dataesr/scientific-paragraphs-categorization huggingface dataset:
Introduction: Vascular endothelial growth factor (VEGF) has been implicated in mediating the effect of antidepressants (AD) and electroconvulsive therapy on depression since it plays a significant role in the neurogenesis. However, the serum VEGF level has not been investigated so far in association with rTMS treatment in patients with major depressive disorder (MDD). Objectives: The aim of our study was to compare the effect of the antidepressants and of the repetitive transcranial magnetic stimulation on the serum vascular endothelial growth factor and its association with the responsiveness to the treatments. Methods: A dataset of 50 patients with TRD who were treated with AD (n=33) and bilateral rTMS for 2x5 days (n=17) was analysed (sample 'rTMS&AD'). Montgomery-Asberg Depression Scale (MADRS) was used for monitoring the symptom changes.
Introduction: We conducted a national longitudinal survey among healthcare workers in the context of the Covid-19 pandemic, (1) to assess mental health and (2) to describe the results of an intervention to improve capacity of resilience. Non-participation is rarely studied despite being an important methodological matter when performing studies on mental health. Objectives: The study aims to describe and identify the factors associated with non-participation of healthcare workers to the intervention part of a national longitudinal study on the psychological impact of the COVID-19 pandemic. Methods: Participants were recruited from April to October 2021 via an Internet link widely disseminated. Data collected include participant' socio-demographic, occupational and working conditions, general health, professional burnout and mental health.
Acknowledgements The authors acknowledge collaborative support from the  Amsterdam Institute for Global Health and Development (AIGHD) ,  Netherlands  and the African Population and  Health Research Center (APHRC) in Nairobi, Kenya. We would like to thank all the participants for their valuable contributions to this study. We would also like to thank  Nina Schat  (AIGHD) and  Phyllis Mungai  (APHRC), our project management team for providing support and administrative coordination of the project activities. We are grateful to the  Ministry of Health Kenya , its partners, local county authorities and stakeholders that allowed us to carry out this facility health assessment survey.
Methods An online survey was fulfilled by 8 004 students at the University of Lorraine, using the Lime Survey software, for 4 days in April 2020. This survey has already been described in a previous publication  (Essadek and Rabeyron, 2020). Socio-demographic data have been collected about: age, gender, financial situation (precarious or not), housing (alone or with other people) and work. Data about COVID-19 exposure have also been assessed: contact with COVID-19 positive people, COVID-19 symptoms and COVID-19 diagnosis (by an MD or by a PCR). Students also fulfilled three mental health scales, validated in French, to measure levels of depression (Patient Health Questionnaire, PHQ-9; range 0-27)  Kroenke et al. , 2001) , anxiety (Generalized Anxiety Disorder, GAD-7; range 0-21)  (Spitzer et al.
Finally, bivariate analyses were performed to compare MS with and without symptoms of depression, anxiety and distress. We performed multivariate logistic regressions in MS only, in order to determine potential risk factors for symptoms of depression, anxiety and distress. All associated factors (p <. 20) in the bivariate analyses were included, including years of study, COVID-19 diagnosis, precarious situation, job. Only age was not included because of its collinearity with the years of study. The data analyses were performed by using R software (version 4. 0. 2). All tests were two-tailed. The significant level was set at <0. 05.
Methods We conducted a cross-sectional electronic survey in order to: (1) investigate the organizational characteristics of acute care facilities worldwide in preventing and managing infections in surgery; (2) assess participants' perception regarding ICP measures, antibiotic prescribing practices, and SC; (3) describe awareness about the global burden of AMR and IPC measures; and (4) determine the role of the coronavirus disease 2019 (COVID-19) pandemic on said awareness. The population target was represented by the HCWs registered in the database of the Global Alliance for Infections in Surgery (GAIS). A total of 1432 HCWs were contacted via e-mail with an invitation letter and a survey link (Google Docs, Alphabet Inc. , Mountain View, CA, USA). The survey was open for one month, between May 22, 2021, and June 22, 2021.
