More attention should be paid to Omicron-associated sepsis: a multicenter retrospective study in south China.

Background: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly transmissible but causes less severe disease compared to other variants. However, its association with sepsis incidence and outcomes is unclear. This study aimed to investigate the incidence of Omicron-associated sepsis, as per the Sepsis 3.0 definition, in hospitalized patients, and to explore its relationship with clinical characteristics and prognosis. Methods: This multicenter retrospective study included adults hospitalized with confirmed SARS-CoV-2 infection across six tertiary hospitals in Guangzhou, China from November 2022 to January 2023. The Sequential Organ Failure Assessment (SOFA) score and its components were calculated at hospital admission to identify sepsis. Outcomes assessed were need for intensive care unit (ICU) transfer and mortality. Receiver operating characteristic curves evaluated the predictive value of sepsis versus other biomarkers for outcomes. Results: A total of 299 patients (mean age: 70.1±14.4 years, 42.14% female) with SOFA score were enrolled. Among them, 152 were categorized as non-serious cases while the others were assigned as the serious group. The proportion of male patients, unvaccinated patients, patients with comorbidity such as diabetes, chronic cardiovascular disease, and chronic lung disease was significantly higher in the serious than non-serious group. The median SOFA score of all enrolled patients was 1 (interquartile range, 0-18). In our study, 147 patients (64.19%) were identified as having sepsis upon hospital admission, with the majority of these septic patients (113, representing 76.87%) being in the serious group, the respiratory, coagulation, cardiovascular, central nervous, and renal organ SOFA scores were all significantly higher in the serious compared to the non-serious group. Among septic patients, 20 out of 49 (40.81%) had septic shock as indicated by lactate measurement within 24 hours of admission, and the majority of septic patients were in the serious group (17/20, 76.87%). Sepsis was present in 118 out of 269 (43.9%) patients in the general ward, and among those with sepsis, 34 out of 118 (28.8%) later required ICU care during hospitalization. By contrast, none of the patients without sepsis required ICU care. Moreover, the mortality rate was significantly higher in patients with than without sepsis. Conclusions: A considerable proportion of patients infected with Omicron present with sepsis upon hospital admission, which is associated with a poorer prognosis. Therefore, early recognition of viral sepsis by evaluation of the SOFA score in hospitalized coronavirus disease 2019 patients is crucial.

Patient Controlled Subcutaneous Analgesia of Hydromorphone Versus Morphine to Treat Moderate and Severe Cancer Pain: A Randomized Double-Blind Controlled Trial.

CONTEXT: Hydromorphone and morphine are the common drugs used for the treatment of moderate to severe cancer pain. Patient controlled subcutaneous analgesia (PCSA) is an effective technique to manage cancer pain. However, few studies have been conducted to show the efficacy and safety of PCSA of hydromorphone for the relief of cancer pain. OBJECTIVES: To explore the short-term efficacy and safety of PCSA elicited by hydromorphone for moderate to severe cancer pain. METHODS: This was a single-center, randomized, active-controlled, double-blind trial (from April 2019 to August 2021). Sixty patients with moderate to severe cancer pain were randomized (1:1) to hydromorphone or morphine groups according to drug delivery by PCSA. The primary outcome was the pain intensity measured by a numerical rating scale (NRS) at 72 hours. Secondary outcomes included pain intensity measured by NRS at baseline, 15 minutes, 30 minutes, two hours, eight hours, 24 hours and 48 hours. The daily occurrence of breakthrough pain (BTP), impact of pain on quality of life measured by the brief pain inventory (BPI), the daily additional consumption of opioids and the incidence of adverse events were also recorded. Adverse events included nausea, vomiting, dizziness, constipation and respiratory depression. RESULTS: A total of 57 patients (28 patients in the hydromorphone group and 29 patients in the morphine group) in the West China Hospital of Sichuan University were investigated. The mean (standard deviation [SD]) NRS in the two groups at baseline was 7.8 (1.7) in the hydromorphone group and 7.6 (1.7) in the morphine group, and at 72 hours were 3.4 (1.8) and 3.2 (1.5), respectively. The postoperative NRS in both groups was decreased significantly compared to baseline. The mean (SD) NRS at 30 minutes in the hydromorphone group was significantly lower than in the morphine group (3.9 [2.6] vs. 5.3 [2.1], P = 0.035). The daily occurrence of BTP in both groups at 48 hours and 72 hours decreased significantly compared to the corresponding baseline (P < 0.05), and there was no significant difference between the two groups. The total scores and sub-item scores of BPI at 24 hours and 72 hours after PCSA in both groups decreased significantly from baseline. A comparison of daily additional consumption of opioids between the two groups revealed no statistically significant difference. There were no significant differences in the incidences of nausea, vomiting, dizziness or constipation between the two groups (P > 0.05). CONCLUSION: This study found that the PCSA of both hydromorphone and morphine could effectively and safely relieve short-term moderate to severe cancer pain. Of note, the PCSA of hydromorphone took effect more quickly than that of morphine.

