Puntaje predictivo de emergencias médicas en un servicio médico quirúrgico, usando variables clínicas y los diagnósticos de ingreso
Background: The medical alert system (MAS) was created for the timely handling of clinical decompensations, experienced by patients hospitalized at the Medical Surgical Service (MSS) in a private clinic. It is activated by the nurse when hemodynamic, respiratory, neurological, infectious or metaboli...
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| Autores principales: | , , , , , |
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| Lenguaje: | Spanish / Castilian |
| Publicado: |
Sociedad Médica de Santiago
2017
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| Materias: | |
| Acceso en línea: | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0034-98872017000200002 |
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| Sumario: | Background: The medical alert system (MAS) was created for the timely handling of clinical decompensations, experienced by patients hospitalized at the Medical Surgical Service (MSS) in a private clinic. It is activated by the nurse when hemodynamic, respiratory, neurological, infectious or metabolic alterations appear, when a patient falls or complains of pain. A physician assesses the patient and decides further therapy. Aim: To analyze the clinical and demographic characteristics of patients who activated or not the MAS and develop a score to identify patients who will potentially activate MAS. Material and Methods: Data from 13,933 patients discharged from the clinic in a period of one year was analyzed. Results: MAS was activated by 472 patients (3.4%). Twenty two of these patients died during hospital stay compared to 68 patients who did not activate the alert (0.5%, p < 0.01). The predictive score developed considered age, diagnosis (based on the tenth international classification of diseases) and whether the patient was medical or surgical. The score ranges from 0 to 9 and a cutoff ≥ 6 provides a sensitivity and specificity of 37 and 81% respectively and a positive likelihood ratio (LR+) of 1.9 to predict the activation of MAS. The same cutoff value predicts death with a sensitivity and specificity of 80% and a negative predictive value of 99.8%. Conclusions: This score may be useful to identify hospitalized patients who may have complications during their hospital stay. |
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