The association of antiplatelet agents with mortality among patients with non-COVID-19 community-acquired pneumonia: a systematic review and meta-analysis.

Background: Community-acquired pneumonia (CAP) triggers inflammatory and thrombotic host responses driving morbidity and mortality. Antiplatelet agents may favorably modulate these pathways; however, their role in non-COVID-19 CAP remains uncertain. Objectives: To evaluate the association of antiplatelet agents with mortality in hospitalized patients with non-COVID-19 CAP. Methods: We conducted a systematic review and meta-analysis of observational studies and randomized controlled trials (RCTs) of adult patients hospitalized for non-COVID-19 CAP exposed to antiplatelet agents (acetylsalicylic acid or P2Y12 inhibitors). We searched MEDLINE, Embase, and CENTRAL from inception to August 2023. Our primary outcome was all-cause mortality: meta-analyzed (random-effects models) separately for observational studies and RCTs. For observational studies, we used adjusted mortality estimates. Results: We included 13 observational studies (123,012 patients; 6 reported adjusted mortality estimates) and 2 RCTs (225 patients; both high risk of bias). In observational studies reporting hazard ratio, antiplatelet agents were associated with lower mortality (hazard ratio, 0.65; 95% CI, 0.46-0.91; I 2  = 85%; 4 studies, 91,430 patients). In studies reporting adjusted odds ratio, antiplatelet agent exposure was associated with reduced odds of mortality (odds ratio, 0.67; 95% CI, 0.45-1.00; I 2  = 0%; 2 studies, 24,889 patients). Among RCTs, there was a nonsignificant association with mortality (risk ratio, 0.66; 95% CI, 0.20-2.25; I 2  = 54%; 2 studies, 225 patients). By the Grading of Recommendations, Assessment, Development, and Evaluation criteria, the certainty of the evidence was low, primarily due to risk of bias. Conclusion: In hospitalized patients with non-COVID-19 CAP, antiplatelet agents may be associated with reduced mortality compared with usual care or placebo, but the certainty of evidence is low.

Post-insufflation diaphragm contractions in patients receiving various modes of mechanical ventilation.

BACKGROUND: During mechanical ventilation, post-insufflation diaphragm contractions (PIDCs) are non-physiologic and could be injurious. PIDCs could be frequent during reverse-triggering, where diaphragm contractions follow the ventilator rhythm. Whether PIDCs happens with different modes of assisted ventilation is unknown. In mechanically ventilated patients with hypoxemic respiratory failure, we aimed to examine whether PIDCs are associated with ventilator settings, patients' characteristics or both. METHODS: One-hour recordings of diaphragm electromyography (EAdi), airway pressure and flow were collected once per day for up to five days from intubation until full recovery of diaphragm activity or death. Each breath was classified as mandatory (without-reverse-triggering), reverse-triggering, or patient triggered. Reverse triggering was further subclassified according to EAdi timing relative to ventilator cycle or reverse triggering leading to breath-stacking. EAdi timing (onset, offset), peak and neural inspiratory time (Tineuro) were measured breath-by-breath and compared to the ventilator expiratory time. A multivariable logistic regression model was used to investigate factors independently associated with PIDCs, including EAdi timing, amplitude, Tineuro, ventilator settings and APACHE II. RESULTS: Forty-seven patients (median[25%-75%IQR] age: 63[52-77] years, BMI: 24.9[22.9-33.7] kg/m2, 49% male, APACHE II: 21[19-28]) contributed 2 ± 1 recordings each, totaling 183,962 breaths. PIDCs occurred in 74% of reverse-triggering, 27% of pressure support breaths, 21% of assist-control breaths, 5% of Neurally Adjusted Ventilatory Assist (NAVA) breaths. PIDCs were associated with higher EAdi peak (odds ratio [OR][95%CI] 1.01[1.01;1.01], longer Tineuro (OR 37.59[34.50;40.98]), shorter ventilator inspiratory time (OR 0.27[0.24;0.30]), high peak inspiratory flow (OR 0.22[0.20;0.26]), and small tidal volumes (OR 0.31[0.25;0.37]) (all P ≤ 0.008). NAVA was associated with absence of PIDCs (OR 0.03[0.02;0.03]; P < 0.001). Reverse triggering was characterized by lower EAdi peak than breaths triggered under pressure support and associated with small tidal volume and shorter set inspiratory time than breaths triggered under assist-control (all P < 0.05). Reverse triggering leading to breath stacking was characterized by higher peak EAdi and longer Tineuro and associated with small tidal volumes compared to all other reverse-triggering phenotypes (all P < 0.05). CONCLUSIONS: In critically ill mechanically ventilated patients, PIDCs and reverse triggering phenotypes were associated with potentially modifiable factors, including ventilator settings. Proportional modes like NAVA represent a solution abolishing PIDCs.

