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Record W1999130942 · doi:10.1089/end.2008.9724

Number of Needle Passes Does Not Correlate with the Diagnostic Yield of Renal Fine Needle Aspiration Cytology

2008· article· en· W1999130942 on OpenAlexfundno aff
Sero Andonian, Zeph Okeke, Deidre A. Okeke, Chiara Sugrue, Patricia Wasserman, Benjamin R. Lee

Bibliographic record

VenueJournal of Endourology · 2008
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsnot available
FundersMcGill University
KeywordsMedicineFine needle aspiration cytologyFine-needle aspirationCytologyDiagnostic accuracyRenal massRadiologyBiopsyKidneyPathologyNephrectomyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Renal Fine Needle Aspiration Cytology (FNAC) has gained popularity due to increasing options in management of renal lesions such as energy ablation and active surveillance. The diagnostic yield of renal FNAC varies between 40-90%. We hypothesized that adequate and diagnostic FNA samples would be associated with higher number of needle passes and higher number of slides examined. PATIENTS AND METHODS: The pathology database at our institution was retrospectively searched for renal FNACs performed between 1995 and 2005. Patient gender, side, indication, cytological diagnosis, final histological diagnosis when available, number of needle passes performed, number of slides examined, and adequacy of the FNAC sample as determined by Diff Quik staining by the cytotechnologist (CS) were recorded. Chi square test was performed for statistical analysis. RESULTS: Out of 377 renal biopsies performed, 259 were core biopsies for medical renal disease, and 118 were FNACs for renal lesions, including 16 for indeterminate complex renal cysts and 102 for solid renal masses. Indeterminate renal cysts were excluded from the study. Out of 102 FNACs for solid renal masses, 22 were inadequate with 13 (59%) being non-diagnostic; and 80 FNACs were adequate with 3 (4%) being non-diagnostic. The number of needle passes was not significantly different between non-diagnostic and diagnostic samples (2.5 vs 3.2); and between inadequate and adequate samples (3.4 vs 3.0). Similarly, the number of slides examined was not significantly different between non-diagnostic and diagnostic samples (9.5 vs 10.9); and between inadequate and adequate samples (11.3 vs 10.6). Diff Quik adequate samples had significantly higher diagnostic yields when compared to Diff Quik inadequate samples (965 vs 41%; p<0.01). CONCLUSIONS: The number of needle passes and microscopic slides examined did not correlate with sample adequacy or diagnostic yield of renal FNAC. Sample adequacy as determined by Diff Quik staining correlated with diagnostic FNAC. Despite the retrospective nature of this study, a cytotechnologist should be present during the FNA procedure to ensure adequate samples have been obtained to increase the diagnostic yield of renal FNAC.

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)0.001
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 score0.101
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.027
GPT teacher head0.255
Teacher spread0.228 · 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".

Quick stats

Citations11
Published2008
Admission routes1
Has abstractyes

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