Two-lung ventilation with artificial pneumothorax on cerebral desaturation and early postoperative cognitive outcome: a randomized controlled trial.

BACKGROUND: The effect of two lung ventilation (TLV) with carbon dioxide artificial pneumothorax on cerebral desaturation and postoperative neurocognitive changes in elderly patients undergoing elective minimally invasive esophagectomy (MIE) is unclear. OBJECTIVES: The first aim of this study was to compare the effect of TLV and one lung ventilation (OLV) on cerebral desaturation. The second aim was to assess changes in early postoperative cognitive outcomes of two ventilation methods. METHODS: This prospective, randomized, controlled trial enrolled patients 65 and older scheduled for MIE. Patients were randomly assigned (1:1) to TLV group or OLV group. The primary outcome was the incidence of cerebral desaturation events (CDE). Secondary outcomes were the cumulative area under the curve of desaturation for decreases in regional cerebral oxygen saturation (rSO2) values below 20% relative to the baseline value (AUC.20) and the incidence of delayed neurocognitive recovery. RESULTS: Fifty-six patients were recruited between November 2019 and August 2020. TLV group had a lower incidence of CDE than OLV group [3 (10.71%) vs. 13 (48.14%), P = 0.002]. TLV group had a lower AUC.20 [0 (0-35.86) % min vs. 0 (0-0) % min, P = 0.007], and the incidence of delayed neurocognitive recovery [2 (7.4%) vs. 11 (40.7%), P = 0.009] than OLV group. Predictors of delayed neurocognitive recovery on postoperative day 7 were age (OR 1.676, 95% CI 1.122 to 2.505, P = 0.006) and AUC.20 (OR 1.059, 95% CI 1.025 to 1.094, P < 0.001). CONCLUSION: Compared to OLV, TLV had a lower incidence of CDE and delayed neurocognitive recovery in elderly patients undergoing MIE. The method of TLV combined with carbon dioxide artificial pneumothorax may be an option for these elderly patients. Chinese Clinical Trial Registry (identifier: ChiCTR1900027454).

[Advances in nanobody screening technology].

Nanobody (Nb) is a novel type of antibody discovered in the serum of Camelidae. It is characterized by its small size, high specificity, stability, and ease of preparation. Nanobodies exhibit the ability to identify hidden epitopes and have diverse applications across various fields. This review aims to introduce three key stages in the screening and optimization of nanobodies, including nanobody library construction, in vitro surface display, and affinity maturation. We provide a brief description of preparation and characteristics of natural, immunological, and semi-synthetic/synthetic libraries. Additionally, we systematically explain eight in vitro display methods, including phage display, yeast display, bacterial display, ribosome display/mRNA display, and eukaryotic cell display. Furthermore, we discuss the application of yeast two-hybrid system high-throughput sequencing and mass spectrometry identification. A thorough analysis of their advantages and limitations is presented in this protocols. Finally, we summarize the platforms for in vitro or computer-aided affinity maturation techniques aimed at enhancing the functional stability of nanobodies. Consequently, this review provides a comprehensive approach to the integrated utilization of various technologies for the rapid development of stable, reliable, and specific nanobody-based drugs or diagnostic agents.

Antipsychotics and the QTc Interval During Delirium in the Intensive Care Unit: A Secondary Analysis of a Randomized Clinical Trial.

