To assess the prevalence and factors associated with cyberbullying and cyber-victimisation among high school adolescents of Pokhara Metropolitan City, Nepal.

A cross-sectional study.

Pokhara Metropolitan City, Nepal.

We used convenient sampling to enrol 450 adolescents aged 16–19 years from four distinct higher secondary schools in Pokhara Metropolitan City.

We administered the Cyberbullying and an Online Aggression Survey to determine the prevalence of cyberbullying and cyber-victimisation. Univariate and multivariate logistic regression analyses were performed to estimate the ORs and 95% CIs. Data were analysed using STATA V.13.

The 30-day prevalence of cyberbullying and cyber-victimisation was 14.4% and 19.8%, and the over-the-lifetime prevalence was 24.2% and 42.2%, respectively. Posting mean or hurtful comments online was the most common form of both cyberbullying and cyber-victimisation. Compared with females, males were more likely to be involved in cyberbullying (adjusted OR (AOR)=13.52; 95% CI: 6.04 to 30.25; p value

The study recommends the implementation of cyber-safety educational programmes, and counselling services including the rational use of internet and periodic screening for cyberbullying in educational institutions. The enforcement of strong anti-bullying policies and regulations could be helpful to combat the health-related consequences of cyberbullying.

A non-contrast CT head scan (NCCTH) is the most common cross-sectional imaging investigation requested in the emergency department. Advances in computer vision have led to development of several artificial intelligence (AI) tools to detect abnormalities on NCCTH. These tools are intended to provide clinical decision support for clinicians, rather than stand-alone diagnostic devices. However, validation studies mostly compare AI performance against radiologists, and there is relative paucity of evidence on the impact of AI assistance on other healthcare staff who review NCCTH in their daily clinical practice.

A retrospective data set of 150 NCCTH will be compiled, to include 60 control cases and 90 cases with intracranial haemorrhage, hypodensities suggestive of infarct, midline shift, mass effect or skull fracture. The intracranial haemorrhage cases will be subclassified into extradural, subdural, subarachnoid, intraparenchymal and intraventricular. 30 readers will be recruited across four National Health Service (NHS) trusts including 10 general radiologists, 15 emergency medicine clinicians and 5 CT radiographers of varying experience. Readers will interpret each scan first without, then with, the assistance of the qER EU 2.0 AI tool, with an intervening 2-week washout period. Using a panel of neuroradiologists as ground truth, the stand-alone performance of qER will be assessed, and its impact on the readers’ performance will be analysed as change in accuracy (area under the curve), median review time per scan and self-reported diagnostic confidence. Subgroup analyses will be performed by reader professional group, reader seniority, pathological finding, and neuroradiologist-rated difficulty.

The study has been approved by the UK Healthcare Research Authority (IRAS 310995, approved 13 December 2022). The use of anonymised retrospective NCCTH has been authorised by Oxford University Hospitals. The results will be presented at relevant conferences and published in a peer-reviewed journal.

NCT06018545.

To summarise evidence on the effectiveness of Platelet-Rich Plasma (PRP) gel and Leucocyte and Platelet Rich Fibrin (L-PRF) gel as agents promoting ulcer healing compared with the standard wound dressing techniques alone.

Systematic review.

Individual patient randomised controlled trials on skin ulcers of all types excluding traumatic lesions.

Intervention group: treatment with topical application of L-PRF gel or PRP gel to the wound surface.

Control group: treatment with standard skin ulcer care using normal saline, normgel or hydrogel dressings.

Medline (Ovid), Excerpta Medica Database (EMBASE), Scopus, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Web of Science and manual search of studies from previous systematic reviews and meta-analyses. The papers published from 1946 to 2022 with no restriction on geography and language were included. The last date of the search was performed on 29 August 2022.

Independent reviewers identified eligible studies, extracted data, assessed risk of bias using V.2 of the Cochrane risk-of-bias tool for randomised trials tool and assessed certainty of evidence by using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach.

Time to complete healing, proportion healed at a given time and rate of healing.

Seven studies met the inclusion criteria, five using PRP gel and two using L-PRF gel. One study showed a better proportion of complete healing, three reported reduced meantime to complete healing and five showed improved rate of healing per unit of time in the intervention group. The risk of bias was high across all studies with one exception and the GRADE showed very low certainty of evidence.

The findings show potential for better outcomes in the intervention; however, the evidence remains inconclusive highlighting a large research gap in ulcer treatment and warrant better-designed clinical trials.

CRD42022352418.

Clinic-based or community-based interventions can improve adherence to guideline-directed medication therapies (GDMTs) among patients with heart failure (HF). However, opportunities for such interventions are frequently missed, as providers may be unable to recognise risk patterns for medication non-adherence. Machine learning algorithms can help in identifying patients with high likelihood of non-adherence. While a number of multilevel factors influence adherence, prior models predicting non-adherence have been limited by data availability. We have established an electronic health record (EHR)-based cohort with comprehensive data elements from multiple sources to improve on existing models. We linked EHR data with pharmacy refill data for real-time incorporation of prescription fills and with social determinants data to incorporate neighbourhood factors.

Patients seen at a large health system in New York City (NYC), who were >18 years old with diagnosis of HF or reduced ejection fraction (

Among 39 963 patients in the cohort, the average age was 73±14 years old, 44% were female and 48% were current/former smokers. The common comorbid conditions were hypertension (77%), cardiac arrhythmias (56%), obesity (33%) and valvular disease (33%). During the study period, 33 606 (84%) patients had an active prescription of beta blocker, 32 626 (82%) had ACEi/ARB/ARNI, 11 611 (29%) MRA and 7472 (19%) SGLT2i. Ninety-nine per cent were from urban metropolitan areas.

We will use the established cohort to develop a machine learning model to predict medication adherence, and to support ancillary studies assessing associates of adherence. For external validation, we will include data from an additional hospital system in NYC.