Ventilation In Intensive Care Unit Research Articles

Derivation and external validation of predictive models for invasive mechanical ventilation in intensive care unit patients with COVID-19

BackgroundThis study aimed to develop prognostic models for predicting the need for invasive mechanical ventilation (IMV) in intensive care unit (ICU) patients with COVID-19 and compare their performance with the Respiratory rate-OXygenation (ROX) index.MethodsA retrospective cohort study was conducted using data collected between March 2020 and August 2021 at three hospitals in Rio de Janeiro, Brazil. ICU patients aged 18 years and older with a diagnosis of COVID-19 were screened. The exclusion criteria were patients who received IMV within the first 24 h of ICU admission, pregnancy, clinical decision for minimal end-of-life care and missing primary outcome data. Clinical and laboratory variables were collected. Multiple logistic regression analysis was performed to select predictor variables. Models were based on the lowest Akaike Information Criteria (AIC) and lowest AIC with significant p values. Assessment of predictive performance was done for discrimination and calibration. Areas under the curves (AUC)s were compared using DeLong’s algorithm. Models were validated externally using an international database.ResultsOf 656 patients screened, 346 patients were included; 155 required IMV (44.8%), 191 did not (55.2%), and 207 patients were male (59.8%). According to the lowest AIC, arterial hypertension, diabetes mellitus, obesity, Sequential Organ Failure Assessment (SOFA) score, heart rate, respiratory rate, peripheral oxygen saturation (SpO2), temperature, respiratory effort signals, and leukocytes were identified as predictors of IMV at hospital admission. According to AIC with significant p values, SOFA score, SpO2, and respiratory effort signals were the best predictors of IMV; odds ratios (95% confidence interval): 1.46 (1.07–2.05), 0.81 (0.72–0.90), 9.13 (3.29–28.67), respectively. The ROX index at admission was lower in the IMV group than in the non-IMV group (7.3 [5.2–9.8] versus 9.6 [6.8–12.9], p < 0.001, respectively). In the external validation population, the area under the curve (AUC) of the ROX index was 0.683 (accuracy 63%), the AIC model showed an AUC of 0.703 (accuracy 69%), and the lowest AIC model with significant p values had an AUC of 0.725 (accuracy 79%).ConclusionsIn the development population of ICU patients with COVID-19, SOFA score, SpO2, and respiratory effort signals predicted the need for IMV better than the ROX index. In the external validation population, although the AUCs did not differ significantly, the accuracy was higher when using SOFA score, SpO2, and respiratory effort signals compared to the ROX index. This suggests that these variables may be more useful in predicting the need for IMV in ICU patients with COVID-19.ClinicalTrials.gov identifier:NCT05663528.

Modes of administration of nitric oxide devices and ventilators flow-by impact the delivery of pre-determined concentrations

BackgroundNitric oxide (NO) is a strong vasodilator, selectively directed on pulmonary circulation through inhaled administration. In adult intensive care units (ICU), it is mainly used for refractory hypoxemia in mechanically ventilated patients. Several medical delivery devices have been developed to deliver inhaled nitric oxide (iNO). The main purpose of those devices is to guarantee an accurate inspiratory NO concentration, whatever the ventilator used, with NO2 concentrations lower than 0.3 ppm. We hypothesized that the performances of the different available iNO delivery systems could depend on their working principle and could be influenced by the ventilator settings. The objective of this study was to assess the accuracy of seven different iNO-devices combined with different ICU ventilators’ flow-by to reach inspiratory NO concentration targets and to evaluate their potential risk of toxicity.MethodsWe tested seven iNO-devices on a test-lung connected to distinct ICU ventilators offering four different levels of flow-by. We measured the flow in the inspiratory limb of the patient circuit and the airway pressure. The nitric oxide/nitrogen (NO/N2) flow was measured on the administration line of the iNO-devices. NO and NO2 concentrations were measured in the test-lung using an electrochemical analyzer.ResultsWe identified three iNO-device generations based on the way they deliver NO flow: “Continuous”, “Sequential to inspiratory phase” (I-Sequential) and “Proportional to inspiratory and expiratory ventilator flow” (Proportional). Median accuracy of iNO concentration measured in the test lung was 2% (interquartile range, IQR -19; 36), -23% (IQR -29; -17) and 0% (IQR -2; 0) with Continuous, I-Sequential and Proportional devices, respectively. Increased ventilator flow-by resulted in decreased iNO concentration in the test-lung with Continuous and I-Sequential devices, but not with Proportional ones. NO2 formation measured to assess potential risks of toxicity never exceeded the predefined safety target of 0.5 ppm. However, NO2 concentrations higher than or equal to 0.3 ppm, a concentration that can cause bronchoconstriction, were observed in 19% of the different configurations.ConclusionWe identified three different generations of iNO-devices, based on their gas administration modalities, that were associated with highly variable iNO concentrations’ accuracy. Ventilator’s flow by significantly impacted iNO concentration. Only the Proportional devices permitted to accurately deliver iNO whatever the conditions and the ventilators tested.

