Los Angeles Prehospital Stroke Screen
| Los Angeles Prehospital Stroke Screen (LAPSS) | |
|---|---|
| Synonyms | LAPSS |
| Purpose | identifying potential stroke patients |
The Los Angeles Prehospital Stroke Screen (abbreviated LAPSS) is a method of identifying potential stroke patients in a pre-hospital setting.[1]
Screening criteria
- No history of seizures or epilepsy
- Age 45 years or older
- At baseline, patient is not bedridden and does not use a wheelchair
- Blood glucose between 60 and 400 mg/dL
- Obvious asymmetry-unilateral weakness with any of the following motor exams:
- Facial Smile/Grimace
- Grip
- Arm Strength
If all of the above criteria are met (or not ascertainable) the LAPSS is positive for stroke. Patients may still be experiencing a stroke even if LAPSS criteria are not met.[2]
Validity
A January 2000 study, conducted by 3 teams of Los Angeles-based paramedic units resulted in "sensitivity of 91% (95% CI, 76% to 98%), specificity of 97% (95% CI, 93% to 99%), positive predictive value of 86% (95% CI, 70% to 95%), and negative predictive value of 98% (95% CI, 95% to 99%). With correction for the 4 documentation errors, positive predictive value increased to 97% (95% CI, 84% to 99%)."[3]
In a Chinese study, Beijing paramedics using the protocol, completed LAPSS screenings in an average of 4.3±3.0 minutes (median, 5 minutes). The study resulted in a sensitivity of 78.44% and a specificity of 90.22%.[4]
See also
References
- ^ American Heart Association - Stroke
- ^ Department of Health Services, County of Los Angeles - Treatment Protocol
- ^ Kidwell, CS; Starkman, S; Eckstein, M; Weems, K; Saver, JL (31 Jan 2000). "Identifying stroke in the field. Prospective validation of the Los Angeles prehospital stroke screen (LAPSS)". Stroke. 31 (1): 71–6. doi:10.1161/01.str.31.1.71. PMID 10625718.
- ^ Chen, S; Sun, H; Lei, Y; Gao, D; Wang, Y; Wang, Y; Zhou, Y; Wang, A; Wang, W; Zhao, X (2013-08-07). "Validation of the Los Angeles pre-hospital stroke screen (LAPSS) in a Chinese urban emergency medical service population". PLOS ONE. 8 (8): e70742. Bibcode:2013PLoSO...870742C. doi:10.1371/journal.pone.0070742. PMC 3737357. PMID 23950994.