| Literature DB >> 32286468 |
Zhu Zhu1,2, Sahar Osman1, Dana Stradling1, Mohammad Shafie1, Wengui Yu3.
Abstract
Methamphetamine use has emerged as a risk factor for intracerebral hemorrhage (ICH). We aim to investigate the clinical characteristics and outcomes of methamphetamine-associated ICH (Meth-ICH) versus Non-Meth-ICH. Patients with ICH between January 2011 and December 2017 were studied. Meth-ICH and Non-Meth-ICH were defined by history of abuse and urine drug screen (UDS). The clinical features of the 2 groups were explored. Among the 677 consecutive patients, 61 (9.0%) were identified as Meth-ICH and 350 as Non-Meth ICH. Meth-ICH was more common in Hispanics (14.6%) and Whites (10.1%) as compared to Asians (1.2%). Patients with Meth-ICH were more often younger (51.2 vs. 62.2 years, p < 0.001), male (77.0% vs. 61.4.0%, p < 0.05), and smokers (44.3% vs. 13.4%, p < 0.001). Non-Meth-ICH was more likely to have history of hypertension (72.61% v. 59%, p < 0.05) or antithrombotic use (10.9% vs. 1.6%, p < 0.05). There was no significant difference in clinical severity, hospital length of stay (LOS), rate of functional independence (29.5% vs. 25.7%, p = 0.534), or mortality (18.0% vs. 24.6%, p = 0.267) between the 2 groups. Methamphetamine use was not an independent predictor of poor outcome. Despite difference in demographics, Meth-ICH is similar to Non-Meth ICH in hospital course and outcome.Entities:
Mesh:
Substances:
Year: 2020 PMID: 32286468 PMCID: PMC7156410 DOI: 10.1038/s41598-020-63480-z
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Flow chart for patient selection. Meth-ICH: reported a history methamphetamine use or had a positive urine drug screen (marked in pink); Non-Meth-ICH: denied a history of methamphetamine use and had a negative urine drug screen (marked in blue).
Figure 2Racial disparities in the prevalence of Meth-ICH.
Characteristics of patients with Meth-ICH or Non-Meth-ICH.
| Variables | Meth-ICH (n = 61) | Non-Meth-ICH (n = 350) | |
|---|---|---|---|
| Age | 51.2 ± 7.5 | 62.2 ± 15.9 | |
| Male | 47 (77.0) | 215 (61.4) | |
| Hypertension | 36 (59.0) | 254 (72.6) | |
| Diabetes | 9 (14.8) | 83 (23.7) | 0.121 |
| Hyperlipidemia | 7 (11.5) | 70 (20.0) | 0.115 |
| Cardiac diseases | 3 (4.9) | 37 (10.6) | 0.169 |
| Antithrombotic agents | 1 (1.6) | 38 (10.9) | |
| Smoking | 27 (44.3) | 47 (13.4) | |
| SBP, mmHga | 180.9 ± 41.5 | 181.2 ± 40.6 | 0.711 |
| DBP, mmHga | 102.5 ± 24.1 | 99.5 ± 23.9 | 0.678 |
| NIHSS | 19 (6, 27) | 12 (2, 22) | 0.065 |
| GCS | 10 (4,16) | 14 (10, 18) | 0.084 |
| ICH location | 0.001 | ||
| Deep | 35 (57.4) | 163 (46.6) | 0.119 |
| Lobar | 10 (16.4) | 133 (38.0) | |
| Brainstem | 8 (13.1) | 26 (7.4) | 0.137 |
| Cerebellum | 3 (4.9) | 22 (6.3) | 0.783 |
| Primary IVH | 5 (8.2) | 5 (1.4) | 0.009 |
| Multifocal | 0 (0) | 1 (0.3) | 1.000 |
| IVH | 35 (57.4) | 167 (47.7) | 0.164 |
| ICH score | 0.911 | ||
| 0 | 16 (26.2) | 94 (26.9) | |