COVID-19-Related Cholangiopathy: Histological Findings.

We subjected post-COVID-19 cholestasis liver samples to routine staining techniques and cytokeratin 7 immunostaining and semi-quantitatively analyzed the portal and parenchymal changes. All ten patients, five men, had a median age of 56, an interquartile range (IQR) of 51-60, and required intensive care unit and mechanical ventilation. The median and IQR liver enzyme concentrations proximal to biopsy were in IU/L: ALP 645 (390-1256); GGT 925 (664-2169); ALT 100 (86-113); AST 87 (68-106); and bilirubin 4 (1-9) mg/dL. Imaging revealed intrahepatic bile duct anomalies and biliary casts. We performed biopsies at a median of 203 (150-249) days after molecular confirmation of infection. We found portal and periportal fibrosis, moderate-to-severe ductular proliferation, and bile duct dystrophy in all patients, while we observed hepatocyte biliary metaplasia in all tested cases. We observed mild-to-severe parenchymal cholestasis and bile plugs in nine and six cases. We also observed mild swelling of the arteriolar endothelial cells in five patients. We observed a thrombus in a small portal vein branch and mild periductal fibrosis in one case each. One patient developed multiple small biliary infarctions. We did not observe ductopenia in any patient. The alterations were like those observed in SSC-CIP; however, pronounced swelling of endothelial cells, necrosis of the vessel walls, and thrombosis in small vessels were notable.

Novel High-tech, Low-cost Ventilation for Military Use, Mass Casualty Incidents, Stockpiling, and Underserved Communities.

Despite the significant need for mechanical ventilation in- and out-of-hospital, mechanical ventilators remain inaccessible in many instances because of cost or size constraints. Mechanical ventilation is especially critical in trauma scenarios, but the impractical size and weight of standard mechanical ventilators restrict first responders from carrying them in medical aid bags, leading to reliance on imprecise manual bag-mask ventilation. This is particularly important in combat-related injury, where airway compromise and respiratory failure are leading causes of preventable death, but medics are left without necessary mechanical ventilation. To address the serious gaps in mechanical ventilation accessibility, we are developing an Autonomous, Modular, and Portable Ventilation platform (AMP-Vent) suitable for austere environments, prolonged critical care, surgical applications, mass casualty incidents, and stockpiling. The core system is remarkably compact, weighing <2.3 kg, and can fit inside a shoebox (23.4 cm × 17.8 cm × 10.7 cm). Notably, this device is 65% lighter than standard transport ventilators and astoundingly 96% lighter than typical intensive care unit ventilators. Beyond its exceptional portability, AMP-Vent can be manufactured at less than one-tenth the cost of conventional ventilators. Despite its reduced size and cost, the system's functionality is uncompromised. The core system is equipped with closed-loop sensors and advanced modes of ventilation (pressure-control, volume-control, and synchronized intermittent mandatory ventilation), enabling quality care in a portable form factor. The current prototype has undergone preliminary preclinical testing and optimization through trials using a breathing simulator (ASL 5000) and in a large animal model (swine). This report aims to introduce a novel ventilation system and substantiate its promising performance through evidence gathered from preclinical studies. Lung simulator testing was performed using the ASL 5000, in accordance with table201.105 "pressure-control inflation-type testing" from ISO 80601-2-12:2020. Following simulations, AMP-Vent was tested in healthy 10-kg female domestic piglets. The Children's Hospital of Philadelphia Institutional Animal Care and Use Committee approved all animal procedures. Swine received 4-min blocks of alternating ventilation, where AMP-Vent and a conventional anesthesia ventilator (GE AISYS CS2) were used to titrate to varied end-tidal carbon dioxide (EtCO2) goals with the initial ventilator switching for each ascending target (35, 40, 45, 50, 55 mmHg). During ASL 5000 simulations, AMP-Vent exhibited consistent performance under varied conditions, maintaining a coefficient of variation of 2% or less within each test. In a large animal study, AMP-Vent maintained EtCO2 and SpO2 targets with comparable performance to a conventional anesthesia ventilator (GE AISYS CS2). Furthermore, the comparison of minute ventilation (Ve) distributions between the conventional anesthesia ventilator and AMP-Vent at several EtCO2 goals (35, 40, 45, 50, and 55 mmHg) revealed no statistically significant differences (p = 0.46 using the Kruskal-Wallis rank sum test). Preclinical results from this study highlight AMP-Vent's core functionality and consistent performance across varied scenarios. AMP-Vent sets a benchmark for portability with its remarkably compact design, positioning it to revolutionize trauma care in previously inaccessible medical scenarios.

