Pre-hospital delay, thrombolysis timing, and their impact on functional recovery in acute ischemic stroke

INTRODUCTION

Stroke remains one of the leading causes of mortality and long-term disability worldwide and constitutes a major public-health challenge in both developed and developing countries.^[1] In India, the epidemiological profile of stroke has changed markedly over the past few decades. Once considered relatively uncommon, stroke has emerged as a major non-communicable disease due to demographic aging, rapid urbanization, and increasing prevalence of vascular risk factors such as hypertension, diabetes, and obesity.^[2,3] Current estimates indicate that India contributes approximately 15– 18% of the global stroke burden, with an annual incidence ranging from 116 to 163/100,000 population.^[4] Among all stroke subtypes, acute ischemic stroke (AIS) accounts for nearly 70–80% of cases.^[5]

AIS occurs due to the sudden occlusion of a cerebral artery, leading to interruption of blood supply and subsequent brain infarction. The management of AIS is highly time sensitive, reflected in the concept of the “golden window” of treatment. It is estimated that approximately 1.9 million neurons are lost every minute during untreated cerebral ischemia, emphasizing the urgency of rapid intervention.^[6] Intravenous thrombolysis using recombinant tissue plasminogen activator within 4.5 h of symptom onset and mechanical thrombectomy up to 6–24 h in selected patients have demonstrated significant improvements in neurological and functional outcomes.^[7,8] However, the benefits of these therapies depend heavily on minimizing delays across the entire stroke-care pathway.

The time interval between symptom onset and hospital arrival, referred to as pre-hospital delay (PHD), represents a critical barrier to effective stroke treatment. Multiple studies from different parts of India have reported median PHDs ranging from 6 to 12 h, which greatly exceed the recommended therapeutic window for thrombolysis.^[9-11] Several factors contribute to these delays, including poor public awareness of stroke symptoms, lack of knowledge regarding the urgency of treatment, inadequate emergency transport systems, socio-economic constraints, and referral delays between healthcare facilities.^[12] Awareness of classic stroke warning signs – such as facial droop, arm weakness, and speech disturbance – remains limited among the general population in both urban and rural settings.^[4,13] In addition, many patients initially seek care from local practitioners or traditional healers before reaching specialized stroke centers, further prolonging treatment delays.^[14]

Even after reaching a thrombolysis-capable hospital, additional delays may occur during in-hospital management. The door-to-needle (DTN) time, defined as the interval between hospital arrival and initiation of thrombolytic therapy, is recommended to be ≤60 min according to guidelines of the American Heart Association/American Stroke Association.^[15] In practice, however, DTN times in many Indian hospitals often exceed this benchmark. Delays may arise from prolonged triage procedures, imaging bottlenecks, laboratory turnaround times, absence of pre-hospital notification systems, and inadequate coordination among stroke-care teams.^[16,17] Evidence suggests that reducing DTN time significantly improves patient outcomes; each 15 min reduction in DTN has been associated with a 4% decrease in in-hospital mortality and a 5% increase in the likelihood of independent ambulation at discharge.^[18]

The combined duration of pre-hospital and in-hospital delays determines the onset-to-needle (OTN) time, which is a key determinant of the effectiveness of reperfusion therapy. Patients who arrive within the therapeutic window but experience prolonged in-hospital delays may lose the potential benefits of thrombolysis, while those presenting beyond 4.5 h become ineligible for treatment altogether.^[19] Consequently, analyzing the individual components of treatment delay, including patient decision time, emergency transport delay, referral pathways, door-to-imaging (DTI) time, and DTN time, is essential for identifying gaps within the stroke-care system.

Functional outcomes after ischemic stroke are commonly assessed using the modified Rankin Scale (mRS) at 90 days. Several studies have shown that shorter OTN and DTN times are associated with improved functional recovery, typically defined as an mRS score of 0–2.^[7,18,20] Nevertheless, evidence from India remains limited and variable, partly due to differences in healthcare infrastructure, baseline stroke severity, and patient comorbidities.^[9,10,21] Factors such as age, baseline National Institutes of Health Stroke Scale (NIHSS) score, infarct location, collateral circulation, hypertension, and diabetes also influence outcomes; however, treatment timing remains one of the most modifiable determinants in clinical practice.^[5,16,22]

Stroke-care infrastructure in India is heterogeneous. While tertiary centers in metropolitan areas have advanced stroke units and neuro-interventional facilities, many patients in rural or semi-urban regions depend on hospitals lacking imaging or thrombolysis capabilities.^[3,8] As a result, fewer than 10% of stroke patients reach a thrombolysis-capable center within the recommended treatment window.^[12,23] Although several studies from northern and eastern India have examined delays in stroke care, region-specific data from Tamil Nadu, one of India’s better-performing health systems with established emergency services such as the “108 ambulance” network, remain limited.^[15,21]

In this context, the present prospective observational study was conducted among consecutive patients with AIS receiving reperfusion therapy at a tertiary care center in Tamil Nadu between January 2023 and December 2024. The study aimed to quantify pre-hospital and in-hospital delays, examine their relationship with neurological and functional outcomes at 90 days, and identify critical points in the stroke-care pathway that may serve as targets for quality improvement within the regional healthcare system.

