A Severe Case of Diabetic Lumbosacral Radiculoplexus Neuropathy: A Diagnosis of Exclusion.

Diabetic lumbosacral radiculoplexus neuropathy (DLSRPN), also known as diabetic amyotrophy, is a rare disease of exclusion that is difficult to diagnose due to its non-specific clinical presentation of neuropathy, autonomic symptoms, and potential weight loss. Due to this, many differential diagnoses are raised before making a diagnosis of such an uncommon disease. However, once the diagnosis is made, the management of this disease can vary. Here, we would like to discuss the etiology, pathophysiology, diagnosis, and management of this disease, as well as present a rare case of diabetic lumbosacral radiculoplexus neuropathy in a 50-year-old male.

Multiplex Gastrointestinal Panel Testing in Hospitalized Patients With Acute Diarrhea in Thailand.

Background: Multiplex gastrointestinal (GI) panel testing is widely used for outpatient diagnosis of diarrhea. However, the clinical practicality of multiplex testing in hospitalized diarrheal subjects has not yet been thoroughly elucidated. Methods: We enrolled hospitalized subjects with acute diarrhea. The subjects' stool samples were collected in triplicate; 1 sample was tested using traditional diagnoses, and the other 2 were tested using Allplex (AP) and FilmArray (FA) GI panel testing. Clinical data were reviewed and analyzed. Results: Of the 199 subjects, 92 (46.5%) were male, and the mean age was 66.3 years. The median (interquartile range) onset of diarrhea was 6 (2--14) days after hospitalization. One hundred fifty-one patients (75.9%) had sepsis, and 166 (83.4%) had received prior or were receiving current antimicrobial therapy. Positive stool cultures were obtained from 4/89 (4.5%), and Clostridioides difficile toxin gene tests were positive in 14/188 (7.4%) patients. AP and FA multiplex tests were positive for GI pathogens in 49/199 (24.6%) and 40/199 (20.1%), respectively. The target most frequently detected by AP was Aeromonas spp. Both assays commonly detected enteropathogenic E. coli (EPEC), C. difficile toxin gene, and Salmonella spp.; neither assay detected pathogens in 75.4% and 79.9%. Fever (odds ratio [OR], 2.05; 95% CI, 1.08-3.88; P = .028), watery diarrhea (OR, 2.69; 95% CI, 1.25-5.80; P = .011), and antimicrobial therapy (OR, 2.60; 95% CI, 1.18-5.71; P = .018) were independent factors associated with the negative multiplex test result. Conclusions: Multiplex GI panel testing effectively detects enteric pathogens associated with diarrhea in hospitalized subjects. The etiology remains undiagnosed in >75% of cases. Factors contributing to negative test results should be considered before implementing the tests.

Clinical features, MRI, molecular alternations, and prognosis of astrocytoma based on WHO 2021 classification of central nervous system tumors: A single-center retrospective study.

BACKGROUND: The diagnosis of glioma has advanced since the release of the WHO 2021 classification with more molecular alterations involved in the integrated diagnostic pathways. Our study aimed to present our experience with the clinical features and management of astrocytoma, IDH mutant based on the latest WHO classification. METHODS: Patients diagnosed with astrocytoma, IDH-mutant based on the WHO 5th edition classification of CNS tumors at our center from January 2009 to January 2022 were included. Patients were divided into WHO 2-3 grade group and WHO 4 grade group. Integrate diagnoses were retrospectively confirmed according to WHO 2016 and 2021 classification. Clinical and MRI characteristics were reviewed, and survival analysis was performed. RESULTS: A total of 60 patients were enrolled. 21.67% (13/60) of all patients changed tumor grade from WHO 4th edition classification to WHO 5th edition. Of these, 21.43% (6/28) of grade II astrocytoma and 58.33% (7/12) of grade III astrocytoma according to WHO 4th edition classification changed to grade 4 according to WHO 5th edition classification. Sex (p = 0.042), recurrent glioma (p = 0.006), and Ki-67 index (p < 0.001) of pathological examination were statistically different in the WHO grade 2-3 group (n = 27) and WHO grade 4 group (n = 33). CDK6 (p = 0.004), FGFR2 (p = 0.003), and MYC (p = 0.004) alterations showed an enrichment in the WHO grade 4 group. Patients with higher grade showed shorter mOS (mOS = 75.9 m, 53.6 m, 26.4 m for grade 2, 3, and 4, respectively, p = 0.01). CONCLUSIONS: Patients diagnosed as WHO grade 4 according to the 5th edition WHO classification based on molecular alterations are more likely to have poorer prognosis. Therefore, treatment should be tailored to their individual needs. Further research is needed for the management of IDH-mutant astrocytoma is needed in the future.

