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1159
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Hypoglycemia
Differential
... Diagnosis and Workup
Algorithm
... true (Whipple's
triad
... #Hypoglycemia #
Differential
... Diagnosis #Workup #
Algorithm
Initial
triage
of ... neutropenic adult -
Algorithm
... #neutropenia #
Algorithm
... #indications #
differential
Consolidation Pattern -
Differential
...
Algorithm
#Diagnosis ... #
Radiology
#Pulmonary ... Consolidation #Pattern #
Differential
... #
Algorithm
#RadiologyAssistant
casualty incident
triage
... Amberg-Schwandorf
Algorithm
... for Primary
Triage
... category #Management #
Triage
... MassCasualty #Incident #
Algorithm
â–º
Interstitial Pattern -
Differential
...
Algorithm
#Diagnosis ... #
Radiology
#Pulmonary ... Interstitial #Pattern #
Differential
... #
Algorithm
#RadiologyAssistant
Mass Pattern -
Differential
...
Algorithm
#Diagnosis ... #
Radiology
#Pulmonary ... Mass #Pattern #
Differential
... #
Algorithm
#RadiologyAssistant
Battery Ingestion
Triage
... Treatment Guideline -
Algorithm
... Battery #Ingestion #
Algorithm
Sinus Tachycardia
Differential
...
Algorithm
- ... #Tachycardia #
Differential
... #
Algorithm
#Diagnosis ... #
Cardiology
#Causes
Atelectasis Pattern -
Differential
...
Algorithm
#Diagnosis ... #
Radiology
#Pulmonary ... Atelectasis #Pattern #
Differential
... #
Algorithm
#RadiologyAssistant
Hyperprolactinemia
Differential
... Diagnosis and Workup
Algorithm
...
Thiago
Mendes @mendesthiagob ... Hyperprolactinemia #Prolactin #
Differential
... Diagnosis #Workup #
Algorithm
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![Primary mass casualty incident triage:
The Amberg-Schwandorf Algorithm for Primary Triage (ASAV) [4]. I = red category, II = yellow category,](data:image/jpeg;base64,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 "Primary mass casualty incident triage:
The Amberg-Schwandorf Algorithm for Primary Triage (ASAV) [4]. I = red category, II = yellow category, ...")
