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A study of factors delaying hospital arrival of patients with acute stroke.
Correspondence Address:
Thrombolytic therapy for acute ischaemic stroke has recently become available in India but its success depends on initiating the treatment in the narrow therapeutic time window. There is commonly a delay of several hours before patients with acute stroke seek medical attention. A prospective study was conducted to assess the factors influencing this delay in admission of acute stroke cases. 110 cases (71 males, 39 females) of acute stroke that arrived within 72 hours at our hospital casualty were recruited. A standardized structured questionnaire was given to patients or their attendants. The median time to casualty arrival was 7.66 hours with 25% cases arriving within 3 hours and 49 % cases within 6 hours. Distance from hospital, contact with a local doctor and low threat perception of symptoms of stroke were independent factors associated with delay in arrival. Living in city, presence of family history and older age were associated with early arrival. There was no correlation with patients' or attendants' sex, educational status, history of previous stroke or transient ischaemic attack, subtype or severity of stroke, time of stroke and availability of transport. Adequate measures need to be taken to improve the public awareness of stroke and the role of local doctors.
Medical treatment of acute stroke with thrombolytics has recently become available in India. Start of treatment in the narrow therapeutic time window is crucial for successful treatment with these agents. The therapeutic window is less than 3 hours for thrombolytic agents and the best results may be attained with administration within 90 minutes. Recombinant tissue plasminogen activator (r-tPA) has been approved in USA for acute stroke treatment within a 3 hours time frame.[1],[2] However, it has been seen that patients with acute stroke are often admitted late. Median time from onset to admission ranged in previous studies[3],[4],[5],[6],[7],[8],[9],[10] from 4 hours to more than 24 hours. Some studies[11] have concluded that early neurological attention is associated with better functional outcome and shorter hospitalisation. Intervention further improves the outcome. With the availability of effective treatment for acute stroke, it is important to analyse the factors responsible for the delay. Studies from western countries[3],[4],[5],[6],[7],[8],[9],[10] have evaluated the factors associated with delayed or early arrival of acute stroke patients to hospital. Factors like living alone, retired working status, referral pattern, contact with local medical personnel, nocturnal onset, ischaemic stroke have been found to delay arrival while day time stroke, haemorrhagic stroke, severe stroke, previous history of stroke favour early arrival. The socio-cultural profile in India is different from that in western countries. In India, most of the people live in villages and towns, they prefer living in joint families, general level of education and awareness is low and they opt for alternative modalities of treatment for such illness. There is lack of adequate and fast transport facilities that worsen the scenario. Therefore, this study was initiated to analyse the influence of demographic, medical, personal, attitudinal and social factors on time elapsed before arrival of patients of stroke to the casualty department of All India Institute of Medical Sciences, New Delhi.
All patients admitted to neurology wards of the hospital from April'97 to July'98 were included if they fulfilled the criteria for diagnosis of stroke. Stroke was defined, according to the WHO definition,[12] as 'rapidly developing clinical sign of focal (or global) disturbance of cerebral function, lasting more than 24 hours or leading to death with no apparent cause other than of vascular origin'. Time of onset of stroke was defined as the time when the patient or observer first became aware of the symptoms. All stroke patients were seen in the emergency department by a resident in neurology. An emergency computerized axial tomography scan (CT scan) was done if not already available and the patients admitted to neurology ward at the earliest. A thorough clinical examination was conducted and findings recorded in a pre- designed form. Patients/attendants were asked regarding the time elapsed between first becoming aware of symptoms and reaching to this hospital. The decision regarding treatment was left on the treating neurologist. A standard structured questionnaire was completed for every patient by interviewing the patient (if possible) and the accompanying attendant/relative. The questionnaire documented the patient's age, sex, past history of transient ischaemic attack (TIA), stroke, educational level, whether living alone or not, any stroke education, recognition of stroke by patient/relative/doctor. Relation, age, sex and educational status of attendant/relative were also recorded. The patient/attendant was asked whether he believed that the symptoms would improve spontaneously (low threat perception). Time of contact with a local doctor was recorded if they contacted a local doctor. Time of arrival to the hospital was the time noted on casualty services records. For the purpose of this study, time elapsed between onset and casualty arrival was taken as outcome variable. Statistical Analysis : Data was entered into SPSS PC + Version 4.0.1.Using logical operations and range functions, the variables under consideration were checked for accuracy and errors thus detected were corrected. Distribution of all the continuous data was examined. As the dependent variable was found to have exponential distribution, natural logarithmic transformation was done to normalize the distribution and to justify the use of t - test, analysis of variance and multiple regression. Time elapsed between onset of stroke and arrival to casualty was taken as dependent variable. Bivariate analysis between dependent and independent variables having two groups or analysis of variance for independent variables having more than two groups were performed. The independent variables found to have a 'p' value of < 0.25 were selected for multivariate analysis. The 'p' value of < 0.25 was taken so that no variable of importance was excluded from multivariate analysis. Multivariate analysis was done using multiple regression model with the dependent variable in logarithmic form (for reasons given above). Backward step-wise procedure was used for model building.
