Ventilator-associated pneumonia by Weeksella virosa: case report.

BACKGROUND: Weeksella virosa pneumonia is an infection that has been described as a healthcare-associated infection. This is a rare gram-negative anaerobic bacterium associated with the use of mechanical ventilation for a long period of time and is more frequent in immunosuppressed patients. This is the first case reported in the state of Veracruz and the second in Mexico. CASE PRESENTATION: We present the case of a 64-year-old female from Veracruz, Mexico who developed an infectious process in the right pelvic limb after a transcatheter aortic valve replacement procedure and subsequently developed sudden cardiorespiratory arrest requiring mechanical ventilation, with subsequent imaging studies demonstrating a pneumonic process associated with a nosocomial infection. DISCUSSION AND CONCLUSIONS: We should take into consideration that this pathogen affects not only adults with multiple comorbidities but also children with renal, hepatic, or oncological pathologies, as well as immunocompromised patients, who should be considered high-risk populations for W. virosa infection.

Detectable Concentrations With Inhaled Tobramycin in Critically Ill Infants and Children Following Implementation of Standardized Protocol.

BACKGROUND: A protocol was established for ventilator-associated tracheitis or pneumonia using inhaled tobramycin 300 mg every 12 hours in mechanically ventilated children via a vibrating mesh nebulizer, 30 cm from the endotracheal tube in the inspiratory loop of the mechanical ventilator. OBJECTIVES: The primary objective was to determine the incidence of detectable tobramycin trough concentrations >0.5 µg/mL. Secondary objectives included a comparison of clinical characteristics between those with and without detectable concentrations and identification of patients with acute kidney injury (AKI) as defined by the Kidney Diseases Improving Global Outcomes (KDIGO) criteria. METHODS: This was a single-center retrospective study of critically ill children <18 years without cystic fibrosis receiving inhaled tobramycin between July 1, 2016, and August 31, 2021. Data collection included demographics, tobramycin regimen, and renal function. Analysis was performed using SAS 9.4, with a P-value <0.05, and a multivariable regression model was performed to identify factors for detectable concentrations and AKI. RESULTS: Forty-four patients (66 courses) were included, with an overall age of 0.83 years. Thirty (68%) patients had detectable concentrations and 9 (20.5%) developed AKI. No significant differences in demographics, diagnosis, mechanical ventilation settings, and number of nephrotoxins were noted between those with and without detectable concentrations or AKI. Multivariable regressions did not identify factors associated with detectable concentrations or AKI. CONCLUSION AND RELEVANCE: Detectable concentrations occurred with the majority of courses, with AKI associated with approximately one-fourth of courses. Clinicians should consider utilizing trough monitoring for all mechanically ventilated critically ill children receiving inhaled tobramycin.

Accuracy of respiratory muscle assessments to predict weaning outcomes: a systematic review and comparative meta-analysis.

BACKGROUND: Several bedside assessments are used to evaluate respiratory muscle function and to predict weaning from mechanical ventilation in patients on the intensive care unit. It remains unclear which assessments perform best in predicting weaning success. The primary aim of this systematic review and meta-analysis was to summarize and compare the accuracy of the following assessments to predict weaning success: maximal inspiratory (PImax) and expiratory pressures, diaphragm thickening fraction and excursion (DTF and DE), end-expiratory (Tdiee) and end-inspiratory (Tdiei) diaphragm thickness, airway occlusion pressure (P0.1), electrical activity of respiratory muscles, and volitional and non-volitional assessments of transdiaphragmatic and airway opening pressures. METHODS: Medline (via Pubmed), EMBASE, Web of Science, Cochrane Library and CINAHL were comprehensively searched from inception to 04/05/2023. Studies including adult mechanically ventilated patients reporting data on predictive accuracy were included. Hierarchical summary receiver operating characteristic (HSROC) models were used to estimate the SROC curves of each assessment method. Meta-regression was used to compare SROC curves. Sensitivity analyses were conducted by excluding studies with high risk of bias, as assessed with QUADAS-2. Direct comparisons were performed using studies comparing each pair of assessments within the same sample of patients. RESULTS: Ninety-four studies were identified of which 88 studies (n = 6296) reporting on either PImax, DTF, DE, Tdiee, Tdiei and P0.1 were included in the meta-analyses. The sensitivity to predict weaning success was 63% (95% CI 47-77%) for PImax, 75% (95% CI 67-82%) for DE, 77% (95% CI 61-87%) for DTF, 74% (95% CI 40-93%) for P0.1, 69% (95% CI 13-97%) for Tdiei, 37% (95% CI 13-70%) for Tdiee, at fixed 80% specificity. Accuracy of DE and DTF to predict weaning success was significantly higher when compared to PImax (p = 0.04 and p < 0.01, respectively). Sensitivity and direct comparisons analyses showed that the accuracy of DTF to predict weaning success was significantly higher when compared to DE (p < 0.01). CONCLUSIONS: DTF and DE are superior to PImax and DTF seems to have the highest accuracy among all included respiratory muscle assessments for predicting weaning success. Further studies aiming at identifying the optimal threshold of DTF to predict weaning success are warranted. TRIAL REGISTRATION: PROSPERO CRD42020209295, October 15, 2020.

