Academic Unit Research Articles

Facing psychological effects of the COVID-19 pandemic. A view from the perception of medical students from 1st to 6th year of the Faculty of Medical Sciences of the National University of Asunción.

The COVID-19 pandemic presented itself with characteristics of a critical global incident that impacted the mental health of members of the educational community. In March 2020, the Faculty of Medical Sciences, FCM, was the first academic unit of the National University of Asunción, UNA, to revert to an emergency digital format, with total suspension of face-to-face classes. This paper explores how the pandemic impacted students´ lives at FCM-UNA, from their perception, to understand and identify possible emerging mental health problems and accompany the process of adaptation to the new normal in the post-pandemic. The work is descriptive, and qualitative, with an interpretative approach. The target population was students from 1st to 6th year of medical school who voluntarily agreed to participate in the research. The information collection technique was the focus group, applied in two phases, phase 1 - exploratory and phase 2 - deepening. The unit of analysis was the speeches of the participants. The results obtained reveal that the first phase of the pandemic took place in a virtual context of pain, fear, and helplessness in tension with the subsequent resilient struggle to transform this adversity, manifested by the students. The psycho-social dimension of the construction of professional identity was perhaps the most affected. The observations made have served as a basis for the planning and implementation of guidelines for the detection of risk cases, accompaniment, and guidance, providing adequate teaching support in the post-pandemic period.

A PATHWAY TO SYSTEMIC CHANGES IN STEM LEADERSHIP: INCREASING REPRESENTATION OF WOMEN THROUGH THE EXTERNAL MENTOR PROGRAM

Leadership advancement is more difficult for women in STEM than their male counterparts, and while women are as committed to their academic careers, they face many systemic barriers. Mentoring programs can be one effective approach to mitigating these barriers by facilitating individuals' career development, in turn creating organizational changes. Through quantitative and qualitative analysis, using a case study approach, this paper examines the External Mentor Program outcomes with respect to supporting women faculty in their own career advancement and in creating systemic changes. We found that participants were generally satisfied with this program, reporting an increase in research and writing productivity, as well as expanded networking opportunities and an improvement in their own mentoring abilities. The External Mentor Program also had an effect on the women faculty's departments' culture and climate, which potentially has the ability to transform the larger organization/institution. Change within individual academic units is foundational to shifts in the overarching structures at the college and university level. This mentoring program has shown positive outcomes for both the individuals participating as well as their departments, and subsequently the university at large.

Gap Analysis of Strategies and Experiences of Academic Units with Licensure Examinations

Gap Analysis of Strategies and Experiences of Academic Units with Licensure Examinations

Presenting a Model for Virtual Education Using Interpretive Structural Modeling Method at Farhangian University of Khorasan Razavi

Objective: The primary goal of this research was to present a model for virtual education using the interpretive structural modeling method at Farhangian University in Khorasan Razavi. Method: The current research methodology was qualitative and applied in nature. Participants included faculty members from Farhangian University in Khorasan Razavi, selected purposively with a sample size of 13 individuals. The research tool was semi-structured interviews, the validity of which was established through face validity, and reliability was determined by an agreement coefficient between coders, resulting in a 0.85 upon re-coding between the researcher and an external coder. Additionally, a researcher-developed questionnaire was designed based on qualitative findings and distributed among the sample members. Data analysis employed coding analysis, and for the initial stage of identifying factors, the interpretive structural modeling (SIM) method was used. Findings: The findings indicated that the virtual education model consists of five levels and priorities, including: Level One: Futuristic Vision; Level Two: Targeted Educational Quality, Measurability, Support Services, Information and Content; Level Three: Accessibility, Knowledge Management, and Flexibility in Education; Level Four: Pedagogical, Technological Factors, and Organizational Factors; and Level Five: Integrated Management. Conclusion: Based on this research, the board of trustees, policymakers, senior managers, and the central university planning organization can work towards improving virtual education at Farhangian University, specifically as a pilot in Farhangian University of Khorasan Razavi. The managers of this academic unit can create conditions to implement the findings of this research to enhance education, particularly virtual education at this university.

