Discussion

In this study, we have measured the effect of pre-existing conditions and medical complications on SAH mortality, while controlling for age, sex, and the severity of neurological injury. Of the 637 patients in our cohort, 94 died within a year of their initial SAH diagnosis (14.76%), of which 85 patients died during the hospitalization episode (13.3%). These mortality rates are similar to those previously reported for in-hospital and one-year mortalities (12.6%–13.9%), for SAH patients who were admitted to the hospital and underwent angiography or neurosurgical clipping of an aneurysm. ^{Reference Stienen, Germans and Burkhardt26,Reference Ronkainen, Niskanen, Rinne, Koivisto, Hernesniemi and Vapalahti27} Male sex was not significantly associated with mortality in our cohort OR, 1.45 [95% CI 0.90–2.33]. This finding is consistent with recent studies which show sex does not appear associated with mortality, when controlling for other risk factors including the severity of the neurological injury and age. ^{Reference Abulhasan, Alabdulraheem, Simoneau, Angle and Teitelbaum6–Reference Lantigua, Ortega-Gutierrez and Schmidt9,Reference Claassen, Vu and Kreiter28}

In our cohort, age was not found to be associated with mortality OR, 1.00 [95% CI 0.99–1.02]. While several studies looking at new SAH patients have found that increasing age is associated with increased mortality, ^{Reference Abulhasan, Alabdulraheem, Simoneau, Angle and Teitelbaum6–Reference Lee, Ouyang and John10} a large institutional study looking exclusively at patients who were treated with angiography or neurosurgical clipping found that increasing age was not associated with increased mortality. ^{Reference Degos, Gourraud and Tursis29} Our findings are consistent with this study and may be due to patients selected to undergo aneurysmal treatments are deemed medically and neurologically salvageable and may share similar clinical characteristics.

Compared to patients with no pre-existing conditions, having 1 or 2 pre-existing conditions did not significantly increase mortality at 1 year but having ≥3 pre-existing conditions was associated with increased one-year mortality OR 3.74, [95% CI 1.25–9.57]. Compared to patients with no medical complications, having 2 or ≥3 complications was associated with increased one-year mortality, OR 2.42 [95% CI 1.25–4.69], and OR 2.69 [95% CI 1.43–5.07], respectively, after controlling for age, sex, severity of neurological injury, and the number of pre-existing conditions.

When looking at which specific pre-existing conditions affect mortality, Norberg et al., reported patients with a history of cardiac disease HR, 2.31 [95% CI 1.26–4.22], cerebrovascular disease HR, 2.35 [95% CI 1.19–4.66], and renal disease HR, 3.23 [95% CI 1.18–8.96], showed higher risks of mortality [36]. In our cohort, we also reported cardiac disease, including congestive heart failure OR, 3.98 [95% CI 1.10–14.37], and myocardial infarction OR, 4.78 [95% CI 1.26–18.15], cerebrovascular disease OR, 2.99 [95% CI 1.00–8.97], and renal disease OR, 3.98 [95% CI 1.10–14.37, to be associated with increased mortality on univariate logistic regression analysis (Table 3). They had however also reported hypertension to be associated with increased mortality, HR, 1.74 [95% CI 1.18–2.57], which we did not, and they had not reported malignancy or diabetes to be associated, which we did OR, 2.29 [95% CI 1.03–5.09] and OR, 2.26 [95% CI 1.15–4.44], respectively. These differences may be due to several methodological differences including the use of chart review in the Norberg study to determine pre-existing conditions, a different geographic location (Montréal versus Sweden), and the fact we selected only patients who had undergone angiography or neurosurgical treatment of the aneurysm. Previous research on SAH has shown that geographic location can affect the risk of rupture of aneurysms. This is particularly true for Scandinavian countries which have been found to have a high risk of aneurysmal rupture when compared to North American countries. ^{Reference Bijlenga, Gondar and Schilling30} Of note, on multivariate logistic regression, controlling for age, sex, the severity of neurological injury and medical complications (Table 5), none of the pre-existing conditions was found to be associated with increased mortality. As seen in Table 2, pre-existing conditions are associated with increased odds of patients having medical complications.

