Nuts and bolts of lung ultrasound: utility, scanning techniques, protocols, and findings in common pathologies
Bibliographic record
Abstract
Point of Care ultrasound (POCUS) of the lungs, also known as lung ultrasound (LUS), has emerged as a technique that allows for the diagnosis of many respiratory pathologies with greater accuracy and speed compared to conventional techniques such as chest x-ray and auscultation. The goal of this narrative review is to provide a simple and practical approach to LUS for critical care, pulmonary, and anesthesia providers, as well as respiratory therapists and other health care providers to be able to implement this technique into their clinical practice. In this review, we will discuss the basic physics of LUS, provide a hands-on scanning technique, describe LUS findings seen in normal and pathological conditions (such as mainstem intubation, pneumothorax, atelectasis, pneumonia, aspiration, COPD exacerbation, cardiogenic pulmonary edema, ARDS, and pleural effusion) and also review the training necessary to achieve competence in LUS.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".