Public and Clinician Perspectives on Ventilator Withdrawal in Vegetative State Following Severe Acute Brain Injury: A Vignette Survey.

BACKGROUND: The vegetative state (VS) after severe acute brain injury (SABI) is associated with significant prognostic uncertainty and poor long-term functional outcomes. However, it is generally distinguished from imminent death and is exempt from the Life-Sustaining Treatment (LST) Decisions Act in Korea. Here, we aimed to examine the perspectives of the general population (GP) and clinicians regarding decisions on mechanical ventilator withdrawal in patients in a VS after SABI. METHODS: A cross-sectional survey was undertaken, utilizing a self-reported online questionnaire based on a case vignette. Nationally selected by quota sampling, the GP comprised 500 individuals aged 20 to 69 years. There were 200 doctors from a tertiary university hospital in the clinician sample. Participants were asked what they thought about mechanical ventilator withdrawal in patients in VS 2 months and 3 years after SABI. RESULTS: Two months after SABI in the case, 79% of the GP and 83.5% of clinicians had positive attitudes toward mechanical ventilator withdrawal. In the GP, attitudes were associated with spirituality, household income, religion, the number of household members. On the other hand, clinicians' attitudes were related to their experience of completing advance directives (AD) and making decisions about LST. In this case, 3 years after SABI, 92% of the GP and 94% of clinicians were more accepting of ventilator withdrawal compared to previous responses, based on the assumption that the patient had written AD. However, it appeared that the proportion of positive responses to ventilator withdrawal decreased when the patients had only verbal expressions (82% of the GP; 75.5% of clinicians) or had not previously expressed an opinion regarding LST (58% of the GP; 39.5% of clinicians). CONCLUSION: More than three quarters of both the GP and clinicians had positive opinions regarding ventilator withdrawal in patients in a VS after SABI, which was reinforced with time and the presence of AD. Legislative adjustments are needed to ensure that previous wishes for those patients are more respected and reflected in treatment decisions.

A New Model of Air-Oxygen Blender for Mechanical Ventilators Using Dynamic Pressure Sensors.

Respiratory diseases are among the leading causes of death globally, with the COVID-19 pandemic serving as a prominent example. Issues such as infections affect a large population and, depending on the mode of transmission, can rapidly spread worldwide, impacting thousands of individuals. These diseases manifest in mild and severe forms, with severely affected patients requiring ventilatory support. The air-oxygen blender is a critical component of mechanical ventilators, responsible for mixing air and oxygen in precise proportions to ensure a constant supply. The most commonly used version of this equipment is the analog model, which faces several challenges. These include a lack of precision in adjustments and the inspiratory fraction of oxygen, as well as gas wastage from cylinders as pressure decreases. The research proposes a blender model utilizing only dynamic pressure sensors to calculate oxygen saturation, based on Bernoulli's equation. The model underwent validation through simulation, revealing a linear relationship between pressures and oxygen saturation up to a mixture outlet pressure of 500 cmH2O. Beyond this value, the relationship begins to exhibit non-linearities. However, these non-linearities can be mitigated through a calibration algorithm that adjusts the mathematical model. This research represents a relevant advancement in the field, addressing the scarcity of work focused on this essential equipment crucial for saving lives.