Dexamethasone Use to Reduce Mechanical Ventilation and Bronchopulmonary Dysplasia in the Neonatal Intensive Care Unit.

Ventilator-dependent neonates are at risk of bronchopulmonary dysplasia (BPD), a chronic lung disease. Dexamethasone may be used to facilitate extubation and reduce the incidence of BPD. To determine the efficacy of dexamethasone in reducing the incidence of established BPD at 36 weeks postmenstrual age (PMA); to establish the rate of extubation success; to determine the factors affecting extubation success; and to describe complications associated with dexamethasone therapy. A chart review was conducted at Surrey Memorial Hospital, in Surrey, British Columbia, for neonates who received dexamethasone to reduce the development of BPD between July 1, 2016, and June 30, 2022. A total of 47 neonates met the inclusion criteria. Of the 45 neonates still alive at 36 weeks PMA, all (100%) had BPD. Use of dexamethasone led to extubation success for 21 (47%) of these 45 neonates. The mean PMA at dexamethasone initiation was 30.7 weeks for neonates with extubation success, compared with 28.6 weeks for those with extubation failure (p = 0.001). Complications occurred in 43 (91%) of the 47 neonates. BPD occurred in all of the neonates, despite a 47% extubation success rate. The timing of dexamethasone initiation was associated with extubation success. Further research is required to determine the dose and timing of dexamethasone needed to reduce the incidence of BPD.

Is Ventilator-associated Event Algorithm Ideal for Surveillance? – Experience from a Neurosurgery Intensive Care Unit in Kerala

ABSTRACT Background: The ventilator-associated event (VAE) surveillance algorithm was brought in to replace the clinical ventilator-associated pneumonia (VAP) surveillance by NHSN in January 2013. This study intends to find the correlation of these surveillance criteria with the clinical VAP rates in a neurosurgery intensive care unit (ICU). Materials and Methods: This was a retrospective analysis of records of patients undergoing invasive mechanical ventilation in a neurosurgery ICU during a 3-month period. Results: Thirty-seven patients underwent invasive mechanical ventilation. The mean age was 56 years. Hypertension was the most common comorbidity among 22 (59.4%) patients. The neurological diagnosis was traumatic brain injury in 19 cases, nontraumatic intracranial hemorrhage in 12 cases, and ischemic stroke in 6 cases. Twenty-one patients had respiratory sample culture positivity and 14 were clinical VAP. The total ventilator days assessed were 82. The clinical VAP rate was 170.7, and the probable VAP (PVAP) rate for the same period was 12.19. Among the 14 patients who developed clinical VAP, 13 (88%) were hospital acquired and caused by multidrug-resistant pathogens. Six patients died during their ICU stay. ICU stay of more than 7 days was significantly associated with a clinical VAP. Conclusions: VAE was found to correlate poorly with a clinical diagnosis of VAP. When used as a surveillance tool in an ICU, it was found to miss important infection-related events in ventilated patients.

Patients’ experiences of mechanical ventilation in intensive care units in low- and lower-middle-income countries: protocol of a systematic review

BackgroundMechanical ventilation (MV) in intensive care units (ICUs) is a stressful experience for patients. However, these experiences have not been systematically explored in low- and lower-middle-income countries (LLMICs). This systematic review (SR) aims to explore the patients’ experiences of MV in ICUs in LLMICs and the factors influencing their experiences.MethodsThe PICO framework will be used to operationalize the review question into key concepts: population (mechanically ventilated adult patients in ICUs), phenomenon of interest (experiences) and context (LLMICs). PubMed, Embase, PsycINFO, CINAHL, Cochrane Library, Scopus and Web of Science will be systematically searched since database inception. Citation, reference list and PubMed-related article searching of included studies will be done to ensure literature saturation. Empirical peer-reviewed literature exploring adult patients’ (aged ≥ 18 years) experiences of MV in ICUs in LLMIC will be included. All study designs (quantitative, qualitative and mixed methods) will be included. Two independent reviewers will perform screening, data extraction and critical appraisal. The mixed-methods appraisal tool (MMAT) and Popay’s narrative synthesis will be used for critical appraisal and data synthesis, respectively.DiscussionThis SR aims to bridge a gap in knowledge as previous evidence synthesis has described this phenomenon in developed countries. The review design, with the inclusion of quantitative, qualitative and mixed-methods studies, intends to provide a rich and in-depth exploration of the issue. The findings will be presented as themes, subthemes and their explanatory narratives. The gaps in available literature will be identified, and implications of SR findings on policy, practice and future research will be presented. The strength of this SR lies in its systematic, comprehensive, transparent, robust and explicit methodology of identifying, collating, assessing and synthesizing available evidence. By prior registration and reporting of this SR protocol, we aim to ensure transparency and accountability and minimize bias.Systematic review registrationPROSPERO CRD42024507187