110 cases (71 males, 39 females) that arrived in casualty within 72 hours of onset of symptoms were included. The temporal characteristics of patients are shown in Table I. The mean age of the patients was 58.9 years. Median time to casualty arrival was 7.66 hours. About 25% patients were admitted within 3 hours, 49% within 6 hours and 87% within 24 hours. Most strokes (62.7%) were ischaemic. In one case, CT scan could not be done but the clinical possibility was intracerebral haemorrhage (ICH). The interval between onset and arrival was not influenced by the time of the day at which stroke occurred (p>0.09). Time elapsed from awareness to arrival was taken as dependent variable measured on a continuous scale upto 2 decimal places. Variables of interest were tested in a bivariate analysis against time elapsed before arrival. Place of living was subdivided into three sub groups as different variables- city, town and village. Place of residence (p=0.0007), sense of urgency of attendant (p=0.038), availability of transport (p=0.023), threat perception (p=0.001), distance (p=0.001), contact with a local doctor (p<0.0001) and history of previous stroke (p=0.02) were significantly associated with the time elapsed before arrival [Table:II]. As several independent variables were likely to be correlated, their independent association with time elapsed before arrival was examined in a multivariate analysis. Variables, which on bivariate analysis, had p value upto 0.25, were included for this analysis. Multiple linear regression analysis showed that distance, contact with local doctor and low threat perception were independent factors associated with delay in arrival. Living in city, presence of family history and older age were associated with early arrival. The final analysis is shown in Table III. Patient's sex (p=0.19), type of stroke (p=0.07), time consumption in transport arrangement (p=0.12), sex of attendant (p=0.17), level of education of patient (p=0.84) and attendant (p>0.05), attendants' relation with patient (p=0.56), recognition of symptoms as stroke (p=0.89) were not found to have significant association with the time elapsed on bivariate analysis. Motor response of GCS at presentation was divided in two groups 1-5 and > 6, and values of 0 and 1 were given respectively. This division was done to divide patients into 'unconscious' and 'conscious' group, which was more likely to affect the decision of relatives of bringing the patients to the hospital. It was not significant (p=0.36) on bivariate analysis. History of hypertension, diabetes, cardiac disease, transient ischaemic attacks (TIA), previous stroke, smoking, alcoholism was also not significant on bivariate analysis. Patients occupation had significant correlation (p=0.04) on bivariate analysis but none on multiple regression analysis. Servicing personnel arrived late with a mean delay of 10.91 hours. Others group which mainly comprised of housewives and retired persons arrived early with a mean delay of 5.64 hours. Multiple regression analysis of important variables was also done for cases arriving in the casualty within 24 hours. Local doctor contact, distance, low threat perception and residence in a city were independent statistically significant predictor variables. Time of arrival was splitted into two groups i.e. <6 hours and >6 hours and multivariate logistic regression analysis was repeated which also identified same factors delaying hospital arrival of patients.
