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10.3390/ijerph18116083

http://scihub22266oqcxt.onion/10.3390/ijerph18116083
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34200028!8200245!34200028
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suck abstract from ncbi


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pmid34200028      Int+J+Environ+Res+Public+Health 2021 ; 18 (11): ä
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  • The Risk of Hospitalization in COVID-19 Patients Can Be Predicted by Lung Ultrasound in Primary Care #MMPMID34200028
  • Martinez-Redondo J; Comas C; Pujol Salud J; Crespo-Pons M; Garcia-Serrano C; Bravo MO; Peruga JMP
  • Int J Environ Res Public Health 2021[Jun]; 18 (11): ä PMID34200028show ga
  • BACKGROUND: The usefulness of Lung Ultrasound (LUS) for the diagnosis of interstitial syndrome caused by COVID-19 has been broadly described. The aim of this study was to evaluate if LUS may predict the complications (hospital admission) of COVID-19 pneumonia in primary care patients. METHODS: This observational study collects data from a cohort of 279 patients with clinical symptoms of COVID-19 pneumonia who attended the Balaguer Primary Health Care Area between 16 March 2020 and 30 September 2020. We collected the results of LUS scans reported by one general practitioner. We created a database and analysed the absolute and relative frequencies of LUS findings and their association with hospital admission. We found that different LUS patterns (diffuse, attenuated diffuse, and predominantly unilateral) were risk factors for hospital admission (p < 0.05). Additionally, an evolutionary pattern during the acute phase represented a risk factor (p = 0.0019). On the contrary, a normal ultrasound pattern was a protective factor (p = 0.0037). Finally, the presence of focal interstitial pattern was not associated with hospital admission (p = 0.4918). CONCLUSION: The lung ultrasound was useful to predict complications in COVID-19 pneumonia and to diagnose other lung diseases such as cancer, tuberculosis, pulmonary embolism, chronic interstitial pneumopathy, pleuropericarditis, pneumonia or heart failure.
  • |*COVID-19[MESH]
  • |Hospitalization[MESH]
  • |Humans[MESH]
  • |Lung/diagnostic imaging[MESH]
  • |Primary Health Care[MESH]
  • |SARS-CoV-2[MESH]


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