Which Demographic and Clinical Characteristics Can Better Predict the Length of Hospital Stay among Traumatic Patients? A Retrospective Single-Center, Registry-Based Study.

Background: Lengthy hospitalization may lead to an increased hospital-acquired patient complication, including infections, as well as increased costs for both healthcare systems and patients. A few studies evaluated the impact of various clinical and demographic variables on patients' length of stay (LOS). Hence, in this study, we aimed to investigate the impact of various variables on traumatic patients' LOS. Methods: This is a retrospective single-center, registry-based study of traumatic patients admitted to Taleqani, a major trauma center in Kermanshah, Iran. A Minimal Dataset (MDS) was developed to retrieve traumatic data on demographic and clinical aspects. We used univariable and multiple quantile regression models to evaluate the association between independent variables, including ISS, GCS, and SBP, with LOS. LOS is practically defined as the time interval between hospital admission and discharge. The LOS durations have been presented as median (Q1 to Q3) hours. A p-value of <0.05 was considered statistically significant. Results: A total of 2708 cases were included in this study, with 1989 (73.4%) of them being male. The median LOS was 87.00 (48.00 to 144.00) hours. When adjusted for systolic blood pressure (SBP), Glasgow Coma Scale (GCS), Injury Severity Score (ISS), and cause of injury, the two characteristics of spine/back and multiple trauma were significantly associated with the higher LOS, with 43 (20.5 to 65.48) and 24 (10.39 to 37.60) hours more than extremities (P < 0.001 and P = 0.005). Besides, the patients admitted due to road traffic injuries (RTI) were discharged 16 and 41 hours later than falling and cutting/stabbing (P = 0.008 and < 0.001, respectively). Moreover, the patients with ISS≥16 and 9≤ISS≤15 had a median of 51 (21 to 80) and 34 (22 to 45) LOS hours more, compared to 1≤ISS≤8, respectively (P < 0.001). The trauma cases experiencing SBP ≤ 90 mmhg on admission had a median of 41 (20 to 62) hours more hospitalization period than those with SBP> 90 mmhg (P < 0.001). At last, the patients with GCS of 9 to 12 and GCS of 3 to 8 were hospitalized for 39 and 266 hours more than GCS of 13 to 15 (P < 0.001). Conclusion: Determining independent determinants of prolonged LOS may lead to better identifying at-risk patients on admission. Trauma care providers should consider the following risk factors for increased LOS: higher ISS, Lower GCS, and SBP, multiple trauma or spine injury, and trauma resulting from falling or cutting/stabbing. As a result, the impact of extended LOS might be reduced by intervening in the related influencing factors.

Which Factors Are Associated With Comorbid Psychiatric Conditions in Patients Affected by Substance Use Disorders? The Impact of COVID-19 Pandemic on Dual-Diagnosis Subjects.

OBJECTIVE: To investigate demographic/cinical variables associated to dual diagnosis and the psychological reaction of dual-diagnosis patients to COVID-19 pandemic. METHODS: Information was collected at the Addiction Service of Monza, Italy. The Impact of Event Scale-Revised (IES-R), a self-report questionnaire measuring the subjective response to a traumatic event, was administered. Univariate analyses and binary logistic regression were performed. IES-R scores were compared between groups defined by qualitative variables through one-way analyses of variance (ANOVA). RESULTS: 118 outpatients were included, 48.3% with dual diagnosis. Alcohol use disorder and being female were associated to dual diagnosis. IES-R scores were significantly higher in the dual-diagnosis group, especially for personality disorders (PDs). IES-R scores were higher in patients taking treatment for substance use disorder (SUD). CONCLUSIONS: Females and alcohol abusers were at-risk subjects for dual diagnosis. Patients with SUD and PDs may benefit from additional support, especially when traumatic life events occur. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04694482.

Suicidal behaviour among patients with congestive cardiac failure in a Nigerian teaching hospital.