Importance: Antipsychotic medications, often prescribed for delirium in intensive care units (ICUs), may contribute to QTc interval prolongation. Objective: To determine whether antipsychotics increase the QTc interval in patients with delirium in the ICU. Design, Setting, and Participants: An a priori analysis of a randomized clinical trial in medical/surgical ICUs within 16 centers across the US was conducted. Participants included adults with delirium in the ICU with baseline QTc interval less than 550 ms. The study was conducted from December 2011 to August 2017. Data analysis was performed from April 25 to August 18, 2021. Interventions: Patients were randomized 1:1:1 to intravenous haloperidol, ziprasidone, or saline placebo administered twice daily until resolution of delirium, ICU discharge, or 14 days. Main Outcomes and Measures: Twelve-lead electrocardiograms were used to measure baseline QTc before study drug initiation and telemetry was used to measure QTc before each subsequent dose of study drug. Unadjusted day-to-day changes in QTc were calculated and multivariable proportional odds regression was used to estimate the effects of antipsychotics vs placebo on next-day maximum QTc interval, adjusting for prespecified baseline covariates and potential interactions with sex. Safety end points, including the occurrence of torsade de pointes, were evaluated. All analyses were conducted based on the intention to treat principle. Results: A total of 566 patients were randomized to haloperidol (n = 192), ziprasidone (n = 190), or placebo (n = 184). Median age was 60.1 (IQR, 51.4-68.7) years; 323 were men (57%). Baseline median QTc intervals across the groups were similar: haloperidol, 458.0 (IQR, 432.0-479.0) ms; ziprasidone, 451.0 (IQR, 424.0-472.0) ms; and placebo, 452.0 (IQR, 432.0-472.0) ms. From day 1 to day 2, median QTc changed minimally: haloperidol, -1.0 (IQR, -28.0 to 15.0) ms; ziprasidone, 0 (IQR, -23.0 to 20.0) ms; and placebo, -3.5 (IQR, -24.8 to 17.0) ms. Compared with placebo, neither haloperidol (odds ratio [OR], 0.95; 95% CI, 0.66-1.37; P = .78) nor ziprasidone (OR, 1.09; 95% CI, 0.75-1.57; P = .78) was associated with next-day QTc intervals. Effects were not significantly modified by sex (P = .41 for interaction). There were 2 occurrences of nonfatal torsade de pointes, both in the haloperidol group. Neither was associated with study drug administration. Conclusions and Relevance: The findings of this trial suggest that daily QTc interval monitoring during antipsychotic use may have limited value in patients in the ICU with normal baseline QTc and few risk factors for QTc prolongation. Trial Registration: ClinicalTrials.gov Identifier: NCT01211522.

Evaluation of MERRA-2 and CAMS reanalysis for black carbon aerosol in China.

Black carbon (BC) constitutes a pivotal component of atmospheric aerosols, significantly impacting regional and global radiation balance, climate, and human health. In this study, we evaluated BC data in two prominent atmospheric composition reanalysis datasets: the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and the Copernicus Atmosphere Monitoring Service (CAMS), and analyzed the causes of their deviations. This assessment is based on observational data collected from 34 monitoring stations across China from 2006 to 2022. Our research reveals a significant and consistent decline in BC concentrations within China, amounting to a reduction exceeding 67.33%. However, both MERRA-2 and CAMS reanalysis data fail to capture this declining trend. The average annual decrease of BC in MERRA-2 from 2006 to 2022 is only 0.06 µg/m3 per year, while the BC concentration in CAMS even increased with an average annual value of 0.014 µg/m3 per year. In 2022, MERRA-2 had overestimated BC concentration by 20% compared to observational data, while CAMS had overestimated it by approximately 66%. In the regional BC concentration analysis, the data quality of the reanalysis data is better in the South China (RM = 0.59, RC = 0.53), followed by the North China (RM = 0.50, RC = 0.42). Reanalysis BC data in Northwest China and the Tibetan Plateau are difficult to use for practical analysis due to their big difference with observation. In a comparison of the anthropogenic BC emissions inventory used in the two atmospheric composition reanalysis datasets with the Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC) emissions inventory, we found that: Despite the significant decline in China's BC emissions, MERRA-2 still relies on the 2006 emissions inventory, while CAMS utilizes emission inventories that even show an increasing trend. These factors will undoubtedly lead to greater deviations between reanalysis and observational data.

Association between nasopharyngeal colonization with multiple pneumococcal serotypes and total pneumococcal colonization density in young Peruvian children.

