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ObjectiveTo describe the health and well-being of children and young people (CYP) seeking asylum subjected to Australia’s immigration policy of indefinite mandatory detention on Nauru.DesignCross-sectional analysis of a cohort of CYP seeking asylum.SettingAustralian paediatric clinicians from 10 health services completed detailed health assessments around the time of transfer from Nauru, mostly to Australia.ParticipantsSixty-two CYP who were ≤18 years on entry into offshore immigration detention on Nauru between 2013 and 2019. Mean age at health assessment was 9 years.Main measuresHealth outcomes were categorised as physical, mental or neurodevelopmental concerns/conditions. Risk and protective factor data were collected using the adverse childhood experiences and refugee-specific adverse childhood experiences tools.ResultsOver half of the CYP (n=32, 52%) were held on Nauru for ≥4 years. The vast majority of CYP had physical health (n=55, 89%) and mental health (n=49, 79%) concerns including self-harm or suicidal ideation/attempt (n=28, 45%). Mental health concerns were more likely in CYP who were school-aged (p=0.001), had been held on Nauru for ≥1 year (p=0.01); originated from the Eastern Mediterranean region (pConclusionsThis study highlights the almost universal physical and mental health difficulties in a sample of CYP who experienced forced migration and were subjected to Australia’s offshore immigration detention policy. Immigration detention in recipient countries, a known adverse childhood experience, may contribute to or exacerbate harmful outcomes in CYP seeking asylum.

The radiation dose sheet generated by the CT scanner is a form that displays important information about an examination. It functions as a road map for the examination, detailing what CT examinations were performed and what parameters were used to perform them. One essential element of the radiation dose sheet, the volume CT dose index (CTDI

Caregiving encompasses the nurturing, tasks, resources, and services that meet the day-to-day needs of children and youth with special health care needs (CYSHCN) at home. Many gaps exist in the strategies currently offered by the health care system to meet the caregiving needs of CYSHCN. The work of family caregivers of CYSHCN is known to be extensive, but it is so poorly understood that it has been described as "invisible". This invisibility leads to poor communication and gaps in understanding between professional health care providers and family caregivers. To address these gaps, health care researchers must work with family caregivers to incorporate their expertise on caregiving and create meaningful and sustainable research partnerships. A growing body of research is attempting to remedy the problem of caregiving invisibility and lay better foundations for successful integration between health care settings, family caregiving, professional caregiving, and community supports for families of CYSHCN. We identify high-priority gaps in CYSHCN caregiving research and propose research questions that are designed to accelerate growth in evidence-based understanding of the work of family caregivers of CYSHCN and how best to support them.

PURPOSE Variability in computed tomography images intrinsic to individual scanners limits the application of radiomics in clinical and research settings. The development of reproducible and generalizable radiomics-based models to assess lesions requires harmonization of data. The purpose of this study was to develop, test, and analyze the efficacy of a radiomics data harmonization model. MATERIALS AND METHODS Radiomic features from biopsy-proven untreated hepatic metastasis (N = 380) acquired from 167 unique patients with pancreatic, colon, and breast cancers were analyzed. Radiomic features from volume-match 551 samples of normal liver tissue and 188 hepatic cysts were included as references. A novel linear mixed effect model was used to identify effects associated with lesion size, tissue type, and scanner model. Six separate machine learning models were then used to test the effectiveness of radiomic feature harmonization using multivariate analysis. RESULTS Proposed model identifies and removes scanner-associated effects while preserving cancer-specific functional dependence of radiomic features on the tumor size. Data harmonization improves the performance of classification models by reducing the scanner-associated variability. For example, the multiclass logistic regression model, LogitBoost, demonstrated the improvement in sensitivity in the range from 15% to 40% for each type of liver metastasis, whereas the overall model accuracy and the kappa coefficient increased by 5% and 8% accordingly. CONCLUSION The model removed scanner-associated effects while preserving cancer-specific functional dependence of radiomic features.

Aim To identify the highest-priority clinical research areas related to children with neurological impairment and medical complexity among clinicians and caregivers. Method A modified, three-stage Delphi study using online surveys and guided by a steering committee was completed. In round 1, clinicians and family caregivers suggested clinical topics and related questions that require research to support this subgroup of children. After refinement of the suggestions by the steering committee, participants contributed to 1 (family caregivers) or 2 (clinicians) subsequent rounds to develop a prioritized list. Results A diverse international expert panel consisting of 49 clinicians and 12 family caregivers provided 601 responses. Responses were distilled into 26 clinical topics comprising 126 related questions. The top clinical topics prioritized for research were irritability and pain, child mental health, disorders of tone, polypharmacy, sleep, aspiration, behavior, dysautonomia, and feeding intolerance. The clinician expert panel also prioritized 10 specific research questions. Interpretation Study findings support a research agenda for children with neurological impairment and medical complexity focused on addressing clinical questions, prioritized by an international group of clinicians and caregivers.