Three reminders were sent, after 7, 14, and 21 days. The selfadministered questionnaire (Additional File 1) was designed by a multidisciplinary team of investigators (including a surgeon, an epidemiologist, and an infectious disease physician) and was piloted among three physicians for face and content validity. The survey was written in English. Participation was voluntary but not anonymous; however, the confidentiality of respondents and their choices was ensured by de-identifying responses prior to data analysis. No incentives for participation were given. Data were automatically entered into an Excel database (Microsoft Corporation, Redmond, Washington, USA). Published recommendations for the development and implementation of web-based surveys were applied to the design of our questionnaire  [13, 14].
Statistical analysis Descriptive analysis for categorical variables is presented as frequency and percentage or median with interquartile range (IQR). Data regarding participants' perceptions and awareness were collapsed into four categories as follows: 1-4, not respected/important/involved/aware; 5-6, slightly respected/important/involved/aware; 7-8, respected/important/involved/aware; 9-10, very respected/important/involved/aware. Categorical data were compared by chi-square or Fisher exact tests, as appropriate, using Stata 11 software (StataCorp, College Station, TX, USA). All tests were two-sided; p-values < 0. 05 were considered significant.
Study sample, recruitment, and data collection Practitioners' panel To evaluate the content of the survey, a convenient sample of ten chiropractors aware of the NAD guidelines were invited to join the practitioners' panel. There were selected by the first author based on their age, and diversity and locations of their private practice (urban or rural). All chiropractors included in the panel were chiropractic interns' supervisors at the clinic and employed by IFEC. Potential participants were invited by email sent by the first author on November 12th, 2020. The online survey was available for 3 weeks from November 12th, 2020 to December 3rd, 2020. Three reminders were sent on November 19th and 26th, 2020 and on December 1st, 2020. If a positive response was sent by email, a weblink to the survey was proposed for potential participants in a second email.
Socio-demographic data and guidelines use indicators Sociodemographic data were collected by 9 questions (Additional file 2 written in French) including gender, age, academic year, and number of patients treated at this stage in the clinic. Indicators of guidelines utilization in clinical practice was measured using accepted international recommendations including French ones  [7] [8] [9] [10] [11] [12] [13]. According to the question about which guideline they used, participants were free to complete an openended question, if the guideline was not included in the proposed list. The use of guidelines was also inquired by asking participants if they used it to: (1) make a diagnosis; (2) choose a treatment; and (3) evaluate prognosis. Finally, the last question asked whether they attended a course about guidelines utilization during their undergraduate program.
Acknowledgements We thank  Charlène Cheron  (CC),  Arnaud Lardon  (AL),  Gaëtan Barbier  (GB),  Mégane Pasquier  (MP),  Florian Barbier-Cazorla  (FBC),  Claire Henriot-Jehel  ( CHG ) for taking part in the elaboration of the survey as researchers-chiropractors. We thank the participants for taking part in this study.
A concentration of 1. 1 nM of DNA was used. DNA sequencing data was acquired using NovaSeq control software NCS v1. 6. All information regarding samples, quality checks, experimental procedures, and the resulting data that was generated is available as Supplementary File 1. Metabolon Inc. (Durham, NC, USA) was contracted to conduct the metabolomics analysis for human faecal samples as previously described  [31]. Each sample extract was analysed on four independent instrument platforms: two different separate reverse phase ultra-high performance liquid chromatography-tandem mass spectroscopy analysis (RP/UPLC-MS/MS) with positive ion mode electrospray ionisation (ESI), a RP/UPLC-MS/MS with negative ion mode ESI, as well as a by hydrophilic-interaction chromatography (HILIC)/UPLC-MS/MS with negative ion mode ESI.
6-1  [40]. Random Forest classification of the 124 urine samples in which glyphosate could be measured, was performed by using faecal microbiome parameters as predictors using R package Caret (version 6. 0-84)  [41]. Since the two classes were not balanced (58 nonorganic food consumers and 66 organic food consumers), down-sampling was done prior to processing with the trainControl function. Input variables were scaled and centred. The optimisation of the number of variables for splitting at each tree node (mtry) was done with default parameters. Accuracy was estimated using repeated cross-validation (5-fold, repeated 10 times). The model was trained using 66% of the dataset while the quality of this model was evaluated using predicted sample classification of the remaining 34% of the dataset.
