Cost of tuberculosis-related aeromedical retrievals in the Torres Strait, Australia

Tuberculosis (TB) remains a disease of public health significance at the Australia / Papua New Guinea (PNG) international border. In the remote Torres Strait Islands, aeromedical evacuation is a necessary but costly component of TB management and patients with critical care needs require support to prevent onward TB transmission. A detailed costing of an exemplar TB patient from PNG who presented to a Queensland Health facility in the Torres Strait and required urgent aeromedical evacuation was performed. Data were drawn from patient charts, financial and clinical information systems used within Queensland Health and the Torres and Cape Hospital and Health Service. The total cost of aeromedical evacuation was AUD 124,280; 54% of the cost was attributed to travel. Between 2016 and 2019, 19 patients diagnosed with TB were medically evacuated from an outer Torres Strait Island with a median length of hospital stay of 57 days. Aeromedical evacuation and medical management costs require adequate budget allocation.

COVID-19 Pandemic in a Vulnerable Population: Prevalence and Correlates of Anxiety

Background: The COVID-19 pandemic has produced negative mental health outcomes. These effects were more prominent in vulnerable communities that experienced prior similar disasters. The study aimed to examine the likelihood and correlates of anxiety symptoms among Fort McMurray (FMM) residents, during the COVID-19 pandemic. Methods: A cross-sectional online survey questionnaire was applied between 24 April and 2 June 2021, at FMM, to gather sociodemographic, COVID-19, and clinical information, including generalized anxiety disorder (using GAD-7 scale). Results: Overall, 186 individuals completed the survey (response rate 74.7%). Most of the respondents were females (159, 85.5%); above 40 years (98, 52.7%); employed (175, 94.1%); and in relationship (132, 71%). The prevalence of moderate-to-severe anxiety was (42.5%, 71) on GAD-7 self-reported scale. Subscribers who reported that they would like to receive mental health support; have received no family support since COVID-19 declaration; and have lost their job during the pandemic were all more likely to report moderate-to-severe anxiety (OR = 3.39; 95% CI: 1.29–8.88), (OR = 4.85; 95% CI: 1.56–15.03), and (OR = 4.40; 95% CI: 1.01–19.24), respectively. Conclusions: Anxiety levels were high among FMM residents, compared to levels before COVID-19. Clinical and social factors significantly predicted likely anxiety in the Fort McMurray population, during the COVID-19 pandemic. It is imperative that resources are mobilized to support vulnerable communities during the COVID-19 pandemic.

The Application of Whole−Exome Sequencing in Patients With FUO

BackgroundFever of unknown origin (FUO) is still a challenge for clinicians. Next-generation sequencing technologies, such as whole exome sequencing (WES), can be used to identify genetic defects in patients and assist in diagnosis. In this study, we investigated the application of WES in individuals with FUO.MethodsWe performed whole-exome sequencing on 15 FUO patients. Clinical information was extracted from the hospital information system.ResultsIn 7/15 samples, we found positive results, including potentially causative mutations across eight different genes: CFTR, CD209, IRF2BP2, ADGRV 1, TYK2, MEFV, THBD and GATA2.ConclusionsOur results show that whole-exome sequencing can promote the genetic diagnosis and treatment of patients with FUO.

Viral Coinfection and Nasal Cytokines in Children With Clinically Diagnosed Acute Sinusitis

Objective: Children with no pathogenic bacteria in the nasopharynx are unlikely to have acute bacterial sinusitis. We evaluated whether information on clinical presentation, viral co-detection, and mucosal cytokine levels could be used to predict presence of bacteria in the nasopharynx.Method: We obtained nasopharyngeal (NP) swabs from children diagnosed with acute sinusitis. NP swabs were processed for bacterial culture, viral PCR testing, and cytokine expression. We examined whether results of the bacterial culture could be predicted based on the presence of clinical information, presence of viruses or mucosal cytokine levels.Results: We enrolled 174 children; 123 (71%) had a positive culture for potentially pathogenic bacteria and 51 (29%) had normal flora. 122/174 (70%) tested positive for one or more viruses. Compared to children with normal flora, children with pathogenic bacteria were more likely to have viruses (p < 0.01), but this relationship disappeared when we adjusted for age. Children with pathogenic bacteria in their nasopharynx and children with normal flora had similar levels of nasal cytokines.Conclusion: In children with clinically diagnosed acute sinusitis, clinical presentation, levels of nasal cytokines, and presence of viruses do not differentiate children with and without pathogenic bacteria in their nasopharynx.

Hematologic manifestations of SARS-CoV-2 infection and MIS-C in hospitalized children. Results of the PICNIC registry.