OBJECTIVES: We examined the association of nasopharyngeal (NP) pneumococcal co-colonization (>1 pneumococcal serotype) and pneumococcal density in young Peruvian children enrolled in a prospective cohort study. METHODS: NP swabs collected monthly from children aged <3 years during both asymptomatic and acute respiratory illness (ARI) periods underwent culture-enriched microarray for pneumococcal detection and serotyping and lytA polymerase chain reaction for density assessment. We examined the serotypes commonly associated with co-colonization and the distribution of densities by co-colonization, age, current ARI, and other covariates. The association of co-colonization and pneumococcal density was assessed using a multivariable mixed-effects linear regression model, accounting for repeated measures and relevant covariates. RESULTS: A total of 27 children contributed 575 monthly NP samples. Pneumococcus was detected in 302 of 575 (53%) samples, and co-colonization was detected in 61 of these 302 (20%). The total densities were higher during ARI than non-ARI periods and lowest among the youngest children, increasing with age. In the multivariable analysis, there was no significant association between pneumococcal density and co-colonization (coefficient estimate 0.22, 95% confidence interval 0.11-0.55; reference: single-serotype detections). Serotypes 23B and 19F were detected significantly more frequently as single isolates. CONCLUSION: Pneumococcal co-colonization was common and not associated with increased pneumococcal density. Differential propensity for co-colonization was observed among individual serotypes.

Research progress of child athlete’s speech sound disorders

Child athletes with speech sound disorders may experience difficulties communicating with coaches, teammates, and others in sports-related contexts. To improve communication abilities and overall athletic performance, research has made progress in exploring the impact of speech therapy and exercise programs on child athletes with speech sound disorders. These programs aim to enhance neural connections between the brain regions responsible for speech production and motor skills needed for sports, as well as boost confidence in social situations. By utilizing advanced diagnostic tools, such as speech sound assessments and imaging techniques, researchers have identified new methods for identifying and treating speech sound disorders in child athletes. This paper reviews the recent research progress on child athlete's speech sound disorders, discussing the implications for speech therapy and exercise programs in sports training, as well as the potential for improved communication and athletic performance. (AU)

Description and evaluation of a newly developed emission inventory processing system (EMIPS).

Commonly available emission inventories are often incompatible with the input requirements of atmospheric chemistry models due to temporal and spatial resolution, pollutant types, etc. We present the Emission Inventory Processing System (EMIPS) version 1, an open-source and multi-scale atmospheric emission modeling framework that prepares specific emissions inputs for atmospheric chemistry models. EMIPS is a multifunctional and user-friendly system, coded in Jython and developed on the MeteoInfo software platform. It allows users to freely combine and process emission inventories to generate model-ready emissions data. The core functions of EMIPS include preprocessing, temporal allocation, spatial allocation, chemical speciation, and vertical allocation. We detail the implementation of each function in the body of this paper, and several examples are provided for illustration. The emission outputs obtained with EMIPS have been evaluated by simulating four pollutants (PM2.5, PM10, NO2, and O3) concentrations in January 2017 using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), and comparison of model results with the observations indicates the model can reproduce the temporal and spatial patterns of pollutants, suggesting that EMIPS is capable of supporting atmospheric chemistry modeling. We expect this work could help to improve air quality research and forecast.

A repository for the publication and sharing of heterogeneous materials data.

National Materials Data Management and Service platform (NMDMS) is a materials data repository for the publication and sharing of heterogeneous materials scientific data and follows the FAIR principles: Findable, Accessible, Interoperable, and Reusable. To ensure data are 'Interoperable, NMDMS uses a user-friendly semi-structured scientific data model, named dynamic container', to define, exchange, and store heterogeneous scientific data. Then, a personalized yet standardized data submission subsystem, a rigorous project data review and publication subsystem, and a multi-granularity data query and retrieval subsystem collaboratively make data 'Reusable', 'Findable', and 'Accessible'. Finally, China's "National Key R&D Program: Material Genetic Engineering Key Special Project" has adopted NMDMS to publish and share its project data. There are 12,251,040 pieces of data published in NMDMS since 2018, under 87 categories and 1,912 user-defined schemas from 45 projects. The platform has been accessed 908875 times, and 2403,208 pieces of data have been downloaded. In short, NMDMS effectively accelerates the publication and sharing of material project data in China.

