolysis administration in out-of-hospital cardiac arrest (OHCA) cases, data for the thrombolysis group were collected over five years to gather a sufficient sample size for meaningful analysis. In contrast, the non-thrombolysis control group data were collected within a single year, where the higher volume of cases allowed for a more substantial sample size for comparison. The study included adult patients (≥ 18 years) who experienced OHCA between 1st April 2022 and 31st March 2023 (control group), and from the establishment of the cardiac arrest registry to 31st March 2023 (thrombolysis group), with advanced life support provided by clinicians from the South East Coast Ambulance Service NHS Foundation Trust (SECAmb). Patients were excluded if they were known to be pregnant or if their cardiac arrest was caused by a known or suspected traumatic event. This selection was made to focus specifically on medical causes of OHCA and to avoid the confounding effects of trauma-related arrests, which have different underlying pathophysiology and response to treatments like thrombolysis. The remaining patients were divided into two groups based on whether they received thrombolysis from a Critical Care Paramedic (CCP) during the prehospital phase of care. Due to the low number of thrombolysis cases, yearly breakdowns were not provided to maintain patient anonymity. As a result, trends in thrombolysis use and outcomes over time could not be formally analysed. Primary and Secondary Outcomes Primary Outcome : The primary outcome was the rate of survival at 30 days post-arrest. This outcome was selected to assess the long-term effects of thrombolysis in OHCA patients. As the study was designed to investigate futility, the aim was to determine whether thrombolysis fails to improve survival rates at 30 days, particularly when compared to the control group. Secondary Outcome : The secondary outcome was the rate of return of spontaneous circulation (ROSC) at hospital arrival. ROSC was defined as the return of a palpable pulse and/or measurable blood pressure following resuscitation efforts. These data were collected from prehospital patient care records as documented by attending ambulance staff. ROSC was considered present if sustained until hospital arrival; transient or brief ROSC events without sustained circulation were not included in the analysis. Defibrillator recordings were not systematically reviewed to confirm ROSC duration, so documentation relied on clinician-reported outcomes. This outcome aimed to investigate whether thrombolysis could lead to early success in resuscitation. However, as the study investigates futility, it sought to assess whether thrombolysis has minimal or no benefit in achieving ROSC compared to the control group. This observational study adhered to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines to ensure rigorous reporting of its design, methodology, and results. The STROBE checklist was followed throughout the study, focusing on transparency in participant selection, data collection, and statistical analysis STATISTICAL ANALYSIS Patient Population and Sample Size Considerations A basic review of the clinical records revealed approximately 170 administrations of thrombolysis within the study period. Given the low frequency of thrombolysis in out-of-hospital cardiac arrest (OHCA), this number of cases was necessary to conduct a meaningful analysis. It is assumed that the majority of these cases involved OHCA patients, though a detailed breakdown was not available for all instances. Due to the small number of survivors in the thrombolysis group, a basic power calculation indicated that to detect a meaningful difference in survival to 30 days, an effect size of approximately 72% would be needed to achieve 80% power (α = 0.05). This is based on the national survival rate for OHCA, which is approximately 8.3%. In contrast, for return of spontaneous circulation (ROSC) at the hospital, a much smaller effect size (33%) would be necessary, given the typical ROSC rate of around 30% in OHCA patients. As the required effect sizes are large and the sample size for thrombolysis is small, it is likely that the study will not reach 80% power, especially for the primary outcome of survival. Given these constraints, a post-hoc power analysis was conducted to assess the actual statistical power of the study after data collection. This helped gauge how well the study was powered to detect potential differences, despite the limitations posed by a small number of survivors. Descriptive Statistics Descriptive statistics were used to summarise the baseline characteristics of the study cohort. Means, medians, standard deviations, and frequencies were calculated for variables such as patient demographics, initial cardiac arrest rhythm, time to first intervention, and other relevant factors. This step provided an overview of the cohort and the distribution of key clinical characteristics. Comparative Analysis A comparative analysis was conducted to assess the differences between patients who received thrombolysis and those who did not. The following statistical tests were employed to evaluate the association between thrombolysis administration and the primary and secondary outcomes: Chi-Square Test or Fisher's Exact Test : These tests were used to assess the association between thrombolysis and the primary outcome (30-day survival) as well as the secondary outcome (ROSC at hospital). Given the small number of survivors, Fisher's Exact Test was preferred for its ability to handle small, expected frequencies. Comparative Analysis : The rates of survival at 30 days and ROSC at the hospital were compared between the thrombolysis and control groups to evaluate the potential efficacy of thrombolysis in improving these outcomes. However, given the low survival rate in the thrombolysis group, this analysis focused on demonstrating futility. Logistic Regression Analysis To investigate the association between thrombolysis and the primary and secondary outcomes while adjusting for potential confounders, logistic regression analysis was performed. This approach allows for the evaluation of multiple variables simultaneously, adjusting for confounding factors that may influence survival or ROSC outcomes. The following types of logistic regression were used: Univariable Logistic Regression : This analysis assessed the relationship between thrombolysis (Yes/No) and binary outcomes (e.g., survival) without considering other variables. This model provides a basic understanding of the association between thrombolysis and outcomes. Multivariable Logistic Regression : This more comprehensive approach adjusted for multiple factors, such as age, presenting rhythm, and intra-arrest circumstances, allowing for a better understanding of the independent association between thrombolysis and outcomes. This analysis aimed to evaluate the futility of thrombolysis after controlling for important confounders. The following confounders were included in the multivariable logistic regression model to adjust for potential biases: age, gender, witnessed status, initial rhythm and presence of bystander CPR. These variables were selected based on their established relevance to OHCA outcomes. Odds Ratios and Confidence Intervals The odds ratios (OR) and corresponding 95% confidence intervals (CI) were derived from the logistic regression output. These measures were calculated as the exponentiated coefficients from the logistic regression model, providing insight into the strength and direction of the association between thrombolysis and the likelihood of specific outcomes (such as survival). Odds Ratios (OR) : An odds ratio greater than 1 indicates a higher likelihood of the outcome associated with thrombolysis administration. Conversely, an OR less than 1 suggests a reduced likelihood of the outcome with thrombolysis. Given the study's futility design, an OR less than 1 would indicate a poorer outcome with thrombolysis. 95% Confidence Intervals (CI) : The CI represents the range within which the true odds ratio is likely to fall with 95% confidence. A wide CI, especially if it includes 1.0, suggests that the estimate is imprecise, which may be due to the small sample size and low number of survivors in the thrombolysis group. Post-Hoc Power Analysis A post-hoc power analysis was conducted to assess the statistical power of the study after data collection. This analysis estimated the likelihood of detecting a true effect based on the observed sample size, effect size, and significance level. A power of 0.8 or higher is typically considered sufficient, but given the small number of survivors and large effect sizes required, the power in this study was likely lower than optimal. The post-hoc analysis helped quantify the study’s ability to detect significant differences, highlighting the challenges posed by the sparse data. RESULTS Patients and Interventions Patients A total of 2,829 patients who experienced out-of-hospital cardiac arrest (OHCA) were included in this retrospective cohort study (see Fig. 1). Among these, 171 patients received Thrombolysis as part of their resuscitation efforts, administered by Critical Care Paramedics (CCPs) in line with the South East Coast Ambulance Service NHS Foundation Trust’s clinical practice guidelines. The demographic and clinical characteristics of the patients are summarized in Table 1. The mean age of the study population was 67.5 years (SD = 15), with 66% of patients being male. The characteristics of patients in the Thrombolysis group were compared to those in the non-Thrombolysis control group, comprising 2,658 patients, to identify potential differences in baseline characteristics and outcomes. Interestingly, the thrombolysis group had a significantly higher proportion of VT/VF as the presenting rhythm (58%) compared to the non-thrombolysis group (23%). Given that VT/VF is typically associated with better survival outcomes (historically 20%-25%), the lower survival rate in the thrombolysis group (4%) is unexpected and warrants further exploration. Interventions The primary intervention of interest was the administration of Thrombolysis to patients presenting with OHCA. Thrombolysis was administered based on clinical guidelines, primarily for cases where a thromboembolic cause was suspected or confirmed. The Thrombolysis was administered alongside standard Advanced Life Support (ALS) procedures, in accordance with the established prehospital protocols for OHCA management. In contrast, the control group (2,658 patients) received only standard ALS, without thrombolytic intervention. Both groups were managed under comparable