The Current Status of the Use of Internet Hospitals for Outpatients With Pain: Retrospective Study.

BACKGROUND: The national "Internet +" policies and the emergence of internet hospitals have created a new direction for the management of pain outside of the hospital. Nevertheless, there are no consolidated studies conducted by pain physicians on the current state of internet hospital-based online medical services used by patients with pain outside of a hospital setting. OBJECTIVE: In this retrospective study, we aimed to examine the status of the use of internet hospitals by patients who experience pain. Moreover, we identified the factors that influenced patients' decisions to make an online visit through the internet hospital. METHODS: Detailed information was collected online and offline from outpatients with pain at the information technology center of West China Hospital of Sichuan University from February 2020 to April 2022. Binary logistic regression analysis was conducted to identify the determinants that influenced patients' decisions to make an online visit to the internet hospital. RESULTS: Over a 2-year period, 85,266 pain-related clinic visits were recorded. Ultimately, 39,260 patients were enrolled for the analysis, with 12.9% (5088/39,260) having online visits. Both online and offline clinics had a greater number of visits by women than men. The average age of patients attending the online clinic was 46.85 (SD 16.56) years, whereas the average age of patients attending the offline clinic was 51.48 (SD 16.12) years. The majority of online clinic visitors (3059/5088, 60.1%) were employed, and one of the most common occupations was farming (721/5088, 14.2%). In addition, 51.8% (2635/5088) of patients who participated in the online clinics lived outside the hospital vicinity. Young (odds ratio [OR] 1.35, 95% CI 1.01-1.81; P=.045) and middle-aged (OR 1.98, 95% CI 1.81-2.16; P<.001) patients, employed patients (OR 1.11, 95% CI 1.04-1.18; P=.002), nonlocal patients (OR 1.57, 95% CI 1.48-1.67; P<.001), and the ordinary staff (OR 1.19, 95%CI 1.01-1.39; P=.03) were more likely to have the intention to choose online visits through the internet hospitals. CONCLUSIONS: Internet hospitals are flourishing as a more efficient and promising method of pain management and follow-up for patients with pain outside the hospital. People with pain who are young, working, and not in the vicinity of hospitals are more likely to visit internet hospitals.

A diagnostic model for sepsis-induced acute lung injury using a consensus machine learning approach and its therapeutic implications.

BACKGROUND: A significant proportion of septic patients with acute lung injury (ALI) are recognized late due to the absence of an efficient diagnostic test, leading to the postponed treatments and consequently higher mortality. Identifying diagnostic biomarkers may improve screening to identify septic patients at high risk of ALI earlier and provide the potential effective therapeutic drugs. Machine learning represents a powerful approach for making sense of complex gene expression data to find robust ALI diagnostic biomarkers. METHODS: The datasets were obtained from GEO and ArrayExpress databases. Following quality control and normalization, the datasets (GSE66890, GSE10474 and GSE32707) were merged as the training set, and four machine learning feature selection methods (Elastic net, SVM, random forest and XGBoost) were applied to construct the diagnostic model. The other datasets were considered as the validation sets. To further evaluate the performance and predictive value of diagnostic model, nomogram, Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC) were constructed. Finally, the potential small molecular compounds interacting with selected features were explored from the CTD database. RESULTS: The results of GSEA showed that immune response and metabolism might play an important role in the pathogenesis of sepsis-induced ALI. Then, 52 genes were identified as putative biomarkers by consensus feature selection from all four methods. Among them, 5 genes (ARHGDIB, ALDH1A1, TACR3, TREM1 and PI3) were selected by all methods and used to predict ALI diagnosis with high accuracy. The external datasets (E-MTAB-5273 and E-MTAB-5274) demonstrated that the diagnostic model had great accuracy with AUC value of 0.725 and 0.833, respectively. In addition, the nomogram, DCA and CIC showed that the diagnostic model had great performance and predictive value. Finally, the small molecular compounds (Curcumin, Tretinoin, Acetaminophen, Estradiol and Dexamethasone) were screened as the potential therapeutic agents for sepsis-induced ALI. CONCLUSION: This consensus of multiple machine learning algorithms identified 5 genes that were able to distinguish ALI from septic patients. The diagnostic model could identify septic patients at high risk of ALI, and provide potential therapeutic targets for sepsis-induced ALI.