Position Statement of ISCCM Committee on Weaning from Mechanical Ventilator.

Background and purpose: Weaning from a mechanical ventilator is a milestone in the recovery of seriously ill patients in Intensive care. Failure to wean and re-intubation adversely affects the outcome. The method of mechanical ventilation (MV) varies between different ICUs and so does the practice of weaning. Therefore, updated guidelines based on contemporary literature are designed to guide intensivists in modern ICUs. This is the first ISCCM Consensus Statement on weaning complied by a committee on weaning. The recommendations are intended to be used by all the members of the ICU (Intensivists, Registrars, Nurses, and Respiratory Therapists). Methods: A Committee on weaning from MV, formed by the Indian Society of Critical Care Medicine (ISCCM) has formulated this statement on weaning from mechanical ventilators in intensive care units (ICUs) after a review of the literature. Literature was first circulated among expert committee members and allotted sections to each member. Sections of the statement written by sectional authors were peer-reviewed on multiple occasions through virtual meetings. After the final manuscript is accepted by all the committee members, it is submitted for peer review by central guideline committee of ISCCM. Once approved it has passed through review by the Editorial Board of IJCCM before it is published here as "ISCCM consensus statement on weaning from mechanical ventilator". As per the standard accepted for all its guidelines of ISCCM, we followed the modified grading of recommendations assessment, development and evaluation (GRADE) system to classify the quality of evidence and strength of recommendation. Cost-benefit, risk-benefit analysis, and feasibility of implementation in Indian ICUs are considered by the committee along with the strength of evidence. Type of ventilators and their modes, ICU staffing pattern, availability of critical care nurses, Respiratory therapists, and day vs night time staffing are aspects considered while recommending for or against any aspect of weaning. Result: This document makes recommendation on various aspects of weaning, namely, definition, timing, weaning criteria, method of weaning, diagnosis of failure to wean, defining difficult to wean, Use of NIV, HFOV as adjunct to weaning, role of tracheostomy in weaning, weaning in of long term ventilated patients, role of physiotherapy, mobilization in weaning, Role of nutrition in weaning, role of diaphragmatic ultrasound in weaning prediction etc. Out of 42 questions addressed; the committee provided 39 recommendations and refrained from 3 questions. Of these 39; 32 are based on evidence and 7 are based on expert opinion of the committee members. It provides 27 strong recommendations and 12 weak recommendations (suggestions). Conclusion: This guideline gives extensive review on weaning from mechanical ventilator and provides various recommendations on weaning from mechanical ventilator. Though all efforts are made to make is as updated as possible one needs to review any guideline periodically to keep it in line with upcoming concepts and standards. How to cite this article: Clerk AM, Shah RJ, Kothari J, Sodhi K, Vadi S, Bhattacharya PK, et al. Position Statement of ISCCM Committee on Weaning from Mechanical Ventilator. Indian J Crit Care Med 2024;28(S2):S233-S248.

Ventilation Difficulty Caused by Obstructed Heated Breathing Circuit.

For perioperative hypothermia prevention, a heated, humidified breathing circuit equipped with a fluid-warming unit inside the inspiratory limb has been developed. We report a ventilation difficulty caused by an obstructed heated breathing circuit. Cotton surrounding the hot wire, temperature sensor, and fluid tubing in the distal inspiratory limb was irregularly thicker than that of a normal circuit and nearly blocked the lumen. Despite carrying out routine checks on the anesthesia workstation preoperatively, we failed to make a prediagnosis by omitting the flow test after changing the circuit. This case puts emphasis on a routine flow test with a meticulous examination of the heated breathing circuit before every procedure.

Expiratory Muscles of Respiration and Weaning Failure: What do We Know So Far?

How to cite this article: Majeed NA, Nasa P. Expiratory Muscles of Respiration and Weaning Failure: What do We Know So Far? Indian J Crit Care Med 2023;27(1):1-3.

