A living experience proposal for the co-occurring diagnosis of avoidant/restrictive food intake disorder and other eating disorders.

The eating and feeding disorder section of the Diagnostic and Statistical Manual of Mental Disorders 5 Text Revision (DSM-5-TR) is organized by a diagnostic algorithm that limits the contemporaneous assignment of multiple eating disorder diagnoses. Avoidant/restrictive food intake disorder (ARFID) is a disturbance in food intake typically associated with lack of interest in food, food avoidance based on sensory characteristics, and/or fear of aversive consequences from eating. According to the DSM-5-TR, an ARFID diagnosis cannot be made when weight or shape disturbances are present, and ARFID cannot be co-diagnosed with other eating disorders characterized by these disturbances. However, emerging evidence from both clinical and lived experience contexts suggests that the co-occurrence of ARFID with multiple other types of eating disorders may be problematically invisibilized by this trumping scheme. The diagnostic criteria for ARFID can contribute to inappropriate diagnosis or exclusion from diagnosis due to excessive ambiguity and disqualification based on body image disturbance and other eating disorder pathology, even if unrelated to the food restriction or avoidance. This harmfully limits the ability of diagnostic codes to accurately describe an individual's eating disorder symptomatology, impacting access to specialized and appropriate eating disorder care. Therefore, revision of the DSM-5-TR criteria for ARFID and removal of limitations on the diagnosis of ARFID concurrent to other full-syndrome eating disorders stands to improve identification, diagnosis, and support of the full spectrum of ARFID presentations.

Strategic Framework for Strengthening Health Laboratory Services in the COVID-19 Pandemic in Iran.

Background & Objective: Providing equitable access to good quality, timely, and affordable laboratory testing has always been a top priority for the Ministry of Health and Medical Education (MoH-ME) and the Reference Health Laboratory (RHL). Considering the significant role of medical laboratories in disease surveillance, RHL developed a strategic plan to manage laboratory services during the COVID-19 pandemic based on the "Strategic Framework for strengthening health laboratory services, 2016-2020" proposed by the World Health Organization (WHO). This article describes the steps taken to establish the strategic framework in Iran. Methods: Firstly, a National Laboratory Committee was formed in MoH-ME and a situation analysis was conducted to explore the strengths, weaknesses, opportunities, and threats in different components of our laboratory system. Gaps and resources needed to address those gaps were determined; then, RHL outlined operational processes and mechanisms for monitoring the activities. Results: The WHO strategic roadmap and its six strategic goals concerning leadership, quality, human resources, safety and security, laboratory networking, and rational use of laboratory testing, helped us to promote national laboratory services in accordance with health system requirements in the COVID-19 pandemic. Conclusion: The establishment of a national molecular laboratory network with more than 500 laboratories from different sectors may result in timely access to countrywide laboratory services and would be beneficial for future COVID-19 and/or other viral outbreaks. Continual evaluation of the COVID-19 laboratories' performance, production of PCR test kits by the local manufacturers, and development of a platform for virtual training would be other accomplishments that Iran achieved in coping with the recent pandemic.

Childhood Gender Diversity and Mental Health: Protocol for the Longitudinal, Observational Gender Journey Project.

BACKGROUND: Prepubertal transgender, nonbinary, and gender-diverse (TGD) children (ie, those asserting gender identity, expressing gender-role behavior outside of culturally defined norms for their sex registered at birth, or both) are presenting in greater numbers to pediatric gender clinics across the United States and abroad. A large subset of TGD children experiences gender dysphoria, that is, distress that arises from the incongruence between gender identity and sex registered at birth. A lack of consensus exists regarding care for prepubertal TGD children due, in part, to a dearth of empirical research on longitudinal developmental trajectories of gender identity, role behavior, and gender dysphoria (when present). OBJECTIVE: The objective of this National Institutes of Health-funded study is to provide evidence to inform clinical care for prepubertal TGD children by establishing a US longitudinal cohort (N=248) of prepubertal TGD children and their caregivers that is followed prospectively at 6-month intervals across 18 months. METHODS: At each timepoint, clinical and behavioral data are collected via web-based visit from child and caregiver reporters. Latent class analysis, among other methods, is used to identify subgroups and longitudinally characterize the gender identity and gender-role behavior of TGD children. These models will define longitudinal patterns of gender identity stability and characterize the relationship between TGD classes and mental and behavioral health outcomes, including the moderating role of social gender transition (when present), on these associations. RESULTS: Baseline data collection (N=248) is complete, and the identification of TGD subgroups based on gender identity and expression using latent class analysis is anticipated in 2024. The completion of all 4 waves of data collection is anticipated in July 2024, coinciding with the start of a no-cost study extension period. We anticipate longitudinal analyses to be completed by winter 2024. CONCLUSIONS: Through a longitudinal observational design, this research involving prepubertal TGD children and their caregivers aims to provide empirical knowledge on gender development in a US sample of TGD children, their mental health symptomology and functioning over time, and how family initiated social gender transition may predict or alleviate mental health symptoms or diagnoses. The research findings have promise for clinicians and families aiming to ensure the best developmental outcome for these children as they develop into adolescents. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55558.

