Evidence map›Paper›PMID 41859087›Full record

ArticleFrontiers in immunology2026

Case Report: A 69-year-old woman with dermatopathic lymphadenopathy and hypercalcemia after COVID-19 infection.

Danli Hu, Yanchun Li, Shen Shen

Abstract readCase Reports
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Danli HuDepartment of General Medicine, Beijing Chao-yang Hospital, Capital Medical University, Beijing, China.
Yanchun LiDepartment of Nephrology, Beijing Chao-yang Hospital, Capital Medical University, Beijing, China.
Shen ShenDepartment of Nephrology, Beijing Chao-yang Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patient concerns: A 69-year-old female presented with hypercalcemia, recurrent fever, and lymphadenectasis following COVID-19 infection. Positron emission tomography/computed tomography (PET-CT) revealed no suspicious malignancy. Lymph node biopsy from bilateral inguinal areas suggested Langerhans cell histiocytosis, supporting a possible diagnosis of dermatopathic lymphadenitis or rare Langerhans cell histiocytosis. The immunohistology staining showed that the proliferated Langerhans cells in lymph nodes expressed CD68, CD1a, and S100, further supporting the diagnosis of dermatopathic lymphadenitis. Diagnosis and intervention: The patient was diagnosed with dermatopathic lymphadenopathy. The patient underwent a therapy of prednisone acetate at 30 mg per day. Then, glucocorticoid was gradually decreased by 2.5 mg per 2 weeks, until it reached 7.5 mg per day. Salmon calcitonin was subcutaneously injected to decrease the calcium level and relieve pain during hospitalization. Outcomes: During the 3 months of treatment, the systemic symptoms were significantly alleviated. The lymph nodes of the right inguinal area and the serum calcium level decreased to normal. She remained in remission for an additional 4 years. Lessons: Coexistence of the two unrelated diseases, dermatopathic lymphadenopathy and hypercalcemia, was rare. Immune dysregulation and persistent inflammatory responses post-COVID-19 infection may be the potential mechanism for hypercalcemia.

Indexed as

COVID-19Histiocytosis, Langerhans-CellHypercalcemiaLymphadenopathySARS-CoV-2AgedFemaleHumansLymph NodesPositron Emission Tomography Computed TomographyCOVID-19 infectiondermatopathic lymphadenopathyhypercalcemiaimmune dysfunctioninflammation

Identifiers

PMID41859087
PMCPMC12996087

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.