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Record W4389032239 · doi:10.1093/ofid/ofad500.894

849. Histopathology of Cutaneous Invasive Fungal Infections in a Tertiary Cancer Center: Causes, Discordance with Culture, and Histopathologic Determinants of Outcome

2023· article· en· W4389032239 on OpenAlexaff
Pavandeep Gill, Sebastian Wurster, Jeffrey J. Tarrand, Xinyang Jiang, Jing Ning, Ying Jiang, Phyu P. Aung, Woo Cheal Cho, Jonathan L. Curry, Carlos A. Torres‐Cabala, Doina Ivan, Víctor G. Prieto, Dimitrios P. Kontoyiannis, Priyadharsini Nagarajan

Bibliographic record

VenueOpen Forum Infectious Diseases · 2023
Typearticle
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsRoyal Jubilee HospitalUniversity of British Columbia
Fundersnot available
KeywordsHistopathologyMedicinePathologyMalignancyCancerMucormycosisInternal medicineGastroenterology

Abstract

fetched live from OpenAlex

Abstract Background Cutaneous invasive fungal infections CIFIs (primary or secondary to hematogenous seeding) are frequent and often fatal in immunocompromised cancer patients (pts). There is a paucity of studies on the prognostic significance and concordance of histopathologic features with cultures. Methods We reviewed all pts with histologically diagnosed CIFIs at MD Anderson Cancer Center (06/2016-06/2020). Demographic, clinical, histopathologic [organism, distribution (dermis/subcutis, blood vessels/nerves/epidermis), density of fungi and host response (inflammation, fibrosis)], culture, and outcome (all-cause mortality) data were recorded. Results We identified 61 pts (median age: 60 years, range: 8-81); 37 (61%) were male. Most had hematologic malignancy (n=58, 95%), especially acute leukemia (n = 40, 66%). CIFI was primary in 53 pts (87%), with acute onset (≤ 1 week) in 66% of pts; 37 pts (61%) had multiple skin lesions. Fungal organisms were seen on H&E-stained sections in 47 cases (77%), whereas ancillary studies (GMS/PAS) were required in 14 cases (23%). Of the 59 concurrent microbiology cultures, only 43 (73%) were positive. In 16 cases, fungal order/genus was identified by both histopathology and culture; 13/16 (81%) were concordant (Fleiss’ kappa 0.67, Fig 1A). The causative fungal order/genus was determined in 55 pts (90%), most commonly Fusarium (n = 22, 36%) or Mucorales (n = 12, 20%, Fig. 1B). Angiotropism was most frequently associated with Fusarium (19/22, 88%), and neurotropism with Mucorales (8/12, 67%, Table 1). Eighty-four-day all-cause mortality rate was 62% (66% and 50% in CIFIs caused by molds and yeasts, respectively). Fungal angiotropism (p = 0.001, Fig 2A) and neurotropism (p < 0.001, Fig 2B) were associated with significantly increased mortality, while lymphocytic inflammation, seen only in 20%, was associated with reduced mortality (p = 0.024, Fig 2C). Figure 1 (A) Concordance of histopathologically determined and cultured fungal order/genus. Fleiss’ kappa 0.67 (“substantial agreement”), p < 0.001. (B) Distribution of causative fungal pathogens. Figure 2 Histopathological features significantly associated with 84-day all-cause mortality in CIFI patients. Error bands denote 95% confidence interval. Mantel-Cox log-rank test. Table 1 Association between type of organism and histopathological characteristics. Six patients with no identified organism were excluded. Fisher’s exact test. Abbreviation: PEH = pseudoepitheliomatous hyperplasia. Conclusion CIFIs have poor prognosis, especially when caused by molds and if fungal angio-/neurotropism is identified. Inflammation may be associated with better prognosis. Since cultures might be false negative (27%) or discordant (19%), more efforts are needed for culture-independent molecular detection of fungi. Incorporation of histopathologic features might inform prognostic risk stratification. Disclosures Dimitrios P. Kontoyiannis, MD, MS, ScD, PhD, AbbVie: Board Member|Astellas: Grant/Research Support|Cidara: Board Member|Gilead: Grant/Research Support|Merck: Advisor/Consultant|Scynexis/MSGERC: Board Member

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.315
Teacher spread0.298 · 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 source (direct Gemma or distilled Codex), 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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Citations0
Published2023
Admission routes1
Has abstractyes

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