Background: Suicidal behaviour is an established psychiatric complication of congestive cardiac failure (CCF), contributing significantly to morbidity and death by suicide. The magnitude and risk factors for suicidal behaviour among patients with CCF are yet to be unpacked, especially in developing nations such as Nigeria. Aim: To determine the prevalence of suicidal behaviour and the risk factors associated with suicidal behaviour, among patients with CCF in Nigeria. Setting: Cardiology outpatient clinic of Lagos State University Teaching Hospital, Lagos, Nigeria. Methods: A cross-sectional study was conducted among 98 randomly selected patients with a diagnosis of CCF. Participants were assessed with a socio-demographic and clinical factors questionnaire and Beck Scale of Suicidal Ideation. Chi-square test, t-test and logistic regression were used to analyse data. Results: The prevalence of suicidal ideation and suicidal attempt among patients with CCF was 52% and 1%, respectively. No socio-demographic factor was significantly associated with suicidal ideation. Clinical factors associated with suicidal ideation were age at diagnosis (p = 0.042), aetiology of CCF (p = 0.001) and severity of CCF (p = 0.032). Only the severity of CCF (odds ratio [OR] = 20.557, p = 0.014) predicted suicidal ideation among patients with CCF. Conclusion: Suicidal behaviour constitutes a huge burden among the outpatient CCF population. The identification of clinical risk factors for suicidal ideation (age at diagnosis, aetiology and severity of CCF) further illuminates a pathway to mortality among patients with CCF. Contribution: The findings lend a voice to the need for screening for suicidal behaviour, suicide prevention programmes, surveillance systems and government policies that support mental health for patients with CCF.

Risk factors for labour induction and augmentation: a multicentre prospective cohort study in India.

Background: Guidelines for labour induction/augmentation involve evaluating maternal and fetal complications, and allowing informed decisions from pregnant women. This study aimed to comprehensively explore clinical and non-clinical factors influencing labour induction and augmentation in an Indian population. Methods: A prospective cohort study included 9305 pregnant women from 13 hospitals across India. Self-reported maternal socio-demographic and lifestyle factors, and maternal medical and obstetric histories from medical records were obtained at recruitment (≥28 weeks of gestation), and women were followed up within 48 h after childbirth. Maternal and fetal clinical information were classified based on guidelines into four groups of clinical factors: (i) ≥2 indications, (ii) one indication, (iii) no indication and (iv) contraindication. Associations of clinical and non-clinical factors (socio-demographic, healthcare utilisation and lifestyle related) with labour induction and augmentation were investigated using multivariable logistic regression analyses. Findings: Over two-fifths (n = 3936, 42.3%, 95% confidence interval [CI] 41.3-43.3%) of the study population experienced labour induction and more than a quarter (n = 2537, 27.3%, 95% CI 26.4-28.2%) experienced augmentation. Compared with women with ≥2 indications, those with one (adjusted odds ratio [aOR] 0.50, 95% CI 0.42-0.58) or no indication (aOR 0.24, 95% CI 0.20-0.28) or with contraindications (aOR 0.12, 95% CI 0.07-0.20) were less likely to be induced, adjusting for non-clinical characteristics. These associations were similar for labour augmentation. Notably, 34% of women who were induced or augmented did not have any clinical indication. Several maternal demographic (age at labour, parity and body mass index in early pregnancy), healthcare utilization (number of antenatal check-ups, duration of iron-folic acid supplementation and individuals managing childbirth) and socio-economic factors (religion, living below poverty line, maternal education and partner's occupation) were independently associated with labour induction and augmentation. Interpretation: Although decisions about induction and augmentation of labour in our study population in India were largely guided by clinical recommendations, we cannot ignore that more than a third of the women did not have an indication. Decisions could also be influenced by non-clinical factors which need further research. Funding: The MaatHRI platform is funded by a Medical Research Council Career Development Award (Grant Ref: MR/P022030/1) and a Transition Support Award (Grant Ref: MR/W029294/1).

Evaluation des Troubles Cognitifs Chez des Patients Tunisiens Atteints de Trouble Bipolaire en Rémission : Étude Cas-Témoins: Assessment of Cognitive Impairment in Tunisian Patients With Bipolar Disorder in Remission: A Case-Control Study.

OBJECTIVES: Our aims were to assess cognitive impairment in bipolar patients in remission compared with healthy controls, and to study its connection to clinical and therapeutic factors. METHODOLOGY: This was a case-control study of patients with bipolar disorder (BD) in remission and matched healthy controls. It was carried out at the Hédi Chaker University Hospital in Sfax, Tunisia. The Screen for Cognitive Impairment in Psychiatry (SCIP) scale was used to assess cognitive function in patients and controls. This scale comprises subtests for verbal learning with immediate (VLT-I) and delayed (VLT-D) recall, working memory (WMT), verbal fluency (VFT) and information processing speed (PST). RESULTS: We recruited 61 patients and 40 controls. Compared with controls, patients had significantly lower scores on the overall SCIP scale and on all SCIP subtests (p < 0.001 throughout) with moderate to high effects. In multivariate analysis, the presence of psychotic characteristics correlated with lower scores on the overall SCIP (p = 0.001), VLT-I (p = 0.001) and VLT-D (p = 0.007), WMT (p = 0.002) and PST (p = 0.008). Bipolar II correlated with lower LTV-I scores (p = 0.023). Age of onset and duration of the disorder were negatively correlated with PST scores (p < 10-3 and p = 0.007, respectively). Predominantly manic polarity correlated with lower VFT scores (p = 0.007). CONCLUSIONS: Our study showed that bipolar patients in remission presented significantly more marked cognitive impairments, affecting various cognitive domains, than the controls. These cognitive impairments appear to be linked to clinical and therapeutic factors that are themselves considered to be factors of poor prognosis in BD.

