Increased risk of ischemic stroke in patients with burn injury: a nationwide cohort study in Taiwan

This study was conducted in accordance to the tenets of the Helsinki Declaration. The Institutional Review Board of Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Taiwan, approved the study. The need for informed consent was waived because patient record/information was anonymous and no identifiers were employed.

The Taiwanese National Health Insurance (NHI) program was initiated in 1995, and has been described in detail previously [11‐13]. Utilizing the Longitudinal Health Insurance Database (2005), a dataset comprising 1,000,000 individuals who were representative beneficiaries of the NHI program was randomly sampled.

The representative population sample was systematically tracked between January 1, 2003 and December 31, 2012. Individuals aged >18 years who were alive in 2005 were initially identified. Burn injury was defined by the ICD-9-CM codes 940–949. Only patients hospitalized for burn injuries were enrolled in the study, thereby excluding those sustaining mild burns. Ischemic stroke was defined by ICD-9-CM codes 433–437 [14]. To maximize the scope of our study, we included only those patients hospitalized for stroke. Patients with burn injuries and any type of stroke diagnosed before January 1, 2005 were excluded from the study to ensure all enrolled cases and events were new. We chose to focus on ischemic stroke alone to avoid any possible overlap between the ICD-9-CM codes for traumatic intracranial hemorrhage and hemorrhagic stroke. Patients diagnosed with hemorrhagic stroke during follow-up were also excluded. After excluding patients according to the aforementioned criteria, we identified 1,787 patients hospitalized with burn injuries and 741,510 without burn injuries. Each group was followed from the hospitalization date or January 1, 2005 (baseline) to December 31, 2012 (end of the study period) for verification of a diagnosis of ischemic stroke during the study period. Patients who were no longer beneficiaries of the NHI Program (due to death or transfer) or were still healthy at the end of the follow-up period were carefully monitored (Fig. 1).

We investigated the validity of the ICD-9-CM codes for the identification of burn injuries and ischemic stroke. The codes were validated by analyzing medical records randomly selected from the electronic database from 2010 to 2012 at the Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation. We then estimated the positive predictive value (PPV). A systematic chart review confirmed the diagnosis in 45 of 50 randomly selected patients with codes for burn injuries, thereby validating a PPV of 90 % (95 % CI, 78.2 %–96.7 %). In addition, the diagnosis was also confirmed in 47 of 50 randomly selected patients with codes for ischemic stroke, validating a PPV of 94 % (95 % CI, 83.5 %–98.7 %).

To better understand the effect of burn injury on the risk of ischemic stroke, several covariates were selected including age, sex, urbanization level (i.e., urban, suburban, and rural), and socioeconomic status (SES). Income-related insurance payment amounts were used as a proxy measure of individual SES at follow-up [15]. The prevalence of selected comorbidity factors (i.e., diabetes, hypertension, coronary artery disease, hyperlipidemia, history of alcohol intoxication, malignancies, heart failure, atrial fibrillation, history of smoking and peripheral artery disease) and the Charlson Comorbidity Index (CCI) were determined using discharge diagnoses either during outpatient clinic visits or hospitalizations before January 1, 2005. The CCI represents a scoring system with weighted factors of important concomitant diseases and is widely used in the ICD-9-CM coded administrative databases [14].

The high-dimensional propensity score (hdPS), available as an SAS macro from the Brigham and Women’s Hospital [16, 17], is a multistep, empirically driven algorithm that is used to adjust for confounding bias. Candidate covariates from predefined data dimensions, such as clinical treatment received, medications administered based on the Anatomical Therapeutic Chemical (ATC) Classification System, and coded diagnoses reported in this study from January 1, 2003 to December 31, 2004, were identified using the SAS macro. It automatically assesses the repetition of the same codes, prioritizes covariates, and identifies covariates for adjustment. We selected the top 500 variables most likely to result in a bias.

In addition to these 500 variables, the pre-selected covariates were analyzed with a logistic regression model to estimate the predicted probability (propensity score) of exposure of the study subjects to burn injuries when compared with the healthy population. This exposure is conditional on all the included covariates. After using a standard greedy matching algorithm to match all burn injury patients with 100 non-burn injury patients having the closest propensity scores [18, 19], we compared the risk for the development of ischemic stroke between the two groups.

To further validate the accuracy of our results, we also performed sensitivity analyses to evaluate the extent of the effect of an unmeasured confounder on the results [20]. A two-tailed p-value of 0.05 was considered significant.

Our study was associated with several limitations. We used administrative data to generate our findings and ICD-9-CM codes for defining burn injury and ischemic stroke. These codes are often not as useful for precise operative definitions, since they are primarily used for insurance reimbursement. Thus, it is impossible to accurately determine the sensitivity, specificity, and clinical accuracy of the diagnoses when employing such data. To mitigate the number of false-positive cases, the inclusion criteria for burn injury and ischemic stroke patients were restricted to only those patients who had been hospitalized. The high PPVs that we observed validated the selection process, despite the size of our study and the use of a local database.

In the present study, the relationship between the affected body region(s) and risk of ischemic stroke in burn injury patients was not evaluated because we were able to obtain only limited information from the administrative database. Individual studies will be required to determine whether HRs differ significantly among different body regions (e.g., head versus torso).

In our study, subgroup analyses in patients with severe burn injuries to evaluate the severity-response effects were not performed. As mentioned previously, severe burn patients may have more comorbid risk factors (e.g., restricted mobility and higher mortality), possibly precluding ischemic stroke diagnosis.

Finally evaluation of other possible risk factors of burn injuries and ischemic stroke by the matched cohort method was complicated by the use of propensity score analyses to adjust for possible confounders. Although extensive adjustments for many possible covariates were made, the possibility of the presence of unmeasured confounders and overmatching bias remain. However, the adjusted HR for ischemic stroke in burn injury was sufficiently significant to indicate that the residual confounders may be unable to completely account for the results.