prehospital care protocols, with uniformity in the application of ALS procedures. However, post-arrival at various hospitals, interventions were beyond the control of the research team. While all receiving hospitals were Level 1 emergency departments, access to advanced interventions, such as targeted temperature management and primary percutaneous coronary intervention (PPCI), varied between institutions, and could have influenced the study outcomes. Primary and Secondary Outcomes Primary Outcome The primary outcome, 30-day survival, was significantly lower in the Thrombolysis group compared to the non-Thrombolysis group. The survival rate in the Thrombolysis group was 4%, whereas the non-Thrombolysis group had a survival rate of 9%. The unadjusted odds ratio (OR) for survival at 30 days in the Thrombolysis group was 0.36 (95% CI: 0.16–0.81), indicating a lower likelihood of survival in the Thrombolysis group. After adjusting for potential confounders, the adjusted OR was 0.08 (95% CI: 0.04–0.19), showing a statistically significant worsening in survival with thrombolysis compared to the control group. However, the model fit was poor-moderate (R² = 0.27), suggesting that the logistic regression model may not fully capture all the variables influencing survival and that the results should be interpreted with caution. The modest fit further underscores the need for caution in drawing conclusions from the adjusted analysis. Secondary Outcome The secondary outcome of return of spontaneous circulation (ROSC) at hospital arrival was assessed. The ROSC rate was significantly higher in the Thrombolysis group compared to the non-Thrombolysis group. However, while this finding was statistically significant, the clinical relevance of this result is unclear, particularly since it did not translate into improved long-term survival. The ROSC rates and statistical comparisons are detailed in Table 2. To provide a clearer understanding of the influence of confounders, Tables 3 and 4, and Figs. 2 and 3, present the full logistic regression estimates for all covariates, including odds ratios, confidence intervals, and p-values. These results highlight the substantial impact of factors such as age, initial rhythm, and witnessed status on survival outcomes. Subgroup Analysis Given the primary objective to assess the impact of Tenecteplase on 30-day survival rates, subgroup analyses were intended to explore whether there were any differential effects of thrombolysis based on key variables such as age, gender, witnessed arrest, and presenting rhythm. However, the logistic regression model demonstrated a poor to moderate fit to the data, as indicated by a low to moderate R-squared value and lack of model compliance. As a result, reliable subgroup analyses were not feasible, and meaningful interpretations for specific subgroups could not be derived. The substantial limitations in the data quality and model fit suggest that the observed relationships in the overall cohort may not hold consistently within these subgroups. Although the study intended to explore subgroups to identify whether Tenecteplase had differential effects, these analyses were compromised by the aforementioned model limitations. Given the lack of robust results, any conclusions drawn about subgroup differences should be treated with caution. Post-Hoc Power Analysis A post-hoc power analysis was conducted to evaluate the statistical power of the study. This analysis revealed that the study had 81% power to detect a significant difference in the primary outcome (30-day survival) at an alpha level of 0.05. This suggests that the study had sufficient power to detect meaningful differences in survival outcomes, though the small number of survivors and poor model fit still limit the interpretability of the results. Table 1: Descriptive characteristics Characteristic Overall (N=2,829) Thrombolysis (N= 171) No Thrombolysis (N =2,658) Mean age +/- SD – yr 67.56 +/- 15.42 56.2 +/- 15.4 68.2 +/- 15.4 Sex – no. (%) Male 1,856 (66) 131 (76.6) 1725 (65) Female 973 (34) 40 (23.4) 933 (35) Initial rhythm – no. (%) Ventricular fibrillation/pulseless ventricular tachycardia 707 (25) 99 (58) 608 (23) Asystole 1224 (44) 21 (12) 1203 (45) PEA 587 (21) 39 (22) 548 (21) Non-shockable (AED) 193 (7) 6 (3) 187 (7) Not recorded 107 (4) 6 (3) 101 (3) Unknown 11 (<1) 0 11 (<1) Witnessed – no. (%) Bystander 1587 (56) 97 (57) 1490 (56) EMS 364 (13) 57 (34) 307 (11) None 855 (30 16 (9) 839 (32) Unknown 23 (<1) 1 (<1) 22 (1) Mean total shocks +/- SD 8 +/- 6.05 4.1 +/- 4 Table 2: 30-Day Survival Rates and Odds Ratios for Thrombolysis vs. Non-Thrombolysis Administration Outcome TNK No TNK Odds Ratio (95% CI) Unadjusted Adjusted* R 2 value Primary Outcome Survival at 30 days – no/total no. (%) 6/171 (4) 254/2658 (10) 0.36 (0.16-0.81) 0.07 (0.03-0.17) 0.31 Secondary Outcome ROSC at hospital – no/total no. (%) 67/171 (39) 712/2658 (27) 1.75 (1.27-2.41) 0.31 (0.20-0.48) 0.04 Discussion This study aimed to evaluate the impact of Thrombolysis administration on survival outcomes in patients presenting with out-of-hospital cardiac arrest (OHCA). The primary outcome, 30-day survival, showed a survival rate of 4% in the Thrombolysis group, significantly lower than the 10% survival rate in the control group. The disproportionately high rate of VT/VF in the thrombolysis group, coupled with markedly lower survival, suggests that these patients may have had additional poor prognostic factors that were not fully captured in our dataset. One possible explanation is selection bias—thrombolysis may have been given in cases where a thromboembolic cause was strongly suspected, which could indicate more severe underlying pathology. Additionally, while VT/VF is generally associated with higher survival rates, thrombolysis may have introduced adverse effects, such as increased bleeding or impaired CPR efficacy, potentially offsetting the survival advantage typically seen in this group. Future studies should aim to identify whether certain subgroups of VT/VF patients respond differently to thrombolysis in the OHCA setting. The unadjusted odds ratio (OR) for survival in the Thrombolysis group was 0.36 (95% CI 0.16–0.81), indicating a lower likelihood of survival with thrombolysis. After adjusting for potential confounders, the adjusted OR further decreased to 0.08 (95% CI 0.04–0.19), suggesting a significantly lower odds of survival associated with thrombolysis administration. These findings support the hypothesis of futility in thrombolysis for improving long-term survival in patients with OHCA, highlighting that thrombolysis may not be a beneficial intervention in this setting. In contrast, the secondary outcome of return of spontaneous circulation (ROSC) at to hospital arrival showed an unadjusted OR of 1.75, suggesting an increase in ROSC for the thrombolysis group. However, when adjusted for potential confounders, the adjusted OR for ROSC was 0.21 (95% CI 0.14–0.33), indicating that Thrombolysis was associated with a lower likelihood of achieving ROSC after accounting for confounding variables. This discrepancy between the unadjusted and adjusted ORs suggests that substantial confounding is present in the relationship between thrombolysis and outcomes. The unadjusted OR may overestimate the benefit of thrombolysis, while the adjusted OR more accurately reflects its true effect after accounting for baseline differences between groups. This highlights the importance of considering confounding factors when interpreting the observed associations. The difference in results underscores the importance of considering confounders and context when interpreting the effects of thrombolysis. While thrombolysis has been shown to be beneficial in conditions such as STEMI and massive pulmonary embolism, its efficacy in OHCA is likely limited due to several factors: Delayed Administration and Systemic Hypoperfusion : Unlike in STEMI or PE where circulation remains intact, OHCA involves profound systemic hypoperfusion. This could limit the distribution and efficacy of Tenecteplase, reducing its potential benefits. Lack of Circulatory Support : Effective thrombolysis requires adequate circulation to deliver and activate the drug at the clot site. In OHCA, the reliance on CPR may not be sufficient to ensure adequate drug perfusion to affected areas. Underlying Non-Thrombotic Aetiologies : The heterogeneity of OHCA causes means that many patients receiving thrombolysis may not have actually had a thromboembolic event. This could dilute any potential positive effects of the drug. Increased Bleeding Risk : Given the invasive nature of resuscitation efforts, including repeated vascular access and mechanical chest compressions, thrombolysis in OHCA carries an increased risk of bleeding complications, potentially offsetting any survival benefits. While stratification by witnessed status and other subgroups might have offered additional insights, the study’s primary aim of demonstrating futility in survival outcomes was not dependent on such stratification. The absence of significant survival benefit across the entire cohort supports the conclusion that thrombolysis does not improve outcomes in OHCA, regardless of subgroup Due to poor model fit and compliance with model assumptions, detailed subgroup analyses could not be performed. While the primary analysis indicates that Thrombolysis did not improve survival, the limitations in the model fit prevent robust conclusions about the potential benefits of thrombolysis for specific patient subgroups (e.g., age, rhythm, or witnessed arrest status). Therefore, the study provides limited evidence of thrombolysis efficacy across various patient profiles. A post-hoc power analysis yielded a power of 81% at an alpha of 0.05, indicating adequate power to detect significant differences. However, a MacFaddens R 2 value of 0.27 suggests that only 27% of the variance in survival outcomes was explained by the model, implying that other unmeasured variables may be influencing the results. The modest model fit further emphasises the need for caution in interpreting the findings, as unaccounted factors may play a significant role in survival outcomes. Despite the small number of survivors in the Thrombolysis group, the findings still show no survival benefit, which aligns with the study's goal of demonstrating futility. The small sample size, while limiting statistical power, does not change the conclusion that thrombolysis does not improve survival outcomes in this setting. The findings from this study consistently support the hypothesis of futility, demonstrating that Thrombolysis does not significantly improve survival