OBJECTIFS: Nos objectifs étaient d'évaluer les troubles cognitifs chez des patients bipolaires en rémission comparativement à des témoins sains et d'étudier leur rapport avec les facteurs cliniques et thérapeutiques. MÉTHODES: Il s'agissait d'une étude cas-témoins, menée auprès de patients atteints de trouble bipolaire (TBP) en rémission et de témoins sains appariés. Elle a été réalisée au centre hospitalo-universitaire (CHU) Hédi Chaker de Sfax (Tunisie). L'échelle the Screen for cognitive impairment in psychiatry (SCIP) a été utilisée pour l'évaluation des fonctions cognitives chez les patients et les témoins. Cette échelle se compose des sous-échelles d'apprentissage verbal avec rappel immédiat (VLT-I) et différé (VLT-D), de la mémoire de travail (WMT), de la fluence verbale (VFT) et de la vitesse de traitement de l'information (PST). RÉSULTATS: Nous avons recruté 61 patients et 40 témoins. Comparés aux témoins, les cas avaient des scores totaux du SCIP et de toutes les sous-échelles du SCIP significativement plus bas (p < 0,001 partout) avec des tailles d'effet modérées à élevées. Dans l'analyse multivariée, la présence de caractéristiques psychotiques était corrélée à l'abaissement des scores du SCIP total (p = 0,001), du VLT-I (p = 0,001) et VLT-D (p = 0,007), du WMT (p = 0,002), et du PST (p = 0,008). Le TBP de type 2 était corrélé à l'abaissement du score de VLT-I (p = 0,023). L'âge de début et la durée d'évolution du trouble étaient corrélés négativement au score PST (p < 10−3 et p = 0,007 respectivement). La polarité maniaque prédominante était corrélée à l'abaissement du score VFT (p = 0,007). CONCLUSIONS: Notre étude a montré que les patients bipolaires en rémission présentaient des troubles cognitifs touchant différents domaines cognitifs, significativement plus marqués que chez les témoins. Ces troubles cognitifs semblent être liés à des facteurs cliniques et thérapeutiques considérés eux-mêmes comme des facteurs de mauvais pronostic de la maladie bipolaire.

Clinical Evaluation After Discontinuation of Galcanezumab in Japanese Patients with Episodic and Chronic Migraine: Analysis of a Randomized, Placebo-Controlled Trial and Open-label Extension Study.

INTRODUCTION: This analysis of two Japanese clinical trials evaluated efficacy and safety after galcanezumab (GMB) discontinuation in patients with episodic migraine (EM) and chronic migraine (CM). METHODS: Data were from a 6-month, randomized, double-blind, placebo [PBO]-controlled primary trial (patients with EM) and a 12-month open-label extension trial (patients with EM/CM). Patients received 6 months' (primary) or 12/18 months' (extension) treatment with GMB 120 mg (GMB120) plus 240-mg loading dose or 240 mg (GMB240) with 4 months' post-treatment follow-up. Efficacy was assessed as number of monthly migraine headache days during post-treatment. Safety was assessed via post-treatment-emergent adverse events (PTEAEs). RESULTS: The analysis population included 186 patients from the primary trial (PBO N = 93; GMB120 N = 45; GMB240 N = 48), 220 patients with EM from the extension trial (PBO/GMB120 N = 57; PBO/GMB240 N = 55; GMB120/GMB120 N = 55; GMB240/GMB240 N = 53), and 55 patients with CM (GMB120 N = 28; GMB240 N = 27). In patients with EM receiving 6 months' GMB120, mean standard deviation (SD) monthly migraine headache days increased from 5.69 (4.64) at treatment end to 6.24 (4.37) at end of follow-up but did not return to pre-treatment levels (8.80 [2.96]). In the extension trial, mean monthly migraine headache days in patients with EM receiving GMB120 were 4.13 (3.85) after 12 months and 4.45 (3.78) at end of follow-up, and 3.59 (3.48) after 18 months and 3.91 (3.57) at end of follow-up. Monthly migraine headache days in patients with CM (12 months' GMB120) were 10.71 (4.61) at treatment end and 11.17 (5.64) at end of follow-up (pre-treatment 20.15 [4.65]). Similar results were seen for patients receiving GMB240. The most observed PTEAE after GMB discontinuation was nasopharyngitis. CONCLUSION: Galcanezumab exhibited post-treatment efficacy for up to 4 months in Japanese patients with EM and with CM. No unexpected safety signals were observed. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT02959177 and NCT02959190.

