OBJECTIVE: Recent advancements in brain-computer interface (BCI) technology have seen a significant shift towards incorporating complex decoding models such as deep neural networks (DNNs) to enhance performance. These models are particularly crucial for sophisticated tasks such as regression for decoding arbitrary movements. However, these BCI models trained and tested on individual data often face challenges with limited performance and generalizability across different subjects. This limitation is primarily due to a tremendous number of parameters of DNN models. Training complex models demands extensive datasets. Nevertheless, group data from many subjects may not produce sufficient decoding performance because of inherent variability in neural signals both across individuals and over time METHODS: To address these challenges, this study proposed a transfer learning approach that could effectively adapt to subject-specific variability in cortical regions. Our method involved training two separate movement decoding models: one on individual data and another on pooled group data. We then created a salience map for each cortical region from the individual model, which helped us identify the input\'s contribution variance across subjects. Based on the contribution variance, we combined individual and group models using a modified knowledge distillation framework. This approach allowed the group model to be universally applicable by assigning greater weights to input data, while the individual model was fine-tuned to focus on areas with significant individual variance RESULTS: Our combined model effectively encapsulated individual variability. We validated this approach with nine subjects performing arm-reaching tasks, with our method outperforming (mean correlation coefficient, r = 0.75) both individual (r = 0.70) and group models (r = 0.40) in decoding performance. In particular, there were notable improvements in cases where individual models showed low performances (e.g., r = 0.50 in the individual decoder to r = 0.61 in the proposed decoder) CONCLUSIONS: These results not only demonstrate the potential of our method for robust BCI, but also underscore its ability to generalize individual data for broader applicability.

Deep vein thrombosis is a recognised complication of lower limb cast immobilisation and post operative state immobilisation. A national survey revealed that low molecular weight heparin (LMWH) is the favoured strategy for thromboprophylaxis in the latter context. However, clinicians need to be aware of the fact that the use of LMWH might incur the risk of subsequent development of heparin-induced thrombocytopenia, with its attendant life-threatening thrombotic complications. Some of the patients who develop those complications might be admitted under the care of general physicians, hence the importance of raising awareness of this issue.

OBJECTIVE: To identify factors associated with the need for a deep etonogestrel contraceptive implant removal as compared to superficial removal.
METHODS: We conducted a retrospective cohort study of patients undergoing contraceptive implant removal from January 2014 to January 2023. We extracted key patient characteristics from electronic health record review and compared patients requiring deep removal versus routine superficial removal using Chi-squared, Fischer\'s exact, and Mann-Whitney U test. A multivariate logistic regression identified variables associated with increased odds of requiring a deep implant removal.
RESULTS: The deep and superficial removal groups included 162 and 585 patients, respectively. Deep removal was associated with younger age at removal (median 25.0 vs 26.0 years, p = 0.005), lower body mass index (BMI) at insertion (median 23.2 kg/m2 vs 26.6 kg/m2, p = 0.024), BMI≥ 40 kg/m2 at removal (15.2% vs 7.0%, p = 0.007), weight gain during implant use (median 6.6 vs 1.8 kg, p ≤ 0.001), longer duration of use (median 36.0 vs 27.5 months, p < 0.001), implant exchange (37.3% vs 17.4%, p < 0.001), and insertion by non-physician (43.3% vs 19.3%, p < 0.001) or non-obstetrican and gynecologist (31.4% vs 11.8%, p < 0.001). Lower BMI at insertion (aOR 0.92, [95% CI 0.87-0.98]), weight gain during use (aOR 1.06 [95% CI 1.02-1.10]), and longer duration of use (aOR 1.05 [95% CI 1.02-1.07]) remained significantly associated with deep removal in regression analysis.
CONCLUSIONS: We identified lower BMI at insertion, weight gain during use, and longer duration of use as independent factors associated with increased likelihood of needing a deep contraceptive implant removal.
CONCLUSIONS: Clinicians should utilize proper technique when inserting contraceptive implants, especially in patients at risk for deep insertion, and ensure immediate referral to Centers of Experience for patients with non-palpable implants.

Randomized studies showed that robotic surgery was short-term useful and safe for cancer patients. We investigated whether robots improve deep resection margins or superficial resection margins for radial resection margins in terms of short-term results. From an institutional database, we selected all superficial groups (≤ 3 mm) and deeper groups (≥ 4 mm) with rectal cancer treated with resection for a year. We evaluated the short-term post-operative 90-day outcomes on a radial resection size-based margin differentiation, including the first bowel movement, length of hospital stay, sepsis, and harvested lymph node. The main results were grades III-IV on the Clavien-Dindo scale and complications. We found 120 patients who had oncologic resection of rectal cancer; 42 patients with a superficial radial resection margin of ≤ 3 mm, all the following outcomes improved: the harvested lymph node, proximal resection margin, TME, flatus time, liquid diet duration, anastomotic leakage, and sepsis. Among these advantages were a reduced risk of metastasis and an overall reduction in local recurrence.

