Reporting individual symptoms in postoperative delirium studies: Protocol for a systematic review
Bibliographic record
Abstract
Objectives Delirium is a nonspecific cerebral syndrome characterised by an acute and transient alteration in cognition and attention. This may affect memory, orientation, language and perception, which cannot be accounted for by pre-existing dementia. Delirium studies often report delirium as a dichotomous outcome, providing limited information into the potential phenotypes of delirium which are present within the population, and the symptom profiles patients are experiencing. Delirium is particularly common in patients who have undergone surgery. In this systematic review, we aim to identify studies of these populations which report and record symptoms of delirium individually, as well as whether they record delirium psychomotor subtype and severity. Methods This systematic review has been registered with Prospero: CRD42021236622 This systematic review will be conducted in accordance with PRISMA 2020 guidelines. We will search Medline, Embase and Web of Science for studies of any language and any publication date. An example of the search strategy is shown in Table 1. These studies will include only patients over the age of 18, and patients undergoing surgery of any type in hospital, who develop postoperative delirium, and report its individual symptoms. Only studies that report individual symptoms of delirium will be included. We will include all clinical trials, randomised controlled trials, observational studies, and qualitative studies including interventional design studies. Case reports, cases series, editorials, reviews, systematic reviews and animal studies will be excluded. Studies which include patients with pre-existing diagnosed dementia, pre-operative delirium, Wernicke’s encephalopathy, brain tumours, brain aneurysms, neurological disorders or studies involving alcohol abuse and withdrawal will also be excluded. Two independent, blinded, reviewers will assess abstracts and titles for eligibility. Results Due to the nature of our research question, we anticipate a high number of studies to be included for full-text review. This stage will involve 8 fully-trained independent reviewers; each paper will be screened in duplicate, and quality-control methods conducted. Data will be extracted and quality appraised using the Newcastle Ottawa Scale, by two independent reviewers. Missing data will be addressed by contacting study authors in the first instance, but alternatively by noting the limitation or excluding the study, depending on the extent of the missing data. Our findings of how many studies report on individual delirium symptoms will be reported by a narrative synthesis. Discussion/Conclusion Current methods of reporting delirium by dichotomous outcome or psychomotor subtype provide little information on the full clinical and biological profile of the patient. This is limiting knowledge of the potential delirium phenotypes. By reporting, discussing and comparing the differences in symptoms reported in delirium studies, we can highlight the importance of individuality in reports, alongside the spectrum of delirium presentations that occur. This would emphasise the importance of identifying subphenotypes of delirium, expanding knowledge of the condition and therefore progressing research into targeted treatments. This review should encourage the study of symptom profiles occurring in various populations, alongside predisposing and precipitating delirium risk factors.
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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 | 0.074 | 0.114 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.023 | 0.022 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.083 | 0.009 |
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".