The accuracy of simplified calculation of mechanical power: a simulation study.

Background: Mechanical ventilation (MV) is an important life-saving method in the intensive care unit (ICU). A lower mechanical power (MP) is associated with a better MV strategy. However, traditional MP calculating methods are complicated, and algebraic formulas seem to be rather practical. The aim of the present study was to compare the accuracy and application of different algebraic formulas calculating MP. Methods: A lung simulator, TestChest, was used to simulate pulmonary compliance variations. Using the TestChest system software, the parameters, including compliance and airway resistance, were set to simulate various acute respiratory distress syndrome (ARDS) lungs. Ventilator was also set to volume- and pressure-controlled modes with various parameter values (respiratory rate, RR, time of inspiration, Tinsp, positive end-expiratory pressure, PEEP) to ventilate the simulated lung of ARDS (with various respiratory system compliance, Crs). For the lung simulator, resistance of airway (Raw) was fixed to 5 cmH2O/L/s. Crs below lower inflation point (LIP) or above upper inflation point (UIP) was set to 10 mL/cmH2O. The reference standard geometric method was calculated offline with a customized software. Three algebraic formulas for volume-controlled and three for pressure-controlled were used to calculate MP. Results: The performances of the formulas were different, although the derived MP were significantly correlated with that derived from the reference method (R2>0.80, P<0.001). Under volume-controlled ventilation, medians of MP calculated with one equation was significantly lower than that with the reference method (P<0.001). Under pressure-controlled ventilation, median of MP calculated with two equations were significantly higher (P<0.001). The maximum difference was over 70% of the MP value calculated with the reference method. Conclusions: The algebraic formulas may introduce considerably large bias under the presented lung conditions, especially in moderate to severe ARDS. Cautious is required when selecting adequate algebraic formulas to calculate MP based on the formula's premises, ventilation mode, and patients' status. In clinical practice, the trend rather than the value of MP calculated by formulas should require more attention.

LncRNA modulates Hippo-YAP signaling to reprogram iron metabolism.

Iron metabolism dysregulation is tightly associated with cancer development. But the underlying mechanisms remain poorly understood. Increasing evidence has shown that long noncoding RNAs (lncRNAs) participate in various metabolic processes via integrating signaling pathway. In this study, we revealed one iron-triggered lncRNA, one target of YAP, LncRIM (LncRNA Related to Iron Metabolism, also named ZBED5-AS1 and Loc729013), which effectively links the Hippo pathway to iron metabolism and is largely independent on IRP2. Mechanically, LncRIM directly binds NF2 to inhibit NF2-LATS1 interaction, which causes YAP activation and increases intracellular iron level via DMT1 and TFR1. Additionally, LncRIM-NF2 axis mediates cellular iron metabolism dependent on the Hippo pathway. Clinically, high expression of LncRIM correlates with poor patient survival, suggesting its potential use as a biomarker and therapeutic target. Taken together, our study demonstrated a novel mechanism in which LncRIM-NF2 axis facilitates iron-mediated feedback loop to hyperactivate YAP and promote breast cancer development.

Corrigendum: Construction and validation of a robust prognostic model based on immune features in sepsis.

[This corrects the article DOI: 10.3389/fimmu.2022.994295.].

Ferroptosis, pyroptosis and necroptosis in acute respiratory distress syndrome.