Association between cholinesterase activity and critical illness brain dysfunction.

BACKGROUND: Delirium is a frequent manifestation of acute brain dysfunction and is associated with cognitive impairment. The hypothesized mechanism of brain dysfunction during critical illness is centered on neuroinflammation, regulated in part by the cholinergic system. Point-of-care serum cholinesterase enzyme activity measurements serve as a real-time index of cholinergic activity. We hypothesized that cholinesterase activity during critical illness would be associated with delirium in the intensive care unit (ICU) and cognitive impairment after discharge. METHODS: We enrolled adults with respiratory failure and/or shock and measured plasma acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) activity on days 1, 3, 5, and 7 after enrollment. AChE values were also normalized per gram of hemoglobin (AChE/Hgb). We assessed for coma and delirium twice daily using the Richmond Agitation Sedation Scale and the Confusion Assessment Method for the ICU to evaluate daily mental status (delirium, coma, normal) and days alive without delirium or coma. Cognitive impairment, disability, and health-related quality of life were assessed at up to 6 months post-discharge. We used multivariable regression to determine whether AChE, AChE/Hgb, and BChE activity were associated with outcomes after adjusting for relevant covariates. RESULTS: We included 272 critically ill patients who were a median (IQR) age 56 (39-67) years and had a median Sequential Organ Failure Assessment score at enrollment of 8 (5-11). Higher daily AChE levels were associated with increased odds of being delirious versus normal mental status on the same day (Odds Ratio [95% Confidence Interval] 1.64 [1.11, 2.43]; P = 0.045). AChE/Hgb and BChE activity levels were not associated with delirious mental status. Lower enrollment BChE was associated with fewer days alive without delirium or coma (P = 0.048). AChE, AChE/Hgb, and BChE levels were not significantly associated with cognitive impairment, disability, or quality of life after discharge. CONCLUSION: Cholinesterase activity during critical illness is associated with delirium but not with outcomes after discharge, findings that may reflect mechanisms of acute brain organ dysfunction. TRIAL REGISTRATION: NCT03098472. Registered 31 March 2017.

Case report and literature review: Novel compound heterozygous FIG4 variants causing both of peripheral and central nervous system defects.

Background: Pathogenic variants in the FIG4 gene have been described to be associated with a diverse spectrum of syndromes, such as autosomal recessive bilateral temporooccipital polymicrogyria (OMIM 612691), autosomal dominant amyotrophic lateral sclerosis-11 (ALS11; OMIM 612577), autosomal recessive Charcot-Marie-Tooth disease, type 4J (CMT4J; OMIM 611228), and autosomal recessive Yunis-Varon syndrome (YVS; OMIM 216340). Heterozygous FIG4 variants are responsible for ALS11 characterized by progressive muscular weakness, atrophy, and bulbar palsy. CMT4J is a disorder of peripheral nervous system defects mainly presenting with a highly variable onset of proximal and/or distal muscle weakness. YVS is a disorder of severe neurological involvement with central nervous system (CNS) dysfunction and extensive skeletal anomalies. Case Presentation: We reported two Chinese siblings born with a weakness in all limbs. They experienced rapidly progressive weakness in distal limbs. At the age of 6 years, the elder brother presented with severe scoliosis and cervical kyphosis. They both had global developmental delay and a CNS involvement with cognitive deficits and swallowing problems. Genetic screening in the patients' family for inherited diseases was recommended. Novel compound heterozygous variants in the FIG4 gene (c.2148delTinsAA and c.317A > G) were found by whole-exome sequencing in the patients. These variants were confirmed by Sanger sequencing in family members. Conclusions: Herein, we reported two Chinese male patients with CMT4J who presented with abnormal CNS features. CMT4J with CNS involvement has been very rarely reported. We hoped this study could expand the phenotypic and genetic spectrum of FIG4-related diseases. And we helped physicians to understand the genotype-phenotype correlation.

