Cigarette Smoking History and Functional Outcomes after Spontaneous Intracerebral Hemorrhage

Abstract

Background and Purpose:

While cigarette use may be a risk for intracerebral hemorrhage (ICH), animal models suggest that nicotine has a potential neuroprotective effect. The aim of this multicenter study is to determine the effect of smoking history on outcome in ICH patients.

Methods:

We analyzed prospectively collected data from the Ethnic/Racial Variations of Intracerebral Hemorrhage study, and included patients with smoking status data in the analysis. Patients were dichotomized into non-smokers versus ever-smokers, and the latter group was further categorized as former (>30 days before ICH) or current (≤30 days before ICH) smokers. The primary outcome was 90-day modified Rankin Scale (mRS) score shift analysis. Secondary outcomes were in-hospital mortality and mortality, Barthel Index, and self-reported health status measures at 90 days.

Results:

The overall study cohort comprised 1,509 non-smokers and 1,423 ever-smokers (841 former, 577 current, 5 unknown). No difference in primary outcome was observed between non-smokers versus ever-smokers (aOR=1.041 [0.904–1.199], p=0.577). No differences in primary outcome were observed between former (aOR=0.932 [0.791–1.178], p=0.399) or current smokers (aOR=1.178 [0.970–1.431], p=0.098) versus non-smokers. Subgroup analyses by race/ethnicity demonstrated no differences in primary outcome when former and current smokers were compared to non-smokers. Former, but not current, smokers had a lower in-hospital mortality rate (aOR=0.695 [0.500–0.968], p=0.031), which was only observed in Hispanics (aOR=0.533 [0.309–0.921], p=0.024). Differences in self-reported health status measures were only observed in whites.

Conclusion:

Cigarette smoking history does not appear to provide a beneficial effect on 90-day functional outcome in patients with ICH.

Introduction:

Spontaneous intracerebral hemorrhage (ICH) occurs with an annual incidence of approximately 15 to 19 per 100,000 persons.¹ ICH is associated with higher morbidity and mortality rates than other stroke subtypes.^{2, 3} The direct socioeconomic costs of medical care and indirect costs associated with the loss of productivity impose a tremendous economic burden on affected individuals, their families, and society.⁴ Therefore, in addition to therapeutic interventions that attempt to reduce primary brain injury at the onset of ICH, efforts to identify neuroprotective agents that target secondary injury pathways are ongoing.^5–7

Nicotine, an agonist of the α−7 nicotinic acetylcholine receptor (α7-nAChR), has been investigated in several animal models of ICH as a potential neuroprotective agent that mediates the cholinergic anti-inflammatory pathway.^8–12 These studies reported decreased neuronal cell death and infiltration of inflammatory cells into the perihematomal area in subjects administered an α7-nAChR agonist, with resultant improvements in sensorimotor function and animal survival.^9–12 Despite its many detrimental consequences, including potential associations with increased ICH risk, cigarette smoking may have paradoxical neuroprotective effects in patients presenting with ICH via the cholinergic anti-inflammatory pathway mediated by the nicotine content found in cigarettes.^13–19 However, the relationship between smoking status and post-ICH outcomes has not been rigorously investigated. Therefore, the aim of this multicenter, retrospective cohort study is to determine the effect of cigarette smoking and on functional outcomes and health-related quality of life (HRQoL) in ICH patients.

Methods:

Patient Identification, Ethical Approval of Study, and Informed Consent

Institutional review board (IRB) approval and written informed consents were obtained at each site and from all patients (or legal guardians of patients who were unable to provide informed consent) participating in the study, respectively. Patient data from each respective site was de-identified and pooled for analysis. This study follows the guidelines set forth by the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement.