Celebrating the Culture of Interprofessional Collaboration in Athletic Training

Celebrating the Culture of Interprofessional Collaboration in Athletic Training

Teaching practice in higher education. Analysis from educational models

The objective of this study is to describe the teaching practice from the experience of the students, based on the knowledge that teachers have about the subject, the pedagogical abilities or skills they possess, interpersonal relationships, personality characteristics, research associated with the chair, and planning. The method was quantitative with a descriptive scope and cross-sectional design, it was applied in 106 surveys to students of the Psychology Academic Unit of the Autonomous University of Zacatecas, in the State of Zacatecas, Mexico. A self-made instrument called "Teaching practice questionnaire, student perception" was applied with a "Cronbach's Alpha" of 0.93. It was found that if the teacher is critically trained, assesses the teaching and learning processes through dialogue, interacts with other teachers, and builds and lives values in their educational and social context, they will be in agreement with a practice close to a paradigm constructivist.

Decision Support System to Determine Higher Education Resource Needs Using Accreditation Assessment Standards

Accreditation is an activity to evaluate the eligibility of programs and academic units based on predetermined criteria. In an educational institution, accreditation is an important thing to do to improve quality in the field of education because the aim is to improve quality which includes all aspects of education in the form of science, administration, as well as teaching, and educational staff. College managers really need a decision support system that can produce several alternative strategic decisions quickly and accurately. The existence of decision support system tools used to make strategic decisions makes the manager's work lighter and the results are more accurate. In this study, a decision support system approach was applied to determine the resource requirements of tertiary institutions using accreditation assessment standards consisting of a management subsystem model, data management subsystem, and user interface management subsystem. The result of the research is a design of a decision support system that can be used in an educational institution for determining the need of higher education resources.

The Chair's Role in Assurance of Learning

The Chair's Role in Assurance of Learning

970: PHYSIOLOGY-BASED VENTILATOR COMPUTER DECISION SUPPORT OUTPERFORMS CLINICIANS IN AN IN SILICO TRIAL

Introduction: Intensivists are routinely required to titrate alveolar minute ventilation based on blood gas information. Survey data show that intensive care trainees feel insufficiently trained in ventilator management. Bedside decision support has the potential to facilitate more efficient ventilator titration and serve as a teaching tool for trainees. Methods: We developed an online ventilator calculator based upon arterial partial pressure of carbon dioxide (PaCO2) and Henderson-Hasselbalch equations, allowing clinicians to input ventilator parameters as well as current and desired blood gas information. We validated predictions among arterial blood gas (ABG) values from a single quaternary academic pediatric intensive care unit (PICU). We included all ABG values obtained between 1/1/2010 and 12/31/2020 among PICU patients receiving invasive pressure control, volume control, or volume targeted ventilation and concurrent pharmacologic muscle relaxation with a repeat blood gas analysis within 1-24 hours. We excluded ABGs from patients on extracorporeal support. We subsequently performed a retrospective in-silico trial on a subset of ABGs meeting criteria for ventilator weaning (pCO2 < 30 and pH > 7.35 or pCO2 < 50 and pH > 7.50) or escalation (pCO2 > 50 and pH < 7.30 or pCO2 > 45 and pH < 7.20), excluding patients with traumatic brain injury. Clinician behavior was compared against calculator recommendations, with a goal of achieving an ABG value that met neither weaning nor escalation criteria. Results: There were 16,835 included ABGs among 664 patients, with a median (IQR) time between ABGs of 3.8 (2.2-4.4) hours. The median (IQR) difference between predicted and actual PaCO2 values was 0.00 (-3.06-3.00) mmHg. 11,460/16,835 (68.1%) PaCO2 values were within 5 mmHg of predicted, and 14,902/16,835 (88.5%) were within 10 mmHg. There were 2,433 ABGs among 350 patients included in the in-silico trial. Calculator recommendations were preferable to clinician behavior in 1,149/1,534 (74.9%) weaning scenarios and 605/899 (67.3%) escalation scenarios. Conclusions: Computer decision support outperformed clinician actions in this retrospective in-silico trial and may provide a useful teaching tool for trainees. Prospective study is needed to determine feasibility and user satisfaction.

