Splenomegaly is a marker of advanced chronic liver disease and portal hypertension in <scp>HIV</scp> infection
Bibliographic record
Abstract
OBJECTIVES: To evaluate the clinical significance of splenomegaly as a marker of underlying liver disease in people with HIV (PWH). METHODS: We included consecutive PWH from a prospective cohort from 2010 to 2020 with available liver stiffness measurement (LSM) and liver imaging to define splenomegaly (> 13 cm) within 1 year. Cut-offs of LSM > 10 kPa and > 21 kPa were used to identify advanced chronic liver disease (ACLD) and portal hypertension, respectively. Logistic regression multivariable analysis was employed to identify independent predictors of ACLD. RESULTS: In all, 331 PWH were included, 76% of them men, with a median (interquartile range) age of 51.3 (45-58) years, all receiving antiretroviral treatment, and 53% were HIV monoinfected. The PWH with splenomegaly exhibited a higher prevalence of ACLD compared with those with normal spleen size, as per LSM (26% vs. 9%; p = 0.009). Portal hypertension diagnosed by LSM was also more prevalent in PWH with splenomegaly than in those without (15% vs. 2%; p < 0.001). Independent predictors of ACLD were viral hepatitis coinfection [adjusted odds ratio (aOR) = 3.15, 95% confidence interval (CI): 1.65-6.0], lower platelets (aOR = 0.99, 95% CI: 0.99-0.99) and splenomegaly (aOR = 2.41, 95% CI: 1.17-4.99). In patients with available oesophagogastroduodenoscopy, splenomegaly was also associated with higher prevalence of oesophageal varices and other endoscopic findings of portal hypertension (38% vs. 17%; p = 0.027). CONCLUSIONS: Splenomegaly identified on routine imaging may have utility as a marker of ACLD and portal hypertension, prompting further investigations.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".