Administration of vitamin D and its metabolites in critically ill adult patients: an updated systematic review with meta-analysis of randomized controlled trials.

BACKGROUND: The clinical significance of vitamin D administration in critically ill patients remains inconclusive. The purpose of this systematic review with meta-analysis was to investigate the effect of vitamin D and its metabolites on major clinical outcomes in critically ill patients, including a subgroup analysis based on vitamin D status and route of vitamin D administration. METHODS: Major databases were searched through February 9, 2022. Randomized controlled trials of adult critically ill patients with an intervention group receiving vitamin D or its metabolites were included. Random-effect meta-analyses were performed to estimate the pooled risk ratio (dichotomized outcomes) or mean difference (continuous outcomes). Risk of bias assessment included the Cochrane tool for assessing risk of bias in randomized trials. RESULTS: Sixteen randomized clinical trials with 2449 patients were included. Vitamin D administration was associated with lower overall mortality (16 studies: risk ratio 0.78, 95% confidence interval 0.62-0.97, p = 0.03; I2 = 30%), reduced intensive care unit length of stay (12 studies: mean difference - 3.13 days, 95% CI - 5.36 to - 0.89, n = 1250, p = 0.006; I2 = 70%), and shorter duration of mechanical ventilation (9 studies: mean difference - 5.07 days, 95% CI - 7.42 to - 2.73, n = 572, p < 0.0001; I2 = 54%). Parenteral administration was associated with a greater effect on overall mortality than enteral administration (test of subgroup differences, p = 0.04), whereas studies of parenteral subgroups had lower quality. There were no subgroup differences based on baseline vitamin D levels. CONCLUSIONS: Vitamin D supplementation in critically ill patients may reduce mortality. Parenteral administration might be associated with a greater impact on mortality. Heterogeneity and assessed certainty among the studies limits the generalizability of the results. TRIAL REGISTRATION: PROSPERO international prospective database of systematic reviews (CRD42021256939-05 July 2021).

Plasma Soluble Suppression of Tumorigenicity-2 Associates with Ventilator Liberation in Acute Hypoxemic Respiratory Failure.

Rationale: Standard physiologic assessments of extubation readiness in patients with acute hypoxemic respiratory failure (AHRF) may not reflect lung injury resolution and could adversely affect clinical decision-making and patient outcomes. Objectives: We hypothesized that elevations in inflammatory plasma biomarkers sST2 (soluble suppression of tumorigenicity-2) and IL-6 indicate ongoing lung injury in AHRF and better inform patient outcomes compared with standard clinical assessments. Methods: We measured daily plasma biomarkers and physiologic variables in 200 patients with AHRF for up to 9 days after intubation. We tested the associations of baseline values with the primary outcome of unassisted breathing at Day 29. We analyzed the ability of serial biomarker measurements to inform successful ventilator liberation. Measurements and Main Results: Baseline sST2 concentrations were higher in patients dead or mechanically ventilated versus breathing unassisted at Day 29 (491.7 ng/ml [interquartile range (IQR), 294.5-670.1 ng/ml] vs. 314.4 ng/ml [IQR, 127.5-550.1 ng/ml]; P = 0.0003). Higher sST2 concentrations over time were associated with a decreased probability of ventilator liberation (hazard ratio, 0.80 per log-unit increase; 95% confidence interval [CI], 0.75-0.83; P = 0.03). Patients with higher sST2 concentrations on the day of liberation were more likely to fail liberation compared with patients who remained successfully liberated (320.9 ng/ml [IQR, 181.1- 495.6 ng/ml] vs. 161.6 ng/ml [IQR, 95.8-292.5 ng/ml]; P = 0.002). Elevated sST2 concentrations on the day of liberation decreased the odds of successful liberation when adjusted for standard physiologic parameters (odds ratio, 0.325; 95% CI, 0.119-0.885; P = 0.03). IL-6 concentrations did not associate with outcomes. Conclusions: Using sST2 concentrations to guide ventilator management may more accurately reflect underlying lung injury and outperform traditional measures of readiness for ventilator liberation.