Systemic sclerosis (SSc) patients are classified according to degree of skin fibrosis (limited and diffuse cutaneous) and serum autoantibodies. We undertook the present multicenter study to determine if intrinsic subset (IS) classification based upon skin gene expression yields additional valuable clinical information.SSc patients and healthy participants (HP) were classified as Normal-like, Limited, Fibroproliferative and Inflammatory IS using a previously trained classifier. Clinical data were obtained (serum autoantibodies, pulmonary function testing, modified Rodnan Skin scores [mRSS], and high-resolution chest computed tomography [HRCT]). Statistical analyses were performed to compare patients classified by IS, traditional cutaneous classification, and serum autoantibodies.223 participants (165 SSc [115 dcSSc and 50 lcSSc] and 58 HP) were classified. Inflammatory IS patients had higher mRSS (22.1±9.9, p0.001) than other IS and dcSSc (19.4±9.4, p= 0.05) despite similar disease duration (median [IQR] months 14.9[19.9] vs 18.4[31.6], p=0.48). In multivariable modeling, no significant association between mRSS and RNA Pol III (p=0.07) or Scl-70 (p=0.09) was found. Radiographic ILD was more prevalent in Fibroproliferative IS compared to other IS (91%, p=0.04) with similar prevalence between lcSSc and dcSSc (67% vs. 76%, p=0.73). Positive Scl-70 antibody was the strongest ILD predictor (p0.001). Interestingly, all lcSSc/Fibroproliferative patients were demonstrated radiographic ILD.Classification by IS identifies patients with distinct clinical phenotypes versus traditional cutaneous or autoantibody classification. IS classification identifies subgroups of SSc patients with more radiographic ILD (Fibroproliferative), higher mRSS (Inflammatory) and milder phenotype (Normal-like), and may provide additional clinically useful information to current SSc classification systems. This article is protected by copyright. All rights reserved.

Telemedicine technology and regulation have been steadily growing over the last 2 decades. Prior to the coronavirus disease-2019 (COVID-19) pandemic, the availability of telemedicine in health systems and coverage of telemedicine were variable. Sudden and improved access to telemedicine was propelled by the COVID-19 pandemic, during which governments, insurers, and health systems ramped up telemedical utilization with short-term exceptions and waivers. As in-person care opportunities open back up, the presence of telemedicine is not receding and thus its widespread adoption needs to be facilitated outside pandemic-specific conditions. Long-term funding for telemedicine acquisition, centralized electronic health records, extended waivers related to telemedicine coverage and use, a Medicaid expansion that involves parity in telemedicine and in-person care, a nationalized licensure system, and an assessment of what types of care settings can and cannot utilize telemedicine are necessary recommendations to improve the sustainability of telemedicine after the pandemic.

Background There are characteristic findings of coronavirus disease 2019 (COVID-19) on chest images. An artificial intelligence (AI) algorithm to detect COVID-19 on chest radiographs might be useful for triage or infection control within a hospital setting, but prior reports have been limited by small data sets, poor data quality, or both. Purpose To present DeepCOVID-XR, a deep learning AI algorithm to detect COVID-19 on chest radiographs, that was trained and tested on a large clinical data set. Materials and Methods DeepCOVID-XR is an ensemble of convolutional neural networks developed to detect COVID-19 on frontal chest radiographs, with reverse-transcription polymerase chain reaction test results as the reference standard. The algorithm was trained and validated on 14 788 images (4253 positive for COVID-19) from sites across the Northwestern Memorial Health Care System from February 2020 to April 2020 and was then tested on 2214 images (1192 positive for COVID-19) from a single hold-out institution. Performance of the algorithm was compared with interpretations from five experienced thoracic radiologists on 300 random test images using the McNemar test for sensitivity and specificity and the DeLong test for the area under the receiver operating characteristic curve (AUC). Results A total of 5853 patients (mean age, 58 years ± 19 [standard deviation]; 3101 women) were evaluated across data sets. For the entire test set, accuracy of DeepCOVID-XR was 83%, with an AUC of 0.90. For 300 random test images (134 positive for COVID-19), accuracy of DeepCOVID-XR was 82%, compared with that of individual radiologists (range, 76%–81%) and the consensus of all five radiologists (81%). DeepCOVID-XR had a significantly higher sensitivity (71%) than one radiologist (60%, P < .001) and significantly higher specificity (92%) than two radiologists (75%, P < .001; 84%, P = .009). AUC of DeepCOVID-XR was 0.88 compared with the consensus AUC of 0.85 (P = .13 for comparison). With consensus interpretation as the reference standard, the AUC of DeepCOVID-XR was 0.95 (95% CI: 0.92, 0.98). Conclusion DeepCOVID-XR, an artificial intelligence algorithm, detected coronavirus disease 2019 on chest radiographs with a performance similar to that of experienced thoracic radiologists in consensus. © RSNA, 2020 Supplemental material is available for this article. See also the editorial by van Ginneken in this issue.

