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Record W4213194752 · doi:10.1097/cm9.0000000000001973

Use of edaravone to decrease perioperative neurocognitive disorders in elderly patients with hip replacement

2022· letter· en· W4213194752 on OpenAlexaboutno aff
Yu‐Jing Yuan, Liu-Jia-Zi Shao, Xin Luo, Fu‐Shan Xue

Bibliographic record

VenueChinese Medical Journal · 2022
Typeletter
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDeliriumPerioperativeNeurocognitiveAnxietyDepression (economics)Postoperative cognitive dysfunctionIncidence (geometry)CognitionAnticholinergicMontreal Cognitive AssessmentRandomized controlled trialSurgeryAnesthesiaPsychiatryCognitive impairment

Abstract

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To the Editor: By a randomized controlled trial, Xi et at[1] assessed the effects of edaravone on the development of postoperative delirium (POD) and perioperative neuro-cognitive disorders (PND) in elderly patients with hip replacement and showed that edaravone significantly decreased the incidence of POD within 7 days after surgery and the incidences of PND at 1 and 12 months after surgery. Given that both POD and PND are common complications after hip surgery in elderly patients and have been significantly associated with postoperative death, hospital-acquired complications, persistent cognitive impairments, poor postoperative functional recovery, prolonged duration of hospital stay, and increased healthcare costs,[2,3] their findings have potential implications. However, we noted several issues in the methodology and results of this study on which we would like to invite authors’ comments. First, the study objects were elderly surgical patients with a mean age >72 years. The authors only assessed preoperative cognitive function by the Montreal cognitive assessment score but did not determine whether patients suffered from preoperative neuropsychiatric comorbidities such as anxiety, delirium, depression, and sleep disorders. In fact, these comorbidities are common among elderly patients undergoing hip surgery and cannot be determined by the Montreal cognitive assessment score. It has been shown that these preoperative neuropsychiatric comorbidities are the most established predisposing factors of PND and POD after hip surgery in elderly patients.[2-5] Furthermore, the history of elderly patients’ preoperative medications was not included in the baseline data. The available evidence indicates that anticholinergic drugs and benzodiazepines are widely utilized in managing elderly patients and have been significantly associated with the development and severity of POD.[6] In addition, preoperative hemoglobin and albumin levels were also not provided in baseline data, though preoperative anemia and hypoalbuminemia have been significantly associated with an increased risk of POD in elderly surgical patients.[7] We are concerned that any imbalance in the above preoperative risk factors would have biased their findings. Second, in this study, the modified telephone interview for cognitive status was used to assess the cognitive function of all patients before and after surgery. Furthermore, the incidences of PND at 1 and 12 months after surgery were significantly lower in the edaravone group than in the control group. In the methods, however, the authors did not provide the diagnostic criteria of PND. In 2018, the International Nomenclature Consensus Working Group recommends that definitions of PND in a clinical study must meet the diagnostic criteria of neurocognitive disorders in the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition.[8] Evidently, the use of decreased scores of modified telephone interview alone for cognitive status to diagnose PND in this study cannot achieve the requirements of new recommendations for the definition of PND. Thus, we question the incidence of PND reported in this study. Third, the duration of the hospital stay was shorter in the edaravone group than in the control group, but the authors did not provided the reasons for a prolonged hospital stay in the control group. Most importantly, it was also unclear whether the two groups were comparable with respect to early postoperative complications, such as infection, hemodynamic instability, arrhythmia, sleep disorders, accidental fall, anemia, and pneumonia, which are common after major surgery in elderly patients. It has been shown that these early postoperative complications can significantly increase the risk of POD and prolong the duration of hospital stay after hip surgery in elderly patients.[9] To differentiate the real effect of one factor on the primary endpoint in a randomized controlled trial, we argue that all other possible influencing factors must be standardized for the avoidance of potential bias. Finally, the authors described that primary endpoint were the incidence of POD within 7 days after surgery, the scores of the modified telephone interview for cognitive status, and the activities of daily life at 1 and 12 months after surgery. However, they used the incidence rate of decline in postoperative cognitive function scores to calculate the sample size. In fact, as a basic principle, in a randomized controlled trial, only an important observed parameter can be designed as the primary endpoint and sample size calculation must be performed on solely the primary endpoint. Furthermore, analysis of multiple secondary outcome parameters requires significance levels to be adjusted, for example, using a Bonferroni correction.[10] We believe that clarification of these statistical issues will improve the transparency of this study design. Conflicts of interest None.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.048
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.462
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.048
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.007
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.011
GPT teacher head0.268
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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