Predicting the Risk of In-Hospital Mortality in Traumatic Brain Injury Patients on Invasive Mechanical Ventilation in the Intensive Care Unit: Construction and Validation of an Online Nomogram

To explore mortality risk factors and to construct an online nomogram for predicting in-hospital mortality in traumatic brain injury (TBI) patients receiving invasive mechanical ventilation (IMV) in intensive care unit (ICU). We retrospectively analysed TBI patients on IMV in ICU from MIMIC-Ⅳ database and two hospitals. Least Absolute Shrinkage and Selection Operation (LASSO) regression and multiple logistic regression were used to detect predictors of in-hospital mortality and to construct an online nomogram. The predictive performance of nomogram was evaluated using area under the receiver operating characteristic curves (AUC), calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). 510 from MIMIC-Ⅳ database were enrolled for nomogram construction (80%, n=408) and internal validation (20%, n=102). 185 from two hospitals were enrolled for external validation. LASSO-Logistic regression revealed predictors of in-hospital mortality among TBI patients on IMV in ICU included Glasgow Coma Scale (GCS) after ICU admission, Acute Physiology Score Ⅲ (APS Ⅲ) after ICU admission, neutrophil and lymphocyte ratio after IMV, blood urea nitrogen after IMV, arterial serum lactate after IMV, and in-hospital tracheotomy. The AUC, calibration curves, DCA, and CIC indicated the nomogram had good discrimination, calibration, clinical benefit, and applicability. The multi-model comparisons revealed the nomogram had higher AUC than GCS, APS Ⅲ, and Simplified Acute Physiology Score Ⅱ. We constructed and validated an online nomogram based on routinely recorded factors at admission to ICU and at the beginning of IMV to target prediction of in-hospital mortality among TBI patients on IMV in ICU.

Predictors of Weaning Failure from Mechanical Ventilation in Pediatric Intensive Care Unit

Predictors of Weaning Failure from Mechanical Ventilation in Pediatric Intensive Care Unit

Kindergarten Readiness Assessment Scores in Children who Received Early Life Mechanical Ventilation in the Pediatric Intensive Care Unit

AbstractThe impact of prolonged sedative medication usage on cognitive outcomes of young pediatric intensive care unit (PICU) patients has been incompletely assessed. We aim to assess the feasibility of linking an electronic medical record (EMR) system and a regional database to evaluate performance on standardized testing among PICU survivors. This is a single-center data-linkage study between EMR records and the Child and Household Integrated Longitudinal Data (CHILD) system, which links individual-level data across 35 administrative systems including Kindergarten Readiness Assessment (KRA) scores. The study was performed at a tertiary PICU in Cleveland, Ohio, United States with children born in 2011 or 2012 who received invasive mechanical ventilation and sedation before the age of 3 years in our PICU. We evaluated rate of “on-track” KRA scores, chronic absenteeism, and repeat kindergarten in the study population compared with a propensity score matched cohort from CHILD. Of 182 eligible PICU patients, 98 (54%) had a record identified in CHILD, and 32 had KRA scores available and sufficient data for propensity score matching. Compared with 160 matched controls, PICU patients had a lower rate of “on-track” scores (7/32 [22%] vs 102/160 [64%], p &lt; 0.001) and more chronic absenteeism (14/32 [44%] vs. 34/160 [22%], p = 0.007). There was no difference in rates of repeat kindergarten (8/32 [25%] vs. 36/160 [23%], p = ;−0.759). We determined that linking hospital EMR records to regional databases is a feasible method to explore PICU outcomes. Additional studies are needed to confirm our preliminary finding of poor performance compared with matched controls.