Challenges in the diagnosis and management of tumor-induced osteomalacia: A case report.

The present case report is aimed to highlight the difficulty and the reason for the delayed diagnosis of phosphaturic mesenchymal tumors, emphasizing the need of standardized protocols for diagnosis, surgery and follow-up in high-volume hospitals. The clinical signs and symptoms, diagnostic and therapeutic procedures, immunohistological features were analyzed. Delayed diagnosis of phosphaturic mesenchymal tumor was primarily due to non-specific clinical symptoms such as fatigue, muscular and bone pain, and multiple fractures. This cryptic clinical picture made the diagnosis tricky that led to treatment of patient for non-specific pain and stress fractures before to consider the tumor-induced osteomalacia syndrome. Some well-documented studies were found in the literature in which the history of trauma is a critical trigger of glomus tumors. Extra-subungual tumors most frequently occur in the knee and ankle regions, particularly among young adults, and the diagnosis is typically made approximately 7.2 years after initial symptom onset. The difficult tumor localization represented an additional obstacle to the prompt treatment, leading to delayed curative surgery.

A Descriptive Diagnosis or a Causal Explanation? Accuracy of Depictions of Depression on Authoritative Health Organization Websites.

INTRODUCTION: Psychiatric diagnoses are descriptive in nature, but the lay public commonly misconceives them as causal explanations. It is not known whether this logical error, a form of circular reasoning, can sometimes be mistakenly reinforced by health authorities themselves. In this study, we investigated the prevalence of misleading causal descriptions of depression in the information provided by authoritative mental health organizations on widely accessed internet sites. METHODS: We searched for popular websites managed by leading mental health organizations and conducted a content analysis to evaluate whether they presented depression accurately as a description of symptoms, or inaccurately as a causal explanation. RESULTS: Most websites used language that inaccurately described depression as a causal explanation to depressive symptoms. CONCLUSION: Leading professional medical and psychiatric organizations commonly confound depression, a descriptive diagnostic label, with a causal explanation on their most prominently accessed informational websites. We argue that the scientifically inaccurate causal language in depictions of psychiatric diagnoses is potentially harmful because it leads the public to misunderstand the nature of mental health problems. Mental health authorities providing psychoeducation should clearly state that psychiatric diagnoses are purely descriptive to avoid misleading the public.

The minimal important change is not a universal fixed value across diagnoses when using the FAOS and FAAM in patients undergoing elective foot and ankle surgery.

PURPOSE: This study aimed to calculate region and diagnosis-specific minimal important changes (MICs) of the Foot and Ankle Outcome Score (FAOS) and the Foot and Ankle Ability Measure (FAAM) in patients requiring foot and ankle surgery and to assess their variability across different foot and ankle diagnoses. METHODS: The study used routinely collected data from patients undergoing elective foot and ankle surgery. Patients had been invited to complete the FAOS and FAAM preoperatively and at 3-6 months after surgery, along with two anchor questions encompassing change in pain and daily function. Patients were categorised according to region of pathology and subsequent diagnoses. MICs were calculated using predictive modelling (MICPRED) and receiver operating characteristic curve (MICROC) method and evaluated according to strict credibility criteria. RESULTS: Substantial variability of the MICs between forefoot and ankle/hindfoot region was observed, as well as among specific foot and ankle diagnoses, with MICPRED and MICROC values ranging from 7.8 to 25.5 points and 9.4 to 27.8, respectively. Despite differences between MICROC and MICPRED estimates, both calculation methods exhibited largely consistent patterns of variation across subgroups, with forefoot conditions systematically showing smaller MICs than ankle/hindfoot conditions. Most MICs demonstrated high credibility; however, the majority of the MICs for the FAOS symptoms subscale and forefoot conditions exhibited insufficient or low credibility. CONCLUSION: The MICs of the FAOS and FAAM vary across foot and ankle diagnoses in patients undergoing elective foot and ankle surgery and should not be used as a universal fixed value, but recognised as contextual parameters. This can help clinicians and researchers in more accurate interpretation of the FAOS and FAAM change scores. LEVEL OF EVIDENCE: Level IV.