Background: Radiomics is an emerging tool that involves the extraction of high-throughput features from medical images. These quantitative values can be used to develop predictive models for clinical characteristics and treatment outcomes. We evaluated radiomic features-based models as imaging biomarkers in NSCLC patients. Methods: 71 patients with NSCLC treated with immunotherapy who had pretreatment CT chest with contrast were retrospectively evaluated. The main tumor and 1cm-thick peritumoral space surrounding the tumor were manually segmented using LIFEx software (IMIV/CEA, Orsay, France) by four physicians. Of 255 radiomic features collected, those with >0.4 of Fleiss’ kappa coefficient were selected. The Random Forest (RF) algorithm with mixed effects was used to develop multi-reader models and assess feature importance. The dataset was divided into a training set (75%) and a test set (25%). Bootstrapping with 1,000 iterations was conducted to estimate the model performance. Durable disease control was defined as having no progression of diseases per RECIST 1.1 up to 24 weeks from starting immunotherapy. Results: Among 71 patients, 35 (49.3%) are female and 36 (50.7%) are male. The median age was 66. 48 (67.6%) adenocarcinoma, 13 (18.3%) squamous cell carcinoma, and 10 (14.1%) other histologic types were included. 22 radiomic features were included based on importance in the prediction models from both the tumor and peritumoral space. Each model is trained to predict patients’ durable disease control, TTF1 expression, PD-L1 expression, histology (adenocarcinoma or not), and Neutrophils Lymphocyte Ratio (NLR; greater than 5 or not) status. The statistical results from the models to predict clinical outcomes are shown in Table. Conclusion: The radiomic features-based models lack accuracy in predicting clinical characteristics and outcomes. Further validation with larger cohorts is warranted. Statistics of radiomics-based models in predicting clinical characteristics and treatment outcomes Durable Disease Control(Yes/No)(n=64) TTF1 expression(Yes/No)(n=62) Histology(Adeno/Other)(n=71) NLR(>=5/ Citation Format: Jisang Yu, Yury Velichko, Hyeonseon Kim, Moataz Soliman, Nicolo Gennnaro, Leeseul Kim, Youjin Oh, Trie Arni Djunadi, Jeeyeon Lee, Liam Il-Young Chung, Sungmi Yoon, Zunairah Shah, Soowon Lee, Cecilia Nam, Timothy Hong, Rishi Agrawal, Pascale Aouad, Young Kwang Chae. Radiomics-based machine learning models to predict progression and biomarker status in non-small cell lung cancer (NSCLC) patients treated with immunotherapy. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5619.

Invasive pneumococcal disease (IPD) is associated with significant morbidity and mortality in children. Universal pneumococcal conjugate vaccination has changed the epidemiology of IPD. In vaccinated children, IPD can be a marker of an underlying immunodeficiency.This is a retrospective audit of children younger than 18 years with IPD admitted to 2 tertiary pediatric hospitals in Australia between 2011 and 2017. Data on predisposing conditions, immunologic evaluation, pneumococcal serotype, antibiotic susceptibility and treatment were collected.During the 7-year period, there were 131 presentations with IPD in 127 children; 3 children had recurrent IPD. Patients presented with sepsis (41%), empyema (29%), meningitis (18%), mastoiditis (12%), pneumonia (10%) and septic arthritis (4%). In 19 (15%) presentations, risk factors for IPD were present, including malignancy, hematologic disorder, chronic liver disease, chronic kidney disease and cochlear implant. Pneumococcal serotypes were determined in 78/131 (60%) of presentations: the most frequent serotypes were 19A (19%), 3 (13%), 7F (10%) and 19F (8%) and non-vaccine serotypes 22F (8%), 35B (6%), 15A (4%) and 38 (4%). Overall, 11% of isolates were non-susceptible to ceftriaxone. Only 36 patients (32%) had an immunologic evaluation, and 4 patients had proven or probable immunodeficiency.Although pneumococcal conjugate vaccine serotypes 19A, 3, 19F and 7F remain frequent causes of IPD, non-vaccine serotypes are emerging. Our data support vancomycin treatment for children with pneumococcal meningitis given 11% of our isolates were not susceptible to ceftriaxone. It is important to consider underlying conditions predisposing to IPD in a population with high rates of pneumococcal vaccination.