Factors Associated With Radioactive Iodine Therapy-Acquired Nasolacrimal Duct Obstruction.

OBJECTIVE: To identify factors associated with radioactive iodine (RAI)-acquired nasolacrimal duct obstruction (NLDO). METHODS: Retrospective chart review and telephone surveys of patients who received RAI therapy for thyroid carcinoma at an academic institution were conducted. Telephone surveys were used to screen for post-RAI NLDO diagnoses. Databases were reviewed for documented NLDO, demographics, RAI dose, total number of RAI treatments, and sialadenitis. Routine post-RAI whole-body scintigraphy (WBS) images were analyzed for the presence or absence of 131I sodium iodide (I-131) in the nasolacrimal duct. Intranasal I-131 activity was graded as none, low, moderate, and high; those with moderate or high activity were considered to have "increased" activity. Logistic and ordinal logistic regression models were used to evaluate the associations with NLDO while adjusting for I-131 dose. RESULTS: Of the 209 patients who completed the survey, 15 (7%) had NLDO diagnoses. Increased intranasal I-131 activity on WBS, presence of nasolacrimal I-131 WBS activity, presence of documented post-RAI sialadenitis, and history of >1 RAI treatment were associated with the development of NLDO from univariate analyses (P ≤ .013). After adjusting for the administered dose of I-131, the presence of sialadenitis and nasolacrimal I-131 activity on WBS were the remaining 2 factors significantly associated with NLDO development (P < .001 and P = .01, respectively). CONCLUSIONS: The presence of sialadenitis and nasolacrimal I-131 activity on WBS are I-131 dose-independent correlative factors for RAI-associated NLDO. Patients with these characteristics should be counseled on their increased risk of NLDO after RAI therapy for thyroid carcinoma.

Correlations of FRMD7 gene mutations with ocular oscillations.

Mutations in the FERM domain containing 7 (FRMD7) gene have been proven to be responsible for infantile nystagmus (IN). The purpose of this study is to investigate FRMD7 gene mutations in patients with IN, and to evaluate the nystagmus intensity among patients with and without FRMD7 mutations. The affected males were subdivided into three groups according to whether or not having FRMD7 mutations and the types of mutations. Fifty-two mutations were detected in FRMD7 in 56 pedigrees and 34 sporadic patients with IN, including 28 novel and 24 previous reported mutations. The novel identified mutations further expand the spectrum of FRMD7 mutations. The parameters of nystagmus intensity and the patients' best corrected visual acuity were not statistically different among the patients with and without identified FRMD7 mutations, and also not different among patients with different mutant types. The FERM-C domain, whose amino acids are encoded by exons 7, 8 and 9, could be the harbor region for most mutations. Loss-of-function is suggested to be the common molecular mechanism for the X-linked infantile nystagmus.

Sulfur recycle in biogas production: Novel Higee desulfurization process using natural amino acid salts.

In this work, a desulfurization method using natural amino acid salts (AAS), which can be green prepared by biological fermentation, is proposed to remove H2S from raw biogas. Biogas purification and fertilizer production can be simultaneously achieved to close sulfur recycle. The reaction kinetic characteristics of H2S absorption with three kinds of AAS, including potassium ß-alaninate (PA), potassium sarcosinate (PS) and potassium l-prolinate (PP) are first studied. Kinetic parameters including orders of reaction, rate constants, pre-exponential factors and activation energies are given. AAS absorbent exhibits good potential for biogas desulfurization. Higee (high gravity) technology is utilized to intensify H2S removal. The effects of operating conditions on H2S removal efficiency are investigated and PP shows the best desulfurization performance. The phytotoxicity of AAS and amino acid salt sulfide (AASS) is assessed by the germination index of mungbean seeds. PP and its salt sulfide (PPS) show relatively low phytotoxicity and their allowable agricultural feeding concentrations are below 0.08 M and 0.04 M, respectively. The desulfurization method demonstrates a green route for biogas purification to achieve sulfur recycle.

The incidence of elder abuse under East Asian cultural background: A systematic review and meta-analysis.