Bayesian statistics for clinical research.

Frequentist and Bayesian statistics represent two differing paradigms for the analysis of data. Frequentism became the dominant mode of statistical thinking in medical practice during the 20th century. The advent of modern computing has made Bayesian analysis increasingly accessible, enabling growing use of Bayesian methods in a range of disciplines, including medical research. Rather than conceiving of probability as the expected frequency of an event (purported to be measurable and objective), Bayesian thinking conceives of probability as a measure of strength of belief (an explicitly subjective concept). Bayesian analysis combines previous information (represented by a mathematical probability distribution, the prior) with information from the study (the likelihood function) to generate an updated probability distribution (the posterior) representing the information available for clinical decision making. Owing to its fundamentally different conception of probability, Bayesian statistics offers an intuitive, flexible, and informative approach that facilitates the design, analysis, and interpretation of clinical trials. In this Review, we provide a brief account of the philosophical and methodological differences between Bayesian and frequentist approaches and survey the use of Bayesian methods for the design and analysis of clinical research.

Statistical Power and Performance of Strategies to Analyze Composites of Survival and Duration of Ventilation in Clinical Trials.

BACKGROUND: Patients with acute hypoxemic respiratory failure are at high risk of death and prolonged time on the ventilator. Interventions often aim to reduce both mortality and time on the ventilator. Many methods have been proposed for analyzing these endpoints as a single composite outcome (days alive and free of ventilation), but it is unclear which analytical method provides the best performance. Thus, we aimed to determine the analysis method with the highest statistical power for use in clinical trials. METHODS: Using statistical simulation, we compared multiple methods for analyzing days alive and free of ventilation: the t, Wilcoxon rank-sum, and Kryger Jensen and Lange tests, as well as the proportional odds, hurdle-Poisson, and competing risk models. We compared 14 scenarios relating to: 1) varying baseline distributions of mortality and duration of ventilation, which were based on data from a registry of patients with acute hypoxemic respiratory failure and 2) the varying effects of treatment on mortality and duration of ventilation. RESULTS AND CONCLUSIONS: All methods have good control of type 1 error rates (i.e., avoid false positive findings). When data are simulated using a proportional odds model, the t test and ordinal models have the highest relative power (92% and 90%, respectively), followed by competing risk models. When the data are simulated using survival models, the competing risk models have the highest power (100% and 92%), followed by the t test and a ten-category ordinal model. All models struggled to detect the effect of the intervention when the treatment only affected one of mortality and duration of ventilation. Overall, the best performing analytical strategy depends on the respective effects of treatment on survival and duration of ventilation and the underlying distribution of the outcomes. The evaluated models each provide a different interpretation for the treatment effect, which must be considered alongside the statistical power when selecting analysis models.

Metabolomic studies reveal an organ-protective hibernation state in donor lungs preserved at 10 °C.

OBJECTIVE: Previous reports showed enhanced graft function in both healthy and injured porcine lungs after preservation at 10 °C. The objective of the study is to elucidate the mechanism of lung protection by 10 °C and identify potential therapeutic targets to improve organ preservation. METHODS: Metabolomics data were analyzed from healthy and injured porcine lungs that underwent extended hypothermic preservation on ice and at 10 °C. Tissue sampled before and after preservation were subjected to untargeted metabolic profiling. Principal component analysis was performed to test for the separability of the paired samples. Significantly changed metabolites between the 2 time points were identified and analyzed to determine the underlying metabolic pathways. The levels of respiratory activity of lung tissue at hypothermic temperatures were confirmed using high resolution respirometry. RESULTS: In both healthy and injured lungs (n = 5 per intervention), principal component analysis suggested minimal change in metabolites after ice preservation but significant change of metabolites after 10 °C preservation, which was associated with significantly improved lung function as assessed by ex vivo lung perfusion and lung transplantation. For healthy lungs, lipid energy pathway was found primarily active at 10 °C. For injured lungs, additional carbohydrate energy pathway and anti-ferroptosis pathways aiding organ repair were identified. These metabolic features are also key features involved in mammal hibernation. CONCLUSIONS: Untargeted metabolomics revealed a dynamic metabolic gradient for lungs stored at 10 °C. Elucidating the underlying mechanisms behind this pathway regulation may lead to strategies that will allow organs "hibernate" for days, potentially making organ banking a reality.