Acute respiratory distress syndrome (ARDS) is an acute and uncontrolled pulmonary inflammation caused by various insults. Cell death is a critical mechanism in the pathogenesis of ARDS. Ferroptosis, a novel form of cell death defined as iron-mediated lipid peroxidation, has been shown to play a role in the pathogenesis of ARDS. Additionally, pyroptosis and necroptosis are also involved in the pathophysiological process of ARDS. The crosstalk among ferroptosis, pyroptosis, and necroptosis is getting increasing attention. Therefore, this review will mainly summarize the molecular mechanisms and central pathophysiological role of ferroptosis in ARDS. We will also discuss our understanding of pyroptosis and necroptosis as they pertain to the pathogenesis of ARDS. Furthermore, we also describe the pathological processes that engage crosstalk among ferroptosis, pyroptosis, and necroptosis. We consider that individual pathways of ferroptosis, pyroptosis, and necroptosis are highly interconnected and can compensate for one another to promote cell death.

Changes of blood gas analysis in moderate-to-severe acute respiratory distress syndrome patients during long-term prone position ventilation: a retrospective cohort study.

Background: Prone position ventilation (PPV) has been recommended for patients with acute respiratory distress syndrome (ARDS) to improve oxygenation. However, whether prolonged prone ventilation will aggravate hyperoxia and whether abdominal compression will aggravate permissive hypercapnia acidosis are topics of concern. We carried out a retrospective analysis to investigate the issues above. Methods: Clinical data were collected from 97 moderate-to-severe ARDS patients who received PPV as part of their treatment in the intensive care unit (ICU) of the First Affiliated Hospital of Guangzhou Medical University from November 2015 to May 2021. We collected arterial blood gas of patients according to the 3 periods: supine position ventilation (SPV), PPV early stage (within 4 hours), and PPV middle and late stage (6 hours or later). We established a linear mixed-effects models with "body position changes, times of PPV, gender, age, baseline SOFA, and baseline APACHE II" as fixed effects, and individual and the number of prone positions as random intercept and random slope to investigate the effect of body position changes on blood gas analysis. Results: Among the 97 patients received PPV included, 51 were ICU survivors. Arterial partial pressure of oxygen (PaO2) and PaO2/fraction of inspired oxygen (FiO2) ratio were significantly higher at the early, middle and late stages of PPV than those in SPV [PFR (mmHg): 158 (118.00, 203.00) vs. 161 (129.00, 202.75) vs. 123 (91.75, 163.00), P<0.05]. Despite the synchronized reduction of FiO2, the incidence of hyperoxia in the prone position was still significantly higher than that in the supine position [hyperoxia (%):33.33 vs. 33.56 vs. 12.42, P<0.05]; there was no significant change in arterial carbon dioxide partial pressure (PaCO2) at each stage of PPV, but there was a significant increase in PH at PPV middle and late stages than those at early stage [PH: 7.39 (7.34, 7.42) vs. 7.37 (7.31, 7.41), P<0.05]. Conclusions: Although PPV improves the patients' oxygenation, the associated incidence of hyperoxia exceeds 33%. Down-regulate FiO2 more sharply after PPV is necessary, if oxygenation conditions permit. PPV may alleviate the acidosis associated with permissive hypercapnia in ARDS patients treated with lung protective ventilation strategy (LPVS).

A feasibility study of reduced full-of-view synthetic high-b-value diffusion-weighted imaging in uterine tumors.

OBJECTIVES: This study aimed to evaluate the feasibility of reduced full-of-view synthetic high-b value diffusion-weighted images (rFOV-syDWIs) in the clinical application of cervical cancer based on image quality and diagnostic efficacy. METHODS: We retrospectively evaluated the data of 35 patients with cervical cancer and 35 healthy volunteers from May to November 2021. All patients and volunteers underwent rFOV-DWI scans, including a 13b-protocol: b = 0, 25, 50, 75, 100, 150, 200, 400, 600, 800, 1000, 1200, and 1500 s/mm2 and a 5b-protocol: b = 0, 100, 400, 800,1500 s/mm2. rFOV-syDWIs with b values of 1200 (rFOV-syDWIb=1200) and 1500 (rFOV-syDWIb=1500) were generated from two different multiple-b-value image datasets using a mono-exponential fitting algorithm. According to homoscedasticity and normality assessed by the Levene's test and Shapiro-Wilk test, the inter-modality differences of quantitative measurements were, respectively, examined by Wilcoxon signed-rank test or paired t test and the inter-group differences of ADC values were examined by independent t test or Mann-Whitney U test. RESULTS: A higher inter-reader agreement between SNRs and CNRs was found in 13b-protocol and 5b-protocol rFOV-syDWIb=1200/1500 compared to 13b-protocol rFOV-sDWIb=1200/1500 (p < 0.05). AUC of 5b-protocol syADCmean,b=1200/1500 and syADCminimum,b=1200/1500 was equal or higher than that of 13b-protocol sADCmean,b=1200/1500 and sADCminimum,b=1200/1500. CONCLUSIONS: rFOV-syDWIs provide better lesion clarity and higher image quality than rFOV-sDWIs. 5b-protocol rFOV-syDWIs shorten scan time, and synthetic ADCs offer reliable diagnosis value as scanned 13b-protocol DWIs.