* Abbreviations: CYSHCN — : children and youth with special health care needs FPL — : federal poverty level US children and youth rely on insurance to access health care.1 Families living in or near poverty may qualify for public coverage with income thresholds for eligibility varying from 138% to 325% of the federal poverty level (FPL) across states.2 Other families may have commercial insurance through an employer or direct purchase.3 Families lacking insurance pay out-of-pocket for health care. The adequacy of insurance varies across insurance types,4 with some providing better coverage and access to care than others.5,6 Households with children and youth with special health care needs (CYSHCN) with low-to-middle income (ie, 200% to 399% of FPL) may be particularly sensitive to insurance variations, yet little is known about family perceptions of insurance adequacy.1,3 We compared these perceptions across insurance types for CYSHCN living in low-to-middle income families. We performed a retrospective analysis of 4321 responses of parents of CYSHCN aged 0 to 18 years in the 2016–2017 National Survey of Children’s Health, with family income that was 200% to 399% of FPL, representing 6 056 833 CYSHCN nationally. National Survey of Children’s Health uses … Address correspondence to Jay G. Berry, MD MPH, Boston Children’s Hospital, 21 Autumn St, Room 212.2, Boston, MA 02115, E-mail: Jay.berry{at}childrens.harvard.edu

Background Concerns about potential risks of using contrast media in patients with chronic renal insufficiency limit the utilization of CT angiography in this population. Purpose To evaluate the feasibility of abdominopelvic CTA with very low volumes of contrast media. Material and methods In this retrospective study, 20 patients with chronic renal insufficiency underwent high-pitch abdominopelvic (AP) CTA on a third-generation dual-source CT scanner with 30 mL of nonionic iodinated contrast. The homogeneity of intravascular attenuation at the suprarenal aorta, infrarenal aorta, and the right common iliac artery was measured. Image noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were used to assess objective image quality. Subjective image quality was evaluated on a 5-point scale (1 = unacceptable; 5 = excellent). Results Twelve male and eight female patients underwent CTA of the abdomen and pelvis at 80 kVp. Five CTAs also included the chest (CAP). The mean scan duration was 0.78 ± 0.19 s for AP and 0.96 ± 0.06 s for CAP CTAs. The mean ± SD of attenuation at suprarenal aorta, infrarenal aorta, and right common iliac artery were 235.1 ± 68.0, 249.2 ± 61.3, and 254.4 ± 67.7 HU, respectively. The attenuation was homogeneous across vascular levels (P = 0.06). All scans had diagnostic subjective image quality with the median (IQR) of 3.5 (1.75). CNR and SNR were homogeneous across vascular levels (P = 0.08 and P = 0.14, respectively). Conclusion Sub-second, high-pitch abdominopelvic CTA with a low volume of contrast in patients with chronic renal insufficiency is technically and clinically feasible with good diagnostic image quality and homogenous attenuation across vascular levels.

To evaluate the effect of hepatic metastatic lesion size on inter-reader reproducibility of CT-based 2D radiomics imaging features.Computerized tomography (CT) scans of 59 liver metastases from 34 patients with colorectal cancer were evaluated. Image segmentation was performed manually by three readers blinded to each other's results. For each radiomics feature, we created two datasets by sorting measurements according to size, i.e., (i) from the smallest to the largest lesion and (ii) from the largest to the smallest lesion. The Lin concordance correlation coefficient (CCC) was employed to analyze the reproducibility of radiomics features. In particular, the CCC was computed as a function of a number of elements in the dataset, by gradually adding lesions from each sorted dataset. To evaluate the effect of lesion size, we analyzed the difference between these two functions thus assessing the contribution of small and large lesions into the reproducibility of radiomics features.Inter-reader reproducibility of CT-based 2D radiomics features assessed using Lin's CCC demonstrates tumor-size dependence. For example, the Lin CCC for GLCM contrast equals 0.88 (95% C.I. 0.84 to 0.92, p 0.003) and could change by an additional + / - 0.06 depending on the presence of large or small lesions.Groups of "large" and "small" lesions show different inter-reader reproducibility. The inter-reader reproducibility from the mixed group consisting of "large" and "small" lesions depends on the lesion-size distribution and can vary widely. This finding could partially explain variability in reproducibility of radiomics features in the literature.• Groups of "large" and "small" lesions show different inter-reader reproducibility. • The inter-reader reproducibility from the mixed group consisting of "large" and "small" lesions depends on the lesion-size distribution.