Study Design

The Ethnic/Racial variations of IntraCerebral Hemorrhage (ERICH) study protocol has been previously described in detail.²⁰ In brief, the ERICH study is a multicenter, prospective, case-control study designed to recruit 1,000 non-Hispanic whites, 1,000 non-Hispanic blacks and 1,000 Hispanics with spontaneous ICH. Matched ICH-free controls were recruited via random digit dialing for the identification of genetic and epidemiological risk factors associated with ICH and its outcomes. Participants were derived from 19 United States sites comprising 42 hospitals. Standardized data collection protocol, including a personal interview and medical chart abstraction, was performed on all participants or designated proxies. Patients included in the present study were derived from the ICH case cohort of the ERICH study, and their data was retrospectively analyzed. Patients with primary intraventricular hemorrhage (IVH) and unknown cigarette smoking status were excluded from the study.

ICH Definition

ICH is defined as a spontaneous, nontraumatic, abrupt onset of severe headache, altered level of consciousness, or focal neurological deficit that is associated with a focal collection of blood within the brain parenchyma seen on neuroimaging or at autopsy, and is not attributed to hemorrhagic conversion of a cerebral infarction.²⁰ Warfarin-associated ICH and peripartum ICH are included in the definition. Venous sinus thrombosis-associated hemorrhages, and hemorrhages attributable to vascular malformations, aneurysms, or tumors were excluded. Patient’s eligibility for inclusion in the ERICH study were reviewed by the study neurologists based on clinical presentation and neuroimaging.

Smoking Status

Patients were dichotomized into non-smokers versus ever-smokers, and ever-smokers were further categorized into former or current smokers. Non-smokers were defined as patients who have never had first-hand exposure to cigarette smoke. Former smokers were defined as patients who have previously had first-hand exposure to cigarette smoke, but none ≤30 days prior to presentation with ICH. Current smokers were defined as patients who have had first-hand exposure to cigarette smoke within 30 days of presentation with ICH.

Outcomes

The primary outcome was modified Rankin Scale (mRS) score at 90 days.^{21, 22} The secondary outcomes were in-hospital mortality and mortality, Barthel Index (on a scale of 0 to 100, with higher scores indicating less disability), EuroQol Group 5-Dimension (EQ-5D; on a scale of −0.11 to 1, with higher values indicating better quality of life), and EQ-5D visual analog scale (EQ-5D VAS; on a scale of 0 to 100, with higher values indicating better quality of life) at 90 days.²³ HRQoL metrics were obtained using self-report questionnaires.

Statistical Analysis

All statistical analyses were performed using Stata (version 14.2, College Station, TX). Baseline demographic, clinical, neuroimaging, laboratory, and treatment characteristics were compared between non-smokers versus ever-smokers. Continuous variables were compared using Student’s t or Mann-Whitney U tests, as appropriate. Categorical variables were compared using Pearson’s χ² or Fisher’s exact tests, as appropriate. Univariable ordered logistic, binary logistic, and linear regression analyses were performed to assess the associations between smoking and the primary and secondary outcomes. The findings from the logistic and linear regression analyses were adjusted for covariates with p<0.05.

To avoid listwise deletions due to missing data in multivariable regression models, multiple imputation by chained equations with m=50 was performed. Imputed values for prior ischemic stroke (0.9%), hypertension (0.3%), diabetes mellitus (0.1%), hyperlipidemia (1.6%), coronary artery disease (CAD; 0.4%), history of myocardial infarction (MI; 0.2%), atrial fibrillation (0.1%), carotid artery disease (0.2%), peripheral vascular disease (PVD; 3.1%), alcohol use (7%), antiplatelet use (1.5%), anticoagulant use (1.5%), baseline mRS score (0.4%), white blood cell (WBC) count (2%), platelet count (2.4%), LDL (42.2%), triglycerides (40%), initial ICH volume (3.1%), presence of intraventricular hemorrhage (IVH; 3.1%), admission Glasgow Coma Scale (GCS) score (2.5%), ICH evacuation or decompression (0.1%), external ventricular drain (EVD) placement (0.03%), cerebrospinal fluid (CSF) shunt placement (0.1%), mRS score at 90 days (14.3%), mortality at 90 days (14.4%), Barthel index at 90 days (14.4%), EQ-5D at 90 days (23.7%), and EQ-5D VAS at 90 days (17.3%) were generated using conditional regression models with the following auxiliary variables: age, sex, race/ethnicity, smoking status, lobar ICH location, infratentorial ICH location, and in-hospital mortality. Parameter estimates from analyzing the imputed datasets were pooled according to Rubin’s rules.²⁴