Validity of A new Weaning Index of Discontinuation From Mechanical Ventilation in Intensive Care Unit

Abstract Background Failure to wean from mechanical ventilation (MV) is a frequent problem in the intensive care unit (ICU) setting. Herein, we investigate a new WI measured at the initial spontaneous breathing trial (SBT) in order to predict successful liberation from MV in mechanically ventilated ICU cases. Patients and methods This prospective cross-sectional study consisted of two phases; Phase I was designed to create a new WI from the criteria of 60 mechanically ventilated patients, while Phase II aimed to assess the accuracy of that index in another 40 patients. Patients aged older than 18 years who were receiving controlled-mode MV from day 3 to day 14 and planned to be weaned off MV were included in our study. Contrarily, patients with prior history of poor tolerance to SBT, weaning failure were excluded. Additionally, we also excluded patients with neurological or neuromuscular disorders, tracheostomy, pregnancy, or an active COVID-19 infection. Results The incidence of failed weaning was 33.3% in phase I, and 35% in phase II. Pulmonary causes were the most common indication in both groups. Multivariate regression analysis was done for phase I variables, and the following equation was created; (((Cough strength* 0.743) - 1.927) *0.05 + ((PaCO2 (mmHg)* - 0.126) + 6.786) *0.08 + ((mean airway pressure (CmH2O) * -1.304) + 14.119) *0.193 + ((PaO2/FIO2 * 0.268) - 58.555) *0.328 + ((rapid shallow breathing index * -0.485) + 24.406) *0.353). Using a cut-off value of &amp;gt; 0.69 and applying this index in phase II, it showed a mean value of -1.43 and 4.67 in the failure and success groups, respectively (p &amp;lt; 0.001). This new WI with cutoff value (&amp;gt; 0.69) had 88.5% sensitivity, 57.1% specificity, and a 77.5% accuracy to predict the success of weaning from MV. Conclusion We developed a new WI with good sensitivity and moderate specificity for predicting successful weaning from MV in ICU patients. Its use should be encouraged in the ICU setting, especially by less experienced ICU physicians.

The Future of Artificial Intelligence in Surgery.

Until recently, innovations in surgery were largely represented by extensions or augmentations of the surgeon's perception. This includes advancements such as the operating microscope, tumor fluorescence, intraoperative ultrasound, and minimally invasive surgical instrumentation. However, introducing artificial intelligence (AI) into the surgical disciplines represents a transformational event. Not only does AI contribute substantively to enhancing a surgeon's perception with such methodologies as three-dimensional anatomic overlays with augmented reality, AI-improved visualization for tumor resection, and AI-formatted endoscopic and robotic surgery guidance. What truly makes AI so different is that it also provides ways to augment the surgeon's cognition. By analyzing enormous databases, AI can offer new insights that can transform the operative environment in several ways. It can enable preoperative risk assessment and allow a better selection of candidates for procedures such as organ transplantation. AI can also increase the efficiency and throughput of operating rooms and staff and coordinate the utilization of critical resources such as intensive care unit beds and ventilators. Furthermore, AI is revolutionizing intraoperative guidance, improving the detection of cancers, permitting endovascular navigation, and ensuring the reduction in collateral damage to adjacent tissues during surgery (e.g., identification of parathyroid glands during thyroidectomy). AI is also transforming how we evaluate and assess surgical proficiency and trainees in postgraduate programs. It offers the potential for multiple, serial evaluations, using various scoring systems while remaining free from the biases that can plague human supervisors. The future of AI-driven surgery holds promising trends, including the globalization of surgical education, the miniaturization of instrumentation, and the increasing success of autonomous surgical robots. These advancements raise the prospect of deploying fully autonomous surgical robots in the near future into challenging environments such as the battlefield, disaster areas, and even extraplanetary exploration. In light of these transformative developments, it is clear that the future of surgery will belong to those who can most readily embrace and harness the power of AI.

Application of a cloud platform that identifies patient-ventilator asynchrony and enables continuous monitoring of mechanical ventilation in intensive care unit

BackgroundPatient-ventilator asynchrony (PVA) frequently occurs in mechanically ventilated patients within the ICU and has the potential for harm. Depending solely on the health care team cannot accurately and promptly identify PVA. To address this issue, our team has developed a cloud-based platform for monitoring mechanical ventilation (MV), comprising the PVA-RemoteMonitor system and the 24-h MV analysis report. We conducted a survey to evaluate physicians' satisfaction and acceptance of the platform in 14 ICUs. MethodsData from medical records, clinical information systems, and ventilators were uploaded to the cloud platform and underwent data processing. The data were analyzed to monitor PVA and displayed in the front-end. The 24-h analysis report for MV was generated for clinical reference. Critical care physicians in 14 hospitals' ICUs that involved in the platform participated in a questionnaire survey, among whom 10 physicians were interviewed to investigate physicians’ acceptance and opinions of this system. ResultsThe PVA-RemoteMonitor system exhibited a high level of specificity in detecting flow insufficiency, premature cycle, delayed cycle, reverse trigger, auto trigger, and overshoot, with sensitivities of 90.31 %, 98.76 %, 99.75 %, 99.97 %, 100 %, and 99.69 %, respectively. The 24-h analysis report supplied essential data about PVA and respiratory mechanics. 86.2 % (75/87) of physicians supported the application of this platform. ConclusionsThe PVA-RemoteMonitor system accurately identified PVA, and the MV analysis report provided guidance in controlling PVA. Our platform can effectively assist ICU physicians in the management of ventilated patients.