Feasibility of Multimodal Artificial Intelligence Using GPT-4 Vision for the Classification of Middle Ear Disease: Qualitative Study and Validation.

BACKGROUND: The integration of artificial intelligence (AI), particularly deep learning models, has transformed the landscape of medical technology, especially in the field of diagnosis using imaging and physiological data. In otolaryngology, AI has shown promise in image classification for middle ear diseases. However, existing models often lack patient-specific data and clinical context, limiting their universal applicability. The emergence of GPT-4 Vision (GPT-4V) has enabled a multimodal diagnostic approach, integrating language processing with image analysis. OBJECTIVE: In this study, we investigated the effectiveness of GPT-4V in diagnosing middle ear diseases by integrating patient-specific data with otoscopic images of the tympanic membrane. METHODS: The design of this study was divided into two phases: (1) establishing a model with appropriate prompts and (2) validating the ability of the optimal prompt model to classify images. In total, 305 otoscopic images of 4 middle ear diseases (acute otitis media, middle ear cholesteatoma, chronic otitis media, and otitis media with effusion) were obtained from patients who visited Shinshu University or Jichi Medical University between April 2010 and December 2023. The optimized GPT-4V settings were established using prompts and patients' data, and the model created with the optimal prompt was used to verify the diagnostic accuracy of GPT-4V on 190 images. To compare the diagnostic accuracy of GPT-4V with that of physicians, 30 clinicians completed a web-based questionnaire consisting of 190 images. RESULTS: The multimodal AI approach achieved an accuracy of 82.1%, which is superior to that of certified pediatricians at 70.6%, but trailing behind that of otolaryngologists at more than 95%. The model's disease-specific accuracy rates were 89.2% for acute otitis media, 76.5% for chronic otitis media, 79.3% for middle ear cholesteatoma, and 85.7% for otitis media with effusion, which highlights the need for disease-specific optimization. Comparisons with physicians revealed promising results, suggesting the potential of GPT-4V to augment clinical decision-making. CONCLUSIONS: Despite its advantages, challenges such as data privacy and ethical considerations must be addressed. Overall, this study underscores the potential of multimodal AI for enhancing diagnostic accuracy and improving patient care in otolaryngology. Further research is warranted to optimize and validate this approach in diverse clinical settings.

Dermoscopy Differential Diagnosis Explorer (D3X) Ontology to Aggregate and Link Dermoscopic Patterns to Differential Diagnoses: Development and Usability Study.

BACKGROUND: Dermoscopy is a growing field that uses microscopy to allow dermatologists and primary care physicians to identify skin lesions. For a given skin lesion, a wide variety of differential diagnoses exist, which may be challenging for inexperienced users to name and understand. OBJECTIVE: In this study, we describe the creation of the dermoscopy differential diagnosis explorer (D3X), an ontology linking dermoscopic patterns to differential diagnoses. METHODS: Existing ontologies that were incorporated into D3X include the elements of visuals ontology and dermoscopy elements of visuals ontology, which connect visual features to dermoscopic patterns. A list of differential diagnoses for each pattern was generated from the literature and in consultation with domain experts. Open-source images were incorporated from DermNet, Dermoscopedia, and open-access research papers. RESULTS: D3X was encoded in the OWL 2 web ontology language and includes 3041 logical axioms, 1519 classes, 103 object properties, and 20 data properties. We compared D3X with publicly available ontologies in the dermatology domain using a semiotic theory-driven metric to measure the innate qualities of D3X with others. The results indicate that D3X is adequately comparable with other ontologies of the dermatology domain. CONCLUSIONS: The D3X ontology is a resource that can link and integrate dermoscopic differential diagnoses and supplementary information with existing ontology-based resources. Future directions include developing a web application based on D3X for dermoscopy education and clinical practice.

A case report of neuralgic amyotrophy.