A Rare Case of Peripheral Exophytic Osteoma of the Mandible Arising From an Extraction Site: Cone-Beam Computed Tomography (CBCT) Findings.

A benign osteogenic tumor made up of mature, well-differentiated bone tissue is called an osteoma. Jaw solitary peripheral osteomas are an uncommon occurrence. The mandible is affected more frequently than the maxilla, and the lingual side of the body, the angle, and the inferior border of the jaw are the sites of highest preference. Males are more likely than females to be impacted by osteomas, which can strike at any age. Patients with osteomas should be considered to have Gardner syndrome. This condition includes many embedded or supernumerary teeth, skeletal abnormalities such as osteoma and hyper calcification of the maxillary bones or skull, skin and soft tissue tumors, and gastroenteric polypus. Differential diagnosis is crucial since the development of gastroenteric polyps, which have a potentially malignant progression, occurs before oral and maxillofacial symptoms emerge. Mandibular osteomas are uncommon; even rarer is a massive osteoma with a prevalence of 0.01-0.04% of the population. That's the reason this is being discussed in this article. The primary differential diagnosis and pertinent clinical information from previously published literature are also included in this article.

Impact of federal antipsychotic use policy in nursing homes on new diagnoses for approved indications in dementia residents.

BACKGROUND: Federal policies targeting antipsychotic use among nursing home (NH) residents may have increased reporting of diagnoses for approved uses, including schizophrenia, Tourette's syndrome, and Huntington's Disease (called "exclusionary diagnoses" because they exclude residents from the antipsychotic quality metric). We assessed changes in new exclusionary diagnoses among long-stay NH admissions specifically with dementia following federal policies. METHODS: Retrospective, quarterly, interrupted time-series analysis (2009-2018) of new long-stay NH residents with dementia and no exclusionary diagnoses reported before NH admission. The National Partnership and the addition of facility level antipsychotic use to the Five Star Quality Rating system were key time exposures. Outcome was quarterly facility level predicted percentage of exclusionary diagnoses within 2 years of admission stratified by NH characteristics. RESULTS: For 264,095 long-stay admissions, mean percentage of new exclusionary diagnoses was 2.2% before the Partnership. After the Partnership, there was an unadjusted increase in the percentage over time (slope change, 0.044, p = 0.018), but the percentage never exceeded 2.9%. The Partnership contributed to a one-time decrease in diagnoses in NHs with an intermediate percentage of Black residents (-1.29%, p = 0.004). Before the Partnership, diagnoses were increasing among not-for-profit relative to for-profit NHs (0.044; p = 0.012), but after the Partnership, the pattern reversed. For-profit NHs saw an increase (+0.034, p = 0.002); not-for-profit NHs experienced a decrease (-0.014, p = 0.039). Quality Rating modifications had no significant effect. CONCLUSIONS: Exclusionary diagnosis reporting among long-stay NH residents with dementia, the group most at risk from antipsychotics, did not increase in response to federal policies. Evaluation of reasons for the observed increase in exclusionary diagnoses among non-dementia NH residents is warranted along with continued attention to how to incentivize the appropriate use of medications in residents with dementia that is crucial for high-quality NH care.

On the role of the UMLS in supporting diagnosis generation proposed by Large Language Models.