Toward Precision in Critical Care Research: Methods for Observational and Interventional Studies.

Critical care trials evaluate the effect of interventions in patients with diverse personal histories and causes of illness, often under the umbrella of heterogeneous clinical syndromes, such as sepsis or acute respiratory distress syndrome. Given this variation, it is reasonable to expect that the effect of treatment on outcomes may differ for individuals with variable characteristics. However, in randomized controlled trials, efficacy is typically assessed by the average treatment effect (ATE), which quantifies the average effect of the intervention on the outcome in the study population. Importantly, the ATE may hide variations of the treatment's effect on a clinical outcome across levels of patient characteristics, which may erroneously lead to the conclusion that an intervention does not work overall when it may in fact benefit certain patients. In this review, we describe methodological approaches for assessing heterogeneity of treatment effect (HTE), including expert-derived subgrouping, data-driven subgrouping, baseline risk modeling, treatment effect modeling, and individual treatment rule estimation. Next, we outline how insights from HTE analyses can be incorporated into the design of clinical trials. Finally, we propose a research agenda for advancing the field and bringing HTE approaches to the bedside.

Heparin Dose Intensity and Organ Support-Free Days in Patients Hospitalized for COVID-19.

Background: Clinical trials suggest that therapeutic-dose heparin may prevent critical illness and vascular complications due to COVID-19, but knowledge gaps exist regarding the efficacy of therapeutic heparin including its comparative effect relative to intermediate-dose anticoagulation. Objectives: The authors performed 2 complementary secondary analyses of a completed randomized clinical trial: 1) a prespecified per-protocol analysis; and 2) an exploratory dose-based analysis to compare the effect of therapeutic-dose heparin with low- and intermediate-dose heparin. Methods: Patients who received initial anticoagulation dosed consistently with randomization were included. The primary outcome was organ support-free days (OSFDs), a combination of in-hospital death and days free of organ support through day 21. Results: Among 2,860 participants, 1,761 (92.8%) noncritically ill and 857 (89.1%) critically ill patients were treated per-protocol. Among noncritically ill per-protocol patients, the posterior probability that therapeutic-dose heparin improved OSFDs as compared with usual care was 99.3% (median adjusted OR: 1.36; 95% credible interval [CrI]: 1.07-1.74). Therapeutic heparin had a high posterior probability of efficacy relative to both low- (94.6%; adjusted OR: 1.26; 95% CrI: 0.95-1.64) and intermediate- (99.8%; adjusted OR: 1.80; 95% CrI: 1.22-2.62) dose thromboprophylaxis. Among critically ill per-protocol patients, the posterior probability that therapeutic heparin improved outcomes was low. Conclusions: Among noncritically ill patients hospitalized for COVID-19 who were randomized to and initially received therapeutic-dose anticoagulation, heparin, compared with usual care, was associated with improved OSFDs, a combination of in-hospital death and days free of organ support. Therapeutic heparin appeared superior to both low- and intermediate-dose thromboprophylaxis.

Impact of extended lung protection during mechanical ventilation on lung recovery in patients with COVID-19 ARDS: a phase II randomized controlled trial.

BACKGROUND: Protective ventilation seems crucial during early Acute Respiratory Distress Syndrome (ARDS), but the optimal duration of lung protection remains undefined. High driving pressures (ΔP) and excessive patient ventilatory drive may hinder lung recovery, resulting in self-inflicted lung injury. The hidden nature of the ΔP generated by patient effort complicates the situation further. Our study aimed to assess the feasibility of an extended lung protection strategy that includes a stepwise protocol to control the patient ventilatory drive, assessing its impact on lung recovery. METHODS: We conducted a single-center randomized study on patients with moderate/severe COVID-19-ARDS with low respiratory system compliance (CRS < 0.6 (mL/Kg)/cmH2O). The intervention group received a ventilation strategy guided by Electrical Impedance Tomography aimed at minimizing ΔP and patient ventilatory drive. The control group received the ARDSNet low-PEEP strategy. The primary outcome was the modified lung injury score (mLIS), a composite measure that integrated daily measurements of CRS, along with oxygen requirements, oxygenation, and X-rays up to day 28. The mLIS score was also hierarchically adjusted for survival and extubation rates. RESULTS: The study ended prematurely after three consecutive months without patient enrollment, attributed to the pandemic subsiding. The intention-to-treat analysis included 76 patients, with 37 randomized to the intervention group. The average mLIS score up to 28 days was not different between groups (P = 0.95, primary outcome). However, the intervention group showed a faster improvement in the mLIS (1.4 vs. 7.2 days to reach 63% of maximum improvement; P < 0.001), driven by oxygenation and sustained improvement of X-ray (P = 0.001). The intervention group demonstrated a sustained increase in CRS up to day 28 (P = 0.009) and also experienced a shorter time from randomization to room-air breathing (P = 0.02). Survival at 28 days and time until liberation from the ventilator were not different between groups. CONCLUSIONS: The implementation of an individualized PEEP strategy alongside extended lung protection appears viable. Promising secondary outcomes suggested a faster lung recovery, endorsing further examination of this strategy in a larger trial. Clinical trial registration This trial was registered with ClinicalTrials.gov (number NCT04497454) on August 04, 2020.

