Recent advances and perspectives of postoperative neurological disorders in the elderly surgical patients

Liu, Biying; Huang, Dan; Guo, Yunlu; Sun, Xu; Chen, Cai–Yang; Zhai, Xiaozhu; Jin, Xia; Zhu, Hongying; Li, Peiying; Yu, Weifeng

doi:10.1111/cns.13763

Cited by 45 publications

(27 citation statements)

References 157 publications

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“…This study used a machine learning algorithm to build a predictive model to predict the risk of POD in patients with degenerative spinal disorders, which could suggest appropriate preventive measures for patients at risk, particularly by intervening early and correcting abnormal levels of controllable risk factors, and following the multicomponent intervention guidelines to prevent delirium released by The Hospital Elder Life Program (HELP). 43 , 44 This has implications for the patient's physical and mental health after surgery, early recovery, and savings in healthcare costs and resources. Using machine learning technology to establish disease prediction and risk‐assessment models can help clinicians better identify the factors that truly affect the prevalence and pathophysiology of diseases.…”

Section: Discussionmentioning

confidence: 99%

Automated machine learning‐based model for the prediction of delirium in patients after surgery for degenerative spinal disease

et al. 2022

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Objective This study used machine learning algorithms to identify critical variables and predict postoperative delirium (POD) in patients with degenerative spinal disease. Methods We included 663 patients who underwent surgery for degenerative spinal disease and received general anesthesia. The LASSO method was used to screen essential features associated with POD. Clinical characteristics, preoperative laboratory parameters, and intraoperative variables were reviewed and were used to construct nine machine learning models including a training set and validation set (80% of participants), and were then evaluated in the rest of the study sample (20% of participants). The area under the receiver‐operating characteristic curve (AUROC) and Brier scores were used to compare the prediction performances of different models. The eXtreme Gradient Boosting algorithms (XGBOOST) model was used to predict POD. The SHapley Additive exPlanations (SHAP) package was used to interpret the XGBOOST model. Data of 49 patients were prospectively collected for model validation. Results The XGBOOST model outperformed the other classifier models in the training set (area under the curve [AUC]: 92.8%, 95% confidence interval [CI]: 90.7%–95.0%), validation set (AUC: 87.0%, 95% CI: 80.7%–93.3%). This model also achieved the lowest Brier Score. Twelve vital variables, including age, serum albumin, the admission‐to‐surgery time interval, C‐reactive protein level, hypertension, intraoperative blood loss, intraoperative minimum blood pressure, cardiovascular‐cerebrovascular disease, smoking, alcohol consumption, pulmonary disease, and admission‐intraoperative maximum blood pressure difference, were selected. The XGBOOST model performed well in the prospective cohort (accuracy: 85.71%). Conclusion A machine learning model and a web predictor for delirium after surgery for the degenerative spinal disease were successfully developed to demonstrate the extent of POD risk during the perioperative period, which could guide appropriate preventive measures for high‐risk patients.

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Section: Discussionmentioning

confidence: 99%

Automated machine learning‐based model for the prediction of delirium in patients after surgery for degenerative spinal disease

et al. 2022

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“…However, many other relevant factors in the perioperative period deserve equal attention. Decreased cerebral oxygen levels, inadequate cerebral perfusion due to prolonged hypotension, excessive blood loss, duration of surgery, clinical history of cerebrovascular disease, and postoperative pain are all risk factors for the development of POCD [ 94 , 95 ]. These factors may differentially stimulate the release of cellular inflammatory factors and exacerbate oxidative stress damage.…”

Section: Association Of Ferroptosis With Perioperative Neurocognitive...mentioning

confidence: 99%

Ferroptosis is involved in regulating perioperative neurocognitive disorders: emerging perspectives

