Ensemble learning-assisted prediction of prolonged hospital length of stay after spine correction surgery: a multi-center cohort study.

PURPOSE: This research aimed to develop a machine learning model to predict the potential risk of prolonged length of stay in hospital before operation, which can be used to strengthen patient management. METHODS: Patients who underwent posterior spinal deformity surgery (PSDS) from eleven medical institutions in China between 2015 and 2022 were included. Detailed preoperative patient data, including demographics, medical history, comorbidities, preoperative laboratory results, and surgery details, were collected from their electronic medical records. The cohort was randomly divided into a training dataset and a validation dataset with a ratio of 70:30. Based on Boruta algorithm, nine different machine learning algorithms and a stack ensemble model were trained after hyperparameters tuning visualization and evaluated on the area under the receiver operating characteristic curve (AUROC), precision-recall curve, calibration, and decision curve analysis. Visualization of Shapley Additive exPlanations method finally contributed to explaining model prediction. RESULTS: Of the 162 included patients, the K Nearest Neighbors algorithm performed the best in the validation group compared with other machine learning models (yielding an AUROC of 0.8191 and PRAUC of 0.6175). The top five contributing variables were the preoperative hemoglobin, height, body mass index, age, and preoperative white blood cells. A web-based calculator was further developed to improve the predictive model's clinical operability. CONCLUSIONS: Our study established and validated a clinical predictive model for prolonged postoperative hospitalization duration in patients who underwent PSDS, which offered valuable prognostic information for preoperative planning and postoperative care for clinicians. Trial registration ClinicalTrials.gov identifier NCT05867732, retrospectively registered May 22, 2023, https://classic. CLINICALTRIALS: gov/ct2/show/NCT05867732 .

Advanced Insights into Walnut Protein: Structure, Physiochemical Properties and Applications.

Facing extreme pressure from an increasing population and climate degeneration, it is important to explore a green, safe and environmentally sustainable food source, especially for protein-enriched diets. Plant proteins have gained much attention in recent years, ascribing to their high nutritional value and environmental friendliness. In this review, we summarized recent advances in walnut protein with respect to its geographical distribution, structural and physiochemical properties and functional attributes. As a worldwide cultivated and largely consumptive crop, allergies and some physicochemical limitations have also led to a few concerns about walnut protein. Through comprehensive analysis and discussion, some strategies may be useful for future research, extraction and processing of walnut protein.

Persistent symptoms and conditions among children and adolescents hospitalised with COVID-19 illness: a qualitative study.

OBJECTIVES: There is limited in-depth research exploring persistent symptoms and conditions among children and adolescents who contracted COVID-19 illness that required hospitalisation. The main objective of this study was to conduct qualitative interviews among families who had a child hospitalised with COVID-19 illness to elucidate their child's physical, mental and social health outcomes months after initial acute infection. DESIGN, SETTING AND PARTICIPANTS: A qualitative study that composed of in-depth interviews among families with a child hospitalised with COVID-19 illness in one large urban US paediatric healthcare system. Parents (N=25) were recruited from an ongoing quantitative study to estimate the prevalence of long COVID in children hospitalised with COVID-19 illness. During in-depth interviews, parents were invited to describe their child's post-COVID-19 symptoms and experiences. Interviews were audiotaped, transcribed and coded in NVivo. RESULTS: Seven themes were identified concerning the child's prolonged COVID-19 experiences: (1) post-traumatic stress disorder, (2) social anxiety, (3) severe symptoms on reinfection, (4) worsened pre-existing conditions, (5) lack of insurance coverage for costly treatments, (6) access and utilisation of support systems and (7) overall resilience and recovery. Four parent-specific themes were identified: (1) fear of COVID-19 unknowns, (2) mixed messaging from health information sources, (3) schools being both a support system and a hindrance and (4) desire for and access to support systems. CONCLUSIONS: A subset of children who were hospitalised with COVID-19 illness are experiencing a range of serious mental health impacts related to persistent COVID-19 symptoms. Clinical and public health support strategies should be developed to support these children and their families as they reintegrate in school, social and community activities.

Fluorescent detection of tartrazine based on the supramolecular self-assembly of cationic perylene diimide.

A cationic perylene probe was designed and synthesized for sensitive determination of tartrazine. In the presence of tartrazine, the fluorescence of the perylene probe was quenched by efficient supramolecular self-assembly of the perylene derivate. The quenching is caused by the synergistic effect of noncovalent interactions including static electricity, π-π stacking, and hydrophobic interaction. Benefiting from these advantages, the probe exhibited excellent sensing performance to tartrazine within 2 min. The detection and quantification limit of tartrazine are as low as 2.42 and 8.07 nmol L-1, respectively, with a wide linear operation range from 15 to 500 nmol L-1. Most importantly, due to the high binding affinity (3.22 × 107 mol L-1) between the perylene probe and tartrazine, the sensing system shows great anti-interference capacity. Subsequently, the visualization application of the approach was evaluated by portable device, and the limits of detection for visual detection for test strip, membrane, and hydrogel were 0.5, 0.5, and 5 µmol L-1, respectively. The approach has been applied to monitor tartrazine in various food condiments with recoveries in the range 91.29-108.83%. As far as we know, this is the first report of using perylene-based probe for tartrazine determination, offering a promising strategy for the construction of perylene-based detection system in the field of food safety.

Comparison of Long-Term Complications of COVID-19 Illness among a Diverse Sample of Children by MIS-C Status.

Most pediatric COVID-19 cases are asymptomatic; however, a small number of children are diagnosed with multisystem inflammatory syndrome in children (MIS-C), a rare but severe condition that is associated with SARS-CoV-2 infection. Persistent symptoms of COVID-19 illness in children diagnosed with/without MIS-C is largely unknown. A retrospective EHR review of patients with COVID-19 illness from one pediatric healthcare system to assess the presence of acute (<30 days) and chronic (≥30, 60-120, and >120 days) long-term COVID symptoms was conducted. Patients/caregivers completed a follow-up survey from March 2021 to January 2022 to assess the presence of long COVID. Results showed that non-MIS-C children (n = 286; 54.49% Hispanic; 19.23% non-Hispanic Black; 5.77% other ethnicity; 79.49% government insurance) were younger (mean age 6.43 years [SD 5.95]) versus MIS-C (n = 26) children (mean age 9.08 years, [SD 4.86]) (p = 0.032). A share of 11.5% of children with MIS-C and 37.8% without MIS-C reported acute long COVID while 26.9% and 15.3% reported chronic long COVID, respectively. Females were almost twice as likely to report long symptoms versus males and those with private insurance were 66% less likely to report long symptoms versus those with government insurance. In conclusion, a substantial proportion of ethnically diverse children from low resource backgrounds with severe COVID illness are reporting long-term impacts. Findings can inform pediatric professionals about this vulnerable population in post-COVID-19 recovery efforts.