The Impact of Excision Interval on Equine Melanoma Progression: Time Matters?

Equine melanomas are a common neoplasm in gray horses. However, scientific knowledge about their progression over time is quite scarce. Some owners and veterinarians still believe that early intervention is not necessary, stating that tumors evolve very slowly and intervention could worsen the animal's condition. This work aims to identify clinical and histological differences that may exist between equine melanomas with different excision intervals (time between tumor detection and surgical excision). A total of 42 tumors (13 benign and 29 malignant) from 34 horses were included in this study. There was a statistically significant association between excision interval and tumor size (p = 0.038), with tumors excised later being significantly larger than the ones excised sooner. The excision interval was also statistically associated with the number of tumors (p = 0.011), since the horses that carried a tumor for longer seemed to be prone to have multiple tumors. Furthermore, there was an association between excision interval and malignancy (p = 0.035), with tumor excised later being fives times more likely to be malignant. This study provides evidence of delayed excision's effect on the progression of equine melanomas. Additionally, it reinforces the importance of the early excision of these tumors.

Breast cancer risk prediction using machine learning: a systematic review.

Background: Breast cancer is the leading cause of cancer-related fatalities among women worldwide. Conventional screening and risk prediction models primarily rely on demographic and patient clinical history to devise policies and estimate likelihood. However, recent advancements in artificial intelligence (AI) techniques, particularly deep learning (DL), have shown promise in the development of personalized risk models. These models leverage individual patient information obtained from medical imaging and associated reports. In this systematic review, we thoroughly investigated the existing literature on the application of DL to digital mammography, radiomics, genomics, and clinical information for breast cancer risk assessment. We critically analyzed these studies and discussed their findings, highlighting the promising prospects of DL techniques for breast cancer risk prediction. Additionally, we explored ongoing research initiatives and potential future applications of AI-driven approaches to further improve breast cancer risk prediction, thereby facilitating more effective screening and personalized risk management strategies. Objective and methods: This study presents a comprehensive overview of imaging and non-imaging features used in breast cancer risk prediction using traditional and AI models. The features reviewed in this study included imaging, radiomics, genomics, and clinical features. Furthermore, this survey systematically presented DL methods developed for breast cancer risk prediction, aiming to be useful for both beginners and advanced-level researchers. Results: A total of 600 articles were identified, 20 of which met the set criteria and were selected. Parallel benchmarking of DL models, along with natural language processing (NLP) applied to imaging and non-imaging features, could allow clinicians and researchers to gain greater awareness as they consider the clinical deployment or development of new models. This review provides a comprehensive guide for understanding the current status of breast cancer risk assessment using AI. Conclusion: This study offers investigators a different perspective on the use of AI for breast cancer risk prediction, incorporating numerous imaging and non-imaging features.

A comparison between centralized and asynchronous federated learning approaches for survival outcome prediction using clinical and PET data from non-small cell lung cancer patients.

BACKGROUND AND OBJECTIVE: Survival analysis plays an essential role in the medical field for optimal treatment decision-making. Recently, survival analysis based on the deep learning (DL) approach has been proposed and is demonstrating promising results. However, developing an ideal prediction model requires integrating large datasets across multiple institutions, which poses challenges concerning medical data privacy. METHODS: In this paper, we propose FedSurv, an asynchronous federated learning (FL) framework designed to predict survival time using clinical information and positron emission tomography (PET)-based features. This study used two datasets: a public radiogenic dataset of non-small cell lung cancer (NSCLC) from the Cancer Imaging Archive (RNSCLC), and an in-house dataset from the Chonnam National University Hwasun Hospital (CNUHH) in South Korea, consisting of clinical risk factors and F-18 fluorodeoxyglucose (FDG) PET images in NSCLC patients. Initially, each dataset was divided into multiple clients according to histological attributes, and each client was trained using the proposed DL model to predict individual survival time. The FL framework collected weights and parameters from the clients, which were then incorporated into the global model. Finally, the global model aggregated all weights and parameters and redistributed the updated model weights to each client. We evaluated different frameworks including single-client-based approach, centralized learning and FL. RESULTS: We evaluated our method on two independent datasets. First, on the RNSCLC dataset, the mean absolute error (MAE) was 490.80±22.95 d and the C-Index was 0.69±0.01. Second, on the CNUHH dataset, the MAE was 494.25±40.16 d and the C-Index was 0.71±0.01. The FL approach achieved centralized method performance in PET-based survival time prediction and outperformed single-client-based approaches. CONCLUSIONS: Our results demonstrated the feasibility and effectiveness of employing FL for individual survival prediction in NSCLC patients, using clinical information and PET-based features.