Comparisons of baseline variables among non-smokers, former smokers, and current smokers were performed using analysis of variance, Kruskal-Wallis rank, Pearson’s χ² or Fisher’s exact tests, as appropriate. Univariable and multivariable ordered logistic, binary logistic, and linear regression analyses were performed to assess the associations between smoking status (with non-smokers as the reference category) and the primary and secondary outcomes. Subgroup analyses by race/ethnicity category were performed. Statistical significance was defined as p<0.05, and all tests were two-tailed.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Results:

Non-Smokers vs. Ever-Smokers

Of the 3,000 patients with spontaneous ICH enrolled who were in the ERICH study, 17 and 51 patients were excluded from the present analysis due to a lack of data regarding smoking status and primary IVH, respectively. The remaining 2,932 patients who were eligible for the overall study cohort comprised 1,509 non-smokers and 1,423 ever-smokers.

Table I compares the demographic, clinical, radiologic, and treatment characteristics between non-smokers versus ever-smokers. Ever-smokers were more likely to be male (64% vs. 54%, p<0.001), and there were differences in the distributions of race/ethnicity (p=0.001) and baseline mRS scores (p=0.008) between the two cohorts. Ever-smokers had higher rates of medical comorbidities, including prior ischemic stroke (12% vs. 8%, p<0.001), hyperlipidemia (48% vs. 42%, p<0.001), CAD (19% vs. 14%, p<0.001), prior MI (11% vs. 6%, p<0.001), carotid artery disease (4% vs. 3%, p=0.005), and PVD (3% vs. 2%, p=0.015). Ever-smokers used alcohol (49% vs. 33%, p<0.001) and antiplatelet medications (31% vs. 26%, p=0.002) more frequently, and had lower serum LDL levels (mean 98 vs. 104 mg/dL, p=0.003). Infratentorial ICH location was more common in ever-smokers (15% vs. 12%, p=0.042). The admission GCS scores was higher in ever-smokers (median 15 vs. 14, p<0.001). The rates of pneumonia during acute hospitalization between non-smokers (180/1,509 patients; 12%) and ever-smokers (177/1,423 patients; 12%) were similar (p=0.673).

Table 1 compares the primary and secondary outcomes between non-smokers versus ever-smokers. No difference in the primary outcome (i.e., mRS at 90 days) was found between the two cohorts, even after adjustment for baseline differences in the non-imputed and imputed multivariable models. Ever-smokers had lower rates of in-hospital mortality (OR=0.698 [0.551–0,884], p=0.003), and this difference persisted after adjustments for baseline differences in non-imputed (aOR=0.554 [0.334–0.919], p=0.022) and imputed (aOR=0.744 [0.564–0.982], p=0.037) multivariable models. No differences in mortality, Barthel Index, EQ-5D, or EQ-5D VAS scores were found between the two cohorts in all models.

Table 1.

Comparisons of the primary and secondary outcomes between non-smokers versus ever-smokers.