OBJECTIVE: Elder abuse (EA) is a critical social, health, and economic issue worldwide. To date, there is limited information on EA in certain similar culture-specific subpopulations, especially in East Asia. This study aims to summarize EA incidence in East Asia through a systematic review and meta-analysis and identify its variations and heterogeneity in the incidence estimates. METHODS/DESIGN: The study followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses protocol. Systematic review registration number PROSPERO CRD42020197131. A systematic literature search was performed to identify relevant articles published before July 5th, 2020, from six electronic databases. Two reviewers screened for relevance of the studies against eligible criteria and assessed the bias of the included studies independently. A random-effect model was adopted to estimate the incidence of EA, followed by subgroup analyses and multi meta-regression. Sensitivity and publication bias tests were performed to verify the robustness of the meta-analysis by Stata version 15.1. RESULTS: Twelve eligible studies were included in the meta-analysis, which involved 79,395 subjects from 3 East Asian countries (China, Japan, and South Korea) ranging from 2004 to 2020. The overall incidence of EA was 78.33 per 1000 person-year (95% CI: 39.12-156.87) with high between-study variability (χ2  = 15,568, d.f. = 11, p<0.001; I2  = 99.9%). The sampling method, sample size, scope, instrument, data collection method, income classification, types of participants, and urbanity are all the sources of heterogeneity, which can explain nearly 100% of the variance between studies. CONCLUSIONS: The incidence of EA in this study is not as high as the global level. It may be furtherly underestimated in East Asia due to cultural norms. It is imperative to develop a culture-tailored EA assessment instrument to evaluate potential victims. Future studies should also identify more effective educational programs to raise the public's awareness and promote recognition ability.

Predicting brain function status changes in critically ill patients via Machine learning.

OBJECTIVE: In intensive care units (ICUs), a patient's brain function status can shift from a state of acute brain dysfunction (ABD) to one that is ABD-free and vice versa, which is challenging to forecast and, in turn, hampers the allocation of hospital resources. We aim to develop a machine learning model to predict next-day brain function status changes. MATERIALS AND METHODS: Using multicenter prospective adult cohorts involving medical and surgical ICU patients from 2 civilian and 3 Veteran Affairs hospitals, we trained and externally validated a light gradient boosting machine to predict brain function status changes. We compared the performances of the boosting model against state-of-the-art models-an ABD predictive model and its variants. We applied Shapley additive explanations to identify influential factors to develop a compact model. RESULTS: There were 1026 critically ill patients without evidence of prior major dementia, or structural brain diseases, from whom 12 295 daily transitions (ABD: 5847 days; ABD-free: 6448 days) were observed. The boosting model achieved an area under the receiver-operating characteristic curve (AUROC) of 0.824 (95% confidence interval [CI], 0.821-0.827), compared with the state-of-the-art models of 0.697 (95% CI, 0.693-0.701) with P < .001. Using 13 identified top influential factors, the compact model achieved 99.4% of the boosting model on AUROC. The boosting and the compact models demonstrated high generalizability in external validation by achieving an AUROC of 0.812 (95% CI, 0.812-0.813). CONCLUSION: The inputs of the compact model are based on several simple questions that clinicians can quickly answer in practice, which demonstrates the model has direct prospective deployment potential into clinical practice, aiding in critical hospital resource allocation.

Dealing with missing delirium assessments in prospective clinical studies of the critically ill: a simulation study and reanalysis of two delirium studies.