Proportion of At-Risk Alcohol Consumers According to the New French Guidelines: Cross-Sectional Weighted Analyses From the CONSTANCES Cohort.

Objective: To estimate the proportion of the participants of the French national population-based CONSTANCES cohort exceeding the new low-risk drinking guidelines according to sociodemographic and clinical factors. Methods: From 34,470 participants with follow-up data in 2019, among volunteers aged 18-69 years and invited to enroll in the CONSTANCES cohort in 2016 and 2017, weighted prevalence and odds ratios with 95% confidence intervals (CI) exceeding the guidelines using logistic regressions were presented stratified for age, gender, education, occupational grade, employment, income, marital status, pregnancy, work stress, depression, alcohol dependence, binge drinking, cannabis use, smoking status, e-cigarette use, cardiovascular diseases, and cancer. Results: The guidelines were exceeded more by men at 60.2% (95%CI: 59.3%-61.0%) than by women at 36.6% (95%CI: 35.9%-37.4%). Exceeding the guidelines increased with age, socioeconomic status, smoking, vaping, using cannabis, binge drinking, and alcohol dependence. Being depressed was associated with exceeding the guidelines in women. Even though pregnant women were less likely to exceed the guidelines, 7.6% (95%CI: 5.4%-10.6%) were at-risk drinkers. Conclusion: These findings highlight the need to implement effective prevention measures for at-risk alcohol use among the French population.

Prediction of immunotherapy response in idiopathic membranous nephropathy using deep learning-pathological and clinical factors.

Background: Owing to individual heterogeneity, patients with idiopathic membranous nephropathy (IMN) exhibit varying sensitivities to immunotherapy. This study aimed to establish and validate a model incorporating pathological and clinical features using deep learning training to evaluate the response of patients with IMN to immunosuppressive therapy. Methods: The 291 patients were randomly categorized into training (n = 219) and validation (n = 72) cohorts. Patch-level convolutional neural network training in a weakly supervised manner was utilized to analyze whole-slide histopathological features. We developed a machine-learning model to assess the predictive value of pathological signatures compared to clinical factors. The performance levels of the models were evaluated using the area under the receiver operating characteristic curve (AUC) on the training and validation tests, and the prediction accuracies of the models for immunotherapy response were compared. Results: Multivariate analysis indicated that diabetes and smoking were independent risk factors affecting the response to immunotherapy in IMN patients. The model integrating pathologic features had a favorable predictive value for determining the response to immunotherapy in IMN patients, with AUCs of 0.85 and 0.77 when employed in the training and test cohorts, respectively. However, when incorporating clinical features into the model, the predictive efficacy diminishes, as evidenced by lower AUC values of 0.75 and 0.62 on the training and testing cohorts, respectively. Conclusions: The model incorporating pathological signatures demonstrated a superior predictive ability for determining the response to immunosuppressive therapy in IMN patients compared to the integration of clinical factors.

A hospital-based study of survival in oral cancer patients of Tata Memorial Hospital, Mumbai.

Introduction: Oral cancer represents a significant global public health concern, with the death rate for lip and oral cavity malignancies experiencing a 1.40-fold increase worldwide in the past three decades. This retrospective study aimed to comprehensively understand overall survival (OS) and the influence of sociodemographic and clinical factors on patients diagnosed with oral cavity cancer. Materials and methods: The study focused on oral cancer patients enrolled in 2016 and treated at Tata Memorial Hospital, Mumbai, with a follow-up period extending to 5 years until 2021. Utilising the Kaplan-Meier technique and log-rank test, we examined OS and variations based on sociodemographic factors, while the Cox proportional hazard model allowed us to investigate the simultaneous impact of multiple factors on OS. Results: A total of 1,895 eligible participants were included. The overall 5-year survival rate was 65%. After adjusting for age, gender, education, primary site, tumour grade, TNM staging, treatment intention, status and modality, we found in our study oral cancer patients aged more than 60 years (HR = 1.37, 95% CI: 1.01-1.85, p-value 0.03), patients who had poorly differentiated carcinoma (HR = 2.44, 95% CI: 1.56-3.81, p-value < 0.001), belonged to stage IV as per TNM staging (HR = 2.44, 95% CI: 1.65-3.61, p-value < 0.001), patient who have received partial treatment (HR = 2.44, 95% CI: 1.65-3.61, p-value < 0.001) and only chemotherapy (HR = 3.56, 95% CI: 2.43-5.23, p-value < 0.001) found to have a higher hazard of dying while literate (HR = 0.73, 95% CI: 0.56-0.95, p-value 0.02) are protective. Limitations: The retrospective nature of the study posed constraints in exploring additional variable associations. Implication: Overall early detection, appropriate treatment, and regular follow-up are critical for improving the survival rate of patients with oral cavity cancer. Conclusion: This research proposes that improving the socioeconomic status and promoting proactive treatment-seeking behaviour is crucial for enhancing the survival of oral cancer patients. Cancer hospitals, in collaboration with the wider public healthcare system in India, which includes clinicians and policymakers, should consider these suggestions to enhance cancer treatment and control in low-middle-income countries.