or ROSC rates in out-of-hospital cardiac arrest. In futility studies like this one, the goal is not to show efficacy, but rather to demonstrate that the intervention does not provide any meaningful survival benefit These findings have significant implications for clinical practice, suggesting that Thrombolysis may not provide substantial survival benefits for patients presenting with OHCA. While the unadjusted analysis suggested a higher rate of ROSC in the thrombolysis group, this association did not persist after adjusting for confounders. This suggests that the apparent benefit was likely influenced by underlying differences between the groups rather than a direct effect of thrombolysis. The apparent futility of thrombolysis in improving long-term survival in OHCA is evident, and these results call for reconsideration of thrombolysis use in this context. Although traumatic and paediatric cases were excluded, the underlying aetiology of cardiac arrest was not systematically determined, which may have included patients whose cardiac arrest was not amenable to thrombolysis. This limits the generalisability of the findings to all OHCA cases, as thrombolysis may not be beneficial for all causes of cardiac arrest. Future research should focus on identifying and excluding such cases to better isolate the impact of thrombolysis on those with thromboembolic causes of cardiac arrest, which are most likely to benefit from thrombolytic therapy. Future research is necessary to explore alternative interventions for OHCA patients and refine patient selection criteria for thrombolytic therapy. Investigating specific subgroups who may benefit from thrombolysis, such as those with specific cardiac rhythms or certain clinical characteristics, could provide valuable insights into optimizing treatment protocols. More rigorous studies with larger sample sizes and better model fit are essential to validate these findings and guide future clinical decisions. Limitations This study has several limitations that should be considered. Firstly, the retrospective design introduces the possibility of selection bias and incomplete data capture. Although efforts were made to mitigate these issues through rigorous data collection and statistical adjustment, some residual confounding may still be present. The small number of survivors in the thrombolysis group limits the study's ability to detect meaningful differences, particularly for the primary outcome. Anonymisation constraints prevented analysis of yearly trends in thrombolysis use and outcomes, which may have influenced the findings if practice patterns evolved over time. The reliance on data from a single ambulance trust may limit the generalisability of the findings to broader populations, as differences in patient demographics and clinical practices at other facilities could impact external validity. Additionally, the study was unable to exclude patients with non-thrombolytic treatable causes of cardiac arrest (e.g., arrhythmias), potentially diluting the observed effects of thrombolysis. A key limitation of this study is the possibility that the patients receiving thrombolysis were inherently more critically unwell than those who did not receive it. Patients selected for thrombolysis might have had longer downtimes, more unwitnessed arrests, or worse baseline prognostic factors compared to those who did not receive the intervention. These unmeasured factors could contribute to the negative outcomes observed in the thrombolysis group. While efforts were made to adjust for confounders using logistic regression, residual confounding cannot be ruled out, particularly given the retrospective nature of the study. Future studies should consider prospectively collecting more granular pre-arrest data to better delineate these confounding effects. The use of administrative data and electronic health records introduces potential for misclassification or inaccuracies, particularly given the small number of survivors in the thrombolysis group. Furthermore, variability in post-handover care across multiple hospitals may have introduced inconsistencies in treatment protocols, influencing long-term survival outcomes. Differences in data collection periods for the thrombolysis and control groups may also have contributed to variability in the findings. Thrombolysis data were collected over several years due to infrequent administration, while control data were from a single year. Despite adjustments, these differing periods could affect the comparability of the groups. Finally, the study focused on short-term survival at 30 days, without evaluating longer-term outcomes like functional recovery or quality of life. Future studies should assess these broader outcomes to better understand the full impact of thrombolysis in OHCA. Conclusion This study provides important insights into the impact of Thrombolysis on survival outcomes in patients presenting with out-of-hospital cardiac arrest (OHCA). The analysis revealed that Thrombolysis did not improve overall survival rates. Specifically, the primary outcome analysis showed a survival rate of 4% in the Thrombolysis group, with an adjusted odds ratio (AOR) of 0.08 (95% CI: 0.04–0.19), indicating a substantial 92% decrease in survival odds compared to the control group. These findings suggest that thrombolysis may not provide any meaningful benefit in improving long-term survival in OHCA cases. The secondary outcome of return of spontaneous circulation (ROSC) upon arrival at the hospital showed a decreased rate in the Thrombolysis group, with an adjusted odds ratio of 0.21 (95% CI: 0.14–0.33). This result further questions the benefit of thrombolysis, as it suggests a lower likelihood of achieving ROSC, the immediate measure of resuscitation success. This lack of improvement in ROSC after thrombolysis reinforces the findings of futility in both the short and long-term outcomes. Subgroup analyses were not performed due to issues with model fit and data compliance, meaning that the potential differential effects of Thrombolysis across different patient subgroups (e.g., by age, rhythm, or witness status) remain unexplored. The lack of reliable subgroup analysis limits our understanding of whether specific groups might benefit from thrombolysis. Key limitations of this study include its retrospective design, potential for residual confounding, and reliance on single-centre data, which may limit the generalizability of the findings. Variability in post-handover care across multiple hospitals, as well as differing data collection periods between the Thrombolysis and control groups, may introduce bias into the results. In clinical practice, these findings suggest that Thrombolysis may not offer significant survival benefits for patients experiencing OHCA and should be used cautiously. Given the limitations of this study, future research should focus on refining patient selection criteria, improving model fit to better capture relevant variables, and investigating post-resuscitation care protocols to enhance outcomes for OHCA patients. The failure to observe any meaningful improvement in survival rates with thrombolysis, even after adjusting for confounders, reinforces the futility of thrombolysis in improving outcomes for OHCA patients. This supports the conclusion that thrombolysis does not offer a survival benefit in this context Abbreviations OHCA Out-of-hospital cardiac arrest CCP Critical Care Paramedic STEMi ST-elevation Myocardial Infarction PPCI Primary Percutaneous Coronary Intervention ROSC Return of spontaneous circulation ALS Advanced Life Support Declarations Ethics approval and consent to participate This study received United Kingdom Health Research Authority approval (IRAS: 336178) and internal approval from the Research & Development Board at South East Coast Ambulance Service NHS Foundation Trust, Crawley, UK. All the data utilised for this study were routinely collected as part of standard pre-hospital patient data collection. The need for informed consent was waived by IRAS in accordance with UK national regulations, as the study involved retrospective analysis of anonymized data. A full data privacy impact assessment (DPIA) was performed and approved by the Trust’s information governance department. This study meets the requirements of the Strengthening Reporting of Observational Studies in Epidemiology (STROBE) checklist. Consent for publication Not applicable Availability of data and material The datasets generated and/or analysed during the current study are not publicly available due to privacy and confidentiality concerns but are available from the corresponding author on reasonable request and with appropriate permissions from the South East Coast Ambulance Service NHS Foundation Trust. Competing interests The authors declare that they have no competing interests, Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ contributions Alan Cowley: Conceptualisation, Methodology, Resourced, Data Curation, Formal Analysis, Investigation, Writing – Original Draft, Writing – Review & Editing. Dan Cody: Conceptualisation, Data Curation, Writing – Review & Editing. Eleanor Jaquet: Data Curation, Formal Analysis, Writing – Review and Editing. Magnus Nelson: Conceptualisation,Writing – Review and Editing. Acknowledgements The authors acknowledge the significant contributions made by Eleanor Jaquet (Cardiac Arrest Analyst), Sophie Clark (Quality Improvement Lead) and Mohammad Zaman (Data Scientist) of South East Coast Ambulance Service NHS Foundation Trust for their assistance in their support for the project and data collation/analysis. We acknowledge the use of Python (version 3.10.11) and the associated library ( statsmodel ) for conducting the statistical analyses. References Konstantinides SV, Meyer G, Becattini C, Bueno H, et al. 2019 ESC Guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS): The Task Force for the diagnosis and management of acute pulmonary embolism of the European Society of Cardiology (ESC). Eur Heart J . 2020;41(4):543-603. https://doi.org/10.1093/eurheartj/ehz405. Byrne RA, Rossello X, Coughlan JJ, Barbato E, et al. 2023 ESC Guidelines for the management of acute coronary syndromes: Developed by the task force on the management of acute coronary syndromes of the European Society of Cardiology (ESC). Eur Heart J . 2023;44(38):3720-3826. https://doi.org/10.1093/eurheartj/ehad191. Hitt A, Pateman J. Intra-cardiac arrest thrombolysis in the pre-hospital setting: four cases worth considering. J Paramed Pract . 