UNASSIGNED: Low motivation and suboptimal cognitive skills are common among forensic psychiatric patients. By focusing on doing and experiencing, innovative technologies could offer an alternative to existing treatment for this patient group. One promising technology is DEEP, a VR biofeedback game that teaches diaphragmatic breathing, which has shown its potential in reducing stress in other populations. This exploratory study aimed at identifying if, how and for whom DEEP can be of added value in forensic mental healthcare.
UNASSIGNED: This study used a qualitative approach. Six focus groups with 24 healthcare providers and 13 semi-structured interviews with forensic psychiatric inpatients were conducted in two Dutch forensic mental healthcare organizations. All healthcare providers and patients experienced DEEP before participating. The data were coded inductively, using the method of constant comparison.
UNASSIGNED: The data revealed six themes with accompanying (sub)codes, including (1) the possible advantages and (2) disadvantages of DEEP, (3) patient characteristics that could make DEEP more or (4) less suitable and beneficial, (5) ways DEEP could be used in current treatment, and (6) conditions that need to be met to successfully implement DEEP in forensic mental healthcare. The results showed that DEEP can offer novel ways to support forensic psychiatric patients in coping with negative emotions by practicing diaphragmatic breathing. Its appealing design might be suitable to motivate a broad range of forensic psychiatric patient groups. However, DEEP cannot be personalized, which might decrease engagement and uptake of DEEP long-term. Regarding its place in current care, DEEP could be structurally integrated in existing treatment programs or used ad hoc when the need arises. Finally, this study showed that both healthcare providers and patients would need practical support and information to use DEEP.
UNASSIGNED: With its experience-based and gamified design, DEEP could be useful for forensic mental healthcare. It is recommended that patients and healthcare providers are included in the evaluation and implementation from the start. Besides, a multilevel approach should be used for formulating implementation strategies. If implemented well, DEEP can offer new ways to provide forensic psychiatric patients with coping strategies to better control their anger.

Chemical peeling is a procedure used for cosmetic improvement of the skin or treatment of some medical skin disorders, by the application of chemical exfoliant. In spite of a long history of clinical use of chemical peels, understanding of the science behind the procedure is still evolving. In this article, we review new concepts, understandings, and publications in the field of chemical peels.

Endoscopic procedures are routinely applied to cancer screening programs and surveillance. The preferred technique is usually deep sedation with propofol being a convenient agent allowing for a quicker patient recovery while maintaining a similar safety profile compared to traditional agents. However, adverse events, including respiratory depression and consequent undesirable cardiovascular side effects, may occur. The goal of this work is to evaluate the patient safety impact of adding capnography during endoscopic procedures under deep propofol sedation. Data were retrospectively collected from patients undergoing deep, procedural sedation for gastrointestinal (GI) endoscopy in October 2019 to January 2021 in a single Turkish university hospital. Included in the analysis were all adult patients classified by the American Society of Anesthesiologists (ASA) as I-IV, who were scheduled for GI endoscopy utilizing propofol alone or in combination. Data on 1840 patients were collected, of whom 1610 (730 pre- and 880 post-capnography implemention) met inclusion criteria. The primary outcome was a change in the composite incidence of mild oxygen desaturation (SpO2 75-90% for <60 s), severe oxygen desaturation (SpO2 < 75% anytime or <90% for >60 s), bradycardia (<60 ppm), and tachycardia (>25% from baseline). Without capnography, on average, 7.5 events of the primary endpoint were observed per 100 procedures and 2.9 with additional capnography monitoring (p < 0.001). A significant reduction was observed for mild oxygen desaturation, with a resulting odds ratio of 0.25 (95% CI 0.14 to 0.46). ASA I patients had the highest difference in combined incidence of any oxygen desaturation of 5.85% in the pre-capnography group and 0.64% in the post-capnography group. Although procedural sedation using propofol is not associated with severe adverse events, the incidence of composite adverse events could be reduced with the addition of capnography monitoring.