MATERIALS AND METHODS

RESULTS

Baseline demographic, clinical, and stroke-related characteristics stratified by 90-day functional outcome are summarized in Table 1. A total of 250 consecutive patients with AIS who received reperfusion therapy and completed 90-day follow-up were included in the final analysis. Overall, 131 patients achieved a good functional outcome (mRS 0–2; 52.4%, 95% CI 46.2–58.5), whereas 119 had a poor outcome (mRS 3–6; 47.6%, 95% CI 41.5–53.8). Patients with a good functional outcome were significantly younger than those with a poor outcome (58.3 ± 11.2 vs. 63.9 ± 12.1 years; p = 0.002). Sex distribution was comparable between groups, with no statistically significant difference in the proportion of males. Urban residence was more frequent among patients with good outcomes (64.1% vs. 48.7%; p = 0.01), suggesting a possible influence of healthcare access and system-related factors. Hypertension and diabetes mellitus were significantly more prevalent in the poor-outcome group (hypertension: 82.3% vs. 62.6%, p = 0.001; diabetes: 61.3% vs. 34.4%, p < 0.001), while atrial fibrillation was also more common (16.8% vs. 6.1%; p = 0.009). Patients with good recovery had lower baseline NIHSS scores (median 9 [IQR 6–12] vs. 16 [IQR 12–20]; p < 0.001) and higher ASPECTS values (8.9 ± 0.9 vs. 8.1 ± 1.2; p < 0.001).

Analysis of acute stroke workflow revealed substantial delays across the care pathway, with important implications for functional outcome, as summarized in Table 2. Median OTD time was 215 min, and 147 patients arrived within the benchmark of ≤270 min (58.8%, 95% CI 52.6–64.7; 1 = 0.001). DTI time met the ≤30 min target in 164 patients (65.6%, 95% CI 59.5–71.1; p = 0.03). DTN time emerged as a critical determinant: only 93 patients achieved DTN ≤60 min (37.2%, 95% CI 31.4–43.3), whereas 157 were treated beyond 60 min (62.8%, 95% CI 56.7–68.6; p < 0.001). Similarly, only 60 patients received treatment within OTN ≤180 min (24.0%, 95% CI 19.1–29.7), while 190 were treated later (76.0%, 95% CI 70.3–80.9; p < 0.001). EMS pre-notification was documented in 68 cases (27.2%, 95% CI 22.1–33.0) and was strongly associated with improved outcomes (p < 0.001).

A clear time–outcome gradient was observed across thrombolysis timing categories [Table 3]. Patients treated with DTN ≤60 min had the highest rate of good functional outcome (66.7%, 95% CI 56.6–75.4), compared with 52.1% (95% CI 42.1–61.9) for DTN 61–90 min and 31.7% (95% CI 21.6–44.0) for DTN >90 min. A similar pattern was evident for OTN intervals: 70.0% (95% CI 57.5–80.1) of patients treated within 180 min achieved good outcomes, compared with 59.0% (95% CI 49.2–68.1) for 181–270 min and 33.3% (95% CI 24.5–43.6) when treatment exceeded 270 min. These findings underscore the cumulative detrimental effect of pre-hospital and in-hospital delays on neurological recovery.

In multivariable logistic regression adjusting for demographic, clinical, and workflow variables, several factors independently predicted good functional outcome at 90 days [Table 4; Figure 1]. DTN ≤60 min was associated with more than a two-fold increase in the odds of a good outcome (AOR 2.21, 95% CI 1.33–3.55; p = 0.002). OTN ≤180 min independently conferred benefit (AOR 1.88, 95% CI 1.07–3.21; p = 0.03). Baseline NIHSS <10 remained the strongest clinical predictor (AOR 3.02, 95% CI 1.89–4.76; p < 0.001). Younger age <65 years (AOR 1.72, 95% CI 1.01–2.94; P = 0.047) and urban residence (AOR 1.61, 95% CI 1.00–2.57; p = 0.048) were also independently associated with better outcomes, whereas diabetes mellitus reduced the likelihood of functional independence (AOR 0.64, 95% CI 0.42–0.98; p = 0.04). The model showed acceptable explanatory power and calibration (Nagelkerke R² = 0.28; Hosmer–Lemeshow p = 0.69).