2015;7(1). https://doi.org/10.12968/jpar.2015.7.1.26. Alshaya OA, Alshaya AI, Badreldin HA, Albalawi ST, et al. Thrombolytic therapy in cardiac arrest caused by cardiac etiologies or presumed pulmonary embolism: An updated systematic review and meta-analysis. Res Pract Thromb Haemost . 2022;6(4). https://doi.org/10.1002/rth2.12745. Böttiger BW, Arntz H-R, Chamberlain DA, Bluhmki E, et al. Thrombolysis during resuscitation for out-of-hospital cardiac arrest. N Engl J Med . 2008;359(25):2651-2662. https://doi.org/10.1056/NEJMoa070570. Additional Declarations No competing interests reported. Supplementary Files STROBEchecklistcohort.docx 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. 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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-5198608","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":431726517,"identity":"6a27c3c3-6fd9-44d9-9c6e-8a98ae82710c","order_by":0,"name":"Alan Cowley","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDUlEQVRIiWNgGAWjYDACdijNx8DA+ADMkmBgYIbS2AEzlGYDMg1I1sImQZQW/mbmZw8YamwS29h7zCp/VNjJ685uYHtc8IchcWYDdi0Sh9nMDRiOpSW28Zwxu81zJtlw250D7MYz2xgSZ+Ny2GEGMwnGhsO5bRI5ZrcZ2w4wbruRwCbN28CQOA+HDvnD7N8gWuTfmBX+/HfAHqyF5w9uLQaHeWC28Jgx8DYcSIRoYcPtMMPDPGUSCcfS6tt40oqleY4lJ2+7c7BNmrdNwhiX9+WOt2+T+FBjY8zPfnjjxx81drbbbjcfAzrMRnbGAVz+B4IEMMlhAOUygozHGZHIgP0BMapGwSgYBaNgBAIAsUhUpoekEAsAAAAASUVORK5CYII=","orcid":"","institution":"South East Coast Ambulance Service NHS Foundation Trust","correspondingAuthor":true,"prefix":"","firstName":"Alan","middleName":"","lastName":"Cowley","suffix":""},{"id":431726520,"identity":"cac36bfd-37e8-462b-a1bf-b4047fc53267","order_by":1,"name":"Dan Cody","email":"","orcid":"","institution":"South East Coast Ambulance Service NHS Foundation Trust","correspondingAuthor":false,"prefix":"","firstName":"Dan","middleName":"","lastName":"Cody","suffix":""},{"id":431726521,"identity":"2b2fa8e4-38cf-4b64-aefc-206d4c78ec35","order_by":2,"name":"Eleanor Jaquet","email":"","orcid":"","institution":"South East Coast Ambulance Service NHS Foundation Trust","correspondingAuthor":false,"prefix":"","firstName":"Eleanor","middleName":"","lastName":"Jaquet","suffix":""},{"id":431726522,"identity":"142ad410-25de-441f-8676-b4853298e78d","order_by":3,"name":"Magnus Nelson","email":"","orcid":"","institution":"South East Coast Ambulance Service NHS Foundation Trust","correspondingAuthor":false,"prefix":"","firstName":"Magnus","middleName":"","lastName":"Nelson","suffix":""}],"badges":[],"createdAt":"2024-10-03 13:23:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5198608/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5198608/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81506275,"identity":"33a570f2-cedb-4b3b-8d75-9492a05274b9","added_by":"auto","created_at":"2025-04-28 05:30:13","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":50669,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flowchart.\u003c/p\u003e","description":"","filename":"Studyflowchart.png.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5198608/v1/997a35cc9bc91b6f15cf24a1.jpg"},{"id":84035438,"identity":"5807b3c0-e665-4142-8039-9ce309718112","added_by":"auto","created_at":"2025-06-06 03:53:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1058421,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5198608/v1/1cd8e182-379b-4008-829e-48dabc137bfe.pdf"},{"id":81506271,"identity":"d25b3499-09a7-4467-8926-65b812b3efe6","added_by":"auto","created_at":"2025-04-28 05:30:13","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":33947,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEchecklistcohort.docx","url":"https://assets-eu.researchsquare.com/files/rs-5198608/v1/b60e2ff0faeb284028bcba5c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessing the Futility of Thrombolysis in Out-of-Hospital Cardiac Arrest. A Retrospective Cohort study.","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eClinical trials have demonstrated the efficacy and safety of thrombolytic medications in certain controlled situations, such as ST-elevation myocardial infarction and massive pulmonary embolism, where international guidance recommends thrombolysis as a first- or second-line therapy [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, evidence regarding the use of thrombolysis in out-of-hospital cardiac arrest (OHCA) is limited. While some case studies suggest potential benefits [e.g., 3], the overall body of evidence shows no clear mortality advantage [e.g., 4\u0026ndash;5], and a recent study cautiously suggests inferiority [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Previous studies have often been of low quality or marked by heterogeneity in the thrombolytic agents used, as well as variations in dosing strategies.\u003c/p\u003e \u003cp\u003eWithin the South East Coast Ambulance Service NHS Foundation Trust (SECAmb), thrombolysis is administered by Critical Care Paramedics (CCPs) using Tenecteplase, a tissue-type plasminogen activator. Tenecteplase promotes blood clot breakdown by converting plasminogen into plasmin, the enzyme responsible for clot dissolution. While other thrombolytics are available and commonly used in-hospital, Tenecteplase remains the most pragmatic option for UK paramedics due to its inclusion in Schedule 17 of the Human Medicines Regulations 2012, as well as its simpler dosing regimen compared to alternatives.\u003c/p\u003e \u003cp\u003eIn SECAmb, Tenecteplase is primarily used by CCPs for suspected thrombo-embolic causes of cardiac arrest and, rarely, for ST-elevation myocardial infarction (STEMI) where timely access to primary percutaneous coronary intervention (PPCI) is unavailable. In the context of out-of-hospital cardiac arrest (OHCA), thrombolysis is used selectively by CCPs when a thromboembolic aetiology is strongly suspected. Specifically, Tenecteplase is administered in cases where pulmonary embolism (PE) is believed to be the precipitating cause of cardiac arrest, based on clinical indicators such as sudden cardiac collapse in a patient with known venous thromboembolism risk factors, absence of other obvious causes, and specific rhythm presentations (e.g., pulseless electrical activity with high suspicion of PE). Additionally, thrombolysis may be considered in rare instances of STEMI-induced cardiac arrest where there is significant delay in access to primary percutaneous coronary intervention (PPCI). However, the decision to administer Tenecteplase is typically made in the absence of definitive diagnostic tools, relying on clinical judgment and prehospital protocols.\u003c/p\u003e \u003cp\u003eThis retrospective cohort study aims to explore the futility of thrombolysis in the prehospital management of OHCA, focusing on safety, efficacy, and patient outcomes. The standardised use of a single thrombolytic drug in a homogeneous protocol offers an opportunity to assess whether thrombolysis provides any real-world benefit in this context.\u003c/p\u003e \u003cp\u003eThe study is particularly valuable for several reasons:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eReal-World Evidence\u003c/b\u003e: While clinical trials and in-hospital data provide insights into the safety and efficacy of thrombolytic medications, they often exclude the diverse and complex prehospital patient population encountered in routine clinical practice. This study will contribute real-world evidence on the effectiveness of Tenecteplase in OHCA, focusing on futility in improving survival.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePrehospital Protocol Optimisation\u003c/b\u003e: Understanding whether thrombolysis improves outcomes in OHCA can help refine prehospital treatment protocols for cardiac emergencies. If thrombolysis is shown to offer no meaningful benefit, this study can inform decisions to avoid unnecessary interventions, redirecting resources to more effective treatments.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePatient Outcomes\u003c/b\u003e: This study will evaluate the relationship between prehospital thrombolysis and key clinical outcomes, specifically return of spontaneous circulation (ROSC) at hospital arrival and 30-day survival. Demonstrating futility in these outcomes would provide important evidence against the routine use of thrombolysis in OHCA.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eDecision-Making and Resource Allocation\u003c/b\u003e: The findings could help guide policy decisions regarding the allocation of resources, including the use of thrombolytic drugs in prehospital settings. Demonstrating futility would also impact training priorities for paramedics and CCPs, allowing resources to be directed to interventions with proven efficacy.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eAddressing an Evidence Gap\u003c/b\u003e: Despite the widespread use of thrombolysis in prehospital settings for acute cardiac emergencies, there is a paucity of real-world data specifically evaluating its efficacy in OHCA. This study seeks to fill that gap, with a focus on whether thrombolysis should continue to be employed in this context.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThis study, by evaluating the futility of thrombolysis in improving survival outcomes in OHCA, will provide important insights for clinical practice and decision-making in prehospital emergency care.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient Population\u003c/h2\u003e \u003cp\u003eDue to the low frequency of thrombolysis administration in out-of-hospital cardiac arrest (OHCA) cases, data for the thrombolysis group were collected over five years to gather a sufficient sample size for meaningful analysis. In contrast, the non-thrombolysis control group data were collected within a single year, where the higher volume of cases allowed for a more substantial sample size for comparison.\u003c/p\u003e \u003cp\u003eThe study included adult patients (\u0026ge;\u0026thinsp;18 years) who experienced OHCA between 1st April 2022 and 31st March 2023 (control group), and from the establishment of the cardiac arrest registry to 31st March 2023 (thrombolysis group), with advanced life support provided by clinicians from the South East Coast Ambulance Service NHS Foundation Trust (SECAmb). Patients were excluded if they were known to be pregnant or if their cardiac arrest was caused by a known or suspected traumatic event. This selection was made to focus specifically on medical causes of OHCA and to avoid the confounding effects of trauma-related arrests, which have different underlying pathophysiology and response to treatments like thrombolysis. The remaining patients were divided into two groups based on whether they received thrombolysis from a Critical Care Paramedic (CCP) during the prehospital phase of care.