Puntaje predictivo de emergencias médicas en un servicio médico quirúrgico, usando variables clínicas y los diagnósticos de ingreso
| Autor: | Antonio Vukusich, Gabriel Cavada, Ángel Vargas, César Maquilón, Paula Daza, Claudia Cofré |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
medicine.medical_specialty
Pediatrics business.industry Hospitalized patients MEDLINE Patients Rooms General Medicine Predictive value Likelihood ratios in diagnostic testing Patient room Predictive value of tests Emergency medicine Medicine Emergencies Medical Services business Hospital stay Alert system Risk assessment Hospital Rapid Response Team |
| Zdroj: | Revista médica de Chile v.145 n.2 2017 SciELO Chile CONICYT Chile instacron:CONICYT |
| ISSN: | 0034-9887 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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