Neuralgic muscular atrophy is not uncommon in clinical practice. Due to the different branches of brachial plexus involved in the lesion, the clinical symptoms are different, and there is a lack of clear imaging diagnostic criteria, so the diagnosis of this disease brings great challenges to clinicians. We have certain experience in the diagnosis and treatment of this disease, and hereby select a representative case of neuralgic muscular atrophy to share its diagnosis and treatment process, focusing on analyzing the characteristic symptoms of this disease, valuable imaging data and targeted treatment, so as to enable clinicians to better understand this disease.

A Comparison of Diagnostic and Immunohistochemical Workup and Literature Review Capabilities of Online Artificial Intelligence Assistance Models in Pathology.

Artificial intelligence (AI) is a suite of technologies that enables computers to learn and interpret information like human cognition. It has found applications across various fields, including healthcare, agriculture, astronomy, navigation, and robotics. Within healthcare, AI has the potential to enhance diagnostic accuracy, facilitate drug research, and automate patient experiences. This comparative study focuses on the proficiency of AI in generating accurate differential diagnoses in the field of pathology. Six medical vignettes were crafted, and each scenario was then input into three different AI platforms. The pathologist reviewed and determined the most accurate AI model.

Predictive Factors for Biopsy-Negative Giant Cell Arteritis and Alternative Diagnoses in a Neuro-Ophthalmology Context.

Giant cell arteritis is a challenging diagnosis for patients given the high prevalence of negative temporal artery biopsies (TAB). Despite the lack of histopathological evidence of giant cell arteritis in the TAB, patients can still have TAB-negative giant cell arteritis. The purpose of this paper is to analyse the predictors for TAB-negative giant cell arteritis and the alternative diagnosis of biopsy-negative patients without a giant cell arteritis diagnosis. A retrospective electronic database review of all TABs performed at the Royal Victorian Eye and Ear Hospital from February 2015 to May 2020. Logistic regression analysis was performed to determine predictive factors for a diagnosis of TAB-negative giant cell arteritis. In all cases, a clinical diagnosis of TAB-negative giant cell arteritis was determined by a neuro-ophthalmologist. Alternative diagnoses for negative TABs were identified and explored. A total of 368 TABs were analysed with 287 (78%) negative for histopathological evidence of GCA. Twenty-seven (9.4%) patients were diagnosed and treated as TAB-negative giant cell arteritis. The clinical predictors of a TAB-negative giant cell arteritis diagnosis were the presence of jaw claudication (OR 2.77, 95% CI 1.10-6.98) and CRP (OR 1.02, 95% CI 1.00-1.03). Alternative diagnoses included non-specific headache, non-arteritic anterior ischaemic optic neuropathy, retinal vessel occlusions, and ocular nerve palsies. Predictive factors for a diagnosis of TAB-negative giant cell arteritis were jaw claudication and an elevated CRP. Several alternative diagnoses can be considered for patients with a negative TAB in a neuro-ophthalmology context.

Evaluating ChatGPT-4's Accuracy in Identifying Final Diagnoses Within Differential Diagnoses Compared With Those of Physicians: Experimental Study for Diagnostic Cases.

BACKGROUND: The potential of artificial intelligence (AI) chatbots, particularly ChatGPT with GPT-4 (OpenAI), in assisting with medical diagnosis is an emerging research area. However, it is not yet clear how well AI chatbots can evaluate whether the final diagnosis is included in differential diagnosis lists. OBJECTIVE: This study aims to assess the capability of GPT-4 in identifying the final diagnosis from differential-diagnosis lists and to compare its performance with that of physicians for case report series. METHODS: We used a database of differential-diagnosis lists from case reports in the American Journal of Case Reports, corresponding to final diagnoses. These lists were generated by 3 AI systems: GPT-4, Google Bard (currently Google Gemini), and Large Language Models by Meta AI 2 (LLaMA2). The primary outcome was focused on whether GPT-4's evaluations identified the final diagnosis within these lists. None of these AIs received additional medical training or reinforcement. For comparison, 2 independent physicians also evaluated the lists, with any inconsistencies resolved by another physician. RESULTS: The 3 AIs generated a total of 1176 differential diagnosis lists from 392 case descriptions. GPT-4's evaluations concurred with those of the physicians in 966 out of 1176 lists (82.1%). The Cohen κ coefficient was 0.63 (95% CI 0.56-0.69), indicating a fair to good agreement between GPT-4 and the physicians' evaluations. CONCLUSIONS: GPT-4 demonstrated a fair to good agreement in identifying the final diagnosis from differential-diagnosis lists, comparable to physicians for case report series. Its ability to compare differential diagnosis lists with final diagnoses suggests its potential to aid clinical decision-making support through diagnostic feedback. While GPT-4 showed a fair to good agreement for evaluation, its application in real-world scenarios and further validation in diverse clinical environments are essential to fully understand its utility in the diagnostic process.