Echocardiogram by apical-subcostal protocol in prone position during invasive mechanical ventilation in cardiovascular intensive care unit

AimsTo evaluate the feasibility of a transthoracic echocardiogram using an apical-subcostal protocol in invasive mechanical ventilation (IMV) and prone position.MethodsProspective study of adults who required a prone position during IMV. A pillow was placed only under the left hemithorax in the prone position to elevate and ease the apical and subcostal windows. A critical care cardiologist (prone group) acquired and evaluated the images using the apical-subcostal protocol. Besides, we used ambulatory echocardiograms performed as a comparative group (supine group).Results86 patients were included, 43 in the prone and 43 in the supine. In the prone group, the indication to perform an echocardiogram was hemodynamic monitoring. All patients were ventilated with protective parameters, and the mean end-expiratory pressure was 10.6 cmH2O. The protocol was performed entirely in 42 of 43 patients in the prone group because one patient did not have any acoustic window. In the 43 patients in the prone group analyzed and compared to the supine group, global biventricular function was assessed in 97.7% (p = 1.0), severe heart valve disease in 88.4% (p = 0.055), ruled out of the presence of pulmonary hypertension in 76.7% (p = 0.80), pericardial effusion in 93% (p = 0.12), and volume status by inferior vena cava in 93% (p = 0.48). Comparing prone versus supine position, a statistical difference was found when evaluating the left ventricle apical 2-chamber view (65.1 versus 100%, p < 0.01) and its segmental function (53.4 versus 100%, p < 0.01).ConclusionThe echocardiogram using an apical-subcostal protocol is feasible in patients in the IMV and prone position.Graphical

Manifestation of epidemic process, clinical and epidemiological characteristics of adult patients in the early period of the COVID-19 epidemic in Russia

BACKGROUND: The COVID-19 pandemic became a challenge and caused significant social and economic damage to most countries. For the most objective assessment of the epidemiological and clinical features of COVID-19 during different periods of the epidemic, studies based on a large volume of data on patients identified throughout the Russian Federation are necessary. AIM: To analyze the epidemic process and clinical and epidemiological features of adult patients with COVID-19 identified during the first and second periods of the rise and decline in the incidence of COVID-19 in Russia. MATERIALS AND METHODS: This study included patients aged ≥18 years with a confirmed diagnosis of COVID-19 and identified in the periods from March 2, 2020, to June 30, 2020 (n=286,205) and from November 1, 2020, to January 31, 2021 (n=1 655 022), in Russia. RESULTS: At the early stage of the COVID-19 epidemic in Russia, two periods of the rise and fall in incidence were noted: March–August 2020 and September 2020–May 2021, using the Wald–Wolfowitz test. The median age of the patients with COVID-19 in the first and second periods were 50.0 [37–62] and 52.0 [39–64] years, respectively, and women accounted for 55.5 and 60.1% of the patients, respectively. The distributions of patients according to disease severity in the first and second periods were as follows: mild, 63.0 and 74.4%; moderate, 29.0 and 20.1%; severe, 4.9 and 3.5%; extremely severe, 3.1 and 2.1%, respectively. In the first and second periods, cases were dominated by patients aged 50–59 years (20.5%) and 60–69 years (20.5%), respectively. In both periods, the median duration from the onset of symptoms to diagnosis was 4 days, the median disease durations were 16.0 [12–21] and 13 [10–17], and the median duration of hospitalization were 15.0 [12–20] and 13.0 [10–18]. The hospitalization rates were 48.4 and 25.6% in the first and second periods; transfer rates to the ICU, 7.8 and 10.3%; and invasive mechanical ventilation rates, 5.6 and 7.7%, respectively. In both periods, the median age at death was 73 [66–82] years, with a higher proportion of men aged 30–39, 40–49, 50–59, and 60–69 years. The presence of one or more chronic diseases, as well as male sex, increased the likelihood of death (odds ratio = 10.2 and 1.3 in the first period; odds ratio = 16.0 and 1.6 in the second period). CONCLUSIONS: In the early period of the COVID-19 epidemic in Russia, related to the spread of the wild strain of SARS-CoV-2 and genetically closely related variants, the manifestations of the epidemic process and clinical and epidemiological characteristics of patients varied. In the second period with higher incidence and mortality rates than the first period, the frequency of severe and extremely severe COVID-19 and the frequency and duration of hospitalizations decreased; however, the frequency of transfers into the intensive care unit and artificial lung ventilation slightly increased.