ObjectiveTo identify clinical factors, including esophageal dilation on chest high-resolution computed tomography (HRCT), that are associated with pulmonary function decline in patients with systemic sclerosis (SSc).MethodsPatients fulfilled 2013 SSc criteria and had ≥ 1 HRCT and ≥ 2 pulmonary function tests (PFTs). According to published methods, widest esophageal diameter (WED) and radiographic interstitial lung disease (ILD) were assessed, and WED was dichotomized as dilated (≥ 19 mm) vs not dilated (< 19 mm). Clinically meaningful PFT decline was defined as % predicted change in forced vital capacity (FVC) ≥ 5 and/or diffusion capacity for carbon monoxide (DLCO) ≥ 15. Linear mixed effects models were used to model PFT change over time.ResultsOne hundred thirty-eight patients with SSc met the study criteria: 100 (72%) had radiographic ILD; 49 (35%) demonstrated FVC decline (median follow-up 2.9 yrs). Patients with antitopoisomerase I (Scl-70) autoantibodies had 5-year FVC% predicted decline (–6.33, 95% CI –9.87 to –2.79), whereas patients without Scl-70 demonstrated 5-year FVC stability (+1.78, 95% CI –0.59 to 4.15). Esophageal diameter did not distinguish between those with vs without FVC decline. Patients with esophageal dilation had statistically significant 5-year DLCO% predicted decline (–5.58, 95% CI –10.00 to –1.15), but this decline was unlikely clinically significant. Similar results were observed in the subanalysis of patients with radiographic ILD.ConclusionIn patients with SSc, Scl-70 positivity is a risk factor for FVC% predicted decline at 5 years. Esophageal dilation on HRCT was associated with a minimal, nonclinically significant decline in DLCO and no change in FVC during the 5-year follow-up. These results have prognostic implications for SSc-ILD patients with esophageal dilation.

This clinical report updates a 2006 report from the American Academy of Pediatrics titled “Sexuality of Children and Adolescents With Developmental Disabilities.” The development of a healthy sexuality best occurs through appropriate education, absence of coercion and violence, and developmental acquisition of skills to navigate feelings, desires, relationships, and social pressures. Pediatric health care providers are important resources for anticipatory guidance and education for all children and youth as they understand their changing bodies, feelings, and behaviors. Yet, youth with disabilities and their families report inadequate education and guidance from pediatricians regarding sexual health development. In the decade since the original clinical report was published, there have been many advancements in the understanding and care of children and youth with disabilities, in part because of an increased prevalence and breadth of autism spectrum disorder as well as an increased longevity of individuals with medically complex and severely disabling conditions. During this same time frame, sexual education in US public schools has diminished, and there is emerging evidence that the attitudes and beliefs of all youth (with and without disability) about sex and sexuality are being formed through media rather than formal education or parent and/or health care provider sources. This report aims to provide the pediatric health care provider with resources and tools for clinical practice to address the sexual development of children and youth with disabilities. The report emphasizes strategies to promote competence in achieving a healthy sexuality regardless of physical, cognitive, or socioemotional limitations.

Children with medical technology dependency (MTD) require a medical device to compensate for a vital body function and substantial nursing care. As such, they require constant high-level supervision. Respite care provides caregivers with a temporary break, and is associated with reduced stress; however, there are often barriers. The study utilizes mixed methodology with the National Survey of Children with Special Health Care Needs (NS-CSHCN) and semistructured interviews with state-wide care coordinators to understand the gap for respite care services. Fifty-nine percent of parents who needed respite care received none. Parents of older children with MTD were more likely to report respite needs. Care coordinators described that home health shortages created barriers to respite care utilization, and the lack of respite care can lead to hospital readmission. Although respite care is a vital resource to support families of children with MTD, it is infrequently available, which can have severe consequences.

This cross-sectional study compares cost and payer reimbursement for hospital admissions of children and assesses associations of underpayment by patients’ demographic and clinical characteristics.

Aim Kawasaki disease (KD) is one of the most common causes of acquired cardiac disease in children in high-income countries. The incidence of coronary artery disease (CAD), despite treatment with intravenous immunoglobulin, ranges from 5 to 20%. Determining risk factors for CAD may assist with management and reduce long-term complications. Methods Retrospective data were collected for all patients presenting to the Women's and Children's Hospital with a discharge diagnosis of KD over a 10.5-year period, from 2007 to 2018. Results A total of 141 patients were included in the review; 101 patients fulfilled complete criteria for KD; 25 incomplete criteria and 15 did not meet criteria but were treated for KD. CAD was present in 27.7% of all patients, ranging from ectasia to giant aneurysms based on Z-scores and echocardiogram descriptions. Medium to large aneurysms accounted for 8.5% of all patients with suspected KD. Patients with CAD were more likely to: fulfil incomplete criteria (odds ratio (OR) 4.3, 95% confidence interval (CI) 1.7-10.8, P = 0.0027), be less than 12 months of age (OR 11.38, 95% CI 2.94-44.11, P = 0.0001), have CRP > 100 (OR 2.8, 95% CI 1.31-6.02, P = 0.0068) and have a delay in treatment (average day of illness prior to treatment 8.89 vs. 6.78 (OR 1.19, 95% CI 1.05-1.35, P = 0.0055)). Patients with a Kobayashi score ≥4 had a higher rate of re-treatment with intravenous immunoglobulin (OR 3.16, 95% CI 1.27-7.83, P = 0.013). Conclusion Our data are consistent with previously reported risk factors, and high rates of CAD despite standard treatment.

