Los Angeles Prehospital Stroke Screen

The Los Angeles Prehospital Stroke Screen (abbreviated LAPSS) is a method of identifying potential stroke patients in a pre-hospital setting.[1]

Los Angeles Prehospital Stroke Screen (LAPSS)
SynonymsLAPSS
Purposeidentifying potential stroke patients

Screening criteria
  • No history of seizures or epilepsy
  • Age 45 years or older
  • At baseline, patient is not wheelchair bound or bedridden
  • Blood glucose between 60 and 400 mg/dL
  • Obvious asymmetry-unilateral weakness with any of the following motor exams:
    1. Facial Smile/Grimace
    2. Grip
    3. 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
  1. American Heart Association - Stroke
  2. Department of Health Services, County of Los Angeles - Treatment Protocol
  3. 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.
  4. 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.
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