Construction and validation of a robust prognostic model based on immune features in sepsis.

Purpose: Sepsis, with life-threatening organ failure, is caused by the uncontrolled host response to infection. Immune response plays an important role in the pathophysiology of sepsis. Immune-related genes (IRGs) are promising novel biomarkers that have been used to construct the diagnostic and prognostic model. However, an IRG prognostic model used to predict the 28-day mortality in sepsis was still limited. Therefore, the study aimed to develop a prognostic model based on IRGs to identify patients with high risk and predict the 28-day mortality in sepsis. Then, we further explore the circulating immune cell and immunosuppression state in sepsis. Materials and methods: The differentially expressed genes (DEGs), differentially expressed immune-related genes (DEIRGs), and differentially expressed transcription factors (DETFs) were obtained from the GEO, ImmPort, and Cistrome databases. Then, the TFs-DEIRGs regulatory network and prognostic prediction model were constructed by Cox regression analysis and Pearson correlation analysis. The external datasets also validated the reliability of the prognostic model. Based on the prognostic DEIRGs, we developed a nomogram and conducted an independent prognosis analysis to explore the relationship between DEIRGs in the prognostic model and clinical features in sepsis. Besides, we further evaluate the circulating immune cells state in sepsis. Results: A total of seven datasets were included in our study. Among them, GSE65682 was identified as a discovery cohort. The results of GSEA showed that there is a significant correlation between sepsis and immune response. Then, based on a P value <0.01, 69 prognostic DEIRGs were obtained and the potential molecular mechanisms of DEIRGs were also clarified. According to multivariate Cox regression analysis, 22 DEIRGs were further identified to construct the prognostic model and identify patients with high risk. The Kaplan-Meier survival analysis showed that high-risk groups have higher 28-day mortality than low-risk groups (P=1.105e-13). The AUC value was 0.879 which symbolized that the prognostic model had a better accuracy to predict the 28-day mortality. The external datasets also prove that the prognostic model had an excellent prediction value. Furthermore, the results of correlation analysis showed that patients with Mars1 might have higher risk scores than Mars2-4 (P=0.002). According to the previous study, Mars1 endotype was characterized by immunoparalysis. Thus, the sepsis patients in high-risk groups might exist the immunosuppression. Between the high-risk and low-risk groups, circulating immune cells types were significantly different, and risk score was significantly negatively correlated with naive CD4+ T cells (P=0.019), activated NK cells (P=0.0045), monocytes (P=0.0134), and M1 macrophages (P=0.0002). Conclusions: Our study provides a robust prognostic model based on 22 DEIRGs which can predict 28-day mortality and immunosuppression status in sepsis. The higher risk score was positively associated with 28-day mortality and the development of immunosuppression. IRGs are a promising biomarker that might facilitate personalized treatments for sepsis.