Introduction: Hematologic complications of SARS-CoV-2 infection are well described in hospitalized adults with correlation to adverse outcomes. Information published in children has been limited. Methods: An international multi-centered retrospective registry was established to collect data on the clinical manifestations of SARS-CoV-2 or multisystem inflammatory syndrome (MIS-C) in hospitalized children between February 1, 2020 – May 31, 2021. This sub-study focused on hematologic manifestations. Study variables included patient demographics, comorbidities, clinical presentation, course, laboratory parameters, management, and outcomes. Results: Nine hundred and eighty-five children were enrolled and 915 (93%) had clinical information available; 385 (42%) had symptomatic SARS-CoV-2 infection upon admission, 288 had MIS-C (31.4%) and 242 (26.4%) had alternate diagnosis with SARS-CoV-2 identified incidentally. During hospitalization, 10 children (1%) experienced a thrombotic event, 16 (1.7%) had hemorrhage and 2 (0.2%) had both thrombotic and hemorrhagic episodes. Significant prothrombotic comorbidities included congenital heart disease (p-value = 0.007), central venous catheter (p = 0.04) in children with primary SARS-CoV-2 infection; and obesity (p-value= 0.002), cytokine storm (p= 0.012) in those with MIS-C. Significant pro- hemorrhagic conditions included age > 10 years (p = 0.04), CVC (p= 0.03) in children with primary SARS-CoV-2infection; and thrombocytopenia (0.001), cytokine storm (0.02) in those with MIS-C. Eleven patients died (1.2 %) with no deaths attributed to thrombosis or hemorrhage Conclusion: Thrombotic and hemorrhagic complications are uncommon in children with SARS-CoV-2 infection and observed with underlying co-morbid conditions. Understanding the complete spectrum of hematologic complications in children with SARS-CoV-2 infection or MIS-C requires ongoing multi-center studies.

An explainable machine learning framework for lung cancer hospital length of stay prediction

This work introduces a predictive Length of Stay (LOS) framework for lung cancer patients using machine learning (ML) models. The framework proposed to deal with imbalanced datasets for classification-based approaches using electronic healthcare records (EHR). We have utilized supervised ML methods to predict lung cancer inpatients LOS during ICU hospitalization using the MIMIC-III dataset. Random Forest (RF) Model outperformed other models and achieved predicted results during the three framework phases. With clinical significance features selection, over-sampling methods (SMOTE and ADASYN) achieved the highest AUC results (98% with CI 95%: 95.3–100%, and 100% respectively). The combination of Over-sampling and under-sampling achieved the second-highest AUC results (98%, with CI 95%: 95.3–100%, and 97%, CI 95%: 93.7–100% SMOTE-Tomek, and SMOTE-ENN respectively). Under-sampling methods reported the least important AUC results (50%, with CI 95%: 40.2–59.8%) for both (ENN and Tomek- Links). Using ML explainable technique called SHAP, we explained the outcome of the predictive model (RF) with SMOTE class balancing technique to understand the most significant clinical features that contributed to predicting lung cancer LOS with the RF model. Our promising framework allows us to employ ML techniques in-hospital clinical information systems to predict lung cancer admissions into ICU.

Transition of adolescents with severe asthma from pediatric to adult care in Spain: the STAR consensus

Objective: To assess the consensus level among a multidisciplinary expert panel on the transition of adolescents with severe asthma from pediatric to adult care. Methods: A 61-item survey was developed based on guidelines for other chronic pathologies, covering transition planning, preparation, effective transfer, and follow-up. A two-round Delphi process assessed the consensus level among 98 experts (49 pediatricians, 24 allergists and 25 pulmonologists). Consensus was established with ≥70% agreement. Results: Forty-two items (70%) reached consensus. No age range to initiate the transition was agreed upon by the panelists. The main goal to achieve during the transition identified by the experts is that adolescents gain autonomy to manage their severe asthma and prescribed treatments. The panelists agreed on the importance of developing an individualized plan, promoting patient’s autonomy, and identifying home environment factors. They agreed that the adult healthcare team should have expertise in severe asthma, biologics and management of adolescent patients. Pediatric and adult healthcare teams should share clinical information, agree on the criteria to maintain the biological therapy, and have an on-site joint visit with the patient before the effective transfer. Adult healthcare professionals should closely follow the patient after the effective transfer to ensure correct inhaler technique, treatment adherence and attendance to healthcare appointments. Conclusions: This consensus document provides the first roadmap for Spanish pediatric and adult teams to ensure that key aspects of the transition process in severe asthma are covered. The implementation of these recommendations will improve the quality of care offered to the patient.