The quality control metrics were calculated using the confusionMatrix function from Caret. This function calculates the overall accuracy along a 95% confidence interval, with statistical significance of this accuracy evaluated with a one-side test comparing the experimental accuracy to the 'no information rate'. Shotgun metagenomics datasets were analysed with Rosalind, the BRC/King's College London high-performance computing cluster. First, data was pre-processed using the software package pre-processing v0. 2. 2 (https:// anaco nda. org/ fasni car/ prepr ocess ing). In brief, this package concatenates all forward reads into one file and all reverse reads into another file, and then uses trim_galore to remove Illumina adapters, trim lowquality positions and unknown positions (UN) and discard low-quality (quality < 20 or > 2 Ns) or too-short reads (< 75 bp).
This software package also removes contaminants (phiX and human genome sequences) and ultimately sorts and splits the reads into R1, R2 and UN sets of reads. The microbiome of human faecal samples was analysed using MetaPhlan3 (v 3. 0. 14) [42]  and Humann2 (v 0. 10)  [43]  with the UniRef90 database to characterise composition and function. While pesticides with a detection frequency over 80% were considered as continuous variables, those detected in 50-80% of the samples were dichotomized as detected/undetected as recommended by the European Human Biomonitoring Initiative (HMB4EU) and as previously described  [44]. Pesticides with detection frequencies below 20% were not carried forward in the association study (Table  1 ). The association study was conducted with a linear-mixed model considering age as a covariate and family relationship as a random effect with MaAsLin (Microbiome Multivariable Association with Linear Models) 2.
0 (package version 0. 99. 12) [45]. Metagenome taxa detected in less than 20% of the individuals were removed and 211 species were carried forward for the association analysis. The metabolome data was log-transformed, while the metagenome taxonomic composition was transformed using an arcsine square root transformation. The Benjamini-Hochberg method was used to control the False Discovery Rate (FDR) of the MaAsLin analysis. Shannon and Simpson diversity indices, and species richness, were calculated with the vegan R package version 2. 5-6  [46]. Nonmetric multidimensional scaling of Bray-Curtis dissimilarity with stable solution from random starts, with axis scaling, was performed with vegan R package  [46]. Statistical significance of Bray-Curtis dissimilarity differences according to pesticide residue levels was calculated by Permutational Multivariate Analysis Of Variance (PER-MANOVA) with 1000 permutations  [47].
In this case, when a value is 0, it is not clear whether the species is absent or undetected. In addition, a large number of unidentified factors influence the results of gut microbiome studies  [73]. These factors can be technical covariates such as the DNA extraction procedure  [35, 74] , or the sequencing approach  [75] , demographic differences  [76] , lifestyle changes such as the intake of prescription medications  [77] , alcohol consumption frequency and bowel movement quality  [78] , or even socioeconomic factors  [79]. In addition, there is no gold standard for hardware and software for taxonomic assignment of shotgun metagenomics datasets  [80]. Our study is thus a first step towards the understanding of pesticide-induced gut microbial changes in human populations, but larger studies will be needed.
This is approved by both the French authorities and international standards of data protec- The hosting providers are also certified by the main international standards, including ISO/IEC 27001, and are audited annually by an independent body. ). Some patients proposed a vulval examination by video during the VC. This live video vulval examination was accepted by the physician if no photo was available or if the images were of poor quality. During the 3 month period between March to May 2020, anonymized data on all consecutive VCs were collected prospectively using a standardized electronic database. Data collected included clinical information such as age and diagnosis, as well as information on the consultation, such as whether the consultation was a new or follow-up appointment and whether supplementary imaging (photographs and/or videos) was submitted by the patient.