Electrical impedance tomography for titration of positive end-expiratory pressure in acute respiratory distress syndrome patients with chronic obstructive pulmonary disease.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is one of most common comorbidities in acute respiratory distress syndrome (ARDS). There are few specific studies on the appropriate ventilation strategy for patients with ARDS comorbid with COPD, especially regarding on positive end-expiratory pressure (PEEP) titration. METHODS: To compare the respiratory mechanics in mechanical ventilated ARDS patients with or without COPD and to determine whether titration of PEEP based on electrical impedance tomography (EIT) is superior to the ARDSnet protocol. This is a single center, perspective, repeated measure study. ARDS patients requiring mechanical ventilation who were admitted to the intensive care unit between August 2017 and December 2020 were included. ARDS patients were divided according to whether they had COPD into a COPD group and a non-COPD group. Respiratory mechanics, gas exchange, and hemodynamics during ventilation were compared between the groups according to whether the PEEP level was titrated by EIT or the ARDSnet protocol. RESULTS: A total of twenty-seven ARDS patients including 14 comorbid with and 13 without COPD who met the study eligibility criteria were recruited. The PEEP levels titrated by EIT and the ARDSnet protocol were lower in the COPD group than in the non-COPD group (6.93 ± 1.69 cm H2O vs. 12.15 ± 2.40 cm H2O, P < 0.001 and 10.43 ± 1.20 cm H2O vs. 14.0 ± 3.0 cm H2O, P < 0.001, respectively). In the COPD group, the PEEP level titrated by EIT was lower than that titrated by the ARDSnet protocol (6.93 ± 1.69 cm H2O vs. 10.43 ± 1.20 cm H2O, P < 0.001), as was the global inhomogeneity (GI) index (0.397 ± 0.040 vs. 0.446 ± 0.052, P = 0.001), plateau airway pressure (16.50 ± 4.35 cm H2O vs. 20.93 ± 5.37 cm H2O, P = 0.001), dead space ventilation ratio (48.29 ± 6.78% vs. 55.14 ± 8.85%, P < 0.001), ventilation ratio (1.63 ± 0.33 vs. 1.87 ± 0.33, P < 0.001), and mechanical power (13.92 ± 2.18 J/min vs. 15.87 ± 2.53 J/min, P < 0.001). The cardiac index was higher when PEEP was treated by EIT than when it was titrated by the ARDSnet protocol (3.41 ± 0.50 L/min/m2 vs. 3.02 ± 0.43 L/min/m2, P < 0.001), as was oxygen delivery (466.40 ± 71.08 mL/min/m2 vs. 411.10 ± 69.71 mL/min/m2, P = 0.001). CONCLUSION: Titrated PEEP levels were lower in patients with ARDS with COPD than in ARDS patients without COPD. In ARDS patient comorbid with COPD, application of PEEP titrated by EIT was lower than those titrated by the ARDSnet protocol, which contributed to improvements in the ventilation ratio, mechanical energy, cardiac index, and oxygen delivery with less of an adverse impact on hemodynamics.

Patients with infectious diseases undergoing mechanical ventilation in the intensive care unit have better prognosis after receiving metagenomic next-generation sequencing assay.

OBJECTIVES: To evaluate the relation between metagenomic next-generation sequencing (mNGS) and the prognosis of patients with infectious diseases undergoing mechanical ventilation in the intensive care unit (ICU). METHODS: This is a single-center observational study, comparing nonrandomly assigned diagnostic approaches. We analyzed the medical records of 228 patients with suspected infectious diseases undergoing mechanical ventilation in the ICU from March 2018 to May 2020. The concordance of pathogen results was also assessed for the results of mNGS, culture, and polymerase chain reaction assays. RESULTS: The 28-day mortality of the patients in the mNGS group was lower after the baseline difference correction (19.23% (20/104) vs 29.03% (36/124) , P = 0.039). Subgroup analysis showed that mNGS assay was associated with improved 28-day mortality of patients who are not immunosuppressed (14.06% vs 29.82%, P = 0.018). Not performing mNGS assay, higher acute physiology and chronic health evaluation II score, and hypertension are independent risk factors for 28-day mortality. The mNGS assay presented an advantage in pathogen positivity (69.8% double-positive and 25.0% mNGS-positive only), and the concordance between these two assays was 79.0%. CONCLUSION: mNGS survey may be associated with a better prognosis by reducing 28-day mortality of patients with infectious diseases on mechanical ventilation in the ICU. This technique presented an advantage in pathogen positivity over traditional methods.

Prevalence of Pain and Its Risk Factors Among ICU Personnel in Tertiary Hospital in China: A Cross-Sectional Study.