Impact of iris color on uveal melanoma-related outcomes in 7245 patients at a single ocular oncology center.

PURPOSE: To determine the relationship between iris color and uveal melanoma (UM)-related metastasis and death in a large cohort of patients from a single ocular oncology center. DESIGN: Retrospective case series. SUBJECTS: Patients diagnosed with UM between February 1971 and August 2007. METHODS: Patient information was obtained from chart documentation. MAIN OUTCOME MEASURES: UM-related metastasis and death. RESULTS: Out of 7245 patients, iris color was blue in 3702 (51%), green in 1458 (20%), and brown in 2085 (29%). Mean age was 58 ± 15 years and mean tumor thickness was 5.5 ± 3.3 millimeters. Some clinical features differed between iris color groups, with the blue irides group having a larger proportion of post-equatorial tumors with significantly closer proximity to the foveola and optic disc compared to the brown irides group. At a mean follow-up of 75 months, there was no statistically significant difference in metastasis between the various iris color groups. On univariate analysis, those with blue irides showed a higher incidence of UM-related death compared to the green and brown irides groups (8.3%, 5.9% and 7.5% respectively, p value = 0.02). Kaplan-Meier event free survival from UM-related death significantly differed only between the blue and green irides groups (p value = 0.007) with the green irides group showing the highest survival. However, on multivariate analysis, iris color was not predictive of UM-related death. CONCLUSION: Iris color was not predictive of UM-related metastasis or death. However, Kaplan-Meier survival at 20 years was poorest for blue irides group compared to green.

Lifestyle and clinical risk factors in relation with the prevalence of diabetes in the Indonesian urban and rural populations: The 2018 Indonesian Basic Health Survey.

Aims: To investigate the differences between Indonesian urban and rural populations in the association of lifestyle and clinical factors with diabetes prevalence. Methods: Using database of the 2018 Indonesian Basic Health Survey, which was conducted in April-May 2018, non-pregnant respondents aged ≥15 years old with available blood glucose data (n urban = 17,129, n rural = 16,585) were included in this study. The diagnosis of diabetes was based on the combination of known diabetes, i.e., a previous history of diabetes or use of anti-diabetes medication, and unknown diabetes based on blood glucose criteria. We performed logistic regression analyses separately for the urban and rural populations to examine the association of lifestyle and clinical factors with prevalent diabetes. Results: Indonesian urban population was less physically active, had a lower proportion of adequate fruit and vegetable intake, and had higher individuals with obesity than rural population. Although there were no differences in the total prevalence of diabetes between the two populations (10.9 % vs. 11.0 %, for urban and rural, respectively), the prevalence of known diabetes was twice higher in urban than in rural population (3.8 % vs. 1.9 %). Physical activity was associated with lower risk of diabetes, especially in the urban population [prevalence OR (95 %CI): 0.91 (0.85; 0.98) for urban and 0.94 (0.89; 1.00) for rural). Obesity, hypertension, and dyslipidemia were risk factors for prevalent diabetes in both populations. Conclusions: Indonesian rural population showed relatively better lifestyle and clinical profiles compared to their urban counterparts. However, no differences were observed between the two populations in the relation between risk factors and diabetes. Special attention needs to be addressed to the high prevalence of undiagnosed and untreated diabetes in Indonesia.

Do I care for you more when you really need help? An experimental test of the effect of clinical urgency on compassion in health care.