985: EVALUATION OF DISCHARGE OPIOID PRESCRIBING IN MECHANICALLY VENTILATED ICU PATIENTS

Introduction: Opioids are a core component in the multimodal approach to patient analgesia during invasive mechanical ventilation (IMV). However, the implications of opioid use during IMV on prescribing opioids on hospital discharge is unknown. Methods: We conducted a retrospective cohort study of patients requiring IMV within a tertiary academic medical intensive care unit (MICU) to characterize hospital discharge opioid prescribing patterns between opioid-naive and opioid-users. We included patients that received at least 1 dose of opioid within the first 12-hours of IMV and required IMV for at least 24 hours. Patients were characterized as opioid-naïve or opioid-users based upon opioids prescribed prior to MICU admission. The primary outcome was the percentage of patients prescribed opioids at hospital discharge. Secondary outcomes included the morphine milligram equivalents (MME) per day during IMV, delirium-free days, correlation of pain (critical care pain observation tool (CPOT)) scores and MME during IMV, duration of IMV, and length of hospital stay (LOS). Results: One hundred sixty-seven consecutive patients presenting to the MICU were included. Of these, 128 (76.6%) were opioid-naïve and 39 (23.4%) were opioid-users. Median age was 59 years and 61.7% were Caucasian. More opioid-users had cancer compared to opioid-naïve (35.9% vs 14.8%, p< 0.001). Thirty-two (25%) opioid-naïve and 27 (69.2%) opioid-users were prescribed opioids on discharge. The mean MME prescribed at discharge was higher in opioid-users, compared to opioid-naive (77.2 vs 16.4, p< 0.001). The median quantity of opioids prescribed during IMV did not differ between groups (465 MME in opioid-naïve vs. 467 MME in opioid-user, p=0.49). Median daily CPOT scores did not correlate with MME or dose titrations. There was no difference in duration of IMV or LOS between groups. Opioid-naïve patients had less delirium-free days, compared to opioid-users (0.68 vs. 1.13, p=0.003). Conclusions: Our study found 25% of opioid-naïve patients undergoing IMV were discharged from the hospital on opioids and the daily CPOT score did not correlate with MME and dose titration. It is unclear why 25% of opioid-naïve patients who underwent IMV in a MICU required opioids at hospital discharge and is an area that warrants further investigation.

905: POST-INTUBATION PARTIAL PRESSURE OF O2/FRACTION OF INSPIRED O2 AND IN-HOSPITAL MORTALITY IN COVID-19

Introduction: Early determinants of clinical outcome for SARS-CoV-2 infection (COVID-19) and pneumonia remain a critical need to guide patient management, goals of care discussions, and resource allocation in times of surges. Our hypothesis, there is an association between the Partial pressure of oxygen/Fraction of inspired oxygen (P:F) ratio immediately after intubation in patients with COVID-19 respiratory failure and in-hospital mortality. Methods: This is a cross sectional retrospective observational study in an urban academic tertiary care intensive care unit (ICU). The study was approved by the University’s Institutional Review Board. Patients included in the study were admitted to the medical ICU who tested positive for SARS-CoV-2 requiring escalation of care with intubation and placement on mechanical ventilation. Patients less than 18 years of age or who were pregnant were excluded from the study. Data analysis was conducted using Stata 17.0 software. Univariate logistic regression analyses of the independent variables on the primary outcome were used individually and odds ratios with confidence intervals calculated. Results: The inclusion criteria were met in 78 patients of which two patients were excluded from the study due to multiple missing data points. Participants had an average age of 57.3 years with 68% under 65 and 78% male. The majority of patients (54%) had a BMI ≥30 while 51% had a history of diabetes. Only 14% had a history of chronic kidney disease. Fifty percent of the total sample had Initial post-intubation P:F ratio values < 100 and 50% had values ≥100. Total in-hospital mortality for all patients through the period of observation was 49%. Patients with a P:F ratio of < 100 had 100% increased odds of in-patient mortality. The OR was 2.1 for in-hospital mortality for patients with P:F ratio < 100 (58%), versus those with P:F ratio ≥100 (39%), [95% CI, 0.84 to 5.27], p = 0.11. Bivariate logistic regression analyses for association of in-hospital mortality with individual independent variables did not show significance. Conclusions: The odds of in-hospital mortality is higher when immediate post-intubation P:F ratio is < 100. While this did not reach statistical significance due to the limited size of the study, it remains of clinical interest and warrants further investigation.