Motives and modifying factors for giving or rejecting psychiatric diagnoses in general medicine and psychiatry - a qualitative interview study.

BACKGROUND: There is a discussion among general practitioners and psychiatrists regarding over-diagnosing versus under-reporting of psychiatric diagnoses. A deeper understanding of this topic is relevant for providing reasonable health care and for planning future studies. A crucial factor to understanding this discussion is the difference in the prevalence of a disease in each sector. One way to attain knowledge about such prevalences is the analysis of routine care data of the sector in question. However, diagnosis-related data might be modified by several additional influencing factors. AIMS: This study aims to explore what kind of motives and modifying factors play a role for or against giving psychiatric diagnoses in psychiatric and general medical settings. METHODS: Twenty-six semi-structured interviews were conducted with German physicians in the fields of general medicine and psychiatry. Interviews were analysed using content analysis. RESULTS: The analysis revealed three major motivational categories for finding a diagnosis: (1) "objective matters" such as "categorisation for research"; (2) "functional and performance-related factors" such as "requirement for medication", "billing aspects" that go with certain diagnoses or "access to adequate care" and (3) "Individual factors" such as the "personality of a physician". Similarly, factors emerged that lead to not making psychiatric diagnoses like "fear of stigmatization among patients" or "detrimental insurance status with psychiatric diagnosis". Additionally participants mentioned other reasons for "not diagnosing a psychiatric diagnosis", such as "coding of other clinical pictures". CONCLUSION: The diagnostic process is a complex phenomenon that goes far beyond the identification of medical findings. This insight should be considered when processing and interpreting secondary data for designing health care systems or designing a study.

Can Artificial Intelligence Mitigate Missed Diagnoses by Generating Differential Diagnoses for Neurosurgeons?

BACKGROUND/OBJECTIVE: Neurosurgery emphasizes the criticality of accurate differential diagnoses, with diagnostic delays posing significant health and economic challenges. As large language models (LLMs) emerge as transformative tools in healthcare, this study seeks to elucidate their role in assisting neurosurgeons with the differential diagnosis process, especially during preliminary consultations. METHODS: This study employed 3 chat-based LLMs, ChatGPT (versions 3.5 and 4.0), Perplexity AI, and Bard AI, to evaluate their diagnostic accuracy. Each LLM was prompted using clinical vignettes, and their responses were recorded to generate differential diagnoses for 20 common and uncommon neurosurgical disorders. Disease-specific prompts were crafted using Dynamed, a clinical reference tool. The accuracy of the LLMs was determined based on their ability to identify the target disease within their top differential diagnoses correctly. RESULTS: For the initial differential, ChatGPT 3.5 achieved an accuracy of 52.63%, while ChatGPT 4.0 performed slightly better at 53.68%. Perplexity AI and Bard AI demonstrated 40.00% and 29.47% accuracy, respectively. As the number of considered differentials increased from 2 to 5, ChatGPT 3.5 reached its peak accuracy of 77.89% for the top 5 differentials. Bard AI and Perplexity AI had varied performances, with Bard AI improving in the top 5 differentials at 62.11%. On a disease-specific note, the LLMs excelled in diagnosing conditions like epilepsy and cervical spine stenosis but faced challenges with more complex diseases such as Moyamoya disease and amyotrophic lateral sclerosis. CONCLUSIONS: LLMs showcase the potential to enhance diagnostic accuracy and decrease the incidence of missed diagnoses in neurosurgery.

A Symptom-Checker for Adult Patients Visiting an Interdisciplinary Emergency Care Center and the Safety of Patient Self-Triage: Real-Life Prospective Evaluation.