OBJECTIVES: To experimentally investigate whether more urgent patient presentations elicit greater compassion from health care professionals than less urgent, facilitating future research and thinking to address systemic barriers to compassion in health care. DESIGN: This is a pre-registered online study with an experimental, within-subjects repeated-measure study design. Two clinical vignettes that systematically varied the urgency of patient presentation were utilized. Both vignettes depicted a patient with difficult behaviours typically associated with lower compassion. METHODS: Health care professionals (doctors, nurses and allied health practitioners) recruited from all 20 District Health Boards across Aotearoa/New Zealand completed two vignettes in a counterbalanced order. Paired-sample t-tests were used to test the effect of the presentation urgency on indices of compassion. RESULTS: A total of 939 participants completed the vignettes (20% doctors, 47%, nurses and 33% allied health professionals). As expected, participants reported greater care and motivation to help the more urgent patient. However, the more urgent patient was also perceived as less difficult, and exploratory analyses showed that perceived patient difficulty was associated with lower caring and motivation to help, particularly in the less urgent patient. CONCLUSIONS: This is the first work to experimentally test the relationship between the urgency of patient presentation and compassion in health care. Although the association between urgency and difficulty is complex, our findings are consonant with evolutionary views in which urgent distress elicits greater compassion. A system-wide orientation towards efficiency and urgency may exacerbate this 'bias' which must be addressed to ensure more equitable compassion in health care.

Explaining differences in autism detection timing: Age of diagnosis and associated individual and socio-familial factors in Chinese children.

LAY ABSTRACT: Timely detection is an issue of paramount importance in the care of children with autism spectrum disorder. Whether the delayed autism spectrum disorder diagnosis can be explained by children's clinical presentations and socio-familial status in China is a question to be addressed. We investigated 1235 autism spectrum disorder children from 132 rehabilitation organisations in Shenzhen, China. These children were found to have a mean age of diagnosis of 31.4 ± 12.7 months and a median age of diagnosis of 30.0 months. The majority of these children were able to receive their diagnosis during toddlerhood. However, about one in six were not diagnosed until they entered preschool or later, thus missing the golden window of opportunity for early intervention. The age of diagnosis was likely to be late if the children were older, were less severe and presented with no intellectual impairment. The odds of having a delayed autism spectrum disorder diagnosis were more than 9 times higher among migrant autism spectrum disorder children than among those with local household registrations, thus underscoring the importance of identifying culturally sensitive socio-economic determinants in autism spectrum disorder detection, as these factors are likely to affect the quality of life of many autism spectrum disorder children and their families.

Correlates of malnutrition in patients with heart failure: the role of social support.

AIMS: Heart failure (HF) is a major public health challenge. Malnutrition has a significant effect on HF prognosis. Understanding the impact of social and clinical factors on the risk of malnutrition is necessary because it may aid in improving the health status of HF patients. METHODS AND RESULTS: Three hundred twenty patients with HF who were hospitalized in a heart centre in Shiraz, Iran, from March to November 2022 were studied. Two validated questionnaires were used to evaluate malnutrition and social support: (1) Mini-Nutritional Assessment Short Form and (2) Medical Outcomes Study Social Support Survey. The participants were then divided into three groups: those with normal nutritional status (scores 12-14), those at risk of malnutrition (scores 7-11), and those who were malnourished (scores 0-6). The potential correlates of malnutrition (including socio-demographic, clinical, comorbidities, and laboratory factors) were included in the study. Then, ordinal logistic regression was used to investigate the correlates of malnutrition. The mean age of the participants was 64.2 ± 11.2 years, and more than half were male and married. Normal nutritional status was seen in 110 (34.4%) participants, 151 (47.2%) were at risk of malnutrition, and 58 (18.1%) were malnourished. The mean social support score of the participants was 61.65 ± 12.91. According to the adjusted odds ratios (95% confidence intervals) obtained from multivariate analysis, increased risk of malnutrition was associated with having a lower social support score [0.95 (0.93-0.97), P-value ≤ 0.001], lower body mass index [0.91 (0.86-0.97), P-value = 0.004], higher New York Heart Association classification [1.26 (1.02-1.56), P-value = 0.03], longer duration of disease [1.006 (1.001-1.01), P-value = 0.006], and lower serum albumin level [0.25 (0.08-0.75), P-value = 0.01]. CONCLUSIONS: Besides the clinical conditions affecting the risk of malnutrition in patients with HF, social support may play an important role. Including this factor in HF guidelines and developing educational programmes may help improve HF patients' health.

Risk Factors and Location of Intracranial Aneurysm Rupture in a Consecutive Chinese Han Population.