BACKGROUND: In longitudinal critical care studies, researchers may be interested in summarizing an exposure over time and evaluating its association with a long-term outcome. For example, the number of days a patient has delirium (i.e., brain dysfunction) during their critical care stay is associated with the presence and severity of long-term cognitive problems. In large pragmatic trials and multicenter observational studies, particularly when electronic medical record data is used, the information on daily exposure status may be available at some time points and not at others. Model-based multiple imputation is a well-established, widely adopted method to deal with missing data. But the uncertainty around multiple imputation for summary exposure variables is whether the imputation is to be performed at the summary level or at the daily assessment level. METHODS: We compare the following approaches to imputing and summarizing partially missing longitudinal data: 1) active imputation, where we impute the summary; 2) passive imputation, where we impute the daily missing data, and then compute the summary; 3) ad hoc methods where we assume all missing time points have the a) most or the b) least extreme value; and 4) complete case analysis where only participants with complete data are analyzed. These methods were applied under different missingness mechanisms, varying proportions of missingness, and association of missingness with an auxiliary variable using simulations that closely mirrors real-life critical care data to be relevant to real-world clinical practice. The performance of the approaches were compared using bias of the estimated coefficients, standard error of the estimate and coverage. We also apply these imputation strategies to two datasets in critical care. RESULTS: Simulations show that all methods performed comparably when the proportion of missingness was small, indicating that in such instances, the gain over using any imputation model is minimal. But as the proportion of missingness increases, the passive imputation approach provides efficient and less biased estimates under the missingness at random and missingness completely at random mechanism. CONCLUSIONS: For longitudinal data where a summary exposure is of interest, we recommend practitioners adopting the passive imputation strategy.

AI detection of mild COVID-19 pneumonia from chest CT scans.

OBJECTIVES: An artificial intelligence model was adopted to identify mild COVID-19 pneumonia from computed tomography (CT) volumes, and its diagnostic performance was then evaluated. METHODS: In this retrospective multicenter study, an atrous convolution-based deep learning model was established for the computer-assisted diagnosis of mild COVID-19 pneumonia. The dataset included 2087 chest CT exams collected from four hospitals between 1 January 2019 and 31 May 2020. The true positive rate, true negative rate, receiver operating characteristic curve, area under the curve (AUC) and convolutional feature map were used to evaluate the model. RESULTS: The proposed deep learning model was trained on 1538 patients and tested on an independent testing cohort of 549 patients. The overall sensitivity was 91.5% (195/213; p < 0.001, 95% CI: 89.2-93.9%), the overall specificity was 90.5% (304/336; p < 0.001, 95% CI: 88.0-92.9%) and the general AUC value was 0.955 (p < 0.001). CONCLUSIONS: A deep learning model can accurately detect COVID-19 and serve as an important supplement to the COVID-19 reverse transcription-polymerase chain reaction (RT-PCR) test. KEY POINTS: • The implementation of a deep learning model to identify mild COVID-19 pneumonia was confirmed to be effective and feasible. • The strategy of using a binary code instead of the region of interest label to identify mild COVID-19 pneumonia was verified. • This AI model can assist in the early screening of COVID-19 without interfering with normal clinical examinations.

Prevalence and risk factors for delirium in critically ill patients with COVID-19 (COVID-D): a multicentre cohort study.

