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Respiratory waveforms can be reduced to simple metrics, such as rate, but this may miss information about waveform shape and whole breathing pattern. A novel analysis method quantifying the whole waveform shape identifies AECOPD earlier. https://bit.ly/3M6uIEB., Competing Interests: Conflict of interest: M. Nandi and P.J. Aston are coinventors of SPAR method – Delay coordinate analysis of periodic data, patent number WO2015121679A1, used in this study. Conflict of interest: N. Hart is involved in an investigator-led/industry-funded trial (unrestricted grant) with Resmed. He receives consulting fees from Philips for a hospital patient monitoring programme. He has received payments and honoraria from Fisher and Paykel (chairing an ERS International Congress 2022 symposium) and Philips (lecturing at an ERS International Congress 2022 symposium). He has received financial support for attending meetings from Fisher and Paykel (ERC 2022). He has patents planned, issued or pending for Myotrace (held by Guy's and Thomas’ Foundation Trust). Conflict of interest: R.F. D'Cruz receives consulting fees from Resmed and AstraZeneca. She receives payment or honoraria for lectures, presentations, speakers’ bureaus, manuscript writing or educational events from Fisher Paykel and Resmed. She receives support for attending meetings from Fisher Paykel and Resmed. Conflict of interest: M. Serna-Pascual, M. Volovaya, C.J. Jolley, G.F. Rafferty and J. Steier have declared no conflict of interest., (Copyright ©The authors 2023.)

Background: Electrical stimulation has recently been introduced to treat patients with Obstructive sleep apnoea There are, however, few data on the effects of transcutaneous submental electrical stimulation (TES) on the cardiovascular system. We studied the effect of TES on cardiorespiratory variables in healthy volunteers during head-down-tilt (HDT) induced baroreceptor loading. Method: Cardiorespiratory parameters (blood pressure, heart rate, respiratory rate, tidal volume, airflow/minute ventilation, oxygen saturation, and end-tidal CO2/O2 concentration) were recorded seated, supine, and during head-down-tilt (50) under normoxic, hypercapnic (FiCO 2 5%) and poikilocapnic hypoxic (FiO 2 12%) conditions. Blood pressure (BP) was measured non-invasively and continuously (Finapres). Gas conditions were applied in random order. All participants were studied twice on different days, once without and once with TES. Results: We studied 13 healthy subjects (age 29 (12) years, six female, body mass index (BMI) 23.23 (1.6) kg·m -2 ). A three-way ANOVA indicated that BP decreased significantly with TES (systolic: p = 4.93E-06, diastolic: p = 3.48E-09, mean: p = 3.88E-08). Change in gas condition (systolic: p = 0.0402, diastolic: p = 0.0033, mean: p = 0.0034) and different postures (systolic: 8.49E-08, diastolic: p = 6.91E-04, mean: p = 5.47E-05) similarly impacted on BP control. When tested for interaction, there were no significant associations between the three different factors electrical stimulation, gas condition, or posture, except for an effect on minute ventilation (gas condition/posture p = 0.0369). Conclusion: Transcutaneous electrical stimulation has a substantial impact on the blood pressure. Similarly, postural changes and variations in inspired gas impact on blood pressure control. Finally, there was an interaction between posture and inspired gases that affects minute ventilation. These observations have implications on our understanding of integrated cardiorespiratory control, and may prove beneficial for patients with SDB who are assessed for treatment with electrical stimulation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Alsharifi, Kaltsakas, Pengo, Parati, Serna-Pascual, Rafferty and Steier.)

Logistic regression (LR) is the most common prediction model in medicine. In recent years, supervised machine learning (ML) methods have gained popularity. However, there are many concerns about ML utility for small sample sizes. In this study, we aim to compare the performance of 7 algorithms in the prediction of 1-year mortality and clinical progression to AIDS in a small cohort of infants living with HIV from South Africa and Mozambique. The data set (n = 100) was randomly split into 70% training and 30% validation set. Seven algorithms (LR, Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Naïve Bayes (NB), Artificial Neural Network (ANN), and Elastic Net) were compared. The variables included as predictors were the same across the models including sociodemographic, virologic, immunologic, and maternal status features. For each of the models, a parameter tuning was performed to select the best-performing hyperparameters using 5 times repeated 10-fold cross-validation. A confusion-matrix was built to assess their accuracy, sensitivity, and specificity. RF ranked as the best algorithm in terms of accuracy (82,8%), sensitivity (78%), and AUC (0,73). Regarding specificity and sensitivity, RF showed better performance than the other algorithms in the external validation and the highest AUC. LR showed lower performance compared with RF, SVM, or KNN. The outcome of children living with perinatally acquired HIV can be predicted with considerable accuracy using ML algorithms. Better models would benefit less specialized staff in limited resources countries to improve prompt referral in case of high-risk clinical progression., Competing Interests: The authors have declared that no competing interests exist.