Continuous measurements of respiratory muscle blood flow and oxygen consumption using noninvasive frequency-domain near-infrared spectroscopy and diffuse correlation spectroscopy.

Prior studies of muscle blood flow and muscle-specific oxygen consumption have required invasive injection of dye and magnetic resonance imaging, respectively. Such measures have limited utility for continuous monitoring of the respiratory muscles. Frequency-domain near-infrared spectroscopy and diffuse correlation spectroscopy (FD-NIRS & DCS) can provide continuous surrogate measures of blood flow index (BFi) and metabolic rate of oxygen consumption (MRO2). This study aimed to validate sternocleidomastoid FD-NIRS & DCS outcomes against electromyography (EMG) and mouth pressure (Pm) during incremental inspiratory threshold loading (ITL). Six female and six male healthy adults (means ± SD; 30 ± 7 yr, maximum inspiratory pressure 118 ± 61 cmH2O) performed incremental ITL starting at low loads (8 ± 2 cmH2O) followed by 50-g increments every 2 min until task failure. FD-NIRS & DCS continuously measured sternocleidomastoid oxygenated and deoxygenated hemoglobin + myoglobin (oxy/deoxy[Hb + Mb]), tissue saturation of oxygen (StO2), BFi, and MRO2. Ventilatory parameters including inspiratory Pm were also evaluated. Pm increased during incremental ITL (P < 0.05), reaching -47[-74 to -34] cmH2O (median [IQR: 25%-75%]) at task failure. Ventilatory parameters were constant throughout ITL (all P > 0.05). Sternocleidomastoid BFi and MRO2 increased from the start of the ITL (both P < 0.05). Deoxy[Hb + Mb] increased close to task failure, concomitantly with a constant increase in MRO2, and decreased StO2. Sternocleidomastoid deoxy[Hb + Mb], BFi, StO2, and MRO2 obtained during ITL via FD-NIRS & DCS correlated with sternocleidomastoid EMG (all P < 0.05). In healthy adults, FD-NIRS & DCS can provide continuous surrogate measures of respiratory BFi and MRO2. Increasing sternocleidomastoid oxygen consumption near task failure was associated with increased oxygen extraction and reduced tissue saturation.NEW & NOTEWORTHY This study introduces a novel approach, frequency-domain near-infrared spectroscopy and diffuse correlation spectroscopy (FD-NIRS & DCS), for noninvasive continuous monitoring of respiratory muscle blood flow and metabolic rate of oxygen consumption. Unlike prior methods involving invasive dye injection and magnetic resonance imaging, FD-NIRS & DCS offers the advantage of continuous measurement without the need for invasive procedures. It holds promise for advancing muscle physiology understanding and opens avenues for real-time monitoring of respiratory muscles.

A comparison of computational algorithms for the Bayesian analysis of clinical trials.

