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10.1007/s40271-017-0273-5

http://scihub22266oqcxt.onion/10.1007/s40271-017-0273-5
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C5845075!5845075!28808991
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suck abstract from ncbi


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pmid28808991      Patient 2018 ; 11 (2): 207-16
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  • Light Chain (AL) Amyloidosis: The Journey to Diagnosis #MMPMID28808991
  • McCausland KL; White MK; Guthrie SD; Quock T; Finkel M; Lousada I; Bayliss MS
  • Patient 2018[]; 11 (2): 207-16 PMID28808991show ga
  • Background: Light chain (AL) amyloidosis is a rare, complex disease associated with significant morbidity and mortality. Delays in diagnosis are common and may have detrimental consequences on patients? prognosis. Too little is known regarding the patient journey to diagnosis. Objective: The objective of this study was to describe the patient-reported journey to a correct diagnosis for AL amyloidosis. Methods: Using a mixed-methods approach, data were collected from clinician (n = 4) and patient (n = 10) interviews and a survey of community-based patients with AL amyloidosis (n = 341). Data were used to document the patient experience between the onset of symptoms and the receipt of a diagnosis. Results: Delays in diagnosis were common. Qualitative and quantitative data indicated that initial symptoms were varied and similar to other more prevalent diseases. Two themes regarding the journey to diagnosis emerged: (1) barriers to an early diagnosis; and (2) the emotional toll of the journey. Time to diagnosis was heavily influenced by how patients interpreted their initial symptoms, whether they sought early medical help, and challenges associated with making differential diagnoses. Survey results indicate that patients with primary cardiac involvement were more likely to receive a delayed diagnosis than those with primary kidney involvement. Patients described mixed emotions associated with the eventual diagnosis of AL amyloidosis. Conclusions: These data support a need for better early identification and support for patients seeking a diagnosis. Increasing clinician awareness may reduce the time to diagnosis. Additional research is needed to identify optimal diagnostic testing to reduce delays in treatment initiation and subsequent severe impacts on health.
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