\u003c/p\u003e \u003cp\u003eDue to the low number of thrombolysis cases, yearly breakdowns were not provided to maintain patient anonymity. As a result, trends in thrombolysis use and outcomes over time could not be formally analysed.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePrimary and Secondary Outcomes\u003c/h3\u003e\n\u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePrimary Outcome\u003c/b\u003e: The primary outcome was the rate of survival at 30 days post-arrest. This outcome was selected to assess the long-term effects of thrombolysis in OHCA patients. As the study was designed to investigate futility, the aim was to determine whether thrombolysis fails to improve survival rates at 30 days, particularly when compared to the control group.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eSecondary Outcome\u003c/b\u003e: The secondary outcome was the rate of return of spontaneous circulation (ROSC) at hospital arrival. ROSC was defined as the return of a palpable pulse and/or measurable blood pressure following resuscitation efforts. These data were collected from prehospital patient care records as documented by attending ambulance staff. ROSC was considered present if sustained until hospital arrival; transient or brief ROSC events without sustained circulation were not included in the analysis. Defibrillator recordings were not systematically reviewed to confirm ROSC duration, so documentation relied on clinician-reported outcomes. This outcome aimed to investigate whether thrombolysis could lead to early success in resuscitation. However, as the study investigates futility, it sought to assess whether thrombolysis has minimal or no benefit in achieving ROSC compared to the control group.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e This observational study adhered to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines to ensure rigorous reporting of its design, methodology, and results. The STROBE checklist was followed throughout the study, focusing on transparency in participant selection, data collection, and statistical analysis\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSTATISTICAL ANALYSIS\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003ePatient Population and Sample Size Considerations\u003c/h2\u003e \u003cp\u003eA basic review of the clinical records revealed approximately 170 administrations of thrombolysis within the study period. Given the low frequency of thrombolysis in out-of-hospital cardiac arrest (OHCA), this number of cases was necessary to conduct a meaningful analysis. It is assumed that the majority of these cases involved OHCA patients, though a detailed breakdown was not available for all instances.\u003c/p\u003e \u003cp\u003eDue to the small number of survivors in the thrombolysis group, a basic power calculation indicated that to detect a meaningful difference in survival to 30 days, an effect size of approximately 72% would be needed to achieve 80% power (α\u0026thinsp;=\u0026thinsp;0.05). This is based on the national survival rate for OHCA, which is approximately 8.3%. In contrast, for return of spontaneous circulation (ROSC) at the hospital, a much smaller effect size (33%) would be necessary, given the typical ROSC rate of around 30% in OHCA patients.\u003c/p\u003e \u003cp\u003eAs the required effect sizes are large and the sample size for thrombolysis is small, it is likely that the study will not reach 80% power, especially for the primary outcome of survival. Given these constraints, a post-hoc power analysis was conducted to assess the actual statistical power of the study after data collection. This helped gauge how well the study was powered to detect potential differences, despite the limitations posed by a small number of survivors.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eDescriptive Statistics\u003c/h3\u003e\n\u003cp\u003eDescriptive statistics were used to summarise the baseline characteristics of the study cohort. Means, medians, standard deviations, and frequencies were calculated for variables such as patient demographics, initial cardiac arrest rhythm, time to first intervention, and other relevant factors. This step provided an overview of the cohort and the distribution of key clinical characteristics.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eComparative Analysis\u003c/h2\u003e \u003cp\u003eA comparative analysis was conducted to assess the differences between patients who received thrombolysis and those who did not. The following statistical tests were employed to evaluate the association between thrombolysis administration and the primary and secondary outcomes:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eChi-Square Test or Fisher's Exact Test\u003c/b\u003e: These tests were used to assess the association between thrombolysis and the primary outcome (30-day survival) as well as the secondary outcome (ROSC at hospital). Given the small number of survivors, Fisher's Exact Test was preferred for its ability to handle small, expected frequencies.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eComparative Analysis\u003c/b\u003e: The rates of survival at 30 days and ROSC at the hospital were compared between the thrombolysis and control groups to evaluate the potential efficacy of thrombolysis in improving these outcomes. However, given the low survival rate in the thrombolysis group, this analysis focused on demonstrating futility.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLogistic Regression Analysis\u003c/h3\u003e\n\u003cp\u003eTo investigate the association between thrombolysis and the primary and secondary outcomes while adjusting for potential confounders, logistic regression analysis was performed. This approach allows for the evaluation of multiple variables simultaneously, adjusting for confounding factors that may influence survival or ROSC outcomes.\u003c/p\u003e \u003cp\u003eThe following types of logistic regression were used:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eUnivariable Logistic Regression\u003c/b\u003e: This analysis assessed the relationship between thrombolysis (Yes/No) and binary outcomes (e.g., survival) without considering other variables. This model provides a basic understanding of the association between thrombolysis and outcomes.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eMultivariable Logistic Regression\u003c/b\u003e: This more comprehensive approach adjusted for multiple factors, such as age, presenting rhythm, and intra-arrest circumstances, allowing for a better understanding of the independent association between thrombolysis and outcomes. This analysis aimed to evaluate the futility of thrombolysis after controlling for important confounders.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe following confounders were included in the multivariable logistic regression model to adjust for potential biases: age, gender, witnessed status, initial rhythm and presence of bystander CPR. These variables were selected based on their established relevance to OHCA outcomes.\u003c/p\u003e\n\u003ch3\u003eOdds Ratios and Confidence Intervals\u003c/h3\u003e\n\u003cp\u003eThe odds ratios (OR) and corresponding 95% confidence intervals (CI) were derived from the logistic regression output. These measures were calculated as the exponentiated coefficients from the logistic regression model, providing insight into the strength and direction of the association between thrombolysis and the likelihood of specific outcomes (such as survival).\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eOdds Ratios (OR)\u003c/b\u003e: An odds ratio greater than 1 indicates a higher likelihood of the outcome associated with thrombolysis administration. Conversely, an OR less than 1 suggests a reduced likelihood of the outcome with thrombolysis. Given the study's futility design, an OR less than 1 would indicate a poorer outcome with thrombolysis.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003e95% Confidence Intervals (CI)\u003c/b\u003e: The CI represents the range within which the true odds ratio is likely to fall with 95% confidence. A wide CI, especially if it includes 1.0, suggests that the estimate is imprecise, which may be due to the small sample size and low number of survivors in the thrombolysis group.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePost-Hoc Power Analysis\u003c/h2\u003e \u003cp\u003eA post-hoc power analysis was conducted to assess the statistical power of the study after data collection. This analysis estimated the likelihood of detecting a true effect based on the observed sample size, effect size, and significance level. A power of 0.8 or higher is typically considered sufficient, but given the small number of survivors and large effect sizes required, the power in this study was likely lower than optimal. The post-hoc analysis helped quantify the study\u0026rsquo;s ability to detect significant differences, highlighting the challenges posed by the sparse data.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003ePatients and Interventions\u003c/h2\u003e\n \u003cp\u003e\u003cstrong\u003ePatients\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eA total of 2,829 patients who experienced out-of-hospital cardiac arrest (OHCA) were included in this retrospective cohort study (see Fig.\u0026nbsp;1). Among these, 171 patients received Thrombolysis as part of their resuscitation efforts, administered by Critical Care Paramedics (CCPs) in line with the South East Coast Ambulance Service NHS Foundation Trust\u0026rsquo;s clinical practice guidelines. The demographic and clinical characteristics of the patients are summarized in Table\u0026nbsp;1. The mean age of the study population was 67.5 years (SD\u0026thinsp;=\u0026thinsp;15), with 66% of patients being male. The characteristics of patients in the Thrombolysis group were compared to those in the non-Thrombolysis control group, comprising 2,658 patients, to identify potential differences in baseline characteristics and outcomes. Interestingly, the thrombolysis group had a significantly higher proportion of VT/VF as the presenting rhythm (58%) compared to the non-thrombolysis group (23%). Given that VT/VF is typically associated with better survival outcomes (historically 20%-25%), the lower survival rate in the thrombolysis group (4%) is unexpected and warrants further exploration.