In today’s scenario, a lot of problems are being solved by using different deep learning techniques. This paper used deep convolution neural networks to propose a model for orange fruit disease detection. Traditionally, fruit disease detection was a very time-consuming and manual process but with the advancement of computer and machine learning techniques, the process is becoming automated and faster. Many juice companies like Tropicana and Real continuously used different advanced techniques to distinguish between fresh and diseased fruits. The paper uses a visual geometry group named convolution neural network. Today machine learning techniques with the use of high-speed computing hardware devices have given us an opportunity to use different algorithms that automatically detect objects in an image. The paper used a dataset taken from Kaggle.com which contains three different images of fruits but the model used only oranges images for experimental purpose.

A hygienic environment is necessary for any nation in the world. Hygienic harmony leads to a healthy environment, when there is a healthy environment, there is the order in society, and where there is the order in society, there is the order in a nation, which will lead to a healthy and hygienic world. Like the population, the world garbage is increasing profusely day by day. We are having problems with environmental safety and pollution. It is getting much worse when it comes to society. Humans are destroying nature and leading it toward a polluted, unhealthy and unhygienic environment. So, in this paper, Web-based application is made for smart dustbins. A Web-based monitoring interface is also proposed to show the effective locations of smart dustbins and the percentage of garbage levels on a geographical map. Proposed system uses MQTT protocol for sending and receiving data between different devices. It gives the real-time update of garbage to an end user. Real-time update of the garbage level gives the facility to end user to find out the nearest empty dustbin so that garbage of home can be managed by the dustbin, protecting environment from pollution. The proposed system is divided into three different levels. In first level, data gathering is done by nodes. In the second level on the backend server, the analytics module analyzes data collected by the bin subsystem. In the third level, action of the event is performed according to conditions.

BACKGROUND: Children with neurologic impairment (NI) are at risk for developing co-occurring chronic conditions, increasing their medical complexity and morbidity. We assessed the prevalence and timing of onset for those conditions in children with NI. METHODS: This longitudinal analysis included 6229 children born in 2009 and continuously enrolled in Medicaid through 2015 with a diagnosis of NI by age 3 in the IBM Watson Medicaid MarketScan Database. NI was defined with an existing diagnostic code set encompassing neurologic, genetic, and metabolic conditions that result in substantial functional impairments requiring subspecialty medical care. The prevalence and timing of co-occurring chronic conditions was assessed with the Agency for Healthcare Research and Quality Chronic Condition Indicator system. Mean cumulative function was used to measure age trends in multimorbidity. RESULTS: The most common type of NI was static (56.3%), with cerebral palsy (10.0%) being the most common NI diagnosis. Respiratory (86.5%) and digestive (49.4%) organ systems were most frequently affected by co-occurring chronic conditions. By ages 2, 4, and 6 years, the mean (95% confidence interval [CI]) numbers of co-occurring chronic conditions were 3.7 (95% CI 3.7–3.8), 4.6 (95% CI 4.5–4.7), and 5.1 (95% CI 5.1–5.2). An increasing percentage of children had ≥9 co-occurring chronic conditions as they aged: 5.3% by 2 years, 10.0% by 4 years, and 12.8% by 6 years. CONCLUSIONS: Children with NI enrolled in Medicaid have substantial multimorbidity that develops early in life. Increased attention to the timing and types of multimorbidity in children with NI may help optimize their preventive care and case management health services.

Objective: We assessed the association between (1) severity of vessel wall calcification, (2) number of patent vessels at the ankle and (3) arterial spectral waveform features, as assessed on a focused ankle Duplex ultrasound (DUS), and healing at 12-months in a cohort of patients who had their diabetic foot ulcers conservatively managed. Research design and methods: Scans performed on 50 limbs in 48 patients were included for analysis. Patient health records were prospectively reviewed for 12-months to assess for the outcome of ulcer healing. Results: We identified that the number of waveform components, peak systolic velocity, systolic rise time and long forward flow as well as the number of vessels patent at the ankle on DUS, may be useful independent predictors of healing, as noted by the trend towards statistical significance. Conclusion: Arterial spectral waveform features may be useful in predicting the chance of diabetic foot ulcer healing.