BACKGROUND: Symptom-checkers have become important tools for self-triage, assisting patients to determine the urgency of medical care. To be safe and effective, these tools must be validated, particularly to avoid potentially hazardous undertriage without leading to inefficient overtriage. Only limited safety data from studies including small sample sizes have been available so far. OBJECTIVE: The objective of our study was to prospectively investigate the safety of patients' self-triage in a large patient sample. We used SMASS (Swiss Medical Assessment System; in4medicine, Inc) pathfinder, a symptom-checker based on a computerized transparent neural network. METHODS: We recruited 2543 patients into this single-center, prospective clinical trial conducted at the cantonal hospital of Baden, Switzerland. Patients with an Emergency Severity Index of 1-2 were treated by the team of the emergency department, while those with an index of 3-5 were seen at the walk-in clinic by general physicians. We compared the triage recommendation obtained by the patients' self-triage with the assessment of clinical urgency made by 3 successive interdisciplinary panels of physicians (panels A, B, and C). Using the Clopper-Pearson CI, we assumed that to confirm the symptom-checkers' safety, the upper confidence bound for the probability of a potentially hazardous undertriage should lie below 1%. A potentially hazardous undertriage was defined as a triage in which either all (consensus criterion) or the majority (majority criterion) of the experts of the last panel (panel C) rated the triage of the symptom-checker to be "rather likely" or "likely" life-threatening or harmful. RESULTS: Of the 2543 patients, 1227 (48.25%) were female and 1316 (51.75%) male. None of the patients reached the prespecified consensus criterion for a potentially hazardous undertriage. This resulted in an upper 95% confidence bound of 0.1184%. Further, 4 cases met the majority criterion. This resulted in an upper 95% confidence bound for the probability of a potentially hazardous undertriage of 0.3616%. The 2-sided 95% Clopper-Pearson CI for the probability of overtriage (n=450 cases,17.69%) was 16.23% to 19.24%, which is considerably lower than the figures reported in the literature. CONCLUSIONS: The symptom-checker proved to be a safe triage tool, avoiding potentially hazardous undertriage in a real-life clinical setting of emergency consultations at a walk-in clinic or emergency department without causing undesirable overtriage. Our data suggest the symptom-checker may be safely used in clinical routine. TRIAL REGISTRATION: ClinicalTrials.gov NCT04055298; https://clinicaltrials.gov/study/NCT04055298.

Prevalence of co-occurring diagnoses in people exposed to alcohol prenatally: Findings from a meta-analysis.

BACKGROUND: Individuals with prenatal alcohol exposure (PAE) commonly experience co-occurring diagnoses, which are often overlooked and misdiagnosed and have detrimental impacts on accessing appropriate services. The prevalence of these co-occurring diagnoses varies widely in the existing literature and has not been examined in PAE without an FASD diagnosis. METHOD: A search was conducted in five databases and the reference sections of three review papers, finding a total of 2180 studies. 57 studies were included in the final analysis with a cumulative sample size of 29,644. Bayesian modeling was used to determine aggregate prevalence rates of co-occurring disorders and analyze potential moderators. RESULTS: 82 % of people with PAE had a co-occurring diagnosis. All disorders had a higher prevalence in individuals with PAE than the general population with attention deficit hyperactivity disorder, learning disorder, and intellectual disability (ID) being the most prevalent. Age, diagnostic status, and sex moderated the prevalence of multiple disorders. LIMITATIONS: While prevalence of disorders is crucial information, it does not provide a direct representation of daily functioning and available supports. Results should be interpreted in collaboration with more individualized research to provide the most comprehensive representation of the experience of individuals with PAE. CONCLUSIONS: Co-occurring diagnoses are extremely prevalent in people with PAE, with older individuals, females, and those diagnosed with FASD being most at risk for having a co-occurring disorder. These findings provide a more rigorous examination of the challenges faced by individuals with PAE than has existed in the literature, providing clinicians with information to ensure early identification and effective treatment of concerns to prevent lifelong challenges.

Treatment Effects of Introducing the Neurosequential Model of Therapeutics in a Norwegian Residential Treatment Facility for Children Aged 7-13.