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eInterventions\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe primary intervention of interest was the administration of Thrombolysis to patients presenting with OHCA. Thrombolysis was administered based on clinical guidelines, primarily for cases where a thromboembolic cause was suspected or confirmed. The Thrombolysis was administered alongside standard Advanced Life Support (ALS) procedures, in accordance with the established prehospital protocols for OHCA management.\u003c/p\u003e\n \u003cp\u003eIn contrast, the control group (2,658 patients) received only standard ALS, without thrombolytic intervention. Both groups were managed under comparable prehospital care protocols, with uniformity in the application of ALS procedures. However, post-arrival at various hospitals, interventions were beyond the control of the research team. While all receiving hospitals were Level 1 emergency departments, access to advanced interventions, such as targeted temperature management and primary percutaneous coronary intervention (PPCI), varied between institutions, and could have influenced the study outcomes.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003ePrimary and Secondary Outcomes\u003c/h2\u003e\n \u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003ePrimary Outcome\u003c/h2\u003e\n \u003cp\u003eThe primary outcome, 30-day survival, was significantly lower in the Thrombolysis group compared to the non-Thrombolysis group. The survival rate in the Thrombolysis group was 4%, whereas the non-Thrombolysis group had a survival rate of 9%. The unadjusted odds ratio (OR) for survival at 30 days in the Thrombolysis group was 0.36 (95% CI: 0.16\u0026ndash;0.81), indicating a lower likelihood of survival in the Thrombolysis group. After adjusting for potential confounders, the adjusted OR was 0.08 (95% CI: 0.04\u0026ndash;0.19), showing a statistically significant worsening in survival with thrombolysis compared to the control group. However, the model fit was poor-moderate (R\u0026sup2; = 0.27), suggesting that the logistic regression model may not fully capture all the variables influencing survival and that the results should be interpreted with caution. The modest fit further underscores the need for caution in drawing conclusions from the adjusted analysis.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\"\u003e\n \u003ch2\u003eSecondary Outcome\u003c/h2\u003e\n \u003cp\u003eThe secondary outcome of return of spontaneous circulation (ROSC) at hospital arrival was assessed. The ROSC rate was significantly higher in the Thrombolysis group compared to the non-Thrombolysis group. However, while this finding was statistically significant, the clinical relevance of this result is unclear, particularly since it did not translate into improved long-term survival. The ROSC rates and statistical comparisons are detailed in Table\u0026nbsp;2.\u003c/p\u003e\n \u003cp\u003eTo provide a clearer understanding of the influence of confounders, Tables\u0026nbsp;3 and 4, and Figs.\u0026nbsp;2 and 3, present the full logistic regression estimates for all covariates, including odds ratios, confidence intervals, and p-values. These results highlight the substantial impact of factors such as age, initial rhythm, and witnessed status on survival outcomes.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\"\u003e\n \u003ch2\u003eSubgroup Analysis\u003c/h2\u003e\n \u003cp\u003eGiven the primary objective to assess the impact of Tenecteplase on 30-day survival rates, subgroup analyses were intended to explore whether there were any differential effects of thrombolysis based on key variables such as age, gender, witnessed arrest, and presenting rhythm. However, the logistic regression model demonstrated a poor to moderate fit to the data, as indicated by a low to moderate R-squared value and lack of model compliance. As a result, reliable subgroup analyses were not feasible, and meaningful interpretations for specific subgroups could not be derived. The substantial limitations in the data quality and model fit suggest that the observed relationships in the overall cohort may not hold consistently within these subgroups.\u003c/p\u003e\n \u003cp\u003eAlthough the study intended to explore subgroups to identify whether Tenecteplase had differential effects, these analyses were compromised by the aforementioned model limitations. Given the lack of robust results, any conclusions drawn about subgroup differences should be treated with caution.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\"\u003e\n \u003ch2\u003ePost-Hoc Power Analysis\u003c/h2\u003e\n \u003cp\u003eA post-hoc power analysis was conducted to evaluate the statistical power of the study. This analysis revealed that the study had 81% power to detect a significant difference in the primary outcome (30-day survival) at an alpha level of 0.05. This suggests that the study had sufficient power to detect meaningful differences in survival outcomes, though the small number of survivors and poor model fit still limit the interpretability of the results.\u003c/p\u003e\n \u003cp\u003eTable 1: Descriptive characteristics\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eOverall\u003c/p\u003e\n \u003cp\u003e(N=2,829)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003eThrombolysis\u003c/p\u003e\n \u003cp\u003e(N= 171)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003eNo Thrombolysis\u003c/p\u003e\n \u003cp\u003e(N =2,658)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean age +/- SD \u0026ndash; yr\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e67.56 +/- 15.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e56.2 +/- 15.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e68.2 +/- 15.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex \u0026ndash; no. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1,856 (66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e131 (76.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1725 (65)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e973 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e40 (23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e933 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInitial rhythm \u0026ndash; no. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003eVentricular fibrillation/pulseless ventricular tachycardia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e707 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e99 (58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e608 (23)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003eAsystole\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1224 (44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e21 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1203 (45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003ePEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e587 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e39 (22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e548 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003eNon-shockable (AED)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e193 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e6 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e187 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003eNot recorded\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e107 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e6 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e101 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e11 (\u0026lt;1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e11 (\u0026lt;1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWitnessed \u0026ndash; no. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003eBystander\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1587 (56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e97 (57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1490 (56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003eEMS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e364 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e57 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e307 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e855 (30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e16 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e839 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e23 (\u0026lt;1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e1 (\u0026lt;1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e22 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 290px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean total shocks +/- SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e8 +/- 6.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e4.1 +/- 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eTable 2: 30-Day Survival Rates and Odds Ratios for Thrombolysis vs. Non-Thrombolysis Administration\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTNK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo TNK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 357px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOdds Ratio (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnadjusted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003csup\u003e2\u003c/sup\u003e value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary Outcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eSurvival at 30 days \u0026ndash; no/total no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e6/171 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e254/2658 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.36 (0.16-0.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e0.07 (0.03-0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 601px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecondary Outcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eROSC at hospital \u0026ndash; no/total no. (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e67/171 (39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e712/2658 (27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e1.75 (1.27-2.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 191px;\"\u003e\n \u003cp\u003e0.31 (0.20-0.