Outcome	Non-smokers(n=1,509)	Ever-smokers(n=1,423)	Effect Variable	Unadjusted Value (95% CI)	p-value	Adjusted Value (95% CI)§	p-value	Imputed, Adjusted Value (95% CI)§#	p-value
Primary Outcome
mRS at 90 days, median (IQR)	3 (2–5)	3 (2–5)	Odds Ratio	0.964 (0.840–1.106)	0.597	0.979 (0.798–1.202)	0.842	1.041 (0.904–1.199)	0.577
Secondary Outcomes
Mortality in-hospital, n (%)	190/1,509 (12.6)	130/1,509 (9.1)	Odds Ratio	0.698 (0.551–0.884)	0.003	0.554 (0.334–0.919)	0.022	0.744 (0.564–0.982)	0.037
Mortality at 90 days, n (%)	292/1,509 (22.5)	253/1,214 (20.8)	Odds Ratio	0.906 (0.749–1.096)	0.310	0.941 (0.654–1.354)	0.744	0.997 (0.800–1.242)	0.978
Barthel index at 90 days, median (IQR)*	67.5 (0–100)	70 (5–100)	Beta	2.222 (−1.059–5.503)	0.184	0.787 (−3.150–4.724)	0.695	0.159 (−2.504–2.821)	0.907
EQ-5D score at 90 days, median (IQR) †	0.619 (0–0.833)	0.597 (0.077–0.827)	Beta	−0.007 (−0.038–0.024)	0.647	−0.018 (−0.056–0.020)	0.345	−0.016 (−0.041–0.008)	0.193
EQ-5D VAS score at 90 days, median (IQR) ‡	57.5 (10–80)	55 (20–75)	Beta	0.261 (−2.383–2.904)	0.847	−0.652 (−3.911–2.607)	0.695	−0.824 (−3.032–1.384)	0.465

Non-Smokers vs. Former Smokers and Non-Smokers vs. Current Smokers

After excluding 5 smokers without data regarding the timing of smoking, the study cohort comprised 841 former and 577 current smokers. Table II compares the demographic, clinical, radiologic, and treatment characteristics between non-smokers versus former smokers and between non-smokers versus current smokers. Differences in age, sex, race/ethnicity, prior ischemic stroke, DM, hyperlipidemia, CAD, prior MI, AF, carotid artery disease, PVD, alcohol use, antiplatelet use, anticoagulant use, baseline mRS score, serum LDL level, lobar ICH location, presence of IVH, admission GCS score, and EVD placement were found among the three cohorts. The rates of pneumonia during acute hospitalization among non-smokers (12%), former smokers (96/841 patients; 11%), and current smokers (80/577 patients; 14%) were similar (p=0.353).

Table 2 compares the primary and secondary outcomes between non-smokers versus former smokers and between non-smokers versus current smokers. Former smokers were associated with lower mRS scores compared to non-smokers after adjustments for baseline differences in the non-imputed multivariable model (aOR=0.785 [0.616–0.999], p=0.049). However, this difference was no longer significant in the imputed multivariable model. No difference in the primary outcome was found between non-smokers and current smokers, even after adjustments for baseline differences in the non-imputed and imputed multivariable models. Former smokers had a lower in-hospital mortality rate (OR=0.710 [0.537–0.937], p=0.016), and this difference persisted after adjustments for baseline differences in non-imputed (aOR=0.456 [0.240–0.868], p=0.017) and imputed (aOR=0.695 [0.500–0.968], p=0.031) multivariable models. Former smokers had a higher Barthel Index at 90 days after adjustments for baseline differences (aOR=4.652 [0.300–9.003], p=0.036), although this difference was not present in the imputed multivariable model. Current smokers had a lower EQ-5D score at 90 days (aβ=−0.041 [−0.072–−0.009], p=0.011) in the imputed multivariable model, but no difference was found in the non-imputed multivariable model.

Table 2.

Comparisons of primary and secondary outcomes between non-smokers versus former smokers and between non-smokers versus current smokers.