Where relevant, the number of photographs sent by each patient was recorded and their collective quality was assessed according to a five-point Likert-type scale, rated from 1 (poor quality) to 5 (excellent quality). Data on outcomes such as physician certainty of the diagnosis in new patient consultations ('certain', 'probable' or 'no diagnosis made') and the need for further in-person consultation were also recorded ('immediate in-person consultation required', 'no inperson consultation required and discharged' and 'delayed follow-up booked'). Global physician assessment of the perceived usefulness of VC was graded on a five-point Likert-type scale from 1 ('useless') to 5 ('extremely useful'). Analyzed data were stratified according to the consultation type (new or follow-up) and whether supplementary imaging (photographs or video) were received.
| RESULTS A total of 316 patients from London (n = 199) and Paris (n = 117) were included. Mean age in all patients was 45. 4 years (range 0. 5-94 years) and was comparable when stratified according to clinical site (London mean age 47. 4 years, standard deviation [SD] 21. 1; Paris mean age 42. 0, SD 15. 0). Overall, 18. 7% (n = 59) were new patient consultations and 81. 3% (n = 257) were follow-up. A higher proportion of consultations were for new patients in the Parisian clinics compared to London (45. 3% vs. 3. 0%). Further data on the clinical and consultation characteristics are summarized in Table  1. Those who provided supplementary imaging as photographs and/ or video recordings represented 28. 5% (n = 90) of the total cohort. Notably, a higher proportion of patients attending for new consultations provided supplementary imaging (83.
Conclusion: The most frequent sedation includes an association between an opioid and a benzodiazepine. Non-drug cares are widely used. Though recommended, scores are not often used. Rationale: Computer vision has promising potential for the diagnosis of vital distress in critically ill patients including neurological, respiratory and hemodynamic distress. For instance, measurement of respiratory rate using 3D videos in spontaneous breathing patients and correlation between low cardiac output and thermal distribution using infrared (IR) images were reported in several studies. The aim of our research was to setup a multi-modal video infrastructure to create a clinical video research database and pave the way to real-time vital distress video monitoring within a pediatric intensive care unit (PICU).
Patients and methods/Materials and methods: The specifications of the infrastructure were developed by an interdisciplinary team including clinicians, computer scientists, and hospital information technology personnel. These specifications took into account the requirements of the research ethics board: (1) a multimodal video system (MMVS) that is able to capture color (RGB) videos for neurological distress analysis, 3D videos for respiratory distress analysis and thermal videos for hemodynamic analysis; (2) a MMVS in each room on the ceiling above the patient's bed; (3) security systems to only register videos of patients who have consented to the study;  (4)  automatic data storage on the hospital private servers;  (5)  synchronization of the videos with clinical data collected simultaneously; (6) data classification in a research database.
Results: The MMVS developed included a hardware and a software component (Fig. 1 ). The hardware component consisted of a NVIDIA Jetson Xavier NX mini-computer that has a built-in GPU (NVIDIA Corp, USA) connected to a Kinect Azure RGB-3D camera (Microsoft, USA) and a FLIR Lepton 3. 5 thermal sensor (Teledyne FLIR, USA). Both cameras are pointed towards the patient and are placed in a 3D printed support. The software component included a web user interface for performing the acquisitions in the hospital intranet in a secure manner. The video research database currently includes more than 200 acquisitions and is being used in various studies to assess vital distress signs including facial expressions to estimate sedation level and consciousness using RGB videos, the refinement of tidal volume and respiratory rate measurements in patients using 3D videos, and estimation of the thermal gradient across various parts of the body using IR.
Patients and methods/Materials and methods: Prospective study (NCT04386720). We recorded the low flow PV curve without PEEP of the ventilator in order to assess airway closure and the recruited volume. 1 AT the same time with EIT we analyzed the derived PV curves of each lung. 2 A difference of tidal ventilation of at least 20% between the 2 lungs was considered as asymmetrical ARDS. We compared respiratory mechanic between the 2 lungs in patients with asymmetrical ARDS. Results: We analyzed 26 patients, 18 patients had asymmetrical lung injury, the most injured lung received 28. 5 ± 8. 0% of the tidal ventilation, its compliance was significantly lower than the less injured lung: 11. 9 ± 7. 8 vs 28. 8 ± 14. 3 ml cmH 2 O-1p < 0. 0001 respectively. Thirteen patients had airway closure with an airway opening pressure > 4 cmH 2 O; Global PV curve AOP was 6.