Role of diaphragmatic ultrasound in predicting weaning success from mechanical ventilation in pediatric intensive care unit

BackgroundWeaning off mechanical ventilation (MV) is a critical step in pediatric ICU; however, it lacks standardized criteria. Diaphragmatic ultrasound parameters like diaphragm thickening fraction (DTF), diaphragmatic excursion (DE) and time to peak inspiratory amplitude (TPIA) can be used to assess diaphragmatic muscle strength and to predict weaning success.Aim of studyIs to assess the validity of diaphragmatic ultrasonography as a predictor of weaning outcome from mechanical ventilation in pediatric age group.MethodsProspective cohort study including 30 pediatric patients aged 0–18 years on mechanical ventilation. Ultrasound measurements of diaphragmatic thickening fraction, diaphragmatic excursion and time to peak inspiratory amplitude were taken during the spontaneous breathing trial (SBT) and compared between successful and failed weaning groups.ResultsOut of the included 30 patients (50% male), 19 patients (63.3%) were successfully weaned. Mechanical ventilation duration was significantly longer in the failed weaning group (P = 0.017). There was significant difference between both groups regarding right DE (P = 0.032) and left DE (P = 0.022) with cutoff values of > 4.1 mm and > 5.5 mm with AUC (Area under curve) of 0.737 and 0.831, respectively. There was no statistically significant difference between both groups regarding DTF or TPIA.ConclusionWe have found that DE is a predictor of weaning success, while DTF and diaphragmatic TPIA had no correlation with weaning outcome.

Predictive risk factors for one-year mortality in idiopathic inflammatory myopathy patients with interstitial lung disease: A retrospective, single-center cohort study.

This study aimed to analyze the risk factors for mortality of idiopathic inflammatory myopathy (IIM) patients admitted with interstitial lung disease (ILD) to guide rapid and accurate judgment of clinical prognosis. This retrospective, single-center cohort study was conducted with 135 participants (37 males, 98 females; mean age: 54.8±11.1 years; range, 24 to 85 years) between June 1, 2016, and June 30, 2021. The participants were categorized into the survival group (n=111) and nonsurvivors (n=24) according to whether they survived during the one-year follow-up. The independent risk factors for mortality in one year after discharge were analyzed. Receiver operating characteristic curve analysis was used to determine the accuracy of oxygenation index at baseline combined with pulmonary infection (PI) at follow-up to indicate death in IIM-ILD patients. Compared to the survival group, nonsurvivors were older (p=0.006) and had a higher proportion of anti-MDA5 (melanoma differentiation-associated protein 5) positivity (p<0.001). The ILD duration was shorter (p=0.006), the oxygenation index was lower (p<0.001), and the intensive care unit occupancy rate (p<0.001) and ventilator utilization rate (p<0.001) were elevated in nonsurvivors compared to the survival group. Oxygenation index at baseline (odds ratio [OR]=1.021, 95% confidence interval [CI]: 1.001-1.023, p=0.040) and PI (clinical judgment) at follow-up (OR=16.471, 95% CI: 1.565-173.365, p=0.020) were found as independent risk factors for death in the year after discharge in IIM inpatients with ILD. An oxygenation index ≤279 mmHg at baseline combined with PI at follow-up exhibited a promising predictive value for all-cause death in IIM-ILD patients within one year. Oxygenation index at baseline and PI during follow-up were independent risk factors for death of IIM-ILD patients within one year after discharge. Patients with an oxygenation index ≤279 mmHg at baseline had an increased risk of death once they developed PI during the one-year follow-up.

Advancing ICU patient care with a Real-Time predictive model for mechanical Power to mitigate VILI