Background: Although pain is commonly observed among medical staff, studies on pain among intensive care unit personnel are uncommon, especially intensive care unit (ICU) doctors and workers. Moreover, few studies have focused on the prevalence of pain and the associated factors. Purpose: The aim of this study was to estimate the prevalence of pain among ICU personnel (including doctors, nurses and workers) and explore the risk factors for their pain. Methods: We conducted an online survey that included sociodemographic and work-related items and questions about pain, ergonomics, and psychological factors. We used the short version of the validated Depression-Anxiety-Stress Scale (DASS-21) to assess the relationship between pain and mental disorders. All ICU personnel at West China Hospital of Sichuan University participated in this study. Results: A total of 356 ICU personnel were included in the final analysis. The prevalence of pain was 72.2% among ICU nurses, 64.4% among ICU doctors and 52.9% among ICU workers. The most frequent location of pain was the lower back among nurses (65.9%) and workers (47.1%) and the neck among doctors (49.1%). The factors contributing to pain among ICU personnel were bending or twisting the neck, high levels of psychological fatigue, low self-perceived health status, female sex and high body mass index (BMI). Moreover, participants with pain indicated significantly higher depression (p ≤ 0.001), anxiety (p ≤ 0.001), and stress levels (p = 0.002) than those without pain. Conclusion: This study indicates that ICU personnel exhibit a high prevalence of pain. Many factors, especially psychosocial and ergonomic factors, contribute to pain levels among ICU personnel and the poorer mental health levels observed in those experiencing pain. Therefore, disease prevention and health promotion measures are needed to protect the health of ICU personnel.

Weaning critically ill patients from mechanical ventilation: a protocol from a multicenter retrospective cohort study.

BACKGROUND: Mechanical ventilation (MV) is an important lifesaving method in intensive care unit (ICU). Prolonged MV is associated with ventilator associated pneumonia (VAP) and other complications. However, premature weaning from MV may lead to higher risk of reintubation or mortality. Therefore, timely and safe weaning from MV is important. In addition, identification of the right patient and performing a suitable weaning process is necessary. Although several guidelines about weaning have been reported, compliance with these guidelines is unknown. Therefore, the aim of this study is to explore the variation of weaning in China, associations between initial MV reason and clinical outcomes, and factors associated with weaning strategies using a multicenter cohort. METHODS: This multicenter retrospective cohort study will be conducted at 17 adult ICUs in China, that included patients who were admitted in this 17 ICUs between October 2020 and February 2021. Patients under 18 years of age and patients without the possibility for weaning will be excluded. The questionnaire information will be registered by a specific clinician in each center who has been evaluated and qualified to carry out the study. DISCUSSION: In a previous observational study of weaning in 17 ICUs in China, weaning practices varies nationally. Therefore, a multicenter retrospective cohort study is necessary to be conducted to explore the present weaning methods used in China. TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR) (No. ChiCTR2100044634).

Artificial intelligence for stepwise diagnosis and monitoring of COVID-19.

BACKGROUND: Main challenges for COVID-19 include the lack of a rapid diagnostic test, a suitable tool to monitor and predict a patient's clinical course and an efficient way for data sharing among multicenters. We thus developed a novel artificial intelligence system based on deep learning (DL) and federated learning (FL) for the diagnosis, monitoring, and prediction of a patient's clinical course. METHODS: CT imaging derived from 6 different multicenter cohorts were used for stepwise diagnostic algorithm to diagnose COVID-19, with or without clinical data. Patients with more than 3 consecutive CT images were trained for the monitoring algorithm. FL has been applied for decentralized refinement of independently built DL models. RESULTS: A total of 1,552,988 CT slices from 4804 patients were used. The model can diagnose COVID-19 based on CT alone with the AUC being 0.98 (95% CI 0.97-0.99), and outperforms the radiologist's assessment. We have also successfully tested the incorporation of the DL diagnostic model with the FL framework. Its auto-segmentation analyses co-related well with those by radiologists and achieved a high Dice's coefficient of 0.77. It can produce a predictive curve of a patient's clinical course if serial CT assessments are available. INTERPRETATION: The system has high consistency in diagnosing COVID-19 based on CT, with or without clinical data. Alternatively, it can be implemented on a FL platform, which would potentially encourage the data sharing in the future. It also can produce an objective predictive curve of a patient's clinical course for visualization. KEY POINTS: • CoviDet could diagnose COVID-19 based on chest CT with high consistency; this outperformed the radiologist's assessment. Its auto-segmentation analyses co-related well with those by radiologists and could potentially monitor and predict a patient's clinical course if serial CT assessments are available. It can be integrated into the federated learning framework. • CoviDet can be used as an adjunct to aid clinicians with the CT diagnosis of COVID-19 and can potentially be used for disease monitoring; federated learning can potentially open opportunities for global collaboration.