OBJECTIVE: Traditional knowledge-based and machine learning diagnostic decision support systems have benefited from integrating the medical domain knowledge encoded in the Unified Medical Language System (UMLS). The emergence of Large Language Models (LLMs) to supplant traditional systems poses questions of the quality and extent of the medical knowledge in the models' internal knowledge representations and the need for external knowledge sources. The objective of this study is three-fold: to probe the diagnosis-related medical knowledge of popular LLMs, to examine the benefit of providing the UMLS knowledge to LLMs (grounding the diagnosis predictions), and to evaluate the correlations between human judgments and the UMLS-based metrics for generations by LLMs. METHODS: We evaluated diagnoses generated by LLMs from consumer health questions and daily care notes in the electronic health records using the ConsumerQA and Problem Summarization datasets. Probing LLMs for the UMLS knowledge was performed by prompting the LLM to complete the diagnosis-related UMLS knowledge paths. Grounding the predictions was examined in an approach that integrated the UMLS graph paths and clinical notes in prompting the LLMs. The results were compared to prompting without the UMLS paths. The final experiments examined the alignment of different evaluation metrics, UMLS-based and non-UMLS, with human expert evaluation. RESULTS: In probing the UMLS knowledge, GPT-3.5 significantly outperformed Llama2 and a simple baseline yielding an F1 score of 10.9% in completing one-hop UMLS paths for a given concept. Grounding diagnosis predictions with the UMLS paths improved the results for both models on both tasks, with the highest improvement (4%) in SapBERT score. There was a weak correlation between the widely used evaluation metrics (ROUGE and SapBERT) and human judgments. CONCLUSION: We found that while popular LLMs contain some medical knowledge in their internal representations, augmentation with the UMLS knowledge provides performance gains around diagnosis generation. The UMLS needs to be tailored for the task to improve the LLMs predictions. Finding evaluation metrics that are aligned with human judgments better than the traditional ROUGE and BERT-based scores remains an open research question.

Evaluation of AI-Driven LabTest Checker for Diagnostic Accuracy and Safety: Prospective Cohort Study.

Background: In recent years, the implementation of artificial intelligence (AI) in health care is progressively transforming medical fields, with the use of clinical decision support systems (CDSSs) as a notable application. Laboratory tests are vital for accurate diagnoses, but their increasing reliance presents challenges. The need for effective strategies for managing laboratory test interpretation is evident from the millions of monthly searches on test results' significance. As the potential role of CDSSs in laboratory diagnostics gains significance, however, more research is needed to explore this area. Objective: The primary objective of our study was to assess the accuracy and safety of LabTest Checker (LTC), a CDSS designed to support medical diagnoses by analyzing both laboratory test results and patients' medical histories. Methods: This cohort study embraced a prospective data collection approach. A total of 101 patients aged ≥18 years, in stable condition, and requiring comprehensive diagnosis were enrolled. A panel of blood laboratory tests was conducted for each participant. Participants used LTC for test result interpretation. The accuracy and safety of the tool were assessed by comparing AI-generated suggestions to experienced doctor (consultant) recommendations, which are considered the gold standard. Results: The system achieved a 74.3% accuracy and 100% sensitivity for emergency safety and 92.3% sensitivity for urgent cases. It potentially reduced unnecessary medical visits by 41.6% (42/101) and achieved an 82.9% accuracy in identifying underlying pathologies. Conclusions: This study underscores the transformative potential of AI-based CDSSs in laboratory diagnostics, contributing to enhanced patient care, efficient health care systems, and improved medical outcomes. LTC's performance evaluation highlights the advancements in AI's role in laboratory medicine.

Assessing the Effect of Electronic Health Record Data Quality on Identifying Patients With Type 2 Diabetes: Cross-Sectional Study.

Background: Increasing and substantial reliance on electronic health records (EHRs) and data types (ie, diagnosis, medication, and laboratory data) demands assessment of their data quality as a fundamental approach, especially since there is a need to identify appropriate denominator populations with chronic conditions, such as type 2 diabetes (T2D), using commonly available computable phenotype definitions (ie, phenotypes). Objective: To bridge this gap, our study aims to assess how issues of EHR data quality and variations and robustness (or lack thereof) in phenotypes may have potential impacts in identifying denominator populations. Methods: Approximately 208,000 patients with T2D were included in our study, which used retrospective EHR data from the Johns Hopkins Medical Institution (JHMI) during 2017-2019. Our assessment included 4 published phenotypes and 1 definition from a panel of experts at Hopkins. We conducted descriptive analyses of demographics (ie, age, sex, race, and ethnicity), use of health care (inpatient and emergency room visits), and the average Charlson Comorbidity Index score of each phenotype. We then used different methods to induce or simulate data quality issues of completeness, accuracy, and timeliness separately across each phenotype. For induced data incompleteness, our model randomly dropped diagnosis, medication, and laboratory codes independently at increments of 10%; for induced data inaccuracy, our model randomly replaced a diagnosis or medication code with another code of the same data type and induced 2% incremental change from -100% to +10% in laboratory result values; and lastly, for timeliness, data were modeled for induced incremental shift of date records by 30 days to 365 days. Results: Less than a quarter (n=47,326, 23%) of the population overlapped across all phenotypes using EHRs. The population identified by each phenotype varied across all combinations of data types. Induced incompleteness identified fewer patients with each increment; for example, at 100% diagnostic incompleteness, the Chronic Conditions Data Warehouse phenotype identified zero patients, as its phenotypic characteristics included only diagnosis codes. Induced inaccuracy and timeliness similarly demonstrated variations in performance of each phenotype, therefore resulting in fewer patients being identified with each incremental change. Conclusions: We used EHR data with diagnosis, medication, and laboratory data types from a large tertiary hospital system to understand T2D phenotypic differences and performance. We used induced data quality methods to learn how data quality issues may impact identification of the denominator populations upon which clinical (eg, clinical research and trials, population health evaluations) and financial or operational decisions are made. The novel results from our study may inform future approaches to shaping a common T2D computable phenotype definition that can be applied to clinical informatics, managing chronic conditions, and additional industry-wide efforts in health care.