This study investigates the impact of the Neurosequential Model of Therapeutics (NMT) in child and adolescent psychiatric care, addressing a gap in current clinical methodologies that tend to focus on single problems rather than the interconnected nature of many real-life mental health issues. The study was conducted in a residential setting over an extended period, including children aged 7-13, to observe the effects of implementing NMT. The children presented with complex symptoms and multiple diagnoses. The methods incorporated the NMT approach, emphasizing individualized treatment plans based on each child's unique brain development, and aimed at addressing multiple, interconnected problems simultaneously. Results from multilevel model analyses of behavioral difficulties, measured using the Child Behavior Checklist (CBCL), revealed substantial improvements in treatment effectiveness post-NMT implementation. Despite the limitations, such as a non-randomized participant selection and limited sample size, the findings strongly suggest that NMT enhances care effectiveness in real-world clinical settings, particularly for children with complex mental health issues. The study concludes that relationally oriented milieu therapy, and specifically the NMT approach, holds great promise for advancing pediatric psychiatric care, advocating for its broader application and further research to refine and substantiate its efficacy.

Deaths Among Ambulance Patients Released from the Emergency Department Within the First 24 Hours With Nonspecific Diagnoses - Expected or Not?

BACKGROUND: Emergency patients are frequently assigned nonspecific diagnoses. Nonspecific diagnoses describe observations or symptoms and are found in chapters R and Z of the International Classification of Diseases, 10th edition (ICD-10). Patients with such diagnoses have relatively low mortality, but due to patient volume, the absolute number of deaths is substantial. However, information on cause of short-term mortality is limited. OBJECTIVES: To investigate whether death could be expected for ambulance patients brought to the emergency department (ED) after a 1-1-2 call, released with a nonspecific ICD-10 diagnosis within 24 h, and who subsequently died within 30 days. METHODS: Retrospective medical record review of adult 1-1-2 emergency ambulance patients brought to an ED in the North Denmark Region during 2017-2021. Patients were divided into three categories: unexpected death, expected death (terminal illness), and miscellaneous. Charlson Comorbidity Index (CCI) was assessed. RESULTS: We included 492 patients. Mortality was distributed as follows: Unexpected death 59.2% (n = 291), expected death (terminal illness) 25.8% (n = 127), and miscellaneous 15.0% (n = 74). Patients who died unexpectedly were old (median age of 82 years) and had CCI 1-2 (58.1%); 43.0% used at least five daily prescription drugs, and they were severely acutely ill upon arrival (24.7% with red triage, 60.1% died within 24 h). CONCLUSIONS: More than half of ambulance patients released within 24 h from the ED with nonspecific diagnoses, and who subsequently died within 30 days, died unexpectedly. One-fourth died from a pre-existing terminal illness. Patients dying unexpectedly were old, treated with polypharmacy, and often life-threateningly sick at arrival.

Inability to start or complete upper secondary school strongly predicts unemployment and psychosocial and psychiatric adversities - A register-based follow-up study from southwestern Sweden.

AIM: To study academic, social and psychiatric outcomes among adults in the general population in southwestern Sweden. Groups of individuals born in 1998 and ineligible, eligible but not completed, and eligible and completed upper secondary school were followed in 2020. METHODS: Data were retrieved from Statistics Sweden, the Swedish National Agency for Education, the Longitudinal Integrated Database for Health Insurance and Labour Market Studies, the Swedish National Crime Register and the National Patient Register. The four adverse outcomes neither engaging in post-secondary studies nor having a regular salary, needing social benefits, having any criminal conviction, and having a psychiatric disorder at age ≥16 were examined. RESULTS: Of the final sample of 2706 individuals who had attended 9th grade of compulsory school in 2014, 273 (10%) were ineligible for upper secondary school. Of eligible individuals, 82 (3%) never started, 282 (10%) did not complete and 2065 (77%) completed upper secondary school. Compared with completers, the odds ratios for adverse outcomes were markedly increased for all other groups up to 22 years old. CONCLUSION: Inability to start or complete upper secondary school strongly predicted unemployment and psychosocial and psychiatric adversities. School authorities should consider offering vocational programmes post compulsory school without grade restrictions.

Diagnostic errors in rheumatology and medico-legal consequences.

Medical errors and adverse effects of treatment are inherent to medical practice. Like any other medical specialty, rheumatology is not exempt. Although the problem is imprecisely quantified, according to some authors it affects up to 10% of hospitalised patients. Describing and qualifying misdiagnoses in rheumatology will help us to understand and reduce these. Further, misdiagnosis generates unjustified costs and medico-legal consequences with errors in initial diagnosis the basis for medico-legal disputes involving assessment of work incapacity.