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Figure 1: Forest plot of predictors of good functional outcome at 90 days. CI: Confidence interval, OR: Odds ratio, OTN: Onset to needle, DTN: Door to needle, p value <0.05 is considered as statistically significant.

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When clinical efficacy and safety outcomes were stratified by DTN category [Table 5], earlier thrombolysis was associated with more favorable clinical outcomes, while safety outcomes remained comparable across groups. Rates of early neurological improvement (≥4-point NIHSS reduction) declined progressively with increasing DTN delay (67.7%, 48.9%, and 38.1%; p < 0.001). Length of hospital stay increased significantly with delayed thrombolysis (p = 0.002). Importantly, symptomatic intracerebral hemorrhage occurred in 11 patients overall (4.4%, 95% CI 2.5–7.7) and 90-day mortality in 18 patients (7.2%, 95% CI 4.6–11.1), with no statistically significant increase in these safety endpoints among patients treated more rapidly.

Correlations among acute stroke workflow intervals are summarized in Table 6. DTI showed strong positive correlations with DTN (Spearman r = 0.76, p < 0.001), imaging-to-needle time correlated with DTN (r = 0.68, p < 0.001), OTD correlated strongly with OTN (r = 0.81, p < 0.001), and DTI correlated with imaging-to-needle time (r = 0.59, p < 0.001).

Table 7 compares clinical outcomes and workflow metrics for stroke patients treated in 2023 and 2024. Patients treated in 2024 had a significantly higher percentage of favorable functional outcomes than those treated in 2023 (59.4%, 95% CI 50.7–67.5 vs. 49.2%, 95% CI 40.5–57.9; p = 0.04). Early neurological improvement was also more frequent in 2024 than in 2023 (61.7%, 95% CI 53.1–69.7 vs. 48.4%, 95% CI 39.7–57.1; p = 0.03), suggesting a better early treatment response in the later cohort.

A marked enhancement in stroke care delivery was also apparent in the process-of-care metrics. Median DTN time decreased significantly from 76 min in 2023 to 63 min in 2024 (p = 0.01). EMS pre-notification rates rose from 21.3% to 35.2% (p = 0.02), reflecting better pre-hospital coordination and greater preparedness of the stroke team.

Crucially, safety outcomes remained comparable across the 2 years. The rate of symptomatic intracerebral hemorrhage did not differ significantly between 2023 and 2024 (5.7% vs. 3.9%; p = 0.51). Similarly, 90-day mortality did not differ significantly between the cohorts (9.0% vs. 6.3%; p = 0.42), indicating that improved functional outcomes were achieved without an increase in adverse events.

DISCUSSION

The present prospective observational study, conducted at a tertiary care center in Tamil Nadu, evaluated the relationship between PHD, thrombolysis timing, and functional recovery in patients with AIS. The findings clearly demonstrate that time-to-treatment remains the strongest determinant of neurological and functional outcomes. Shorter OTD and DTN intervals were associated with significantly better 90-day functional recovery, while prolonged delays, both pre-hospital and in-hospital, contributed to poor prognosis, reaffirming the global principle that time is brain. The median PHD of 220 min observed in this study aligns closely with data from other Indian centers, which have reported median values between 200 and 300 min.^[9,11,27] Ghosh et al. from eastern India found that only 27% of patients arrived within 4.5 h of symptom onset, with a median delay of 6 h.^[27] Similarly, Chaturvedi et al. in North India reported that less than one-third of patients reached the hospital within the thrombolysis window.^[9] In our study, 24.9% of patients arrived within 2 h, indicating modest improvement, possibly due to the better functioning of the 108-emergency ambulance network and greater urban penetration of stroke services in Tamil Nadu.^[19,21]

The pattern of rural–urban disparity is consistent with the Indian Stroke Prospective Registry (INSTR) findings, which revealed that rural residence was independently associated with longer OTD time and lower thrombolysis rates.^[23] Our regression analysis confirmed similar trends, with rural patients experiencing an average delay of 38 min even after adjusting for referral and transport factors. These findings highlight persistent geographic inequities in access to timely stroke care in India.^[3,8]

Globally, the median OTD time in developed stroke systems, such as those in the United States and Europe, is between 60 and 90 min, substantially shorter than Indian figures.^[7,15] This difference primarily reflects effective public awareness, pre-notification, and dedicated pre-hospital stroke protocols in high-income countries.^[16] The disparity underscores the urgent need for public health campaigns and EMS integration in India. The median DTN time of 68 min in our cohort demonstrates gradual improvement compared with earlier Indian studies, which reported mean DTN times of 85–100 min.^[7,10,12] Dutta et al. from Kolkata observed a mean DTN of 82 min, with only 25% achieving the ≤60 min benchmark.^[10] In contrast, our center achieved 38% within 60 min, suggesting a positive shift likely attributable to streamlined imaging and pharmacy preparedness. Nevertheless, this remains below the performance reported in Western registries such as “Get with the Guidelines– Stroke,” where median DTN is around 45 min.^[15]

The significant correlation between ambulance pre-notification and shorter DTN in this study mirrors global evidence. Pandian et al. emphasized that early alerts from emergency services allow stroke teams to mobilize, prepare CT suites, and pre-mix thrombolytic agents, reducing door-to-treatment intervals.^[8] Our results confirm this: Patients with pre-notification had a median DTN of 48 min compared to 74 min without pre-alert (p < 0.001). Thus, implementing pre-hospital notification protocols universally could yield immediate benefits without substantial infrastructural investment.