52: PROSPECTIVE REAL-TIME VALIDATION OF A LUNG ULTRASOUND DEEP LEARNING MODEL IN THE INTENSIVE CARE UNIT

Introduction: Lung ultrasound (LUS) shows diagnostic superiority to chest radiography in the ICU setting however its widespread deployment is challenged by limited user base and its dependence on clinical expertise. Artificial intelligence models have been developed to overcome these barriers through LUS automation; however, bedside pragmatic performance has never been demonstrated. In this study, we aimed to evaluate the accuracy of a bedside, real-time deployment of a deep learning model capable of distinguishing between normal (A line pattern) and abnormal (B line pattern) lung parenchyma on lung ultrasound in critically ill patients. Methods: Prospective, observational study evaluating the performance of a previously-trained LUS deep learning (DL) model on 100 admitted patients to an academic intensive care unit (ICU). Enrolled patients received an anterior zone LUS exam (4 views) with frame-by-frame DL model predictions using a portable device. Clip-level model predictions were analyzed and compared to blinded expert review for A vs B line pattern. Four clip-level prediction cutoffs were applied to maximize model sensitivity and specificity at bedside. Results: A total of 100 unique ICU patients (400 clips) were enrolled from two tertiary care sites. The majority of patients were receiving mechanical ventilation (56/100), 12 patients were in the weaning process with ongoing trach-mask trials, 4 patients were on High-Flow Nasal Cannula, 4 were on non-invasive ventilation (BiPAP), and 25 patients were on nasal prongs. The Mindray M9 and Sonosite X-Porte ultrasound machines were used to scan 50 patients each. When compared to gold-standard expert annotation, the real-time inference yielded an accuracy of 95%, sensitivity of 93%, and specificity of 96% for identification of the B line pattern. Varying the prediction cutoffs reveal that diagnostic performance may be readily customized to suit the clinical environment. Conclusions: Promoting the feasibility and direct application of bedside AI in the ICU, we have shown that a binary DL ultrasound model demonstrates excellent bedside accuracy in distinguishing between normal and abnormal lungs when deployed in real-time in the ICU.

Construct Validity of the Stroke Upper-Limb Capacity Scale as a Measure of Upper Extremity Capacity

<h3>Research Objectives</h3> The Stroke Upper-Limb Capacity Scale (SULCS) is a standardized assessment of 10 upper extremity (UE) functional tasks, but there are little data on construct validity in acute stroke. Using International Classification of Function definitions, we hypothesize: H1 – a stronger relationship between the SULCS and another activity measure (Functional Independence Measure Selfcare (FIM-SC)), as compared to the SULCS and an impairment measure Motricity Index-UE (MI-UE)); H2 – a stronger association between the SULCS and UE items on the FIM (eating, grooming and bathing (FIM-E, FIM-G, FIM-Ba, respectively)) compared to FIM items not dependent on UE function (walking, bowel and expression (FIM-W, FIM-Bo, FIM-Exp, respectively)). <h3>Design</h3> Cross-sectional. <h3>Setting</h3> Academic inpatient rehabilitation unit. <h3>Participants</h3> N=341/488 (70%) admissions with complete data, age=70±15 years, time post stroke=10±9 days, length of stay=14±8 days, female=47.2%, Admission Total FIM=60±20, Admission SULCS=5.5±3.6, Admission MI-UE=65±35. <h3>Interventions</h3> N/A. <h3>Main Outcome Measures</h3> SULCS, FIM and MI-UE. <h3>Results</h3> H1: SULCS correlated significantly with FIM-SC and MI-UE (ρ=0.74 and ρ=0.85, respectively; (p< 0.001)). H2: SULCS correlated significantly with upper extremity selfcare items (FIM-E/ρ=0.61, FIM-G/ρ=0.56 and FIM-Ba/ρ=0.60), and significantly but more weakly with non-upper extremity items (FIM-Bo/ρ=0.47, FIM-W/ρ=0.57 and FIM-Exp/ρ=0.37). All p< 0.001. <h3>Conclusions</h3> Contrary to H1, SULCS was similarly and strongly correlated with MI-UE and FIM. The inability to compensate for hemiparesis with the intact extremity on both SULCS and MI-UE may explain this unexpected finding. H2 was generally supported, as SULCS demonstrated stronger correlations with UE selfcare items compared to non-UE items. The correlation between SULCS and FIM-W is likely due to hemiparesis in stroke commonly affecting upper and lower extremities. We conclude that SULCS is likely a valid measure of UE capacity early after stroke. <h3>Author(s) Disclosures</h3> The authors declare that they have no relevant conflicts that relate to the research described in this paper.