However, the oximeters' accuracy appears to vary widely from model to model, leading to an underestimation or an overestimation of actual SaO 2 values. This variability may represent an obstacle to an optimal delivery of oxygen therapy, including the implementation of guidelines. The objective of this study was to assess the accuracy and bias of the SpO 2 value measured by several oximeters compared to the reference value, arterial oxygen saturation (SaO 2 ) measured by arterial gases in intubated and spontaneously breathing patients in the intensive care unit. Patients and methods/Materials and methods: (ClinicalTrials. gov ID: NCT04772183) The study was approved by the local ethics board with a waiver of consent. We included stable patients hospitalized in the ICU with an arterial catheter in place.
CO-81 Differences in clinical characteristics and outcomes between Covid-19 and influenza in critically ill adult patients: a national database study NAOURI Diane 6 , PHAM Tai 2 , DEMOULE Alexandre 2 , MERCAT Alain 5 , BEDUNEAU Gaetan 3 , COMBES Alain 2 , KIMMOUN Antoine 4 , SCHMIDT Matthieu 2 , DRES Martin 2 , JAMME Matthieu 1 1 Hopital privé de l'ouest parisien, Trappes, France; 2 Assistance publique hopitaux de Paris, Paris, France; 3 CHU Rouen, Rouen, France; 4 CHU Nancy, Nancy, France; 5 CHU Angers, Angers, France; 6 Direction de la recherche, des études, de l'évaluation et des statistiques, Paris, France Correspondence: Matthieu JAMME (mat. jamme@gmail. com) Annals of Intensive Care 2022, 12(1):CO-81 Rationale: Until March 2020 and the emergence of coronavirus disease 2019 (COVID-19), influenza was the leading cause of viral acute respiratory failure observed in ICU.
While a few studies have compared flu patients vs. COVID-19, none of them have focused on the most severe forms. The aim of this study is to compare ICU patients admitted for COVID-19 vs. those admitted with influenza. Patients and methods/Materials and methods: We conducted a retrospective cohort study using the French administrative health database (Système National des Données de Santé, SNDS). We included all adult patients hospitalised in French ICUs for whom a complete hospital history was available from 1 March 2020 to 30 June 2021. For the comparative group (influenza cohort), all adult patients hospitalised in ICUs from 1 January 2014 to 31 December 2019 were included. To be included in one of these two groups, the patient had to have an ICD-10 diagnosis code of COVID-19 or influenza regardless of its position in the hospital stay summary.
The cerebral oximetry index (COx) estimates CAR by correlating regional cerebral oxygenation and MAP. By plotting COx against MAP, the optimal MAP (opt-MAP) and the lower and upper limits of MAP corresponding to optimal CAR (LLA and ULA) can be determined. Our aim was to evaluate the feasibility of continuously determining the opt-MAP, LLA, and ULA in children within 48 h of cardiac surgery and to describe CAR parameters according to age and postoperative time frame. Patients and methods/Materials and methods: Using a high-frequency database, we retrospectively included all children admitted in a single pediatric intensive care unit (PICU) after cardiac surgery between May 2020 and June 2021. An algorithm for the continuous calculation of the opt-MAP, ULA, and LLA was developed using a weighted combination of 40 time windows for the calculation of COx and opt-MAP.
We collected demographic and anthropometric parameters, underlying comorbidities, nephrotoxic medicine prescription, clinical features of the acute renal failure with the KDIGO grade, mechanical ventilation characteristics, requirement of kidney replacement therapy and outcomes. Data analysis was performed using SPSS 28. 0 software. Results: During our study period, 147 patients were admitted in our ICU. AKI incidence was 52,2% (71 patients out of 147). According to KDIGO criteria, 16. 9% were staged KDIGO 1, 35. 2% KDIGO 2 and 47. 8% KDIGO 3. The mean age was 61 years, ranged from 27 to 93 years. 38% were considered as elderly (> 65 years old). The main comorbidities were arterial hypertension (66%), diabetes mellitus (54. 9%), atrial fibrillation (28. 1%) and obesity (22. 5%). Acute kidney injury occurred mainly around the 6th day of ICU and resolved after 7 days.