Delay in arrival of acute stroke cases may be caused by organisational, educational, geographical and demographic factors. Geographic, organisational and educational factors have somewhat predictable effect on admission time, however, influence of demographic and medical factors have unpredictable impact. This study has included both predictable and unpredictable factors. Out of 110 cases, who were admitted within 72 hrs, about 25% patients arrived within 3 hours, 49% within 6 hours and 87% within 24 hours. These figures are comparable to studies[2],[3],[4],[5],[6],[9],[10] performed in other countries. The factors that could delay arrival to hospital operate only when patient/attendant becomes aware of symptoms. We have taken stroke onset time as the time when patient/attendant first became aware of symptoms. So the apparent delay in our study may be an under-estimation of the exact delay. The delay in admission was not related to the severity of stroke. GCS motor response was taken as criteria for severity. Patients with motor response 1-5 were admitted earlier but it was not significant on bivariate or multivariate analysis. Others studies[6],[9] have also reported that initial severity of stroke did not influence the admission time. Stroke subtype was not found to have any significant relation on bivariate (p=0.07) or multivariate analysis. Effect of stroke subtype on delay in arrival has been controversial.[3],[4],[5],[6],[7],[10] Jorgensen et al[8] found some relation on univariate analysis but not on multivariate analysis. Studies by Albert et al[4] and Fogelholm et al[7] have shown significant relation. But, they have not included other factors in their study. In more than half of the patients, stroke onset time was not available. All the 110 patients in this study, lived with some attendant and none was living alone, which has been shown to be an independent factor in western studies. This is not a factor in India, probably because, Indians mostly live in joint families or are well looked after by their relatives. Place of living had no effect in previous studies[7],[8] but in India this was suspected to be an important factor because people mostly live in towns and villages. In the present study, the index hospital was in a city, hence 21/110 (19.09%) cases were from villages. Living in city had significant independent association with early arrival on multivariate analysis. Villages are not well connected with city and people usually contact an unqualified practitioner or traditional healers initially. Distance from hospital as a delaying factor has not been studied in previous western studies,[4],[5],[7],[8],[9],[10] because distance was not considered a factor, which could delay in arrival, and also because of easy availability of ambulance services. In our study, distance was found to have independent significant association on multivariate analysis. This is due to long tapping area of the study hospital, which is a premier tertiary care hospital. 36 of 110 attendants of the patients had a low threat perception, though they recognised the symptoms as stroke but thought that it would resolve spontaneously. On multivariate analysis, this was found to be independently significant. This factor has not been evaluated in previous studies. Only Feldman et al[6] studied this factor and he did not find it to be significant but we considered that attendants have got an important role in deciding whether a paralysed patient is to be taken to a hospital or not, as the patient often is drowsy/ aphasic/ disabled and cannot decide himself whether to go to a hospital or not. Availability of transport facility is an important problem in India causing delay in arrival of stroke patients. This factor was found to be significant on bivariate analysis but not on multivariate analysis. Significant early arrival of acute stroke cases has been reported, where ambulance services are easily available.[5] Older patients arrived significantly earlier according to the results of the multivariate analysis. Feldman et al[6] has also made a similar observation. Early arrival of older patients may be due to availability of younger family members capable of arranging transportation. Younger patients may only have children at home and hence not be able to arrange early transportation. Contact with a local doctor after acute stroke had independent significant association with delay in arrival on multivariate analysis. This has been noticed in a previous study as well.[5] In our country, it could be due to large number of unqualified practitioners and also ignorance of qualified practitioners about the need to transfer the patients to an organised stroke care center. History of previous stroke was significant on bivariate analysis. This could be because patients after having a stroke sooner or later contacted qualified knowledgeable medical person who would have explained him about the urgency of acute stroke. However, it was not significant on multivariate analysis. Family history of stroke was found to be an independent factor for delay in arrival. Only Feldman et al[6] studied this factor and found it to be significant. Probably such families were more aware of symptoms of stroke and its consequences. We did not find any correlation with patient's sex, type of stroke, initial level of sensorium, educational level of patient/attendant, knowledge of stroke of the patient, history of hypertension, diabetes, cardiac disease, smoking and alcoholism as in various other studies. History of TIA was also not found to be a significant factor for bringing the patient to hospital early. This could be due to the fact that either the patients did not consult any doctor/hospital for TIA or if they consulted they were not explained about the significance of such symptoms [Table:II]. The factors that we have identified account for about 58% of variation on time elapsed before arrival (adjusted R2= 57.8%). The remaining 42% of the variation may have several underlying factors that could not turn up as statistically significant, because of small sample size. But the factors identified are clearly the most important ones contributing to majority of the variation in time elapsed before arrival. It can, thus, be concluded, that time elapsed before arrival from onset is significantly prolonged by factors like - distance from hospital and contact with a local doctor and low threat perception of attendant. Family history of stroke, older age and living in city is significantly associated with early arrival to casualty, but these are largely non- modifiable. Measures to reduce the delay in arrival of acute stroke patients to specialist will require careful education among the profession and the public of the importance of prompt transfer. This could have an impact on modifiable factors like low threat perception and local doctors' role. Distance related time factor could also be partially dealt with arranging high-speed, easily available ambulance services.
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