Splenic rupture in dairy cattle: Report of 24 cases.

Splenic rupture in cattle is scarcely described in the literature. The aim of this work was to report the occurrence of splenic rupture in cattle in southern Brazil as well as to describe the causes of the condition. Between 2013 and 2022, 24 of the 1769 bovine necropsies performed in southern Brazil were due to splenic rupture, accounting for 1.36% of the diagnoses. Animals died due to hemoperitoneum caused by a rupture in the splenic capsule, typically associated with marked splenomegaly and a large hematoma between the capsule and the parenchyma. Clinical signs were described in a subset of cases (11 of 24 cases, 46%) and included apathy, abdominal pain, mucosal pallor, tachycardia, and respiratory distress. However, the majority (13 of 24 cases, 54%) presented as sudden death. The underlying cause of splenic rupture was established as follows: 16 cases (67%) secondary to babesiosis, 4 cases (17%) due to lymphoma, 1 case (4%) due to a thrombus, 1 case (4%) due to external trauma, 1 case due to a ruptured nodular lymphoid hyperplasia (4%), and 1 case of undetermined cause (4%). Hypovolemic shock caused by splenic rupture is an important cause of death of dairy cattle, and babesiosis and bovine leukemia virus-associated lymphoma are among the most common etiologic diagnoses (84% of cases). The description of the causes of this condition is important to clarify the pathogenesis and occurrence of splenic rupture in dairy cattle.

A False Alarm of Acute Abdomen: Epiploic Appendagitis Case Report and Literature Review.

An acute abdomen that is tender to palpation often represents a life-threatening emergency requiring immediate surgical or medical management. We present a case of acute abdomen with peritoneal signs and symptoms due to epiploic appendagitis (EA) that resolved with a single dose of ibuprofen. EA often mimics appendicitis, diverticulitis, and rarely cholecystitis based on its location. It arises due to ischemic infarction of an epiploic appendage, typically caused by torsion or spontaneous thrombosis of the central draining vein. Despite its rarity, clinicians need to recognize the characteristic imaging findings of EA on CT and ultrasound to avoid unnecessary surgical interventions and to manage the condition conservatively.

A history of childhood schizophrenia and lessons for autism.

The diagnosis of childhood schizophrenia was widely employed in the U.S. from the 1930s to the late 1970s. In this paper I will provide a history of the diagnosis. Some of the earliest publications on childhood schizophrenia outlined the notion that childhood schizophrenia had different types. I will outline the development of these types, outlining differing symptoms and causes associated with various types. I outline how different types of childhood schizophrenia were demarcated from one another primarily on age of onset and the type of psychosis which was believed to be present. I will outline how various child psychiatrists viewed the types of childhood schizophrenia posited by other child psychiatrists. I will outline the process of abandoning childhood schizophrenia. I use my history to challenge what I believe are misconceptions about childhood schizophrenia. Also, I will use my history to draw lessons for thinking about modern notions of autism. It shows potential problems around formulating psychiatric diagnoses around causes and how compromises might be needed to prevent those problems. Additionally, childhood schizophrenia shows that psychiatrists could formulate subtypes that are not based upon functioning levels and that we can conceive of subtypes as dynamic whereby someone can change which subtype they exhibit over time.

Quantitative Edge Analysis Can Differentiate Pancreatic Carcinoma from Normal Pancreatic Parenchyma.