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to evaluate the impact of Thrombolysis administration on survival outcomes in patients presenting with out-of-hospital cardiac arrest (OHCA). The primary outcome, 30-day survival, showed a survival rate of 4% in the Thrombolysis group, significantly lower than the 10% survival rate in the control group. The disproportionately high rate of VT/VF in the thrombolysis group, coupled with markedly lower survival, suggests that these patients may have had additional poor prognostic factors that were not fully captured in our dataset. One possible explanation is selection bias\u0026mdash;thrombolysis may have been given in cases where a thromboembolic cause was strongly suspected, which could indicate more severe underlying pathology. Additionally, while VT/VF is generally associated with higher survival rates, thrombolysis may have introduced adverse effects, such as increased bleeding or impaired CPR efficacy, potentially offsetting the survival advantage typically seen in this group. Future studies should aim to identify whether certain subgroups of VT/VF patients respond differently to thrombolysis in the OHCA setting. The unadjusted odds ratio (OR) for survival in the Thrombolysis group was 0.36 (95% CI 0.16\u0026ndash;0.81), indicating a lower likelihood of survival with thrombolysis. After adjusting for potential confounders, the adjusted OR further decreased to 0.08 (95% CI 0.04\u0026ndash;0.19), suggesting a significantly lower odds of survival associated with thrombolysis administration. These findings support the hypothesis of futility in thrombolysis for improving long-term survival in patients with OHCA, highlighting that thrombolysis may not be a beneficial intervention in this setting.\u003c/p\u003e \u003cp\u003eIn contrast, the secondary outcome of return of spontaneous circulation (ROSC) at to hospital arrival showed an unadjusted OR of 1.75, suggesting an increase in ROSC for the thrombolysis group. However, when adjusted for potential confounders, the adjusted OR for ROSC was 0.21 (95% CI 0.14\u0026ndash;0.33), indicating that Thrombolysis was associated with a lower likelihood of achieving ROSC after accounting for confounding variables. This discrepancy between the unadjusted and adjusted ORs suggests that substantial confounding is present in the relationship between thrombolysis and outcomes. The unadjusted OR may overestimate the benefit of thrombolysis, while the adjusted OR more accurately reflects its true effect after accounting for baseline differences between groups. This highlights the importance of considering confounding factors when interpreting the observed associations. The difference in results underscores the importance of considering confounders and context when interpreting the effects of thrombolysis.\u003c/p\u003e \u003cp\u003eWhile thrombolysis has been shown to be beneficial in conditions such as STEMI and massive pulmonary embolism, its efficacy in OHCA is likely limited due to several factors:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eDelayed Administration and Systemic Hypoperfusion\u003c/b\u003e: Unlike in STEMI or PE where circulation remains intact, OHCA involves profound systemic hypoperfusion. This could limit the distribution and efficacy of Tenecteplase, reducing its potential benefits.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eLack of Circulatory Support\u003c/b\u003e: Effective thrombolysis requires adequate circulation to deliver and activate the drug at the clot site. In OHCA, the reliance on CPR may not be sufficient to ensure adequate drug perfusion to affected areas.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eUnderlying Non-Thrombotic Aetiologies\u003c/b\u003e: The heterogeneity of OHCA causes means that many patients receiving thrombolysis may not have actually had a thromboembolic event. This could dilute any potential positive effects of the drug.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eIncreased Bleeding Risk\u003c/b\u003e: Given the invasive nature of resuscitation efforts, including repeated vascular access and mechanical chest compressions, thrombolysis in OHCA carries an increased risk of bleeding complications, potentially offsetting any survival benefits.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eWhile stratification by witnessed status and other subgroups might have offered additional insights, the study\u0026rsquo;s primary aim of demonstrating futility in survival outcomes was not dependent on such stratification. The absence of significant survival benefit across the entire cohort supports the conclusion that thrombolysis does not improve outcomes in OHCA, regardless of subgroup\u003c/p\u003e \u003cp\u003eDue to poor model fit and compliance with model assumptions, detailed subgroup analyses could not be performed. While the primary analysis indicates that Thrombolysis did not improve survival, the limitations in the model fit prevent robust conclusions about the potential benefits of thrombolysis for specific patient subgroups (e.g., age, rhythm, or witnessed arrest status). Therefore, the study provides limited evidence of thrombolysis efficacy across various patient profiles.\u003c/p\u003e \u003cp\u003eA post-hoc power analysis yielded a power of 81% at an alpha of 0.05, indicating adequate power to detect significant differences. However, a MacFaddens R\u003csup\u003e2\u003c/sup\u003e value of 0.27 suggests that only 27% of the variance in survival outcomes was explained by the model, implying that other unmeasured variables may be influencing the results. The modest model fit further emphasises the need for caution in interpreting the findings, as unaccounted factors may play a significant role in survival outcomes.\u003c/p\u003e \u003cp\u003eDespite the small number of survivors in the Thrombolysis group, the findings still show no survival benefit, which aligns with the study's goal of demonstrating futility. The small sample size, while limiting statistical power, does not change the conclusion that thrombolysis does not improve survival outcomes in this setting.\u003c/p\u003e \u003cp\u003eThe findings from this study consistently support the hypothesis of futility, demonstrating that Thrombolysis does not significantly improve survival or ROSC rates in out-of-hospital cardiac arrest. In futility studies like this one, the goal is not to show efficacy, but rather to demonstrate that the intervention does not provide any meaningful survival benefit\u003c/p\u003e \u003cp\u003eThese findings have significant implications for clinical practice, suggesting that Thrombolysis may not provide substantial survival benefits for patients presenting with OHCA. While the unadjusted analysis suggested a higher rate of ROSC in the thrombolysis group, this association did not persist after adjusting for confounders. This suggests that the apparent benefit was likely influenced by underlying differences between the groups rather than a direct effect of thrombolysis. The apparent futility of thrombolysis in improving long-term survival in OHCA is evident, and these results call for reconsideration of thrombolysis use in this context.\u003c/p\u003e \u003cp\u003eAlthough traumatic and paediatric cases were excluded, the underlying aetiology of cardiac arrest was not systematically determined, which may have included patients whose cardiac arrest was not amenable to thrombolysis. This limits the generalisability of the findings to all OHCA cases, as thrombolysis may not be beneficial for all causes of cardiac arrest. Future research should focus on identifying and excluding such cases to better isolate the impact of thrombolysis on those with thromboembolic causes of cardiac arrest, which are most likely to benefit from thrombolytic therapy.\u003c/p\u003e \u003cp\u003eFuture research is necessary to explore alternative interventions for OHCA patients and refine patient selection criteria for thrombolytic therapy. Investigating specific subgroups who may benefit from thrombolysis, such as those with specific cardiac rhythms or certain clinical characteristics, could provide valuable insights into optimizing treatment protocols. More rigorous studies with larger sample sizes and better model fit are essential to validate these findings and guide future clinical decisions.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations that should be considered. Firstly, the retrospective design introduces the possibility of selection bias and incomplete data capture. Although efforts were made to mitigate these issues through rigorous data collection and statistical adjustment, some residual confounding may still be present. The small number of survivors in the thrombolysis group limits the study's ability to detect meaningful differences, particularly for the primary outcome. Anonymisation constraints prevented analysis of yearly trends in thrombolysis use and outcomes, which may have influenced the findings if practice patterns evolved over time.\u003c/p\u003e \u003cp\u003eThe reliance on data from a single ambulance trust may limit the generalisability of the findings to broader populations, as differences in patient demographics and clinical practices at other facilities could impact external validity. Additionally, the study was unable to exclude patients with non-thrombolytic treatable causes of cardiac arrest (e.g., arrhythmias), potentially diluting the observed effects of thrombolysis.\u003c/p\u003e \u003cp\u003eA key limitation of this study is the possibility that the patients receiving thrombolysis were inherently more critically unwell than those who did not receive it. Patients selected for thrombolysis might have had longer downtimes, more unwitnessed arrests, or worse baseline prognostic factors compared to those who did not receive the intervention. These unmeasured factors could contribute to the negative outcomes observed in the thrombolysis group. While efforts were made to adjust for confounders using logistic regression, residual confounding cannot be ruled out, particularly given the retrospective nature of the study. Future studies should consider prospectively collecting more granular pre-arrest data to better delineate these confounding effects.\u003c/p\u003e \u003cp\u003eThe use of administrative data and electronic health records introduces potential for misclassification or inaccuracies, particularly given the small number of survivors in the thrombolysis group. Furthermore, variability in post-handover care across multiple hospitals may have introduced inconsistencies in treatment protocols, influencing long-term survival outcomes.\u003c/p\u003e \u003cp\u003eDifferences in data collection periods for the thrombolysis and control groups may also have contributed to variability in the findings. Thrombolysis data were collected over several years due to infrequent administration, while control data were from a single year. Despite adjustments, these differing periods could affect the comparability of the groups.\u003c/p\u003e \u003cp\u003eFinally, the study focused on short-term survival at 30 days, without evaluating longer-term outcomes like functional recovery or quality of life. Future studies should assess these broader outcomes to better understand the full impact of thrombolysis in OHCA.