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Original Articles

Insufficient classification of anaemia in general practice: a Danish register-based observational study

, , , , , , & show all
Pages 364-372 | Received 23 Feb 2021, Accepted 26 Apr 2021, Published online: 30 Jul 2021

Figures & data

Table 1. Demographic and clinical characteristics of individuals aged 40–90 years with new-onset anaemia detected in general practice (n = 62,731).

Figure 1. Percentagea of patients with anaemia classified into subtypes of anaemia (n = 62,731). AI: anaemia of inflammation; CIIDA: combined inflammatory iron deficiency anaemia; IDA: iron deficiency anaemia; MCV: mean cell volume. aAdjusted percentages were calculated by setting age at 70–79 years. Error bars = 95% confidence intervals.

Figure 1. Percentagea of patients with anaemia classified into subtypes of anaemia (n = 62,731). AI: anaemia of inflammation; CIIDA: combined inflammatory iron deficiency anaemia; IDA: iron deficiency anaemia; MCV: mean cell volume. aAdjusted percentages were calculated by setting age at 70–79 years. Error bars = 95% confidence intervals.

Figure 2. Percentagea of patients with anaemia who received subsequent laboratory tests in the following 3 months (n = 62,731). CRP: C-reactive protein; RDW: red cell distribution width. aAdjusted percentages were calculated by setting age at 70–79 years. Error bars = 95% confidence intervals.

Figure 2. Percentagea of patients with anaemia who received subsequent laboratory tests in the following 3 months (n = 62,731). CRP: C-reactive protein; RDW: red cell distribution width. aAdjusted percentages were calculated by setting age at 70–79 years. Error bars = 95% confidence intervals.

Table 2. The likelihood and percentage of patients having unclassified anaemia according to the aetiological algorithm and the association with patient characteristics (n = 62,731).

Supplemental material

Supplementary_file_I.docx

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Supplementary_table_I.docx

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