This study aimed to introduce specific image feature analysis, focusing on pancreatic margins, and to provide a quantitative measure of edge irregularity, evidencing correlations with the presence/absence of pancreatic adenocarcinoma. We selected 50 patients (36 men, 14 women; mean age 63.7 years) who underwent Multi-detector computed tomography (MDCT) for the staging of pancreatic adenocarcinoma of the tail of the pancreas. Computer-assisted quantitative edge analysis was performed on the border fragments in MDCT images of neoplastic and healthy glandular parenchyma, from which we obtained the root mean square deviation SD of the actual border from the average boundary line. The SD values relative to healthy and neoplastic borders were compared using a paired t-test. A significant SD difference was observed between healthy and neoplastic borders. A threshold SD value was also found, enabling the differentiation of adenocarcinoma with 96% specificity and sensitivity. We introduced a quantitative measure of boundary irregularity, which correlates with the presence/absence of pancreatic adenocarcinoma. Quantitative edge analysis can be promptly performed on select border fragments in MDCT images, providing a useful supporting tool for diagnostics and a possible starting point for machine learning recognition based on lower-dimensional feature space.

Emergency Call versus General Practitioner Requested Ambulances - Patient Mortality, Disease Severity and Pattern.

Introduction: Ambulance requests by general practitioners for primary care patients (GP-requested) are often omitted in studies on increased demand within emergency care but may comprise a substantial patient group. We aimed to assess acute severity, intensive care unit (ICU) admission, and diagnostic pattern, including comorbidity, and mortality among GP-requested ambulance patients, compared to emergency call ambulance patients. Our hypothesis was that emergency call patients had more severe health issues than GP-requested ambulance patients. Methods: Historic population-based cohort study of ambulance patients in the North Denmark Region, 2016-2020. Hospital contact data including diagnoses, ambulance data, vital signs and vital status was linked using each patient's unique identification number. Primary outcome measure was mortality within 1, 7, and 30 days. Secondary outcomes were disease severity expressed as modified National Early Warning Score (NEWS2), and ICU admission. Admission status and hospital diagnostic pattern, including comorbidity were described and compared. Results: We included 255,487 patients. GP-requested patients (N = 119,361, 46.7%) were older (median years [IQR] 73 [58-83] versus 61 [37-76]) and more had moderate/severe comorbidity (11.9%, N = 13,806 versus 4.9%, N = 6145) than the emergency call patients. Prehospital mNEWS2 median scores were lower for GP-requested patients. For both groups, mNEWS2 was highest among patients aged 66+. GP-requested patients had higher 30-day mortality (9.0% (95% CI: 8.8-9.2), N = 8996) than emergency call patients (5.2% (95% CI: 5.1-5.4), N = 6727). Circulatory (12.0%, 11,695/97,112) and respiratory diseases (11.6%, 11,219/97,112) were more frequent among GP-requested patients than emergency call patients ((10.7%, 12,640/118,102) and (5.8%, 6858/118,102)). The highest number of deaths was found for health issues 'circulatory diseases' in the emergency call group and 'other factors' followed by "respiratory diseases" in the GP-requested group. Conclusion: GP-requested patients constituted nearly half of the EMS volume, they were older, with more comorbidity, had serious conditions with substantial acute severity, and a higher 30-day mortality than emergency call patients.

Prevalence of Developmental, Psychiatric, and Neurologic Conditions in Older Siblings of Children with and without Autism Spectrum Disorder: Study to Explore Early Development.

This study evaluated developmental, psychiatric, and neurologic conditions among older siblings of children with and without autism spectrum disorder (ASD) to understand the extent of familial clustering of these diagnoses. Using data from the Study to Explore Early Development, a large multi-site case-control study, the analyses included 2,963 children aged 2-5 years with ASD, other developmental disabilities (DD group), and a population-based control group (POP). Percentages of index children with older siblings with select developmental, psychiatric, and neurologic conditions were estimated and compared across index child study groups using chi-square tests and multivariable modified Poisson regression. In adjusted analyses, children in the ASD group were significantly more likely than children in the POP group to have one or more older siblings with ASD, developmental delay, attention-deficit/hyperactivity disorder, intellectual disability, sensory integration disorder (SID), speech/language delays, or a psychiatric diagnosis (adjusted prevalence ratio [aPR] range: 1.4-3.7). Children in the DD group were significantly more likely than children in the POP group to have an older sibling with most of the aforementioned conditions, except for intellectual disability and psychiatric diagnosis (aPR range: 1.4-2.2). Children in the ASD group were significantly more likely than children in the DD group to have one or more older siblings with ASD, developmental delay, SID, or a psychiatric diagnosis (aPR range: 1.4-1.9). These findings suggest that developmental disorders cluster in families. Increased monitoring and screening for ASD and other DDs may be warranted when an older sibling has a DD diagnosis or symptoms.