Rationale: In 2016, the American Thoracic Society released clinical practice guidelines for pediatric chronic home invasive ventilation pertaining to discharge practices and subsequent management for patients with invasive ventilation using a tracheostomy. It is not known to what extent current U.S. practices adhere to these recommendations. Objectives: Hospital discharge practices and home health services are not standardized for children with invasive home mechanical ventilation (HMV). We assessed discharge practices for U.S. children with HMV. Methods: A survey of key-informant U.S. clinical providers of children with HMV, identified with purposeful and snowball sampling, was conducted. Topics included medical stability, family caregiver training, and discharge guidelines. Close-ended responses were analyzed using descriptive statistics. Responses to open-ended questions were analyzed using open coding with iterative modification for major theme agreement. Results: Eighty-eight responses were received from 157 invitations. Eligible survey responses from 59 providers, representing 44 U.S. states, included 49.2% physicians, 37.3% nurses, 10.2% respiratory therapists, and 3.4% case managers. A minority, 22 (39%) reported that their institution had a standard definition of medical stability; the dominant theme was no ventilator changes 1–2 weeks before discharge. Nearly all respondents’ institutions (94%) required that caregivers demonstrate independent care; the majority (78.4%) required two trained HMV caregivers. Three-fourths described codified discharge guidelines, including the use of a discharge checklist, assurance of home care, and caregiver training. Respondents described variable difficulty with obtaining durable medical equipment, either because of insurance or durable-medical-equipment company barriers. Conclusions: This national U.S. survey of providers for HMV highlights heterogeneity in practice realities of discharging pediatric patients with HMV. Although no consensus exists, defining medical stability as no ventilator changes 1–2 weeks before discharge was common, as was having an institutional requirement for training two caregivers. Identification of factors driving heterogeneity, data to inform standards, and barriers to implementation are needed to improve outcomes.

Objectives & hypothesis Children with home mechanical ventilation (HMV) require skilled care by trained caregivers, and their families feel the impacts of ubiquitous home nursing shortages. It is unknown which factors determine allocation; no standards for private duty nursing intensity exist. We sought to characterize provider experiences with and opinions on home nursing for children with HMV, hypothesizing providers would describe frequent home nursing gaps across clinical scenarios. Methods Purposeful and snowball sampling identified key informant clinical providers. Survey topics included hours of home nursing received across clinical and family scenarios. Close-ended responses were analyzed using descriptive statistics and open-ended questions coded with iterative modification for major theme agreement. Results A total of 59 respondents represented care of patients from 44 states; 49.2% physicians, 37.3% nurses, 10.2% respiratory therapists, and 3.4% case managers. Nearly all (97%) believed that families should receive more hours during initial home transition, yet less than half (47%) do. The majority (80.7%) thought the presence of other children in the home should influence nursing hours, yet only three (5.3%) reported other children have influence. Across hypothetical medical technology scenarios, providers consistently described children receiving fewer nursing hours than the providers' ideal practice. A third (31.7%) described discharging patients without any home nursing arranged. Conclusions This HMV provider sample highlights pervasive deficiency in home nursing provision with heterogenous interpretation of what constitutes ideal home care. Family and social contextual factors are infrequently considered in nursing allocations. Provider, community health, and family stakeholders must collaborate to generate national community practice standards for children with HMV.

Pulmonary mucormycosis (PM) is an uncommon fungal infection most often seen in immunocompromised patients. The fungus grows on decaying food, soil, and animal excrement. Patients usually become infected by inhalation of spores. The most common risk factors include diabetes mellitus, hematologic malignancy, and solid organ or stem cell transplant. PM can have a nonspecific appearance at imaging. For example, early imaging may show peribronchial ground-glass opacity. Later, the disease progresses to consolidation, nodules, or masses. Because patients are usually immunocompromised, the differential diagnosis often includes invasive pulmonary aspergillosis (IPA). Various radiologic findings suggestive of PM have been identified to help differentiate it from IPA. For example, the reverse halo sign is more closely associated with PM than with IPA. The reverse halo sign is an area of ground-glass opacity surrounded by a rim of consolidation. In addition, the presence of pleural effusions and more than 10 nodules is more suggestive of PM than it is of IPA. PM can progress rapidly in neutropenic patients. Identification of the hyphae in tissue by using endobronchial or percutaneous sampling can allow differentiation from IPA and help confirm the diagnosis of mucormycosis. Because of the high mortality rate associated with PM, early identification of the disease is critical for an improved likelihood of survival. A multimodality treatment approach with antifungal agents and surgical debridement has been shown to improve outcomes. The authors review the risk factors for PM, describe its imaging appearance and disease process, and describe the treatment of the disease. ©RSNA, 2020.

Objective Children with invasive home mechanical ventilation (HMV) are a growing population with complex health service needs. Single institution studies provide insight into successful program structures and outcomes. Our study objectives were to assess health service structures, providers, and programs caring for this population throughout the U.S., and to understand barriers to high-quality care. Design Using purposeful sampling with capture-recapture and snowball sampling methods, we identified key informants for care of the U.S. pediatric HMV population. Informants received web-based surveys with two reminders. Survey domains included respondent characteristics, HMV team composition, and barriers to care. Results Survey response was 71% with 101 completed. Respondents caring for patients in 45 states included physicians (61%), nurses (20%), therapists (12%), case managers (4%), and social workers (2%). Half (53%) of physicians were fellowship trained, most commonly pulmonology (22%) and critical care medicine (13%). The majority (65%) of providers described a dedicated HMV service. The majority (61%) of respondents from a HMV service provided both inpatient and outpatient care. Nearly all respondents (96%) described an inadequate supply of home nurses and 88% reported inadequate respite facilities. Conclusions Children with HMV assistance receive care from a diverse group of providers with varied team structure. Heterogeneity may reflect patient diversity and provider interest, increasing efficacy but challenging standardization nationwide. Despite team structure variability, similar home care difficulties were universally experienced. Data suggest that the home nursing shortage is a national impediment to quality and efficient discharge with limited community-based support for this vulnerable population.