Outcome	Non-smokers(n=1,509)	Former smokers(n=841)	Current smokers (n=577)	Effect Variable	Unadjusted Value (95% CI)#		p-value#		Adjusted Value (95% CI)||**		p-value#		Imputed, Adjusted Value (95% CI)#||**		p-value#
					Former smokers	Current smokers	Former smokers	Current smokers	Former smokers	Current smokers	Former smokers	Current smokers	Former smokers	Current smokers	Former smokers	Current smokers
Primary Outcome
mRS at 90 days, median (IQR)	3 (2–5)	3 (2–5)	3 (2–5)	Odds Ratio	0.996 (0.851–1.167)	0.897 (0.746–1.080)	0.964	0.252	0.785 (0.616–0.999)	1.068 (0.797–1.431)	0.049	0.659	0.932 (0.791–1.098)	1.178 (0.970–1.431)	0.399	0.098
Secondary Outcomes
Mortality in-hospital, n (%)	190/1,509 (12.6)	78/841 (9.3)	49/577 (8.5)	Odds Ratio	0.710 (0.537–0.937)	0.644 (0.463–0.896)	0.016	0.009	0.456 (0.240–0.868)	0.612 (0.292–1.283)	0.017	0.193	0.695 (0.500–0.968)	0.755 (0.507–1.125)	0.031	0.167
Mortality at 90 days, n (%)	292/1,297 (22.5)	161/746 (21.6)	88/463 (19.1)	Odds Ratio	0.947 (0.762–1.178)	0.808 (0.619–1.054)	0.625	0.116	0.758 (0.486–1.183)	0.943 (0.537–1.656)	0.222	0.838	0.908 (0.698–1.181)	1.122 (0.813–1.549)	0.472	0.484
Barthel index at 90 days, median (IQR)*	67.5 (0–100)	70 (0–100)	75 (10–100)	Beta	1.722 (−2.052–5.496)	3.510 (−0.935–7.954)	0.371	0.122	4.652 (0.300–9.003)	1.269 (−3.938–6.477)	0.036	0.633	2.519 (−0.387–5.426)	−1.738 (−5.099–1.624)	0.089	0.311
EQ-5D score at 90 days, median (IQR)†	0.619 (0–0.833)	0.689 (0–0.827)	0.597 (0.118–0.827)	Beta	−0.002 (−0.037–0.034)	−0.011 (−0.053–0.031)	0.929	0.598	0.016 (−0.027–0.060)	−0.015 (−0.067–0.037)	0.459	0.573	0.007 (−0.020–0.035)	−0.041 (−0.072–−0.009)	0.611	0.011
EQ-5D VAS score at 90 days, median (IQR)‡	57.5 (10–80)	60 (12.5–80)	50 (30–75)	Beta	0.124 (−2.921–3.169)	0.875 (−2.697–4.447)	0.936	0.631	2.666 (−1.041–6.373)	−2.324 (−6.774–2.125)	0.158	0.306	1.099 (−1.389–3.588)	−2.834 (−5.736–0.068)	0.386	0.056

* The Barthel index is an ordinal 10-item scale for measuring performance of activities of daily living. Score ranges from 0 to 100, with 0 indicating severe disability, and 100 indicating no disability that interferes with daily activities.† The EuroQoL Group 5-Dimension (EQ-5D) self-report questionnaire is a standardized instrument for the measurement of generic health status in terms of five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Scores range from −0.11 to 1.00, with higher scores indicating better health, and death indicated by score of 0.

^‡The EQ-5D Visual Analog Scale is the second part of the EQ-5D questionnaire, where patient is asked to mark his/her health status on a 20-centimeter vertical scale with end points of 0 (“the worst health you can imagine”) and 100 (“the best health you can imagine”).

^§Values were adjusted for sex, race/ethnicity, history of ischemic stroke, history of hyperlipidemia, history of coronary artery disease, history of myocardial infarction, history of carotid artery disease, history of peripheral vascular disease, alcohol use, antiplatelet use, baseline mRS score, low-density lipoprotein, infratentorial intracerebral hemorrhage location, and admission Glasgow Coma Scale score.