Pressure-flow breath representation eases asynchrony identification in mechanically ventilated patients.

Breathing asynchronies are mismatches between the requests of mechanically ventilated subjects and the support provided by mechanical ventilators. The most widespread technique in identifying these pathological conditions is the visual analysis of the intra-tracheal pressure and flow time-trends. This work considers a recently introduced pressure-flow representation technique and investigates whether it can help nurses in the early detection of anomalies that can represent asynchronies. Twenty subjects-ten Intensive Care Unit (ICU) nurses and ten persons inexperienced in medical practice-were asked to find asynchronies in 200 breaths pre-labeled by three experts. The new representation increases significantly the detection capability of the subjects-average sensitivity soared from 0.622 to 0.905-while decreasing the classification time-from 1107.0 to 567.1 s on average-at the price of a not statistically significant rise in the number of wrong identifications-specificity average descended from 0.589 to 0.52. Moreover, the differences in experience between the nurse group and the inexperienced group do not affect the sensitivity, specificity, or classification times. The pressure-flow diagram significantly increases sensitivity and decreases the response time of early asynchrony detection performed by nurses. Moreover, the data suggest that operator experience does not affect the identification results. This outcome leads us to believe that, in emergency contexts with a shortage of nurses, intensive care nurses can be supplemented, for the sole identification of possible respiratory asynchronies, by inexperienced staff.

Personal care assistants' lived experience of working in the home setting with children and adults on mechanical ventilation.

BACKGROUND: Working as a personal care assistant (PCA) with children and adults on mechanical ventilation in a home setting may be complex and challenging due to the physical and mental working conditions. AIM: To explore the lived experience of working as a (PCA) with patients, children and adults on mechanical ventilation in the home setting. DESIGN AND METHODS: A qualitative study using a phenomenological-hermeneutic approach. Data collection involved semi-structured individual interviews with 20 PCAs (n = 15 women and n = 5 men) in Denmark in 2020. Their work experience with patients on home mechanical ventilation ranged from 8 months to 25 years (median 8 years). The Consolidated Criteria for Reporting Qualitative Research checklist was used as a guideline. FINDINGS: Four main themes emerged from the structural analysis: Being a fly on the wall or part of the family, Always being in a state of readiness is exhausting, Being a team player and Mutual respect is key in the work relationship. CONCLUSION: PCAs had to balance on a knife's edge when working with children and adults on mechanical ventilation in the home setting and try to strike a happy medium. Enduring the job required a proper physical and mental work environment, and thorough preparation, achieved not only through technical training, but also through learning how to be part of a professional relationship characterised by mutual respect and matched expectations. RELEVANCE TO CLINICAL PRACTICE: The findings provide clinical practice with important insights into how to inform, prepare and educate PCAs working with patients on mechanical ventilation in the home setting. Further research into home care education and training programmes with a patient- and family-centred care approach is needed.

Changes in Maximum Tongue Pressure and Postoperative Dysphagia in Mechanically Ventilated Patients after Cardiovascular Surgery.

Background: There is no objective quantitative parameter for dysphagia, and the relationship between changes in maximum tongue pressure values and dysphagia is unknown. This study aimed to determine whether there is a difference in the change in maximal tongue pressure after extubating patients who were ventilated after cardiovascular surgery, with or without dysphagia. Materials and methods: Adult patients who underwent mechanical ventilation via endotracheal intubation following cardiovascular surgery were included. Tongue pressure was measured before cardiovascular surgery and at 6 hours; 3 and 7 days after extubation. Dysphagia was confirmed by the functional oral intake scale (FOIS) on day 7 after extubation; an FOIS level above or equal to 6 was considered "dysphagia-negative." Results: Of 68 patients, 15 (22.1%) were in the dysphagia-positive group, which significantly showed a history of diabetes mellitus, prolonged mechanical ventilation, and postextubation hospitalization. Additionally, the postoperative C-reactive protein level was significantly higher in the dysphagia-positive group than in the dysphagia-negative group. Maximum tongue pressure was significantly lower in the dysphagia-positive group at 3 and 7 days postextubation. Using a cutoff value of 27.6 kPa in a receiver operating characteristic (ROC) curve for maximum tongue pressure at 3 days after extubation, the area under the curve (AUC) was 0.82, sensitivity was 84.9%, and specificity was 84.2%. Conclusion: Tongue pressure at 3 days after extubation is significantly lower in patients with dysphagia after cardiovascular surgery than in patients without dysphagia. If the maximum tongue pressure value is below 27.6 kPa on the third day following extubation, oral intake should be performed with caution. How to cite this article: Yamada T, Ochiai R, Kotake Y. Changes in Maximum Tongue Pressure and Postoperative Dysphagia in Mechanically Ventilated Patients after Cardiovascular Surgery. Indian J Crit Care Med 2022;26(12):1253-1258.

