Postoperative delirium (POD) remains a common, dangerous and resource-consuming adverse event but is often preventable. The whole peri-operative team can play a key role in its management. This update to the 2017 ESAIC Guideline on the prevention of POD is evidence-based and consensus-based and considers the literature between 01 April 2015, and 28 February 2022. The search terms of the broad literature search were identical to those used in the first version of the guideline published in 2017. POD was defined in accordance with the DSM-5 criteria. POD had to be measured with a validated POD screening tool, at least once per day for at least 3 days starting in the recovery room or postanaesthesia care unit on the day of surgery or, at latest, on postoperative day 1. Recent literature confirmed the pathogenic role of surgery-induced inflammation, and this concept reinforces the positive role of multicomponent strategies aimed to reduce the surgical stress response. Although some putative precipitating risk factors are not modifiable (length of surgery, surgical site), others (such as depth of anaesthesia, appropriate analgesia and haemodynamic stability) are under the control of the anaesthesiologists. Multicomponent preoperative, intra-operative and postoperative preventive measures showed potential to reduce the incidence and duration of POD, confirming the pivotal role of a comprehensive and team-based approach to improve patients’ clinical and functional status.

Background/Objectives: This study aims to evaluate and compare the diagnostic accuracy of skin lesion classification among three different classifiers: AI-based image classification, an expert dermatologist, and a non-expert. Given the rising interest in artificial intelligence (AI) within dermatology, it is crucial to assess its performance against human expertise to determine its viability as a reliable diagnostic tool. Methods: This reader study utilized a set of pre-labeled skin lesion images, which were assessed by an AI-based image classification system, an expert dermatologist, and a non-expert. The accuracy of each classifier was measured and compared against the ground truth labels. Statistical analysis was conducted to compare the diagnostic accuracy of the three classifiers. Results: The AI-based image classification system exhibited high sensitivity (93.59%) and specificity (70.42%) in identifying malignant lesions. The AI model demonstrated similar sensitivity and notably higher specificity compared to the expert dermatologist and non-expert. However, both the expert and non-expert provided valuable diagnostic insights, especially in classifying specific cases like melanoma. The results indicate that AI has the potential to assist dermatologists by providing a second opinion and enhancing diagnostic accuracy. Conclusions: This study concludes that AI-based image classification systems may serve as a valuable tool in dermatological diagnostics, potentially augmenting the capabilities of dermatologists. However, it is not yet a replacement for expert clinical judgment. Continued improvements and validation in diverse clinical settings are necessary before widespread implementation.

Postoperative delirium (POD) is an acute alteration of mental state, characterized by reduced awareness and attention, occurring up to five postoperative days after recovery from anesthesia. Several original studies and reviews have identified possible perioperative POD risk factors; however, there is no comprehensive review of the preoperative risk factors in patients diagnosed with POD using only validated diagnostic scales. The aim of this systematic review was to report the preoperative risk factors associated with an increased incidence of POD in patients undergoing non-cardiac and non-brain surgery. The reviewed studies included original research papers that used at least one validated diagnostic scale to identify POD occurrence for more than 24 h. A total of 6475 references were retrieved from the database search, with only 260 of them being suitable for further review. Out of the 260 reviewed studies, only 165 that used a validated POD scale reported one or more preoperative risk factors. Forty-one risk factors were identified, with various levels of statistical significance. The extracted risk factors could serve as a preoperative POD risk assessment workup. Future studies dedicated to the further evaluation of the specific preoperative risk factors’ contributions to POD could help with the development of a weighted screening tool.

Objective (or background): The hippocampus is a thoroughly studied structure of the temporal lobe. In contrast to our current knowledge of hippocampal anatomy, neurophysiology and pathophysiology, scientific literature on the relationship between the hippocampal size and age is limited. Our study aims to further the understanding of this relationship. Methods: 16 hippocampi were anatomized, photographed, measured and analyzed in comparison to age and gender using Pearson and bootstrap analyses with IBM SPSS®. Results: The results for all three independent variables of size, age and gender were not statistically significant. Conclusions: We were unable to show a statistically significant result on the correlation between the size of the hippocampus and age due to small sample size.

Aims: Parkinson’s disease (PD) is mainly a movement disorder, although 30% of PD patients may also suffer from psychosis, which may impair quality of life. PD psychosis (PDPsy) may result following approximately 10 years of treatment using dopaminergic agonists. PDPsy is characterized by recurrent and continuous hallucinations and delusions lasting for at least 1 month. Methods: A 59-year-old female was admitted under Section 2 of the Mental Health Act (MHA) due to concerns raised by the police and her family regarding her mental health. The police were particularly alarmed after she repeatedly contacted them, expressing paranoid delusions. Her confusion and memory issues further contributed to the concerns leading to her admission. She was under the Early Intervention Psychosis team at the time of admission but her engagement with them was very erratic. She was started on quetiapine 50 mg ON but was non-compliant. She was diagnosis with PD 12 years prior to admission, and was still under the neurology team, and being regularly reviewed. The medication prescribed for PD were Sinemet 12.5/25 2 tabs QDS and ropinirole 8 mg BD. Upon admission, the patient reported feeling monitored via 16 satellites connected to her television, broadcasting signals worldwide. She denied calling the police and instead suggested that her phone had been hacked. The police reported that she alleged that she had been sexually assaulted by her ex-partner or individuals organized by him while being drugged, though she had no memory of these events when questioned. She believed she was being followed, a notion she first experienced on a train to Cornwall a year prior. She also alleged that her ex-partner frequently entered her home at night to steal from her. She, also, exhibited delusional beliefs regarding her YouTube presence, asserting that her ex-partner manipulated satellites to influence her views online. Risk factors identified included medication non-compliance, poor insight, risk of falls due to Parkinson’s disease, potential financial exploitation due to engagement with strangers on social media, and vulnerability. Results: The differential diagnosis considered for this patient: Delusional Disorder. Late-Onset Psychosis. Parkinson’s Disease Psychosis. Alzheimer’s Disease with Psychosis. Brief Reactive Psychosis. A literature search showed that management of PDPsy involves a balance between reducing PD medication and introducing an antipsychotic for symptom management. Conclusion: This case highlights the diagnostic challenges of psychosis in Parkinson’s disease and underscores the importance of a multidisciplinary approach in managing psychiatric symptoms in neurodegenerative conditions.