Clinical manifestations and diagnostic methods in pulmonary angiosarcoma: protocol for a scoping review
Bibliographic record
Abstract
BACKGROUND: Angiosarcoma involving the lung can represent either primary or metastatic malignancy. Due to the rarity of this condition, knowledge surrounding the natural history and clinical presentation is scarce. The aim of this scoping review is to summarize the existing literature on pulmonary angiosarcoma, particularly as it pertains to the clinical presentation and ancillary tests used for diagnosis in addition to histopathology. METHODS: We will conduct a systematic search using Ovid MEDLINE and EMBASE electronic databases. Two investigators will independently screen identified titles and abstracts to select articles reporting on pulmonary angiosarcoma. The data will be summarized in a narrative fashion and organized according to aspects of epidemiology, risk factors, clinical presentation, diagnostic methods, and treatment. DISCUSSION: Scoping reviews are increasingly used to synthesize the evidence on a particular topic, to identify gaps in the literature, and to determine if future systematic reviews are feasible. In order to improve the care of patients with angiosarcoma, earlier recognition and diagnosis is required. This review will be valuable for highlighting the range of clinical presentations and the role of imaging and other diagnostic tools in the diagnosis of metastatic and primary pulmonary angiosarcoma. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration: CRD42017059052.
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 | 0.055 | 0.065 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.015 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.048 | 0.007 |
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".