Background: The World Health Organization (WHO) risk assessment algorithm for vertical transmission of HIV (VT) assumes the availability of maternal viral load (VL) result at delivery and early viral control 4 weeks after initiating antiretroviral treatment (ART). However, in many low-and-middle-income countries, VL is often unavailable and mothers' ART adherence may be suboptimal. We evaluate the inclusion of the mothers' self-reported adherence into the established WHO-algorithm to identify infants eligible for enhanced post-natal prophylaxis when mothers' VL result is not available at delivery., Methods: We used data from infants with perinatal HIV infection and their mothers enrolled from May-2018 to May-2020 in Mozambique, South Africa, and Mali. We retrospectively compared the performance of the WHO-algorithm with a modified algorithm which included mothers' adherence as an additional factor. Infants were considered at high risk if born from mothers without a VL result in the 4 weeks before delivery and with adherence <90%., Results: At delivery, 143/184(78%) women with HIV knew their status and were on ART. Only 17(12%) obtained a VL result within 4 weeks before delivery, and 13/17(76%) of them had VL ≥1000 copies/ml. From 126 women on ART without a recent VL result, 99(79%) had been on ART for over 4 weeks. 45/99(45%) women reported suboptimal (< 90%) adherence. A total of 81/184(44%) infants were classified as high risk of VT as per the WHO-algorithm. The modified algorithm including self-adherence disclosure identified 126/184(68%) high risk infants., Conclusions: In the absence of a VL result, mothers' self-reported adherence at delivery increases the number of identified infants eligible to receive enhanced post-natal prophylaxis., (© 2022. The Author(s).)

Objectives: To describe the etiology of community-acquired pneumonia (CAP) in hospitalized children in Spain and analyze the predictors of the etiology., Hypothesis: The different etiological groups of pediatric CAP are associated with different clinical, radiographic, and analytical data., Design: Observational, multicenter, and prospective study., Patient Selection: This study included children aged 1 month to 17 years with CAP, who were hospitalized between April 2012 and May 2019., Methods: An extensive microbiological workup was performed. The clinical, radiographic, and analytical parameters were analyzed for three etiological groups., Results: Among the 495 children included, at least one causative pathogen was identified in 262 (52.9%): pathogenic viruses in 155/262 (59.2%); atypical bacteria (AB), mainly Mycoplasma pneumonia, in 84/262 (32.1%); and typical bacteria (TyB) in 40/262 (15.3%). Consolidation was observed in 89/138 (64.5%) patients with viral CAP, 74/84 (88.1%) with CAP caused by AB, and 40/40 (100%) with CAP caused by TyB. Para-pneumonic pleural effusion (PPE) was observed in 112/495 (22.6%) patients, of which 61/112 (54.5%) presented a likely causative pathogen: viruses in 12/61 (19.7%); AB in 23/61 (37.7%); and TyB in 26/61 (42.6%). Viral etiology was significantly frequent in young patients and in those with low oxygen saturation, wheezing, no consolidation, and high lymphocyte counts. CAP patients with AB as the etiological agent had a significantly longer and less serious course as compared to those with other causative pathogens., Conclusions: Viruses and M. pneumoniae are the main causes of pediatric CAP in Spain. Wheezing, young age, and no consolidation on radiographs are indicative of viral etiology. Viruses and AB can also cause PPE. Since only a few cases can be directly attributed to TyB, the indications for antibiotics must be carefully considered in each patient., (© 2021 The Authors. Pediatric Pulmonology published by Wiley Periodicals LLC.)

Background: We aimed to identify risk factors causing critical disease in hospitalized children with COVID-19 and to build a predictive model to anticipate the probability of need for critical care., Methods: We conducted a multicenter, prospective study of children with SARS-CoV-2 infection in 52 Spanish hospitals. The primary outcome was the need for critical care. We used a multivariable Bayesian model to estimate the probability of needing critical care., Results: The study enrolled 350 children from March 12, 2020, to July 1, 2020: 292 (83.4%) and 214 (73.7%) were considered to have relevant COVID-19, of whom 24.2% required critical care. Four major clinical syndromes of decreasing severity were identified: multi-inflammatory syndrome (MIS-C) (17.3%), bronchopulmonary (51.4%), gastrointestinal (11.6%), and mild syndrome (19.6%). Main risk factors were high C-reactive protein and creatinine concentration, lymphopenia, low platelets, anemia, tachycardia, age, neutrophilia, leukocytosis, and low oxygen saturation. These risk factors increased the risk of critical disease depending on the syndrome: the more severe the syndrome, the more risk the factors conferred. Based on our findings, we developed an online risk prediction tool (https://rserver.h12o.es/pediatria/EPICOAPP/, username: user, password: 0000)., Conclusions: Risk factors for severe COVID-19 include inflammation, cytopenia, age, comorbidities, and organ dysfunction. The more severe the syndrome, the more the risk factor increases the risk of critical illness. Risk of severe disease can be predicted with a Bayesian model., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Limited data exist regarding sex bias and viral decay in children with HIV. We investigated the sex differences in viral decay in 25 perinatally HIV-infected children. Females presented faster phase I viral decay regardless of their age at antiretroviral therapy (ART) initiation, baseline CD4 percentages, or baseline RNA levels. Also, for each month elapsed under ART, females had faster viral decay than males., (© The Author(s) 2021. Published by Oxford University Press on behalf of The Journal of the Pediatric Infectious Diseases Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Some clusters of children with a multisystem inflammatory syndrome (MIS-C) associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been reported. We describe the epidemiological and clinical features of children with MIS-C in Spain. MIS-C is a potentially severe condition that presents in children with recent SARS-CoV-2 infection., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)