OBJECTIVE: The aim of the present study was to retrospectively analyze and investigate the clinical data of 704 cases of ruptured intracranial aneurysms (RIAs) and unruptured intracranial aneurysms (UIAs). The risk factors predicting aneurysm rupture were explored from the perspective of the clinical characteristics of intracranial aneurysm (IA). METHODS: The clinical data of 704 patients with RIAs (494 patients) and UIAs (210 patients) admitted to the Department of Neurosurgery of Tianjin Medical University General Hospital and Tianjin Fifth Central Hospital between January 2016 and May 2022 were analyzed. A detailed analysis of sex, age, history, personal history, drug intake, and site of aneurysm occurrence was performed. Age was analyzed in segments and strata, and parameters with significant differences in the preliminary analysis results were analyzed by logistic regression to predict factors associated with the risk of aneurysm rupture. RESULTS: Among 494 patients with RIA (70.2%) and 210 patients with UIA (29.8%), the logistic regression showed that IA location appeared to be the most significant factor associated with RIA (OR, 95% CI: internal carotid artery (ICA), reference; anterior communicating artery,27.864,12.548-61.878; posterior communicating artery,12.408,6.658-23.124; anterior cerebral artery,5.804,2.333-14.440; middle cerebral artery,9.284,4.599-18.744; posterior circulation arteries, 4.224,2.011-8.871). Age was not a significant factor associated with RIA in the model and Hyperlipidemia (OR: 0.365; 95% CI: 0.171-0.779), Atherosclerosis (OR: 0.277; 95% CI: 0.172-0.446) and Multiple aneurysms (OR: 0.275; 95% CI: 0.177-0.425) patients were less likely to have RIA.IA location and age were the best predictors of RIA using the model. CONCLUSIONS: The present findings indicated that hyperlipidemia and atherosclerosis have a protective effect on aneurysm rupture, and different anatomical sites of IA may be risk factors for the occurrence of IA rupture. Among the anatomical sites of IA, the anterior communicating artery and posterior communicating artery have a higher fracture risk.

Developing and Validating a Simple Risk Score for Patients with Acute Myocardial Infarction.

INTRODUCTION: Mortality from acute myocardial infarction (AMI) remains substantial. The current study is aimed at developing a novel simple risk score for AMI. METHODS: The Coronary Artery Tree description and Lesion EvaluaTion (CatLet) extended validation trial (ChiCTR2000033730) and the CatLet validation trial (ChiCTR-POC-17013536), both being registered with chictr.org, served as the derivation and validation datasets, respectively. Both datasets included 1,018 and 308 patients, respectively. They all suffered from AMI and underwent percutaneous intervention (PCI). The endpoint was 4-year all-cause death. Lasso regression analysis was used for covariate selection and coefficient estimation. RESULTS: Of 26 candidate predictor variables, the four strongest predictors for 4-year mortality were included in this novel risk score with an acronym of BACEF (serum alBumin, Age, serum Creatinine, and LVEF). This score was well calibrated and yielded an AUC (95% CI) statistics of 0.84 (0.80-0.87) in internal validation, 0.89 (0.83-0.95) in internal-external (temporal) validation, and 0.83 (0.77-0.89) in external validation. Notably, it outperformed the ACEF, ACEF II, GRACE scores with respect to 4-year mortality prediction. CONCLUSION: A simple risk score for 4-year mortality risk stratification was developed, extensively validated, and calibrated in patients with AMI. This novel BACEF score may be a useful risk stratification tool for patients with AMI.

Research on the clinical factors of cardiac iron deposition in children with beta-thalassemia major.

Magnetic resonance imaging (MRI) T2* is the gold standard for detecting iron deposition in cardiac tissue, but the technique has limitations and cannot be fully performed in paediatric thalassemia patients. The aim of this study was to analyse clinical data to identify other predictors of cardiac iron deposition. A retrospective analysis was performed on 370 children with ß-TM. According to the cardiac MRI results, patients were allocated to a cardiac deposition group and noncardiac deposition group. Multivariate analysis revealed that genotype and corrected QT interval were associated with cardiac iron deposition, indicating that the-ß0/ß0 genotype conferred greater susceptibility to cardiac iron deposition. Receiver operating characteristic curve (ROC) analysis was performed, and the area under the curve (AUC) of genotype was 0.651. The AUC for the corrected QT interval was 0.711, at a cut-off value of 418.5 ms. ROC analysis of the combined genotype and corrected QT interval showed an AUC of 0.762 with 81.3% sensitivity and 64.7% specificity. Compared to patients with the ß+/ß+ and ß0ß+ genotypes, ß0ß0 children with ß-TM were more likely to have cardiac iron deposition.  Conclusion: The genotype and QTc interval can be used to predict cardiac iron deposition in children with ß-TM who are unable to undergo MRI T2 testing.