^||Values were adjusted for age, sex, race/ethnicity, history of ischemic stroke, history of diabetes mellitus, history of hyperlipidemia, history of coronary artery disease, history of myocardial infarction, history of atrial fibrillation, history of carotid artery disease, history of peripheral vascular disease, alcohol use, antiplatelet use, anticoagulant use, baseline mRS score, low-density lipoprotein, lobar intracerebral hemorrhage, presence of intraventricular hemorrhage, admission Glasgow Coma Scale score, and external ventricular drain placement.

^#Values based on pooled parameter estimates from multiply imputed data using chained equations with m=50.

** Non-smokers as reference category.

Subgroup Analyses by Race/Ethnicity

Tables III, IV, and V compare the demographic, clinical, radiologic, and treatment characteristics between non-smokers versus former smokers and between non-smokers versus current smokers for the subgroups of white, black, and Hispanic ICH patients, respectively. Table VI details the subgroup analysis for whites, including comparisons of the primary and secondary outcomes between non-smokers versus former smokers and between non-smokers versus current smokers. White former smokers had lower mRS scores compared to white non-smokers (OR=0.770 [0.596–0.996], p=0.047). However, this difference was no longer significant in the multivariable models. White former smokers had a higher Barthel Index (β=10.807 [4.635–16.979], p=0.001), and this difference persisted after adjustments for baseline differences in non-imputed (aβ=6.144 [0.553–11.736], p=0.031) and imputed (aβ=6.100 [1.137–11.063], p=0.016) multivariable models. White current smokers had a lower EQ-5D score in the adjusted non-imputed (aβ=−0.133 [−0.210–−0.056], p=0.001) and imputed (aβ=−0.084 [−0.150–−0.018], p=0.012) multivariable models. White current smokers also had a lower EQ-5D VAS score in the adjusted non-imputed multivariable model (aβ=−7.043 [−13.963–−0.123], p=0.046).

Table VII details the subgroup analysis for blacks, including comparisons of the primary and secondary outcomes between non-smokers versus former smokers and between non-smokers versus current smokers. No differences in the primary or secondary outcomes were observed between non-smokers versus either former or current smokers in black participants. Table VIII details the subgroup analysis for Hispanics, including comparisons of the primary and secondary outcomes between non-smokers versus former smokers and between non-smokers and current smokers. Hispanic former (aOR=0.533 [0.309–0.921], p=0.024) and current (aOR=0.430 [0.216–0.856], p=0.016) smokers had lower in-hospital mortality rates in the adjusted imputed multivariable models.

Discussion:

Secondary brain injury after ICH stems from a cascade of events that combines the pathophysiological responses to hematoma formation and release of clot components.⁷ The pronounced inflammatory reaction that ensues after ICH has been implicated in secondary brain injury via microglial activation, leukocyte infiltration, disruption of the blood-brain barrier and upregulation of pro-inflammatory signaling.^{7, 25, 26} However, inflammation has also been associated with brain recovery in the ICH setting.^{7, 27} Therefore, the role of inflammation in brain injury and recovery after ICH has not been completely defined.

Efforts to survey neuroprotective targets and agents that modulate the immune response to ICH have led to the identification of the α7-nAChR and its agonists as possible candidates. The α7-nAChR, a well-characterized member of the ligand-gated ion channel superfamily comprising α- and β-subunits that form pentameric complexes, is widely expressed in neuronal and glial cells in the mammalian brain, as well as in immune cells outside of the central nervous system.^{8, 28–31} Additionally, α7-nAChR activation has been implicated in immune cell modulation via the NF-κB and Jak/STAT signaling pathways.^31–37 Therefore, α7-nAChR agonists have been investigated as potential therapeutic agents in animal ICH models.^8–12 However, the therapeutic effects of α7-nAChR agonists (e.g., nicotine) in ICH patients have not been investigated beyond animal models.

