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10.1016/j.sleep.2020.08.031

http://scihub22266oqcxt.onion/10.1016/j.sleep.2020.08.031
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suck abstract from ncbi


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pmid32937279      Sleep+Med 2020 ; 75 (ä): 294-300
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  • Symptomless multi-variable apnea prediction index assesses adverse outcomes in patients with Corona Virus Disease 2019 #MMPMID32937279
  • Zhang S; Xu Y; Li J; Wu K; Wang T; Su X; Han Q; Xi Y; Gao Y; Wang H; Hu Y; Liu C; Ran P; Zhang N; Zhong N
  • Sleep Med 2020[Nov]; 75 (ä): 294-300 PMID32937279show ga
  • PURPOSE: To explore the relationship between symptomless multi-Variable apnea prediction (sMVAP) index and adverse outcomes of patients with Corona Virus Disease 2019 (COVID-19). METHODS: According to the sMVAP quartiles, we divided all patients into four groups. The clinical electronic medical records, nursing records, laboratory findings, and radiological examinations for all patients with laboratory confirmed Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection were reviewed. Cox proportional hazard ratio (HR) models were used to determine the risk factors associated with in hospital death. RESULTS: A total of 97 patients were included in this study. The "Quartile 4" group 's ICU transfer rate was significantly higher than the "Quartile 1" group. Coronary heart disease, high d-dimer and sMVAP at admission were associated with increased odds of death. CONCLUSIONS: Using the sMVAP index for obstructive sleep apnea hypopnea syndrome (OSAHS) risk assessment, and then predicting the adverse outcomes of COVID-19 patients, is an effective method. Therefore, the use of sMVAP index for OSAHS screening for inpatients with COVID-19 should be vigorously promoted, and high-risk patients should be effectively managed.
  • |*Hospital Mortality[MESH]
  • |Adult[MESH]
  • |Aged[MESH]
  • |COVID-19/*mortality/physiopathology[MESH]
  • |Comorbidity[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Proportional Hazards Models[MESH]
  • |Retrospective Studies[MESH]
  • |Risk Assessment[MESH]
  • |SARS-CoV-2[MESH]
  • |Severity of Illness Index[MESH]


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