Key features of puberty onset and progression can help distinguish self-limited delayed puberty from congenital hypogonadotrophic hypogonadism.

Introduction: Delayed puberty (DP) is a frequent concern for adolescents. The most common underlying aetiology is self-limited DP (SLDP). However, this can be difficult to differentiate from the more severe condition congenital hypogonadotrophic hypogonadism (HH), especially on first presentation of an adolescent patient with DP. This study sought to elucidate phenotypic differences between the two diagnoses, in order to optimise patient management and pubertal development. Methods: This was a study of a UK DP cohort managed 2015-2023, identified through the NIHR clinical research network. Patients were followed longitudinally until adulthood, with a definite diagnosis made: SLDP if they had spontaneously completed puberty by age 18 years; HH if they had not commenced (complete, cHH), or had commenced but not completed puberty (partial, pHH), by this stage. Phenotypic data pertaining to auxology, Tanner staging, biochemistry, bone age and hormonal treatment at presentation and during puberty were retrospectively analysed. Results: 78 patients were included. 52 (66.7%) patients had SLDP and 26 (33.3%) patients had HH, comprising 17 (65.4%) pHH and 9 (34.6%) cHH patients. Probands were predominantly male (90.4%). Male SLDP patients presented with significantly lower height and weight standard deviation scores than HH patients (height p=0.004, weight p=0.021). 15.4% of SLDP compared to 38.5% of HH patients had classical associated features of HH (micropenis, cryptorchidism, anosmia, etc. p=0.023). 73.1% of patients with SLDP and 43.3% with HH had a family history of DP (p=0.007). Mean first recorded luteinizing hormone (LH) and inhibin B were lower in male patients with HH, particularly in cHH patients, but not discriminatory. There were no significant differences identified in blood concentrations of FSH, testosterone or AMH at presentation, or in bone age delay. Discussion: Key clinical markers of auxology, associated signs including micropenis, and serum inhibin B may help distinguish between SLDP and HH in patients presenting with pubertal delay, and can be incorporated into clinical assessment to improve diagnostic accuracy for adolescents. However, the distinction between HH, particularly partial HH, and SLDP remains problematic. Further research into an integrated framework or scoring system would be useful in aiding clinician decision-making and optimization of treatment. .

Splenic artery aneurysm in pregnancy: A systematic review.

OBJECTIVE: Splenic artery aneurysms (SAA) are associated with significant maternal and fetal mortality when ruptured in pregnancy. However, there is no consensus on the optimal obstetric management of both ruptured and asymptomatic SAA. We aimed to evaluate risk factors, presentation, investigation, and management of SAA in pregnancy and puerperium. METHODS: MEDLINE, EMBASE, and Scopus were screened from January 2000 to October 2020 using keywords related to pregnancy and SAA. Articles on ruptured and unruptured SAA in pregnancy until 6 weeks postpartum were considered. Data were extracted by two independent reviewers. Quantitative analysis and narrative synthesis were used. RESULTS: Seventy-five ruptured and nine unruptured SAA cases were included. Mean age was 31.1 ± 5.2 years, of which 47 (64.4%) were multiparous and 46 (54.8%) presented in their third trimester, largely with epigastric and left-sided abdominal pain. The double-rupture phenomenon of delayed blood loss and symptoms was noted in 11 (14.7%); 60 (70.7%) underwent preoperative imaging. Mean SAA size was 23.0 ± 13.6 mm. Ruptured SAA were primarily managed by laparotomy (61, 81.3%) typically with splenectomy,  and unruptured SAA by embolization or laparotomy. There was no mortality in unruptured SAA, but significant mortality on rupture (19, 25.7% maternal; 36, 50.0% fetal). CONCLUSION: Given their predisposition and high mortality in pregnancy, it is crucial that SAAs are promptly diagnosed and managed, requiring increased obstetrician awareness.

Digital health: a neglected part of health curricula?

With growing government investment and a thriving consumer market, digital technologies are rapidly transforming our means of healthcare delivery. These innovations offer increased diagnostic accuracy, greater accessibility and reduced costs compared with conventional equivalents. Despite these benefits, implementing digital health poses challenges. Recent surveys of healthcare professionals (HCPs) have revealed marked inequities in digital literacy across the healthcare service, hampering the use of these new technologies in clinical practice. Furthermore, a lack of appropriate training in the associated ethical considerations risks HCPs running into difficulty when it comes to patient rights. In light of this, and with a clear need for dedicated digital health education, we argue that our focus should turn to the foundation setting of any healthcare profession: the undergraduate curriculum.

The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare.

INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including healthcare. This article reviews AI's present applications in healthcare, including its benefits, limitations and future scope. SOURCES OF DATA: A review of the English literature was conducted with search terms 'AI' or 'ML' or 'deep learning' and 'healthcare' or 'medicine' using PubMED and Google Scholar from 2000-2021. AREAS OF AGREEMENT: AI could transform physician workflow and patient care through its applications, from assisting physicians and replacing administrative tasks to augmenting medical knowledge. AREAS OF CONTROVERSY: From challenges training ML systems to unclear accountability, AI's implementation is difficult and incremental at best. Physicians also lack understanding of what AI implementation could represent. GROWING POINTS: AI can ultimately prove beneficial in healthcare, but requires meticulous governance similar to the governance of physician conduct. AREAS TIMELY FOR DEVELOPING RESEARCH: Regulatory guidelines are needed on how to safely implement and assess AI technology, alongside further research into the specific capabilities and limitations of its medical use.