Predicting the Need for Intubation among COVID-19 Patients Using Machine Learning Algorithms: A Single-Center Study.

Background: Owing to the shortage of ventilators, there is a crucial demand for an objective and accurate prognosis for 2019 coronavirus disease (COVID-19) critical patients, which may necessitate a mechanical ventilator (MV). This study aimed to construct a predictive model using machine learning (ML) algorithms for frontline clinicians to better triage endangered patients and priorities who would need MV. Methods: In this retrospective single-center study, the data of 482 COVID-19 patients from February 9, 2020, to December 20, 2020, were analyzed by several ML algorithms including, multi-layer perception (MLP), logistic regression (LR), J-48 decision tree, and Naïve Bayes (NB). First, the most important clinical variables were identified using the Chi-square test at P < 0.01. Then, by comparing the ML algorithms' performance using some evaluation criteria, including TP-Rate, FP-Rate, precision, recall, F-Score, MCC, and Kappa, the best performing one was identified. Results: Predictive models were trained using 15 validated features, including cough, contusion, oxygen therapy, dyspnea, loss of taste, rhinorrhea, blood pressure, absolute lymphocyte count, pleural fluid, activated partial thromboplastin time, blood glucose, white cell count, cardiac diseases, length of hospitalization, and other underline diseases. The results indicated the J-48 with F-score = 0.868 and AUC = 0.892 yielded the best performance for predicting intubation requirement. Conclusion: ML algorithms are potentials to improve traditional clinical criteria to forecast the necessity for intubation in COVID-19 in-hospital patients. Such ML-based prediction models may help physicians with optimizing the timing of intubation, better sharing of MV resources and personnel, and increase patient clinical status.

Early Elevation of Fibrosis-4 Liver Fibrosis Score Is Associated With Adverse Outcomes Among Patients With Coronavirus Disease 2019.

BACKGROUND: Limited prior data suggest that preexisting liver disease is associated with adverse outcomes among patients with coronavirus disease 2019 (COVID-19). Fibrosis-4 (FIB-4) is a noninvasive index of readily available laboratory measurements that represents hepatic fibrosis. We evaluated the association between FIB-4 at the early stage of infection and COVID-19 outcomes. METHODS: FIB-4 was evaluated at admission in a cohort of 267 patients admitted with early-stage COVID-19 confirmed through reverse-transcription polymerase chain reaction assay. Hazard of ventilator use and of high-flow oxygen was estimated using Cox regression models controlled for covariates. Risks of progression to severe disease and of death/prolonged hospitalization were estimated using multivariable logistic regression models. RESULTS: Forty-one (15%) patients progressed to severe disease, 36 (14%) required high-flow oxygen support, 10 (4%) required mechanical ventilator support, and 1 died. FIB-4 between 1.45 and 3.25 was associated with a greater than 5-fold (95% confidence interval [CI], 1.2-28) increased hazard of high-flow oxygen use, a greater than 4-fold (95% CI, 1.5-14.6) increased odds of progression to severe disease, and an over 3-fold (95% CI, 1.4-7.7) increased odds of death or prolonged hospitalization. FIB-4 >3.25 was associated with a greater than 12-fold (95% CI, 2.3-68. 7) increased hazard of high-flow oxygen use and an over 11-fold (95% CI, 3.1-45) increased risk of progression to severe disease. All associations were independent of sex, number of comorbidities, and inflammatory markers (D-dimer, C-reactive protein). CONCLUSIONS: FIB-4 at the early-stage of COVID-19 had an independent and dose-dependent association with adverse outcomes during hospitalization. FIB-4 provided significant prognostic value for estimating adverse outcomes among COVID-19 patients.