| 1 | 15 (24.6) | 93 (26.6) | |
| 2 | 9 (14.8) | 49 (14.0) | |
| 3 | 11 (18.0) | 51 (14.6) | |
| 4 | 9 (14.8) | 45 (12.9) | |
| 5 | 1 (1.6) | 16 (4.6) | |
| 6 | 0 (0) | 2 (0.6) | |
| Ventilator support | 28 (45.9) | 157 (45.0) | 0.894 |
| Surgical intervention | 27 (44.3) | 103 (29.4) | |
| ICU LOS (days) | 6 ± 6 | 7 ± 6 | 0.903 |
| Hospital LOS (days) | 14 ± 14 | 11 ± 10 | 0.056 |
| mRS at discharge | 0.328 | ||
| mRS 0–2 | 18 (29.5) | 90 (25.7) | 0.534 |
| mRS 3–4 | 23 (37.7) | 102 (29.2) | |
| mRS 5 | 9 (14.8) | 72 (20.6) | |
| mRS 6 (Death) | 11 (18.0) | 86 (24.6) | 0.267 |
Abbreviations: SBP, systolic blood pressure; DBP, diastolic blood pressure;. NIHSS, National Institutes of Health Stroke Scale; GCS, Glasgow Coma Scale;. ICH, intracerebral hemorrhage; IVH, intraventricular hemorrhage;. ICU, Intensive Care Unit; mRS, modified Rankin Scale; LOS, length of stay. aHighest SBP/DBP within 24 hours of admission. Data are n (%), mean ± SD, or median (interquartile range, IQR).
Factors associated with functional independence at discharge.
| Variables | Functional independence (n = 108) | ||
|---|---|---|---|
| Univariate analysis | Multivariate analysis | ||
| OR (95% CI) | |||
| Age | 0.486 | ||
| Male | 0.462 | ||
| Race | 0.304 | ||
| HTN | 0.54 (0.28–1.05) | 0.07 | |
| DM | 0.164 | ||
| Smoking | 1.35 (0.67–2.71) | 0.405 | |
| Antithrombotic agents | 0.390 | ||
| Meth use | 0.534 | ||
| ICH location | 0.394 | ||
| SBP | 0.515 | ||
| DBP | 0.257 | ||
| NIHSS | < | 0.73 (0.67–0.80) | |
| GCS | < | 1.29 (1.07–1.56) | |
| ICH score | 0.89 (0.56–1.30) | 0.454 | |
| Glucose | 0.332 | ||
| Creatinine | 0.583 | ||
| Surgical interventions | 0.88 (0.29–2.68) | 0.821 | |
| Ventilator support | 0.41 (0.13–1.29) | 0.128 | |
Abbreviations: SBP, systolic blood pressure; DBP, diastolic blood pressure; NIHSS. National Institutes of Health Stroke Scale; GCS, Glasgow Coma Scale. ICH, intracerebral hemorrhage; mRS, modified Rankin Scale.
Factors associated with hospital mortality.
| Variables | Hospital mortality (n = 97) | ||
|---|---|---|---|
| Univariate analysis | Multivariate analysis | ||
| OR (95% CI) | |||
| Age | 0.107 | ||
| Male | 0.354 | ||
| Race | 0.137 | ||
| HTN | 0.245 | ||
| DM | 1.58 (0.70–3.55) | 0.272 | |
| Smoking | 0.97 (0.34–2.75) | 0.948 | |
| Antithrombotic agents | 0.935 | ||
| Meth use | 0.267 | ||
| ICH location | 1.07 (0.78–1.47) | 0.679 | |
| SBP | 1.01 (0.99–1.02) | 0.237 | |
| DBP | 0.99 (0.97–1.02) | 0.513 | |
| NIHSS | < | 1.09 (1.02–1.17) | |
| GCS | < | 0.90 (0.78–1.04) | 0.169 |
| ICH score | 2.67 (1.80–3.97) | ||
| Glucose | 1.00 (0.99–1.01) | 0.856 | |
| Creatinine | 0.134 | ||
| Surgical interventions | 0.24 (0.11–0.51) | ||
| Ventilator support | 3.95 (1.37–11.4) | ||
Abbreviations: SBP, systolic blood pressure; DBP, diastolic blood pressure. NIHSS, National Institutes of Health Stroke Scale; GCS, Glasgow Coma Scale. ICH, intracerebral hemorrhage.