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides important insights into the impact of Thrombolysis on survival outcomes in patients presenting with out-of-hospital cardiac arrest (OHCA). The analysis revealed that Thrombolysis did not improve overall survival rates. Specifically, the primary outcome analysis showed a survival rate of 4% in the Thrombolysis group, with an adjusted odds ratio (AOR) of 0.08 (95% CI: 0.04\u0026ndash;0.19), indicating a substantial 92% decrease in survival odds compared to the control group. These findings suggest that thrombolysis may not provide any meaningful benefit in improving long-term survival in OHCA cases.\u003c/p\u003e \u003cp\u003eThe secondary outcome of return of spontaneous circulation (ROSC) upon arrival at the hospital showed a decreased rate in the Thrombolysis group, with an adjusted odds ratio of 0.21 (95% CI: 0.14\u0026ndash;0.33). This result further questions the benefit of thrombolysis, as it suggests a lower likelihood of achieving ROSC, the immediate measure of resuscitation success. This lack of improvement in ROSC after thrombolysis reinforces the findings of futility in both the short and long-term outcomes.\u003c/p\u003e \u003cp\u003eSubgroup analyses were not performed due to issues with model fit and data compliance, meaning that the potential differential effects of Thrombolysis across different patient subgroups (e.g., by age, rhythm, or witness status) remain unexplored. The lack of reliable subgroup analysis limits our understanding of whether specific groups might benefit from thrombolysis.\u003c/p\u003e \u003cp\u003eKey limitations of this study include its retrospective design, potential for residual confounding, and reliance on single-centre data, which may limit the generalizability of the findings. Variability in post-handover care across multiple hospitals, as well as differing data collection periods between the Thrombolysis and control groups, may introduce bias into the results.\u003c/p\u003e \u003cp\u003eIn clinical practice, these findings suggest that Thrombolysis may not offer significant survival benefits for patients experiencing OHCA and should be used cautiously. Given the limitations of this study, future research should focus on refining patient selection criteria, improving model fit to better capture relevant variables, and investigating post-resuscitation care protocols to enhance outcomes for OHCA patients. The failure to observe any meaningful improvement in survival rates with thrombolysis, even after adjusting for confounders, reinforces the futility of thrombolysis in improving outcomes for OHCA patients. This supports the conclusion that thrombolysis does not offer a survival benefit in this context\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eOHCA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Out-of-hospital cardiac arrest\u003c/p\u003e\n\u003cp\u003eCCP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Critical Care Paramedic\u003c/p\u003e\n\u003cp\u003eSTEMi\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;ST-elevation Myocardial Infarction\u003c/p\u003e\n\u003cp\u003ePPCI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Primary Percutaneous Coronary Intervention\u003c/p\u003e\n\u003cp\u003eROSC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Return of spontaneous circulation\u003c/p\u003e\n\u003cp\u003eALS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Advanced Life Support\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study received United Kingdom Health Research Authority approval (IRAS: 336178) and internal approval from the Research \u0026amp; Development Board at South East Coast Ambulance Service NHS Foundation Trust, Crawley, UK. All the data utilised for this study were routinely collected as part of standard pre-hospital patient data collection. The need for informed consent was waived by IRAS in accordance with UK national regulations, as the study involved retrospective analysis of anonymized data. A full data privacy impact assessment (DPIA) was performed and approved by the Trust’s information governance department. This study meets the requirements of the \u003cem\u003eStrengthening Reporting of Observational Studies in Epidemiology\u003c/em\u003e (STROBE) checklist.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available due to privacy and confidentiality concerns but are available from the corresponding author on reasonable request and with appropriate permissions from the South East Coast Ambulance Service NHS Foundation Trust.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests,\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAlan Cowley:\u003c/strong\u003e Conceptualisation, Methodology, Resourced, Data Curation, Formal Analysis, Investigation, Writing – Original Draft, Writing – Review \u0026amp; Editing. \u003cstrong\u003eDan Cody:\u0026nbsp;\u003c/strong\u003eConceptualisation, Data Curation, Writing – Review \u0026amp; Editing. \u003cstrong\u003eEleanor Jaquet:\u0026nbsp;\u003c/strong\u003eData Curation, Formal Analysis, Writing – Review and Editing. \u0026nbsp;\u003cstrong\u003eMagnus Nelson:\u0026nbsp;\u003c/strong\u003eConceptualisation,Writing – Review and Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the significant contributions made by Eleanor Jaquet (Cardiac Arrest Analyst), Sophie Clark (Quality Improvement Lead) and Mohammad Zaman (Data Scientist) of South East Coast Ambulance Service NHS Foundation Trust for their assistance in their support for the project and data collation/analysis.\u003c/p\u003e\n\u003cp\u003eWe acknowledge the use of Python (version 3.10.11) and the associated library (\u003cem\u003estatsmodel\u003c/em\u003e) for conducting the statistical analyses.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKonstantinides SV, Meyer G, Becattini C, Bueno H, et al. 2019 ESC Guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS): The Task Force for the diagnosis and management of acute pulmonary embolism of the European Society of Cardiology (ESC). \u003cem\u003eEur Heart J\u003c/em\u003e. 2020;41(4):543-603. https://doi.org/10.1093/eurheartj/ehz405.\u003c/li\u003e\n\u003cli\u003eByrne RA, Rossello X, Coughlan JJ, Barbato E, et al. 2023 ESC Guidelines for the management of acute coronary syndromes: Developed by the task force on the management of acute coronary syndromes of the European Society of Cardiology (ESC). \u003cem\u003eEur Heart J\u003c/em\u003e. 2023;44(38):3720-3826. https://doi.org/10.1093/eurheartj/ehad191.\u003c/li\u003e\n\u003cli\u003eHitt A, Pateman J. Intra-cardiac arrest thrombolysis in the pre-hospital setting: four cases worth considering. \u003cem\u003eJ Paramed Pract\u003c/em\u003e. 2015;7(1). https://doi.org/10.12968/jpar.2015.7.1.26.\u003c/li\u003e\n\u003cli\u003eAlshaya OA, Alshaya AI, Badreldin HA, Albalawi ST, et al. Thrombolytic therapy in cardiac arrest caused by cardiac etiologies or presumed pulmonary embolism: An updated systematic review and meta-analysis. \u003cem\u003eRes Pract Thromb Haemost\u003c/em\u003e. 2022;6(4). https://doi.org/10.1002/rth2.12745.\u003c/li\u003e\n\u003cli\u003eB\u0026ouml;ttiger BW, Arntz H-R, Chamberlain DA, Bluhmki E, et al. Thrombolysis during resuscitation for out-of-hospital cardiac arrest. \u003cem\u003eN Engl J Med\u003c/em\u003e. 2008;359(25):2651-2662. https://doi.org/10.1056/NEJMoa070570.\u003c/li\u003e\n\u003c/ol\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":false,"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":"Thrombolysis, Out-of-Hospital Cardiac Arrest, Tenecteplase, Return of Spontaneous Circulation, Survival Outcomes, Ambulance, Paramedic","lastPublishedDoi":"10.21203/rs.3.rs-5198608/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5198608/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThrombolysis has been considered a potential intervention to improve outcomes in out-of-hospital cardiac arrest (OHCA). This retrospective cohort study aimed to evaluate whether thrombolysis offers any meaningful survival benefit by assessing 30-day survival and return of spontaneous circulation (ROSC) upon hospital arrival, with a focus on demonstrating futility.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eData from a single-centre registry, comprising 2,862 OHCA patients, including 171 who received thrombolysis, were analysed. Logistic regression was employed to calculate unadjusted and adjusted odds ratios (OR) with 95% confidence intervals (CI) for the primary outcome of 30-day survival and the secondary outcome of ROSC.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe 30-day survival rate in the thrombolysis group was 4%, substantially lower than in the non-thrombolysis group. The unadjusted odds ratio (OR) for survival with thrombolysis was 0.36 (95% CI 0.16\u0026ndash;0.81), and after adjusting for confounders, the OR decreased to 0.08 (95% CI 0.04\u0026ndash;0.19), indicating a significantly reduced likelihood of survival with thrombolysis. The adjusted OR for achieving return of spontaneous circulation (ROSC) was 0.21 (95% CI 0.14\u0026ndash;0.33), suggesting a similarly diminished likelihood of ROSC with thrombolysis. Both models were highly significant for predictors such as shockable rhythm (OR 15.89 for survival, OR 4.14 for ROSC), witnessed bystander CPR (OR 1.99 for survival, OR 2.04 for ROSC). A MacFaddens R-squared value of 0.27 for the primary outcome, represents a moderate model fit at best.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThrombolysis administration in OHCA was associated with a significant reduction in both 30-day survival and ROSC rates, demonstrating the futility of thrombolysis in improving outcomes in this context. The poor fit of the regression models underscores the need for further investigation to identify additional factors that may impact survival, and to reevaluate the use of thrombolysis in OHCA management.\u003c/p\u003e","manuscriptTitle":"Assessing the Futility of Thrombolysis in Out-of-Hospital Cardiac Arrest. A Retrospective Cohort study.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-28 05:29:59","doi":"10.21203/rs.3.rs-5198608/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":"4ba158ee-6b9b-4d5b-b2ae-ec4546c9a3d8","owner":[],"postedDate":"April 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-06T03:53:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-28 05:29:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5198608","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5198608","identity":"rs-5198608","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}