Patients treated within DTN ≤60 min had more than twice the adjusted odds of achieving mRS 0–2 at 90 days (AOR 2.21; 95% CI 1.33–3.55; p = 0.002). This observation parallels data from the Safe Implementation of Thrombolysis in Stroke (SITS-ISTR) registry, where each 15 min reduction in DTN improved odds of a favorable outcome by 5%.^[18] Similar findings were reported in the INSTR registry, where good outcomes were achieved in 64% of patients treated within 60 min versus 42% beyond 90 min.^[12]

The median OTN time of 280 min in our study reflects the combined effect of pre-hospital and in-hospital delays. Consistent with prior evidence,^[16,23] patients treated within 180 min of onset were more likely to achieve neurological improvement and functional independence (AOR for good outcome 1.88; 95% CI 1.07–3.21; p = 0.03). The OTN threshold of ≤180 min, therefore, emerges as a critical operational target in resource-constrained settings. At 90 days, 52.4% of patients achieved good functional recovery, comparable with reports from Indian tertiary centers (45–55%).^[9,10,17] In our cohort, every delay increment was associated with lower recovery rates, reaffirming the dose–response relationship between time and outcome. Baseline severity (NIHSS <10) and younger age were additional independent predictors of favorable outcomes, consistent with international meta-analyses.^[7,18] Interestingly, patients treated with tenecteplase achieved slightly faster DTN and marginally better early improvement than those receiving alteplase, although this difference was not statistically significant. This aligns with recent Indian experiences showing comparable efficacy and simpler logistics for tenecteplase, making it a practical alternative in busy emergency settings.^[12,15]

The observed rise in pre-notification rates (21–35%) mirrors outcomes from Tamil Nadu’s state-wide stroke audit initiative, which emphasized EMS-hospital coordination.^[19] Improvement in 90-day good outcomes from 49% to 59% across consecutive years further validates the cumulative benefit of time optimization. Despite growing institutional expertise, the greatest bottleneck remains PHD, accounting for nearly 60% of total treatment time. Similar patterns are observed across the Indian subcontinent.^[4,9,27] These findings highlight the need for community-level stroke literacy programs, focusing on Face–Arm–Speech–Time recognition, mandatory ambulance use, and discouragement of local or informal first-contact care. Integration of tele-stroke support in peripheral hospitals could facilitate early triage and rapid transfer to thrombolysis-capable centers.^[8,21]

In addition, EMS reform is critical. Structured training for 108 ambulance personnel in stroke identification and pre-notification could shorten OTD times by 30–45 min, as suggested by Pandian et al.^[8] and validated by our regression findings. Policymakers should also ensure equitable distribution of CT and thrombolytic facilities in district hospitals to mitigate rural disadvantage.^[3,23] When benchmarked against international stroke systems, the proportion of patients treated within the golden hour (DTN ≤ 60 min) in our study (38%) remains below the 60–70% reported in North American and European networks.^[15,18] However, the improvement trajectory indicates convergence. The post-thrombolysis good-outcome rate (54.8%) is nearly identical to that of the global SITS registry (55%), demonstrating that once treated, Indian patients achieve outcomes comparable to Western counterparts.^[7,18] Therefore, system delays, not biological or therapeutic differences, are the primary challenge. A key strength of this study is the relatively large sample size and comprehensive retrieval of precise time stamps, verified from multiple sources, ensuring reliability. Inclusion of both IV thrombolysis and bridging therapy enhances external validity.

CONCLUSION

The current findings reaffirm that time remains the most critical modifiable factor influencing outcomes after ischemic stroke. Both pre-hospital and in-hospital delays significantly reduce the likelihood of functional independence at 90 days. Tamil Nadu’s emerging stroke systems demonstrate measurable progress, but further gains require strengthening community awareness, ambulance pre-notification, and hospital workflow integration. By combining public education, EMS training, and data-driven hospital benchmarking, it is possible to replicate the success of global “stroke chain of survival” models within the Indian healthcare ecosystem. Future multicentric prospective studies and state-wide audits are warranted to validate these results and support the creation of time-based quality indicators for national stroke care improvement.