BACKGROUND: Atrial myopathy may underlie the progression of atrial fibrillation (AF) from a treatable disease to an irreversible condition with poor ablation outcomes. Electrophysiological methods to unmask areas prone to re-entry initiation could be key to defining latent atrial myopathy.
METHODS: Consecutive patients referred for AF ablation were prospectively included at four institutions. Decrement evoked potential mapping (DEEP) was performed in eight left atrial sites and five right atrial sites, from two different pacing locations (endocardially from the left atrial appendage, epicardially from the proximal coronary sinus). The electrograms (EGMs) during S1 600 ms drive and after an extra stimulus (S2 at +30 ms above atrial refractoriness) were studied at each location and assessed for decremental properties. Follow-up was 12 months.
RESULTS: Seventy-four patients were included and 85% had persistent AF. A total of 17,614 EGMs were individually analysed and measured. Nine percent of the EGMs showed DEEP properties (local delay of >10 ms after S2) with a mean decrement of 33±26 ms. DEEPs were more frequent in the left atrium than the right atrium (9.4% vs 8.0%; p<0.001) and more prevalent in persistent AF patients than paroxysmal AF patients (9.8% vs 4.6% p=0.001). Atrial DEEPs were more frequently unmasked in normal bipolar voltage areas and by epicardial pacing than endocardial pacing (9.6% vs 8.4%, respectively; p=0.004). Within the left atrium, the roof had the highest prevalence of DEEP EGMs.
CONCLUSIONS: DEEP mapping of both atria is useful for highlighting areas with a tendency for unidirectional block and re-entry initiation. Those areas are more easily unmasked by epicardial pacing from the coronary sinus and more prevalent in persistent AF patients than in paroxysmal AF patients.

Progressive organ-level disorders in the human body are often correlated with diseases in other body parts. For instance, liver diseases can be linked with heart issues, while cancers can be linked with brain diseases (or psychological conditions). Defining such correlations is a complex task, and existing deep learning models that perform this task either showcase lower accuracy or are non-comprehensive when applied to real-time scenarios. To overcome these issues, this text proposes design of an augmented bioinspired deep learning-based multidomain body parameter analysis via heterogeneous correlative body organ analysis. The proposed model initially collects temporal and spatial data scans for different body parts and uses a multidomain feature extraction engine to convert these scans into vector sets. These vectors are processed by a Bacterial Foraging Optimizer (BFO), which assists in identification of highly variant feature sets, which are individually classified into different disease categories. A fusion of Inception Net, XCeption Net, and GoogLeNet Models is used to perform these classifications. The classified categories are linked with other disease types via temporal analysis of blood reports. The temporal analysis engine uses Modified Analytical Hierarchical Processing (MAHP) Model for calculating inter-organ disease dependency probabilities. Based on these probabilities, the model is able to generate a patient-level correlation map, which can be used by clinical experts to suggest remedial treatments, due to which the model was able to identify correlations between brain disorders and kidneys, heart diseases and lungs, heart diseases and liver, brain diseases and different types of cancers with high efficiency when evaluated under clinical scenarios. When validated on MITBIH, DEAP, CT Kidney, RIDER, and PLCO data samples, it was observed that the proposed model was capable of improving accuracy of correlation by 8.5%, while improving precision and recall by 3.2% when compared with existing correlation models under similar clinical scenarios.

The optimal dosing of aspirin (ASA) monotherapy for prophylaxis after total joint arthroplasty is debatable. The objective of this study was to compare two ASA regimens with regards to symptomatic deep venous thrombosis (DVT), pulmonary embolism (PE), bleeding, and infection 90 days after primary total hip arthroplasty (THA) and total knee arthroplasty (TKA).
We retrospectively identified 625 primary THA and TKA surgeries in 483 patients who received ASA for 4 weeks post-op. 301 patients received 325 mg once daily (QD) and 324 patients received 81 mg twice daily (BID). Patients were excluded if they were minors, had a prior venous thromboembolism (VTE), had ASA allergy, or received other VTE prophylaxis drugs.
There was a significant difference in rate of bleeding and suture reactions between the two groups. Bleeding was 7.6% for 325 mg QD and 2.5% for 81 mg BID (p = .0029 Χ2, p = .004 on multivariate logistic regression analysis). Suture reactions were 3.3% for 325 mg QD and 1.2% for 81 mg BID (p = .010 Χ2, p = .027 on multivariate logistic regression analysis). Rates of VTE, symptomatic DVT, and PE were not significantly different. The incidence of VTE was 2.7% for 325 mg QD and 1.5% for 81 mg BID (p = .4056). Symptomatic DVT rates were 1.6% for 325 mg QD and 0.9% for 81 mg BID (p = .4139). Deep infection was 1.0% for 325 mg QD and 0.31% for 81 mg BID (p = .3564).
Low-dose ASA in patients with limited comorbidities undergoing primary THA and TKA is associated with significant lower rates of bleeding and suture reactions than high dose ASA. Low-dose ASA was not inferior to higher dose ASA for the prevention of VTE, wound complications, and infection 90 days postoperatively.