Song

Xue

et al. 2022

J Neuroinflammation

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Since the twenty-first century, the development of technological advances in anesthesia and surgery has brought benefits to human health. However, the adverse neurological effects of perioperative-related factors (e.g., surgical trauma, anesthesia, etc.) as stressors cannot be ignored as well. The nervous system appears to be more “fragile” and vulnerable to damage in developing and aging individuals. Ferroptosis is a novel form of programmed cell death proposed in 2012. In recent years, the regulation of ferroptosis to treat cancer, immune system disorders, and neurodegenerative diseases have seen an unprecedented surge of interest. The association of ferroptosis with perioperative neurocognitive disorders has also received much attention. Cognitive impairment can not only affect the individual’s quality of life, but also impose a burden on the family and society. Therefore, the search for effective preventive and therapeutic methods to alleviate cognitive impairment caused by perioperative-related factors is a challenge that needs to be urgently addressed. In our review, we first briefly describe the connection between iron accumulation in neurons and impairment of brain function during development and aging. It is followed by a review of the pathways of ferroptosis, mainly including iron metabolism, amino acid metabolism, and lipid metabolism pathway. Furthermore, we analyze the connection between ferroptosis and perioperative-related factors. The surgery itself, general anesthetic drugs, and many other relevant factors in the perioperative period may affect neuronal iron homeostasis. Finally, we summarize the experimental evidence for ameliorating developmental and degenerative neurotoxicity by modulating ferroptosis. The suppression of ferroptosis seems to provide the possibility to prevent and improve perioperative neurocognitive impairment.

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“…Postoperative cognitive dysfunction (POCD), a common complication of surgery and anesthesia, has been recognized as a new-onset cognitive impairment after any type of surgical intervention, including cardiac and non-cardiac surgery, especially in the geriatric population, which may persist for a few days, months, or even years [3,4]. POCD is broadly characterized by a series of alterations in neurocognitive conditions and behavior, including impaired memory, poor comprehension, and reduced attention [5]. Previous studies have revealed that the incidence of POCD in older individuals varies from 16.7 to 89% one week after surgery [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Effects of regional cerebral oxygen saturation monitoring on postoperative cognitive dysfunction in older patients: a systematic review and meta-analysis

et al. 2023

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Background: Postoperative cognitive dysfunction (POCD) is common after surgery and anesthesia, particularly in older patients. It has been reported that regional cerebral oxygen saturation (rSO2) monitoring potentially influences the occurrence of POCD. However, its role in the prevention of POCD remains controversial in older patients. Additionally, the quality of evidence on this topic is still relatively poor. Methods: The electronic databases PubMed, EMBASE, Web of Science, and Cochrane Library were systematically searched using the indicated keywords from their inception to June 10, 2022. We limited our meta-analysis to randomized controlled trials (RCTs) that assessed the effects of rSO2 monitoring on POCD in older patients. Methodological quality and risk of bias were assessed. The primary outcome was the incidence of POCD during hospitalization. The secondary outcomes were postoperative complications and the length of hospital stay (LOS). Odds ratios (OR) and 95% confidence intervals (CI) were calculated to determine the incidence of POCD and postoperative complications. The standardized mean difference (SMD) instead of the raw mean difference and 95% CI were calculated for LOS. Results: Six RCTs, involving 377 older patients, were included in this meta-analysis. The incidence of POCD ranges from 17 to 89%, with an overall prevalence of 47% in our pooled analysis. Our results demonstrated that rSO2-guided intervention could reduce the incidence of POCD in older patients undergoing non-cardiac surgery (OR, 0.44; 95% CI, 0.25 to 0.79; P = 0.006) rather than cardiac surgery (OR, 0.69; 95% CI, 0.32 to 1.52; P = 0.36). Intraoperative rSO2 monitoring was also associated with a significantly shorter LOS in older patients undergoing non-cardiac surgery (SMD, -0.93; 95% CI, -1.75 to -0.11; P = 0.03). Neither the incidence of postoperative cardiovascular (OR, 1.12; 95% CI, 0.40 to 3.17; P = 0.83) nor surgical (OR, 0.78; 95% CI, 0.35 to 1.75; P = 0.54) complications were affected by the use of rSO2 monitoring. Conclusion: The use of rSO2 monitoring is associated with a lower risk of POCD and a shorter LOS in older patients undergoing non-cardiac surgery. This may have the potential to prevent POCD in high-risk populations. Further large RCTs are still warranted to support these preliminary findings.

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Recent advances and perspectives of postoperative neurological disorders in the elderly surgical patients

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 45 publications

References 157 publications

Automated machine learning‐based model for the prediction of delirium in patients after surgery for degenerative spinal disease

Automated machine learning‐based model for the prediction of delirium in patients after surgery for degenerative spinal disease

Ferroptosis is involved in regulating perioperative neurocognitive disorders: emerging perspectives

Effects of regional cerebral oxygen saturation monitoring on postoperative cognitive dysfunction in older patients: a systematic review and meta-analysis

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