As seen in Table 5, we completed a multivariate logistic regression, controlling for age, sex, the severity of neurological injury, and the pre-existing conditions and medical complications that were found to be associated with increased mortality on univariate logistic regression (p < 0.05), in Tables 3 and 4. Looking at specific medical complications, respiratory failure was associated with increased mortality in our cohort OR, 4.13 [95% CI 1.33–12.80]. This finding is consistent with Solenski et al., who reported that pulmonary complications were the most common cause of death in their cohort. ^{Reference Solenski, Haley and Kassell31} Sepsis was also associated with increased mortality OR, 4.95 [95% CI 1.37–17.83]. This is consistent with previous groups that had reported hypotension and fever to be associated with mortality. ^{Reference Lantigua, Ortega-Gutierrez and Schmidt9,Reference Wartenberg, Schmidt and Claassen15} Cardiac arrythmias were also associated with increased mortality OR, 2.86 [95% CI 1.39–5.89]. This is consistent with a large prospective study, which reported cardiac arrythmias to be associated with increased mortality, even when controlling for age, and the severity of neurological injury. ^{Reference Wartenberg, Schmidt and Claassen15} This is of particular interest because previous authors had reported that while common, cardiac arrythmias rarely lead to deaths. ^{Reference Solenski, Haley and Kassell31} Shock, pneumonia, acute renal failure, fluid and electrolyte imbalance, acute myocardial infarction were not found to be associated with increase mortality, on multivariate logistic regression analysis, which could be due to the relatively low power of the study. Fever, hypotension, hyperglycemia, and anemia were reported to be associated with increased mortality by previous authors. ^{Reference Lantigua, Ortega-Gutierrez and Schmidt9,Reference Wartenberg, Schmidt and Claassen15} In our cohort, these diagnoses were not associated with increased mortality. This could be due to the fact that these diagnoses are largely based on changes in vital signs and specific laboratory findings which may be more appropriate to collect in institutional cohorts, where these data can be obtained directly.

In our study, we found having 1, 2, and ≥3 pre-existing conditions was associated with a 1.51-, 2.03-, and 3.78-fold increase in odds of patients having experienced at least 1 medical complication, respectively (Table 2). This finding suggests that pre-existing conditions may increase mortality in SAH patients by increasing medical complications. While previous studies had described that pre-existing conditions were associated with increased mortality, the mechanism by which they do so is not well understood. Our study shows that it may be via an increase in medical complications. Further research should aim to better characterize the association between specific pre-existing conditions and specific medical complications.

This study has limitations. The identification of the diagnoses and of the procedures patients underwent was based on ICD-9, ICD-10, CPP, and CCI codes, with their associated risks of misclassification. This is a known limitation of administrative health data. That said, the codes for SAH have been validated by previous research and found to have very good accuracy. ^{Reference Rumalla, Smith, Arnold and Mittal2} We are therefore quite confident our patients were true aneurysmal SAH patients, especially considering we excluded patients with trauma codes and included only patients who had undergone angiography or neurosurgical clipping of an aneurysm. To avoid misclassification of pre-existing conditions, we have strictly used the same diagnostic codes previous authors had used when identifying pre-existing conditions using administrative health data. ^{Reference Deyo, Cherkin and Ciol32,Reference Quan, Sundararajan and Halfon33}

As with all administrative databases, there are limitations in the collection of clinical information. Specifically for our project, we used administrative health data to determine acute medical events and complications that occurred during the hospitalization of patients newly diagnosed with SAH. One of the risks of doing so is misclassifying concomitant ICD codes as acute when they are in fact pre-existing conditions. We took several steps to mitigate this risk. First, we excluded from the ICD codes for medical complications all the codes that had been previously documented as pre-existing conditions in our cohort. Second, we examined every diagnostic codes and only included those that were coding for diagnoses that had been classified as acute medical complications in the SAH literature. ^{Reference Lantigua, Ortega-Gutierrez and Schmidt9,Reference Wartenberg, Schmidt and Claassen15,Reference Solenski, Haley and Kassell31} Third, we have included in appendix 1 all the diagnostic codes that have been retained as medical complications. While there is a risk of misclassification, this methodology has permitted us to analyze the impact of important acute medical events on mortality.

