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Record W4388014063 · doi:10.1111/all.15929

Trends in severe allergic reactions of adults in Finland between 1999 and 2020: A national population study

2023· article· en· W4388014063 on OpenAlexaffabout
Lasse Saarimäki, Juho E. Kivistö, Sauli Palmu, Jennifer L. P. Protudjer, Heini Huhtala, Jussi Karjalainen

Bibliographic record

VenueAllergy · 2023
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAnaphylaxisMedicineIncidence (geometry)Food allergyPopulationConfidence intervalAllergyPediatricsAnaphylactic shockDemographyInternal medicineEnvironmental healthImmunology

Abstract

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Increases in both the incidence of, and hospitalisation for, anaphylaxis and other severe allergic reactions has increased in recent years.1 Indeed, a British study provided evidence of such increase up to sevenfold between 1992 and 2012.2 We previously reported on the temporal patterns amongst the paediatric population, in Finland and Sweden.3 Herein, we report the on trends of severe allergic reactions, between 1999 and 2020 in the entire Finnish adult population, that resulted in hospitalization, as well as anaphylaxis not leading to hospitalization (visits). We used the Finnish National Hospital Discharge register4 to obtain information about hospitalizations using International Classification of Diseases, 10th Revision (ICD-10) (codes of primary diagnoses). Anaphylaxis codes included T78.0 (anaphylactic shock due to adverse food reaction) and T78.2 (anaphylactic shock unspecified). Codes for other allergic reactions included T78.1 (other adverse food reactions not elsewhere classified), T78.3 (angioneurotic oedema) and T78.4 (allergy unspecified). To calculate the annual incidence (per 100,000 person-years [PY]) of hospitalizations, we used annual age-specific mid-populations from Official Statistics of Finland. An incidence rate ratio (IRR) with corresponding 95 percent confidence intervals (95%CI) was used to evaluate mean annual change in hospitalizations. From 1999 to 2020, the cumulative observation time was 93,394,237 PY, during which 9766 Finnish adult persons hospitalized due allergic reactions (Table 1; incidence rate [IR] 10.96/100,000 PY (95%CI 10.48–11.44)). With consideration to anaphylaxis triggers, 3.0% were due adverse food reactions, 0.5% other adverse food effects, 29.7% unspecified anaphylactic reactions, 21.6% angioneurotic oedema and 45.2% unspecified allergic reactions. However, the distribution with specific diagnoses should be interpreted with caution, as the methodology is not able to discern about the aetiology of allergic reactions. The hospitalization incidence increased during the study period approximately by 1% per year (IRR = 1.01; 95%CI 1.00–1.02). Corresponding numbers for anaphylaxis to food and unspecified were 1.05 (95%CI 1.03–1.07) and 1.02 (95%CI 1.01–1.02), respectively (Figure 1). An increase was also noted for angioneurotic oedema (IRR = 1.04; 95%CI 1.03–1.04). Unspecific allergic reactions remained stable over the study period (IRR = 0.99; 95%CI 0.99–1.00). Hospitalizations were lowest in 2008 (IR 9.04; 95%CI 6.53–11.56) and peaked in 2016 (IR 13.26; 95%CI 10.77–15.75). For more detail about results check Appendix S1. The majority (17,382/20,584 reactions; 84.4%) of anaphylaxis (T78.0 + T78.2) did not lead to hospitalization (IR = 16.66; 95%CI 15.45–17.87). During the study period, diagnoses increased (Figure 1), on average, 4%–7% annually (T78.0 IRR = 1.07; 95CI% 1.06–1.08); T78.2 IRR = 1.04; 95CI% 1.04–1.05). Strengths of this study include the longest follow up of which we are aware, data from well-established Finnish registers and the examination of a spectrum of severe allergic diseases, which reflects the overlapping diagnoses noted in real life. Moreover, our study period spans the duration of the Finnish Allergy Program (2008–2018),5 with a noted increased incidence shortly after the commencement of this program. Similarly, our study period includes a period before and after the introduction of anaphylaxis criteria in 2006.6 In year 2013 emergency medicine training program was implemented for physicians working in emergency department settings. Notable limitations include the lack of individual patient data and thus the inability to evaluate the aetiology of allergic reactions or the fulfilment of anaphylaxis criteria, and an inability to assess the severity of anaphylactic reaction. Moreover, it is possible that a single person may have had multiple visits for the same allergic reaction, that is, first in emergency care setting and later in outpatient clinic. In summary, amongst Finnish adults, hospitalizations due allergic reactions and anaphylaxis have been increasing, by approximately 1% and 4%–5% annually, the latter which may be partly attributable to a shift from hospital admissions to emergency care follow up. Lasse Saarimäki: Planning the study, designing the methodology, collecting data, performing statistical analyses, writing the article and being responsible for the publication process. Juho Kivistö: Planning the study, designing the methodology and writing the article. Sauli Palmu: Writing the article and providing expertise in processing results. Heini Huhtala: Performing statistical analyses and writing the article. Jennifer L. P. Protudjer: Writing the article and providing expertise in processing results. Jussi Karjalainen: Planning the study, designing the methodology and writing the article. None. None. Lasse Saarimäki, Juho Kivistö, Sauli Palmu, Heini Huhtala, and Jussi Karjalainen declare no conflicts of interest. Jennifer L. P. Potudjer: JP is Section Head, Allied Health; and Co-Lead, Research Pillar for the Canadian Society of Allergy and Clinical Immunology, and is on the steering committee for Canada's National Food Allergy Action Plan. She reports consulting for Ajonomoto Cambrooke, Novartis, Nutricia and ALK Abelló. The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. Data S1 Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.335
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2023
Admission routes2
Has abstractyes

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