BACKGROUND: To date, 750 000 patients with COVID-19 worldwide have required mechanical ventilation and thus are at high risk of acute brain dysfunction (coma and delirium). We aimed to investigate the prevalence of delirium and coma, and risk factors for delirium in critically ill patients with COVID-19, to aid the development of strategies to mitigate delirium and associated sequelae. METHODS: This multicentre cohort study included 69 adult intensive care units (ICUs), across 14 countries. We included all patients (aged ≥18 years) admitted to participating ICUs with severe acute respiratory syndrome coronavirus 2 infection before April 28, 2020. Patients who were moribund or had life-support measures withdrawn within 24 h of ICU admission, prisoners, patients with pre-existing mental illness, neurodegenerative disorders, congenital or acquired brain damage, hepatic coma, drug overdose, suicide attempt, or those who were blind or deaf were excluded. We collected de-identified data from electronic health records on patient demographics, delirium and coma assessments, and management strategies for a 21-day period. Additional data on ventilator support, ICU length of stay, and vital status was collected for a 28-day period. The primary outcome was to determine the prevalence of delirium and coma and to investigate any associated risk factors associated with development of delirium the next day. We also investigated predictors of number of days alive without delirium or coma. These outcomes were investigated using multivariable regression. FINDINGS: Between Jan 20 and April 28, 2020, 4530 patients with COVID-19 were admitted to 69 ICUs, of whom 2088 patients were included in the study cohort. The median age of patients was 64 years (IQR 54 to 71) with a median Simplified Acute Physiology Score (SAPS) II of 40·0 (30·0 to 53·0). 1397 (66·9%) of 2088 patients were invasively mechanically ventilated on the day of ICU admission and 1827 (87·5%) were invasively mechanical ventilated at some point during hospitalisation. Infusion with sedatives while on mechanical ventilation was common: 1337 (64·0%) of 2088 patients were given benzodiazepines for a median of 7·0 days (4·0 to 12·0) and 1481 (70·9%) were given propofol for a median of 7·0 days (4·0 to 11·0). Median Richmond Agitation-Sedation Scale score while on invasive mechanical ventilation was -4 (-5 to -3). 1704 (81·6%) of 2088 patients were comatose for a median of 10·0 days (6·0 to 15·0) and 1147 (54·9%) were delirious for a median of 3·0 days (2·0 to 6·0). Mechanical ventilation, use of restraints, and benzodiazepine, opioid, and vasopressor infusions, and antipsychotics were each associated with a higher risk of delirium the next day (all p≤0·04), whereas family visitation (in person or virtual) was associated with a lower risk of delirium (p<0·0001). During the 21-day study period, patients were alive without delirium or coma for a median of 5·0 days (0·0 to 14·0). At baseline, older age, higher SAPS II scores, male sex, smoking or alcohol abuse, use of vasopressors on day 1, and invasive mechanical ventilation on day 1 were independently associated with fewer days alive and free of delirium and coma (all p<0·01). 601 (28·8%) of 2088 patients died within 28 days of admission, with most of those deaths occurring in the ICU. INTERPRETATION: Acute brain dysfunction was highly prevalent and prolonged in critically ill patients with COVID-19. Benzodiazepine use and lack of family visitation were identified as modifiable risk factors for delirium, and thus these data present an opportunity to reduce acute brain dysfunction in patients with COVID-19. FUNDING: None. TRANSLATIONS: For the French and Spanish translations of the abstract see Supplementary Materials section.

Effectiveness of Trivalent and Quadrivalent Inactivated Vaccines Against Influenza B in the United States, 2011-2012 to 2016-2017.

BACKGROUND: Since 2013, quadrivalent influenza vaccines containing 2 B viruses gradually replaced trivalent vaccines in the United States. We compared the vaccine effectiveness of quadrivalent to trivalent inactivated vaccines (IIV4 to IIV3, respectively) against illness due to influenza B during the transition, when IIV4 use increased rapidly. METHODS: The US Influenza Vaccine Effectiveness (Flu VE) Network analyzed 25 019 of 42 600 outpatients aged ≥6 months who enrolled within 7 days of illness onset during 6 seasons from 2011-2012. Upper respiratory specimens were tested for the influenza virus type and B lineage. Using logistic regression, we estimated IIV4 or IIV3 effectiveness by comparing the odds of an influenza B infection overall and the odds of B lineage among vaccinated versus unvaccinated participants. Over 4 seasons from 2013-2014, we compared the relative odds of an influenza B infection among IIV4 versus IIV3 recipients. RESULTS: Trivalent vaccines included the predominantly circulating B lineage in 4 of 6 seasons. During 4 influenza seasons when both IIV4 and IIV3 were widely used, the overall effectiveness against any influenza B was 53% (95% confidence interval [CI], 45-59) for IIV4 versus 45% (95% CI, 34-54) for IIV3. IIV4 was more effective than IIV3 against the B lineage not included in IIV3, but comparative effectiveness against illnesses related to any influenza B favored neither vaccine valency. CONCLUSIONS: The uptake of quadrivalent inactivated influenza vaccines was not associated with increased protection against any influenza B illness, despite the higher effectiveness of quadrivalent vaccines against the added B virus lineage. Public health impact and cost-benefit analyses are needed globally.