Similarly, while the gold standard to assess the severity of the neurological injury is the use of the HH and WFNS scores, the variables used in our cohort to assess the extent of the neurological injury and neurological complications have been previously published. ^{Reference Washington, Derdeyn, Dacey, Dhar and Zipfel25} Furthermore, the odds of mortality between the severe neurological injury group and the non-severe neurological group in our cohort OR, 3.42 [95% CI 1.90–6.13], mirror those published in institutional studies comparing HH 1–3 to HH 4 groups OR, 4.08 [95% CI 1.55–7.30]. ^{Reference Lee, Ouyang and John10} One other limitation is the risk of misclassifying pre-existing conditions as medical complications. For medical complications occurring in hospital, to mitigate this risk, only codes that had not been given to patients the year prior to admission were retained and only a priori variables of interest based on the SAH literature were selected. ^{Reference Rumalla, Smith, Arnold and Mittal2,Reference Lantigua, Ortega-Gutierrez and Schmidt9,Reference Norberg, Odenstedt-Herges, Rydenhag and Oras13,Reference Dasenbrock, Angriman and Smith22–Reference Rivero Rodriguez, Scherle Matamoros, Cue, Miranda Hernandez, Pernas Sanchez and Perez Nellar24} Another risk when assessing in hospital medical complications, interventions, and mortality for hospitalized patients using administrative health data is censoring due to patients transfers. To mitigate this risk, we constructed hospitalization episodes which included all transfers within 3 days of the initial SAH admission, as well as the subsequent transfer to another acute care hospital as part of the same hospitalization episode.

One limitation of the statistical analysis is that the models presented in Tables 1, 2 and 5 were not corrected for multiple testing. However, the variable selection described in the Methods section is commonly used, and correcting for multiple testing may be associated with an increased risk of false negatives.

Through the findings in this study, we have shown that pre-existing conditions have an important impact on SAH mortality. The effect measures provided can help physicians be better prepared when dealing with SAH patients with multiple comorbidities, especially those with malignancies, diabetes, congestive heart failure, renal disease, and cerebrovascular disease. By knowing the effect of these pre-existing conditions, on mortality and the increased risk of developing medical complications, physicians may opt for closer observation, monitoring, and laboratory testing for these patients. Importantly, these patients appear at risk of in-hospital medical complications, namely sepsis, respiratory failure, and cardiac arrythmias. Increased monitoring and aggressive management is warranted. Furthermore, public health measures to reduce pre-existing conditions should continue to be put forth. Last, this knowledge on the effect of medical complications on mortality can help physicians guide patients and families as they occur during the initial hospitalization.

One of the major strengths of this study is the generalizability of our findings. The data collected by the PopHR database spanned 17 years, and multiple institutions. Furthermore, the known risk factors for SAH mortality were controlled for via binary multivariate logistic regression models, and the exposures included were collected over the course of the year preceding the initial hospitalization as well as the whole initial hospitalization episode. We opted to include in our analysis only patients who had undergone angiography or neurosurgical clipping of their aneurysm. We did so in order to establish an effect measure for pre-existing conditions and medical complications for patients that were deemed salvageable from a neurological standpoint at the time of admission. While this limits the generalizability of our findings to only patients undergoing procedures, it provides clinically relevant information for physicians caring for this patient population. Taken together, these findings can be generalized to patients newly diagnosed with SAH, admitted alive to an acute care hospital, and who undergo aneurysmal clipping or angiography, in a North American hospital, for patients covered by health insurance.