Objective.Forced vital capacity (FVC) and DLCO are used for screening of systemic sclerosis–associated interstitial lung disease (SSc-ILD). The study purpose was to determine the sensitivity, specificity, and negative predictive value (NPV) (proportion of true negative screening tests) of FVC and DLCO thresholds for SSc-ILD on chest high-resolution computed tomography (HRCT) scans.Methods.Patients fulfilling American College of Rheumatology 2013 SSc criteria with a chest HRCT scan and pulmonary function tests (PFT) were studied. A thoracic radiologist quantified radiographic ILD. Optimal FVC and DLCO % predicted thresholds for ILD were identified using receiver-operating characteristic curves. The FVC and DLCO combinations with greatest sensitivity and specificity were also determined. Subanalysis was performed in patients with positive Scl-70 autoantibodies.Results.The study included 265 patients. Of 188 (71%) with radiographic ILD, 59 (31%) had “normal” FVC (≥ 80% predicted), and 65 out of 151 (43%) had “normal” DLCO (≥ 60% predicted). FVC < 80% (sensitivity 0.69, specificity 0.73), and DLCO < 62% (sensitivity 0.60, specificity 0.70) were optimal thresholds for radiographic SSc-ILD. All FVC and DLCO threshold combinations evaluated had NPV < 0.70. The NPV for radiographic ILD for FVC < 80% was lower in patients with positive Scl-70 autoantibody (NPV = 0.05) compared to negative Scl-70 autoantibody (NPV = 0.57).Conclusion.Radiographic ILD is prevalent in SSc despite “normal” PFT. No % predicted FVC or DLCO threshold combinations yielded high NPV for SSc-ILD screening. “Normal” FVC and DLCO in patients with SSc, especially those with positive Scl-70 autoantibodies, should not obviate consideration of HRCT for ILD evaluation.

Background. Social determinants of health impact child illness. Currently, no instrument exists to identify social need during hospital admission. Methods. Using the UCLA (University of California Los Angeles)-RAND appropriateness method, consensus was reached for an instrument to identify social need in hospitalized children. A panel of 11 experts reviewed candidate indicators through 3 rounds to reach consensus. The instrument then underwent usability testing. Results. Three hundred and forty-seven indicators from the literature were sorted into 18 social risk themes. After 3 rounds, consensus was reached on 82 indicators. Six additional social risk themes were recommended by the panel, resulting in consensus for 18 additional indicators. Final refinement resulted in an instrument containing 86 indicators representing 11 social risk themes. Usability testing identified that the tool was well received by families. Final feedback was incorporated into a post-usability instrument. Conclusions. Using the UCLA-RAND appropriateness method, a new pediatric social risk instrument was created to identify social need for hospitalized children.

Background The primary aim of this study was to evaluate the effectiveness of a training programme to teach a focused bedside ultrasound scan (PAD-scan; Podiatry Ankle Duplex Scan) for the detection of arterial disease in people with diabetes. Methods Five podiatrists and one diabetologist across two hospitals were enrolled in a structured training programme consisting of a training course (1-day), supervised scanning (5-weeks), independent scanning (3-weeks) and a final evaluation of performance (1-day). Time, technical skills (Duplex Ultrasound Objective Structured Assessment of Technical Skills tool (DUOSATS); minimum score = 6, maximum score = 26) and accuracy (level of agreement with vascular scientist PAD-scan assessment) were assessed for every supervised scan and again for the final evaluation of performance. Results A total of 90 PAD-scans in 65 patients were performed during the supervised phase. Participants demonstrated significant improvements in median time (19 min(IQR 13.9–25.5) vs 9.3 min (IQR 7.3–10.5); p = 0.028) and DUOSATS scores (17.5 (IQR 16.8–21) vs 25 (IQR 24–25.3); p = 0.027). At the final evaluation, participants completed scans in 5.4 min (IQR 5.3–5.9), achieved full DUOSAT scores and perfect agreement with the vascular scientist. Conclusion A structured training programme, integrated into diabetic foot clinics, was effective in teaching the PAD-scan Electronic supplementary material The online version of this article (10.1186/s13047-018-0283-0) contains supplementary material, which is available to authorized users.