The effect of oropharyngeal aspiration before position change on reducing the incidence of ventilator- associated pneumonia.

The aim of this study was to investigate the effect of oropharyngeal aspiration on ventilator-associated pneumonia (VAP) incidence just prior to changing patient position. This randomized controlled experimental study was conducted between July 2015 and April 2019 in anesthesiology and reanimation of intensive care unit (ICU). The patients of experimental group underwent oropharyngeal aspiration under surgical aseptic conditions before each position change. Patients of the control group received oropharyngeal aspiration only as needed. The mean age of the patients was 62.87 ± 17.33 years. The mean and median duration of stay in the ICU were 27.28 ± 30.69 and 18.00 days respectively. The mean and median of duration of the mechanical ventilation support were 26.72 ± 30.65 and 18.00 (min 4; max 168) days respectively. Thirty percent of the patients were VAP. The mean duration of VAP development was 7.50 ± 5.07 days. The rate of VAP development was 11.23/1000 mechanical ventilator days. Only 8.3% of the experimental group patients developed VAP; 91.7% of the control group patients developed VAP. The VAP rate in the control group was 16.82/1000 mechanical ventilator days and the VAP rate in the experimental group was 2.41/1000 mechanical ventilator days. Most VAP agents were multidrug resistant. Distribution of isolated microorganisms was as Acinetobacter baumannii, Pseudomonas aeruginosa, Corynebacterium striatum, Staphylococcus aureus, Providencia stuartii, Serratia marcescens, Stenotrophomonas maltophilia, and Aspergillus flavus. In our study, it was concluded that oropharyngeal aspiration performed prior to patient position change prevented the development of VAP.

Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Retrospective, Comparative, Machine Learning Study.

BACKGROUND: Patient safety in the intensive care unit (ICU) is one of the most critical issues, and unplanned extubation (UE) is considered the most adverse event for patient safety. Prevention and early detection of such an event is an essential but difficult component of quality care. OBJECTIVE: This study aimed to develop and validate prediction models for UE in ICU patients using machine learning. METHODS: This study was conducted in an academic tertiary hospital in Seoul, Republic of Korea. The hospital had approximately 2000 inpatient beds and 120 ICU beds. As of January 2019, the hospital had approximately 9000 outpatients on a daily basis. The number of annual ICU admissions was approximately 10,000. We conducted a retrospective study between January 1, 2010, and December 31, 2018. A total of 6914 extubation cases were included. We developed a UE prediction model using machine learning algorithms, which included random forest (RF), logistic regression (LR), artificial neural network (ANN), and support vector machine (SVM). For evaluating the model's performance, we used the area under the receiver operating characteristic curve (AUROC). The sensitivity, specificity, positive predictive value, negative predictive value, and F1 score were also determined for each model. For performance evaluation, we also used a calibration curve, the Brier score, and the integrated calibration index (ICI) to compare different models. The potential clinical usefulness of the best model at the best threshold was assessed through a net benefit approach using a decision curve. RESULTS: Among the 6914 extubation cases, 248 underwent UE. In the UE group, there were more males than females, higher use of physical restraints, and fewer surgeries. The incidence of UE was higher during the night shift as compared to the planned extubation group. The rate of reintubation within 24 hours and hospital mortality were higher in the UE group. The UE prediction algorithm was developed, and the AUROC for RF was 0.787, for LR was 0.762, for ANN was 0.763, and for SVM was 0.740. CONCLUSIONS: We successfully developed and validated machine learning-based prediction models to predict UE in ICU patients using electronic health record data. The best AUROC was 0.787 and the sensitivity was 0.949, which was obtained using the RF algorithm. The RF model was well-calibrated, and the Brier score and ICI were 0.129 and 0.048, respectively. The proposed prediction model uses widely available variables to limit the additional workload on the clinician. Further, this evaluation suggests that the model holds potential for clinical usefulness.