BackgroundInvasive Mechanical Ventilation (IMV) in Intensive Care Units (ICU) significantly increases the risk of Ventilator-Induced Lung Injury (VILI), necessitating careful management of mechanical power (MP). This study aims to develop a real-time predictive model of MP utilizing Artificial Intelligence to mitigate VILI. MethodologyA retrospective observational study was conducted, extracting patient data from Clinical Information Systems from 2018 to 2022. Patients over 18 years old with more than 6 h of IMV were selected. Continuous data on IMV variables, laboratory data, monitoring, procedures, demographic data, type of admission, reason for admission, and APACHE II at admission were extracted. The variables with the highest correlation to MP were used for prediction and IMV data was grouped in 15-minute intervals using the mean. A mixed neural network model was developed to forecast MP 15 min in advance, using IMV data from 6 h before the prediction and current patient status. The model’s ability to predict future MP was analyzed and compared to a baseline model predicting the future value of MP as equal to the current value. ResultsThe cohort consisted of 1967 patients after applying inclusion criteria, with a median age of 63 years and 66.9 % male. The deep learning model achieved a mean squared error of 2.79 in the test set, indicating a 20 % improvement over the baseline model. It demonstrated high accuracy (94 %) in predicting whether MP would exceed a critical threshold of 18 J/min, which correlates with increased mortality. The integration of this model into a web platform allows clinicians real-time access to MP predictions, facilitating timely adjustments to ventilation settings. ConclusionsThe study successfully developed and integrated in clinical practice a predictive model for MP. This model will assist clinicians allowing for the adjustment of ventilatory parameters before lung damage occurs.

Diaphragm Ultrasound in Different Clinical Scenarios: A Review with a Focus on Older Patients.

Diaphragm muscle dysfunction is increasingly recognized as a fundamental marker of several age-related diseases and conditions including chronic obstructive pulmonary disease, heart failure and critical illness with respiratory failure. In older individuals with physical frailty and sarcopenia, the loss of muscle mass and function may also involve the diaphragm, contributing to respiratory dysfunction. Ultrasound has recently emerged as a feasible and reliable strategy to visualize diaphragm structure and function. In particular, it can help to predict the timing of extubation in patients undergoing mechanical ventilation in intensive care units (ICUs). Ultrasonographic evaluation of diaphragmatic function is relatively cheap, safe and quick and can provide useful information for real-time monitoring of respiratory function. In this review, we aim to present the current state of scientific evidence on the usefulness of ultrasound in the assessment of diaphragm dysfunction in different clinical settings, with a particular focus on older patients. We highlight the importance of the qualitative information gathered by ultrasound to assess the integrity, excursion, thickness and thickening of the diaphragm. The implementation of bedside diaphragm ultrasound could be useful for improving the quality and appropriateness of care, especially in older subjects with sarcopenia who experience acute respiratory failure, not only in the ICU setting.

Predictive value of fluid balance before extubation on its outcome in mechanically ventilated adults in the intensive care unit.

Although there are many reasons for extubation failure, maintaining negative or lower positive fluid balances 24 hours before extubation may be a key measure for successful extubation. To assess the predictive value of fluid balance before extubation and its outcome in mechanically ventilated cases in the intensive care unit (ICU). This retrospective cohort study involved collecting clinical data from patients undergoing mechanical ventilation in Lanzhou general adult ICU from January 2022 to December 2022. Based on extubation outcomes, the patients were divided into a successful extubation group and a failed extubation group. Their fluid balance levels 24 h before extubation were compared with analyse the predictive value of fluid balance on extubation outcomes in patients undergoing mechanical ventilation. In this study, clinical data from 545 patients admitted to a general adult ICU were collected. According to the inclusion and exclusion criteria, 265 (48.6%) patients were included, of which 197 (74.3%) were successfully extubated; extubation was unsuccessful in 68 (25.7%) patients. The total intake and fluid balance levels in patients in the failed extubation group 24 h before extubation were significantly higher than those in the successful extubation group, with a median of 2679.00 (2410.44-3193.50) mL versus 2435.40 (1805.04-2957.00) mL, 831.50 (26.25-1407.94) mL versus 346.00 (-163.00-941.50) mL. Receiver operating characteristic (ROC) curve analysis showed that the optimal cut-off value for predicting extubation outcomes was 497.5 mL (sensitivity 64.7%, specificity 59.4%) for fluid balance 24 h before extubation. The area under the ROC curve was 0.627 (95% confidence interval [CI] 0.547-0.707). Based on the logistic regression model, cumulative fluid balance >497.5 mL 24 h before extubation could predict its outcomes in mechanically ventilated patients in the ICU (OR = 5.591, 95% CI [2.402-13.015], p < .05). The fluid balance level 24 h before extubation was correlated with the outcome of extubation in mechanically ventilated patients in the ICU. The risk of extubation failure was higher when the fluid balance level was >497.5 mL. Tracheal intubation is a crucial life support technique for many critically ill patients, and determining the appropriate time for extubation remains a challenge for clinicians. Although there are many reasons for extubation failure, acute pulmonary oedema caused by continuous positive fluid balance and volume overload is one of the main reasons for extubation failure. Therefore, it is very important to study the relationship between fluid balance and extubation outcome to improve the prognosis of patients with invasive mechanical ventilation in ICU.