The Value of Thin Layer Cytology in Cancer Patients’ Pericardial Effusions
Bibliographic record
Abstract
Objective: Early diagnosis and treatment of metastatic pericardial disease are crucial to prevent the life-threatening complication of cardiac tamponade. Thin Layer Cytology (TLC), a widely adopted technique in cytology, has gained significant acceptance for most specimens. Our study aimed to assess the utility of TLC in diagnosing metastatic neoplasms and their origins in pericardial effusions, as well as monitoring response to chemotherapy. Methods: We examined 184 pericardial fluids collected by pericardiocentesis and processed using the ThinPrep liquid-based technique. Various immunocytochemical markers were used to determine the site of metastatic neoplasms. We also evaluated the response to therapy in 53 patients with lung and breast cancer. Results: Out of 184 specimens, 113 pericardial fluids were diagnosed as positive for malignancy, while 71 were negative. Twenty-three cases of unknown primary site were included in the total positive cases. Ninety cases positive for malignancy had a known primary site of origin, including 31 lung carcinomas, 22 breast carcinomas, 10 ovarian carcinomas, 6 T-cell lymphomas, 3 urinary bladder carcinomas, 4 renal carcinomas, 5 adenocarcinomas of the colon, 5 prostate carcinomas, 2 parotid adenocarcinomas, and 2 melanomas. Regarding the 53 cases with chemotherapy treatment, the cytologic examination of pericardial fluid showed a remarkable reduction in neoplastic burden after the third dose of cisplatin or thiotepa instilled into the pericardial cavity. ThinPrep provided excellent preservation of cytomorphological features, high cellularity per slide, and a clear background. This comprehensive analysis provides crucial information about the types and distribution of cancerous cells present in the samples. Conclusions: Thin Layer Cytology (TLC) is a valuable diagnostic tool for detecting metastatic pericardial malignancy. It allows the examination of exfoliated cells from the pericardial fluid, providing crucial information for diagnosis, management, and monitoring the acute responsiveness to intrapericardial chemotherapy. Immunocytochemistry (IHC) can identify specific markers for various types of cancer, enabling a more accurate diagnosis and guiding further treatment decisions.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".