Identifying patterns of innovative organizational culture, transformational leadership style and quality of work life: a qualitative study

Background and Aim: In today's business environment, the basis of competitive advantage has changed from quality to innovation, innovation allows companies to quickly adapt to changes and helps companies find new products and markets. In today's competitive world, the survival of organizations requires special attention to the category of innovative organizational culture. The purpose of this article is to identify patterns of innovative organizational culture, transformational leadership style, and quality of work life, and it is developmental in terms of its purpose. Methodology: The current research is qualitative and the statistical population includes professors of academic units and managers of Azad Universities of Mazandaran. The sampling method of this research was snowball. A semi-structured interview was used to collect information and 20 experts in this field were interviewed. In order to analyze the data in this research, the theme analysis strategy and six-step technique of Clark and Brown (2006) and MAXQDA software were used. Findings: The results of the research showed that in the main theme of innovative culture, four organizing themes of the effects of innovation, organizational learning, individual development of employees and the desire and tendency to innovate were obtained; In the main theme of transformational leadership, two organizing themes of individual considerations, mental motivation, and in the main theme of the quality of working life, three organizing themes of job nature, security and job relations, and rights and benefits were obtained. Conclusion: As a result, paying attention to the extracted factors and making policies for the development and optimization of the use of financial and economic resources to increase the sustainability and competitiveness of the university and to improve and modify the service delivery methods and solutions and suggestions in line with their desirability It was recommended to managers and trustees.

Análisis estadístico y modelo de pronóstico SARIMA aplicado al consumo de energía eléctrica en instalaciones universitarias

Analyzing the energy consumption behavior in buildings is essential for implementing energy-saving and efficient energy use measures without losing attention to the comfort inside the buildings. In this study, a statistical analysis and time series forecast of the energy situation of a group of buildings in a university academic unit in Mexico City was conducted. Seasonal Autoregressive Integrated Moving Average (SARIMA) models were used for the forecast with electrical energy consumption data from 55 months. Training and test partitions were created with these data to generate two SARIMA models. The results showed a strong dependence on the school cycle of electricity consumption, in addition to a shift in the cycle in the first year of the study. The mean absolute percentage error (MAPE) for the training partitions created shows that the best fit is provided by the SARIMA (3,1,1) (1,0,0)12 model for the 48-month separation. In comparison, the SARIMA (2,1,2) (1,0,0)12 model does so for the 43-month test partition. The confidence intervals for the 7- and 12-month forecast are less wide for the SARIMA (3,1,1) (1,0,0)12 model than for the SARIMA (2,1,2) (1,0,0)12 model. Statistical analysis and time series modeling allows a better understanding of the building stock's energy performance and strengthens the energy audit to design or implement energy saving or efficient energy use measures.

Analysis of Self-Organizing Maps and Fuzzy C-Means methods in Clustering Teacher Data for Nominations of Candidates for Education Unit Supervisors

The quality of education is very dependent on the management of education management one of the important factors in the management of education is monitoring and evaluation. Therefore, continuous Education Supervision supported by the appointment of competent supervisors will have implications for the quality of education. Supervision of education management is carried out by the principal or teacher appointed to carry out managerial and academic supervision in certain educational units. The problem that often occurs is that grouping teacher data to be selected as supervisor candidates are still conventional. Therefore, a teacher data grouping model is needed to obtain useful information in planning strategic steps and policy regulations for determining prospective supervisors for academic units. By utilizing Information and Communication Technology, especially in the field of Data Mining, this Teacher Data Grouping research uses the Fuzzy C-Means and Self Organizing Maps method, and the grouping results are analyzed by measuring the spread of data on each grouping formed by using cluster variance. The output of the Teacher Data grouping process using the Fuzzy C-Means and Self Organizing Maps methods can bring up a group of Teacher Data nominations that are competent to be selected as candidates for supervisors for certain educational units. The research results were obtained by forming several groupings in Fuzzy C-Means by providing an error accuracy value of 0.1 and Self Organizing Maps, which is set by the learning rate and learning rate; the results obtained are grouping with 3 clusters by providing a learning rate of 0.8 and a learning rate of 0.7 in the Self Organizing Maps method has a Variant value that is ideal compared to grouping on Fuzzy C-Means and rather than the same method by forming different groups.

Feasibility and Acceptability of Virtual Rounds on an Academic Inpatient Pediatric Unit.

