| Literature DB >> 27668123 |
Aimee M Aysenne1, Karen C Albright2, Tiffany Mathias3, Tiffany R Chang4, Amelia K Boehme5, T Mark Beasley6, Sheryl Martin-Schild3.
Abstract
BACKGROUND: The ICH score is a validated tool for predicting 30-day morbidity and mortality in patients with intracerebral hemorrhage. AIMS AND/OR HYPOTHESIS: The aim of this study is to determine if the ICH score calculated 24 hours after admission is a better predictor of mortality than the ICH score calculated on admission.Entities:
Year: 2013 PMID: 27668123 PMCID: PMC5032904 DOI: 10.1155/2013/605286
Source DB: PubMed Journal: ISRN Stroke ISSN: 2090-9454
Demographics information.
| Age, mean (sd) | 58.07 (1.4) |
| Male, % | 46 (51.7%) |
| Black, % | 67 (75.3%) |
| History of HTN, % | 71 (79.8%) |
| Antihypertensive medications, % | 44 (49.4%) |
| On antithrombotics (AP/AC), % | 32 (36%) |
| History of chronic daily alcohol use, % | 23 (25.8%) |
| Positive urine tox screen, % | 17 (19.1%) |
| ICH score on admission, median | 1 (0–3) |
| Presenting GCS, median | 14 (4–15) |
| First SBP, mean (sd) | 189.7 (3.7) |
| First DBP, mean (sd) | 111.2 (2.6) |
| Baseline NIHSS, median (range) | 15 (0–40) |
| Glucose on admission, mean (sd) | 144.65 (6.7) |
| ICH location | |
| Basal ganglia | 41 (46.1%) |
| Talamus | 18 (20.2%) |
| Pons | 5 (5.6%) |
| Cerebellum | 5 (5.6%) |
| Lobar | 18 (20.2%) |
| Other | 1 (1.1%) |
| ICH tentorial location | |
| Supratentorial | 77 (86.5%) |
| Infratentorial | 11 (12.4%) |
| To t a l | |
| IVH, % | 42 (47.2%) |
| Hydrocephalus, % | 35 (39.3%) |
| Edema on initial HCT, % | 62 (69.7%) |
| Spot sign on CTA, % | 10 (11.2%) |
| Dot sign present on CTA, % | 16 (18%) |
| New IVH, % | 6 (6.7%) |
| ICH expansion, % | 42 (47.2%) |
| Evacuation, % | 12 (13.5%) |
| EVD placed, % | 28 (31.5%) |
| Did patient receive vitamin k? % | 10 (11.2%) |
| Did patient receive FFP? % | 14 (15.7%) |
| Did patient receive platelets? % | 17 (19.1%) |
| Did patient receive NOVO7? % | 4 (4.5%) |
| IVtPA, % | 5 (5.6%) |
| In-hospital infection, % | 33 (37.1%) |
| In-hospital DVT, % | 2 (2.2%) |
| In-hospital UTI, % | 24 (27%) |
| In-hospital bacteremia, % | 12 (13.5%) |
| Best 24 hr GCS, median | 13 (3–15) |
| Follow-up volume, median (range) | 12.3 (0–402) |
| 24-hour ICH score, median | 1.0 (0–5) |
| Transfer patient, % | 8 (9%) |
| Initial shift on HCT, median (range) | 2.0 (0–17) |
| ICH initial volume, median (range) | 12.8 (0–186) |
| ICH volume 24 hrs, median (range) | 11 (0–402) |
| ICH volume growth in 24 hrs, median (range) | 0 (-107-346) |
| Length of stay, median (range) | 10 (2–86) |
| mRS on discharge, median (range) | 4 (1–6) |
| Death, % | 14 (15.7%) |
Baseline ICH score stratified by 24-hour ICH score status.
| ICH score | ICH score of 0 ( | ICH score of 1 ( | ICH score of 2 ( | ICH score of 3 ( | |
|---|---|---|---|---|---|
| Number of patients whose ICH score worsened | 3 (14.3%) | 12 (36.4%) | 3 (15.8%) | 2 (12.5%) | 0.118 |
| Number of patients whose ICH score remained the same | 18 (85.7%) | 18 (54.5%) | 11 (57.9%) | 8 (50.0%) | 0.076 |
| Number of patients whose ICH score improved | 0 | 3 (9.1%) | 5 (26.3%) | 6 (37.5%) | 0.006 |
P value for comparison of each row.
Figure 1Differences in admission and 24-hour ICH score.
Logistic regression models.
| OR | 95% CI | ||
|---|---|---|---|
| Crude model predicting death | |||
| Admission ICH score | 2.933 | 1.510–5.699 | 0.001 |
| 24-hour ICH score | 3.562 | 1.754-7.233 | <0.0001 |
| Crude model predicting poor mRS (5-6) | |||
| Admission ICH score | 3.369 | 1.934-5.869 | <0.001 |
| 24-hour ICH score | 5.975 2 | .812-12.696 | <0.0001 |
| Adjusted model predicting death | |||
| Admission ICH score | 1.580 0 | .684–3.649 | 0.284 |
| 24-hour ICH score | 2.712 | 1.187–6.195 | 0.018 |
| Adjusted model predicting poor mRS (5-6) | |||
| Admission ICH score | 1.904 | 0.937–3.869 | 0.075 |
| 24-hour ICH score | 4.672 1 | .996-10.939 | <0.0001 |
Adjusting for age, baseline NIHSS, and glucose on admission.