Diagnostic accuracy of intraocular pressure measurement for the detection of raised intracranial pressure: meta-analysis
Bibliographic record
Abstract
OBJECT: Because clinical examination and imaging may be unreliable indicators of intracranial hypertension, intraocular pressure (IOP) measurement has been proposed as a noninvasive method of diagnosis. The authors conducted a systematic review and meta-analysis to determine the correlation between IOP and intracranial pressure (ICP) and the diagnostic accuracy of IOP measurement for detection of intracranial hypertension. METHODS: The authors searched bibliographic databases (Ovid MEDLINE, Ovid EMBASE, and the Cochrane Central Register of Controlled Trials) from 1950 to March 2013, references of included studies, and conference abstracts for studies comparing IOP and invasive ICP measurement. Two independent reviewers screened abstracts, reviewed full-text articles, and extracted data. Correlation coefficients, sensitivity, specificity, and positive and negative likelihood ratios were calculated using DerSimonian and Laird methods and bivariate random effects models. The I(2) statistic was used as a measure of heterogeneity. RESULTS: Among 355 identified citations, 12 studies that enrolled 546 patients were included in the meta-analysis. The pooled correlation coefficient between IOP and ICP was 0.44 (95% CI 0.26-0.63, I(2) = 97.7%, p < 0.001). The summary sensitivity and specificity for IOP for diagnosing intracranial hypertension were 81% (95% CI 26%-98%, I(2) = 95.2%, p < 0.01) and 95% (95% CI 43%-100%, I(2) = 97.7%, p < 0.01), respectively. The summary positive and negative likelihood ratios were 14.8 (95% CI 0.5-417.7) and 0.2 (95% CI 0.02-1.7), respectively. When ICP and IOP measurements were taken within 1 hour of another, correlation between the measures improved. CONCLUSIONS: Although a modest aggregate correlation was found between IOP and ICP, the pooled diagnostic accuracy suggests that IOP measurement may be of clinical utility in the detection of intracranial hypertension. Given the significant heterogeneity between included studies, further investigation is required prior to the adoption of IOP in the evaluation of intracranial hypertension into routine practice.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".