Discriminative capacity of the Spanish version of the Inventory of Depression and Anxiety Symptoms-II (IDAS-II) for detecting DMS-5 specific disorders and poor quality of life in a clinical sample.

BACKGROUND: Emotional problems can be evaluated using categorical approaches to guide treatment choices focused on targeting specific disorders, or dimensional approaches to reduce symptom severity. Moreover, recent evidence points out the need to intervene in patients' quality of life (QoL), which often remains low even after the remission of emotional problems. Thus, assessment instruments are needed to provide information on diagnosis, symptom severity, and QoL. The present study aimed to provide diagnostic and QoL cutoffs for the Inventory of Depression and Anxiety Symptoms-II (IDAS-II). METHODS: 273 patients recruited from mental health services in Huelva (Spain) completed the IDAS-II, Mini International Neuropsychiatric Interview, and Short Form-36 Health Survey. Receiver operating characteristic curve analyses were used to establish cutoff values. Diagnostic, balanced, and screening cutoffs were provided for each IDAS-II scale to detect corresponding diagnoses and poor QoL. RESULTS: The specific IDAS-II scales Suicidality, Panic, Social Anxiety, Claustrophobia, and Traumatic Intrusions showed adequate discrimination values for their corresponding diagnoses (suicidal behavior disorder, panic disorder, social anxiety disorder, agoraphobia, and post-traumatic stress disorder, respectively). Both the General Depression and Dysphoria scales showed adequate ability to detect major depressive disorder. The IDAS-II scales showed a higher discrimination ability for Mental Health-related QoL, than for General Health-related QoL. CONCLUSIONS: The diagnostic and QoL cutoffs expand the clinical utility of the IDAS-II in clinical practice and research, making it a comprehensive, detailed, and versatile self-report tool. The IDAS-II allows for the assessment of emotional problems consistent with the dimensional, categorical, transdiagnostic, and QoL approaches.

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.

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.

Alcohol-Specific Inpatient Diagnoses in Germany: A Retrospective Cross-Sectional Analysis of Primary and Secondary Diagnoses from 2012 to 2021.

AIMS: Our study aimed to a) describe the distribution of hospital discharges with primary and secondary alcohol-specific diagnoses by sex and age group, and b) describe how the number of hospital discharges with primary and secondary alcohol-specific diagnoses have changed across different diagnostic groups (categorized by primary International Classification of Diseases, 10th Revision [ICD-10] diagnosis) over time. DESIGN: Retrospective cross-sectional analysis. SETTING: German hospital settings between 2012 and 2021. PARTICIPANTS: All persons aged 15-69 admitted to hospitals as registered in a nationwide data set. MEASUREMENTS: We counted a) the number of all hospital discharges and b) the number of hospital discharges with at least one alcohol-specific secondary diagnosis (secondary alcohol-specific diagnosis) by year, sex, age group, and diagnostic group. One diagnostic group included all primary alcohol-specific diagnoses, while 13 additional groups aligned with ICD-10 chapters (e.g., neoplasms). Alcohol-involvement was defined as either a primary or secondary alcohol-specific diagnosis. FINDINGS: Of 95 417 204 recorded hospital discharges between 2012 and 2021, 3 828 917 discharges (4.0%; 2 913 903 men (6.4%); 915 014 women (1.8%)) involved either a primary or at least one secondary diagnosis related to alcohol. Of all alcohol-involved hospital discharges, 56.8% (1 654 736 discharges) had no primary but only a secondary alcohol-specific diagnosis. Secondary alcohol-specific diagnoses were particularly prevalent in hospital discharges due to injuries. With rising age, alcohol-involvement in hospital discharges due to digestive or cardiovascular diseases increased. Between 2012 and 2021, the rate of alcohol-involved hospital discharges has decreased more in younger as compared with older adults (average change between 2012 and 2021: 15-24: -55%; 25-34: -41%; 35-44: -23%; 45-54: -31%; 55-64: -21%; 65-69: -8%). CONCLUSIONS: The number of alcohol-involved hospital discharges in Germany from 2012 to 2021 more than doubles (from 1 654 736 to 3 828 917) when including secondary alcohol-specific diagnoses. More pronounced declines among younger adults may be attributed to unequal changes in alcohol consumption patterns across the population and to the hazardous effects of long-term alcohol use.

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.