Despite its many limitations and confounders, the potential effects of nicotine on post-ICH sequelae may be gleaned from cigarette smokers who present with ICH. Our analysis of a large, multicenter cohort of ICH patients found no difference in the primary outcome (i.e., mRS at 90 days) between ever-smokers and non-smokers. Similarly, Sembill et al. reported no effect of smoking on mortality or functional outcomes at 12 months.³⁸ We observed a lower rate of in-hospital mortality in ever-smokers, although this effect disappeared at 90 days. Further stratification of ever-smokers into former versus current smokers revealed that former, but not current, smokers had a lower in-hospital mortality rate after adjusting for baseline differences. Former smokers also had better functional outcomes, as measured by the mRS and Barthel Index, whereas current smokers had worse HRQoL, as measured by the EQ-5D score. In an earlier population-based prospective cohort study with a mean follow-up of 10.9 years, Xu et al. found increased mortality risk among Chinese ICH patients >65 years of age who were current smokers compared to non-smokers (aHR=1.80 [1.35–2.40], p<0.001).¹⁷ This association was not observed when former smokers were compared to non-smokers in the same study. Although we did not observe increase mortality risk in current smokers compared to non-smokers, our findings do not support the hypothesis of smoker’s paradox.

Subgroup analyses by race/ethnicity in our study showed that the higher Barthel Index in former smokers and lower HRQoL metrics in current smokers was primarily accounted for by white ICH patients, whereas the lower rate of in-hospital mortality in former smokers was primarily observed in Hispanics. Overall, the findings of this study suggest that cigarette smoking status may affect the functional outcomes and HRQoL of ICH patients at interim follow-up. However, one must recognize that the potentially beneficial effects of nicotine in the setting of ICH, as suggested by previous animal studies, may be negated by the many detrimental systemic consequences of cigarette smoking. Therefore, the combination of reduced in-hospital mortality and better functional outcomes in former smokers and worse HRQoL in current smokers after ICH underscores the importance of smoking cessation.

We acknowledge that our study has several limitations. Our results are contingent upon the accuracy and reliability of smoking status data, which were based on patient self-report and family members of incapacitated patients. Therefore, this study may be subject to reporting and recall biases. Accurate quantification of nicotine exposure was not possible in some patients. That is, the amount of nicotine found among cigarettes may vary, and the number of cigarettes smoked per day may be inconsistent across the duration of a patient’s smoking period. In addition to the lower nicotine dose exposure (per weight) in humans, the exposure examined was pre-ICH. It is also important to note that in comparison to α7-nAChR agonists such as PNU-282987 and PHA-543613, nicotine is non-specific. Additionally, the time interval between the last cigarette and occurrence of ICH may vary substantially among former smokers. Because the ERICH study was not specifically designed to evaluate outcomes associated with smoking, data regarding recurrent ICH and cardiovascular events after hospital discharge were not captured. Furthermore, since the study design was retrospective, power calculations were not performed. Despite our attempts to adjust for baseline differences between non-smokers versus former and current smokers using non-imputed and imputed multivariable models, balancing of both measured and unmeasured variables may still be limited. In addition, any conclusions inferred from the findings of the secondary outcomes must be interpreted with caution, since the multiple comparisons performed within the study may be associated with an elevated false discovery rate. Finally, we are unable to distinguish between the effects of smoking on neuronal and glial structures versus the cerebral vasculature. Specifically, while prior in vivo studies have shown a neuroprotective effect of nicotine, others have revealed that cigarette smoke extract induces phenotypic changes to vascular smooth muscle cells in the cerebral arteries which results in an upregulation of pro-inflammatory genes.³⁹

Conclusions

In addition to its numerous detrimental effects to one’s overall health, cigarette smoking within 30 days of ICH was not associated with improved 90-day functional outcome. Former smokers may have a paradoxically reduced in-hospital mortality rate after ICH, although this effect was no longer present at 90 days. Former smokers may have better functional outcomes at interim follow-up, whereas current smokers appear to have poorer HRQoL.

Abbreviations

mRS

modified Rankin Scale

CI

confidence interval

n

number

IQR

interquartile range

EQ-5D

EuroQoL Group 5-Dimension Self-Report Questionnaire

VAS

Visual Analog Scale