Virtual rounds enable remote participation in bedside clinical encounters. Their effects on education remain poorly characterized and limited by lack of foundational evidence establishing that this approach is welcomed among learners and educators. We assessed technical feasibility and acceptability of incorporating video conferencing into daily work rounds of pediatric residents and attending physicians. We conducted a cross-sectional survey-based study of attending observers and pediatric residents participating in rounds both at the bedside and via video teleconferencing from September to December 2020. Participant experiences were assessed and summarized using parametric Likert-type questions regarding technical issues, efficiency, educational experience, and engagement. Associations between technical aspects and individual perceptions of virtual rounds and self-reported engagement were also measured. Of 75 encounters, 29% experienced technical issues, 45% of which were attributable to a low-quality tablet stand. Negative impacts of virtual rounding on efficiency were reported in 6% of responses. Virtual participants were engaged (70%) and reported educational value for 65% of encounters. Comfort with virtually asking questions (odds ratio 3.3; 95% confidence interval 2.0-5.7) and performing clinical tasks for other patients (odds ratio 0.42; 95% confidence interval 0.2-0.9) were associated with engagement (P <.05). Virtual participation in rounds was technically feasible and maintained educational value and engagement for residents in the majority of encounters, without sacrificing efficiency. Even as restrictions from the coronavirus disease 2019 pandemic are lifted, this rounding model has many important applications, including increasing educational opportunities for remote learners and making multidisciplinary rounds more accessible.

Enablements and Constraints in the Uptake of Digital Technologies for Teaching and Learning

In South African higher education, institutions are exploring pedagogical practices of dealing with a multiple number of emerging technologies. Though the use of educational technologies is an established practice in higher education institutions, its uptake seems to be varied. This chapter draws on a study of educational technologies (EdTechs) in different institutions within the South African higher education context to identify how various academic staff development units (for example, instructional designers in e-learning units) empower academics to integrate technologies in teaching and learning practices. In this chapter, the author analysed data by drawing on Archer's (1995) social realist framework. Data was obtained from an online survey (open-ended questionnaire) and interviews The findings from both data phases reveal a strong call for more theorised approaches in the use of EdTechs to promote digital literacies. In addition, academic development activities were valued as a driver to the uptake of these technologies.

Open and Distance Learning Vision of Higher Education Institutions in Turkey: Implications for Leadership

The current study investigated the open and distance learning vision of higher education institutions in Turkey and revealed several implications for leadership. Considering the potential overlap between vision and mission statements, both of the statements used by 82 units within higher education institutions were qualitatively investigated through content analysis. The findings first revealed that the vision statements of the units cover all system levels from technology to the broader socioeconomic context. Improving quality is the most underlined statement, followed by becoming a leading institution and enabling equity and access. On the other hand, it was observed that there is an overlap between their vision and mission statements, and many of the academic units use similar statements. Based on these findings, several implications were reported for effective leadership in open and distance learning. Although this study encompassed only the context of a specific country, it provided implications for leadership in various contexts.

Inflammatory biomarkers and pendelluft magnitude in ards patients transitioning from controlled to partial support ventilation

The transition from controlled to partial support ventilation is a challenge in acute respiratory distress syndrome (ARDS) patients due to the risks of patient-self-inflicted lung injury. The magnitude of tidal volume (VT) and intrapulmonary dyssynchrony (pendelluft) are suggested mechanisms of lung injury. We conducted a prospective, observational, physiological study in a tertiary academic intensive care unit. ARDS patients transitioning from controlled to partial support ventilation were included. On these, we evaluated the association between changes in inflammatory biomarkers and esophageal pressure swing (ΔPes), transpulmonary driving pressure (ΔPL), VT, and pendelluft. Pendelluft was defined as the percentage of the tidal volume that moves from the non-dependent to the dependent lung region during inspiration, and its frequency at different thresholds (− 15, − 20 and − 25%) was also registered. Blood concentrations of inflammatory biomarkers (IL-6, IL-8, TNF-α, ANGPT2, RAGE, IL-18, Caspase-1) were measured before (T0) and after 4-h (T4) of partial support ventilation. Pendelluft, ΔPes, ΔPL and VT were recorded. Nine out of twenty-four patients (37.5%) showed a pendelluft mean ≥ 10%. The mean values of ΔPes, ΔPL, and VT were − 8.4 [− 6.7; − 10.2] cmH2O, 15.2 [12.3–16.5] cmH2O and 8.1 [7.3–8.9] m/kg PBW, respectively. Significant associations were observed between the frequency of high-magnitude pendelluft and IL-8, IL-18, and Caspase-1 changes (T0/T4 ratio). These results suggest that the frequency of high magnitude pendelluft may be a potential determinant of inflammatory response related to inspiratory efforts in ARDS patients transitioning to partial support ventilation. Future studies are needed to confirm these results.