Novel Molecular Determinants of Response or Resistance to Immune Checkpoint Inhibitor Therapies in Melanoma

BackgroundImmune checkpoint inhibitor (ICI) therapy dramatically prolongs melanoma survival. Currently, the identified ICI markers are sometimes ineffective. The objective of this study was to identify novel determinants of ICI efficacy.MethodsWe comprehensively curated pretreatment somatic mutational profiles and clinical information from 631 melanoma patients who received blockade therapy of immune checkpoints (i.e., CTLA-4, PD-1/PD-L1, or a combination). Significantly mutated genes (SMGs), mutational signatures, and potential molecular subtypes were determined. Their association with ICI responses was assessed simultaneously.ResultsWe identified 27 SMGs, including four novel SMGs (COL3A1, NRAS, NARS2, and DCC) that are associated with ICI efficacy and well-known driver genes. COL3A1 mutations were associated with improved ICI overall survival (hazard ratio (HR): 0.64, 95% CI: 0.45–0.91, p = 0.012), whereas immune resistance was observed in patients with NRAS mutations (HR: 1.42, 95% CI: 1.10–1.82, p = 0.006). The presence of the tobacco smoking-related signature was significantly correlated with inferior prognoses (HR: 1.42, 95% CI: 1.11–1.82, p = 0.005). In addition, the signature resembling that of alkylating agents and a newly discovered signature both exhibited extended prognoses (both HR < 1, p < 0.05). Based on the activities of the extracted 6 mutational signatures, we identified one immune subtype that was significantly associated with better ICI outcomes (HR: 0.44, 95% CI: 0.23–0.87, p = 0.017).ConclusionWe uncovered several novel SMGs and re-annotated mutational signatures that are linked to immunotherapy response or resistance. In addition, an immune subtype was found to exhibit favorable prognoses. Further studies are required to validate these findings.

Prediction of Prognosis in Adult Patients With Carbapenem-Resistant Klebsiella pneumoniae Infection

ObjectiveCarbapenem-resistant Klebsiella pneumoniae (CRKP) infections are associated with poor patient outcomes. We aimed to analyze the clinical information of adult patients with CRKP infection in order to establish a nomogram for mortality risk as well as to determine the treatment effectiveness of different antimicrobial regimens.MethodsAdult patients diagnosed with CRKP infection in a tertiary hospital in Shanghai between September 2019 and March 2021 were included. The clinical characteristics and clinical outcomes of these patients were analyzed.ResultsA total of 199 cases of CRKP infection were examined. Five factors, namely age ≥65 years, respiratory failure, Sequential Organ Failure Assessment score, serum procalcitonin ≥5 ng/mL, and appropriate treatments in 3 days, were found to be associated with 30-day mortality. Upon incorporating these factors, the nomogram achieved good concordance indexes of 0.85 (95% confidence interval [CI]: 0.80–0.90) and well-fitted calibration curves. Receiver-operating characteristic curves for 7-, 15-, and 30-day survival had areas under the curve of 0.90, 0.87, and 0.88, respectively. Three-drug combination therapy was observed to be associated with lower mortality in the high-risk group (adjusted hazard ratio = 0.24, 95% CI: 0.06–0.99) but not in the low-risk group. Ceftazidime–avibactam, fosfomycin, and amikacin were effective against infections caused by CRKP. Tigecycline improved the treatment efficiency in 7 days, but a trend toward increased mortality was seen (HR, 1.69; 95% CI: 0.98–2.94; P = 0.061).ConclusionThe antimicrobial regimen efficacy data and the predictive nomogram established in this study can help clinicians in identifying high-risk adult patients with CRKP infection, improving the therapeutic effect, and reducing mortality.

A Novel Model Based on Necroptosis-Related Genes for Predicting Prognosis of Patients With Prostate Adenocarcinoma

Background: Necroptosis is a newly recognized form of cell death. Here, we applied bioinformatics tools to identify necroptosis-related genes using a dataset from The Cancer Genome Atlas (TCGA) database, then constructed a model for prognosis of patients with prostate cancer.Methods: RNA sequence (RNA‐seq) data and clinical information for Prostate adenocarcinoma (PRAD) patients were obtained from the TCGA portal (http://tcga-data.nci.nih.gov/tcga/). We performed comprehensive bioinformatics analyses to identify hub genes as potential prognostic biomarkers in PRAD u followed by establishment and validation of a prognostic model. Next, we assessed the overall prediction performance of the model using receiver operating characteristic (ROC) curves and the area under curve (AUC) of the ROC.Results: A total of 5 necroptosis-related genes, namely ALOX15, BCL2, IFNA1, PYGL and TLR3, were used to construct a survival prognostic model. The model exhibited excellent performance in the TCGA cohort and validation group and had good prediction accuracy in screening out high-risk prostate cancer patients.Conclusion: We successfully identified necroptosis-related genes and constructed a prognostic model that can accurately predict 1- 3-and 5-years overall survival (OS) rates of PRAD patients. Our riskscore model has provided novel strategy for the prediction of PRAD patients’ prognosis.