Design and simulation of mechanical ventilators.

During this period of COVID-19 pandemic, the lack of medical equipment (like ventilators) leads to complications arising in the medical field. A low-cost ventilator seems to be an alternative substitute to fill the lacking. This paper presents a numerical analysis for predicting the delivered parameters of a low-cost mechanical ventilator. Based on several manufactured mechanical ventilators, two proposed designs are investigated in this study. Fluid-structure interaction (FSI) analysis is used for solving any problems with the first design, and computational fluid dynamic (CFD) analysis with moving boundary is used for solving any issues with the second design. For this purpose, ANSYS Workbench platform is used to solve the set of equations. The results showed that the Ambu-bag-based mechanical ventilator exhibited difficulties in controlling ventilation variables, which certainly will cause serious health problems such as barotrauma. The mechanical ventilator based on piston-cylinder is more satisfactory with regards to delivered parameters to the patient. The ways to obtain pressure control mode (PCM) and volume control mode (VCM) are identified. Finally, the ventilator output is highly affected by inlet flow, length of the cylinder, and piston diameter.

The effect of reverse Trendelenburg position versus semi-recumbent position on respiratory parameters of obese critically ill patients: A randomised controlled trial.

AIMS AND OBJECTIVES: To investigate the effect of reverse Trendelenburg position versus semi-recumbent position on respiratory parameters of obese critically ill patients. BACKGROUND: Reverse Trendelenburg position is recommended for obese patients; however, the effect among critically ill patients, especially those on mechanical ventilation, has limited study. DESIGN: Randomised, controlled pretest, repeated post-test trial with two parallel groups. METHODS: The study started from 13 January 2020-12 March 2020. Adult critically ill patients with a body mass index ≥30 were randomly assigned by computer-generated randomisation to either reverse Trendelenburg position group (intervention) or semi-recumbent position group (active comparator control). Outcome measures were ventilation parameters (dynamic compliance, partial pressure of arterial carbon dioxide and minute volume) and oxygenation parameters (hypoxaemic index and partial pressure of arterial oxygen). Measures were assessed immediately before positioning and after positioning in 10 minutes, 20 minutes and 30 minutes. CONSORT checklist was used to report the current study. SETTINGS: Four general intensive care units. RESULTS: One hundred and ten patients (55 patients in each group) completed the study. The reverse Trendelenburg position group had a higher improvement than the semi-recumbent position group as estimated by mean differences in their dynamic compliance, minute volume, partial pressure of carbon dioxide, partial pressure of oxygen and hypoxaemic index. CONCLUSION: Reverse Trendelenburg position improves obese patients' respiratory parameters more than semi-recumbent position. RELEVANCE TO CLINICAL PRACTICE: This study directs nurses to use the reverse Trendelenburg position, which is an important position for enhancing the parameters of ventilation and oxygenation of obese mechanically ventilated patients.

An effective pressure-flow characterization of respiratory asynchronies in mechanical ventilation.

Ineffective effort during expiration (IEE) occurs when there is a mismatch between the demand of a mechanically ventilated patient and the support delivered by a Mechanical ventilator during the expiration. This work presents a pressure-flow characterization for respiratory asynchronies and validates a machine-learning method, based on the presented characterization, to identify IEEs. 1500 breaths produced by 8 mechanically-ventilated patients were considered: 500 of them were included into the training set and the remaining 1000 into the test set. Each of them was evaluated by 3 experts and classified as either normal, artefact, or containing inspiratory, expiratory, or cycling-off asynchronies. A software implementing the proposed method was trained by using the experts' evaluations of the training set and used to identify IEEs in the test set. The outcomes were compared with a consensus of three expert evaluations. The software classified IEEs with sensitivity 0.904, specificity 0.995, accuracy 0.983, positive and negative predictive value 0.963 and 0.986, respectively. The Cohen's kappa is 0.983 (with 95% confidence interval (CI): [0.884, 0.962]). The pressure-flow characterization of respiratory cycles and the monitoring technique proposed in this work automatically identified IEEs in real-time in close agreement with the experts.