BACKGROUND: Clinical trials are increasingly using Bayesian methods for their design and analysis. Inference in Bayesian trials typically uses simulation-based approaches such as Markov Chain Monte Carlo methods. Markov Chain Monte Carlo has high computational cost and can be complex to implement. The Integrated Nested Laplace Approximations algorithm provides approximate Bayesian inference without the need for computationally complex simulations, making it more efficient than Markov Chain Monte Carlo. The practical properties of Integrated Nested Laplace Approximations compared to Markov Chain Monte Carlo have not been considered for clinical trials. Using data from a published clinical trial, we aim to investigate whether Integrated Nested Laplace Approximations is a feasible and accurate alternative to Markov Chain Monte Carlo and provide practical guidance for trialists interested in Bayesian trial design. METHODS: Data from an international Bayesian multi-platform adaptive trial that compared therapeutic-dose anticoagulation with heparin to usual care in non-critically ill patients hospitalized for COVID-19 were used to fit Bayesian hierarchical generalized mixed models. Integrated Nested Laplace Approximations was compared to two Markov Chain Monte Carlo algorithms, implemented in the software JAGS and stan, using packages available in the statistical software R. Seven outcomes were analysed: organ-support free days (an ordinal outcome), five binary outcomes related to survival and length of hospital stay, and a time-to-event outcome. The posterior distributions for the treatment and sex effects and the variances for the hierarchical effects of age, site and time period were obtained. We summarized these posteriors by calculating the mean, standard deviations and the 95% equitailed credible intervals and presenting the results graphically. The computation time for each algorithm was recorded. RESULTS: The average overlap of the 95% credible interval for the treatment and sex effects estimated using Integrated Nested Laplace Approximations was 96% and 97.6% compared with stan, respectively. The graphical posterior densities for these effects overlapped for all three algorithms. The posterior mean for the variance of the hierarchical effects of age, site and time estimated using Integrated Nested Laplace Approximations are within the 95% credible interval estimated using Markov Chain Monte Carlo but the average overlap of the credible interval is lower, 77%, 85.6% and 91.3%, respectively, for Integrated Nested Laplace Approximations compared to stan. Integrated Nested Laplace Approximations and stan were easily implemented in clear, well-established packages in R, while JAGS required the direct specification of the model. Integrated Nested Laplace Approximations was between 85 and 269 times faster than stan and 26 and 1852 times faster than JAGS. CONCLUSION: Integrated Nested Laplace Approximations could reduce the computational complexity of Bayesian analysis in clinical trials as it is easy to implement in R, substantially faster than Markov Chain Monte Carlo methods implemented in JAGS and stan, and provides near identical approximations to the posterior distributions for the treatment effect. Integrated Nested Laplace Approximations was less accurate when estimating the posterior distribution for the variance of hierarchical effects, particularly for the proportional odds model, and future work should determine if the Integrated Nested Laplace Approximations algorithm can be adjusted to improve this estimation.

Designing a Bayesian adaptive clinical trial to evaluate novel mechanical ventilation strategies in acute respiratory failure using integrated nested Laplace approximations.

BACKGROUND: Adaptive trials usually require simulations to determine values for design parameters, demonstrate error rates, and establish the sample size. We designed a Bayesian adaptive trial comparing ventilation strategies for patients with acute hypoxemic respiratory failure using simulations. The complexity of the analysis would usually require computationally expensive Markov Chain Monte Carlo methods but this barrier to simulation was overcome using the Integrated Nested Laplace Approximations (INLA) algorithm to provide fast, approximate Bayesian inference. METHODS: We simulated two-arm Bayesian adaptive trials with equal randomization that stratified participants into two disease severity states. The analysis used a proportional odds model, fit using INLA. Trials were stopped based on pre-specified posterior probability thresholds for superiority or futility, separately for each state. We calculated the type I error and power across 64 scenarios that varied the probability thresholds and the initial minimum sample size before commencing adaptive analyses. Two designs that maintained a type I error below 5%, a power above 80%, and a feasible mean sample size were evaluated further to determine the optimal design. RESULTS: Power generally increased as the initial sample size and the futility threshold increased. The chosen design had an initial recruitment of 500 and a superiority threshold of 0.9925, and futility threshold of 0.95. It maintained high power and was likely to reach a conclusion before exceeding a feasible sample size. CONCLUSIONS: We designed a Bayesian adaptive trial to evaluate novel strategies for ventilation using the INLA algorithm to efficiently evaluate a wide range of designs through simulation.

When to intubate in acute hypoxaemic respiratory failure? Options and opportunities for evidence-informed decision making in the intensive care unit.

The optimal timing of intubation in acute hypoxaemic respiratory failure is uncertain and became a point of controversy during the COVID-19 pandemic. Invasive mechanical ventilation is a potentially life-saving intervention but carries substantial risks, including injury to the lungs and diaphragm, pneumonia, intensive care unit-acquired muscle weakness, and haemodynamic impairment. In deciding when to intubate, clinicians must balance premature exposure to the risks of ventilation with the potential harms of unassisted breathing, including disease progression and worsening multiorgan failure. Currently, the optimal timing of intubation is unclear. In this Personal View, we examine a range of parameters that could serve as triggers to initiate invasive mechanical ventilation. The utility of a parameter (eg, the ratio of arterial oxygen tension to fraction of inspired oxygen) to predict the likelihood of a patient undergoing intubation does not necessarily mean that basing the timing of intubation on that parameter will improve therapeutic outcomes. We examine options for clinical investigation to make progress on establishing the optimal timing of intubation.

From ICU Syndromes to ICU Subphenotypes: Consensus Report and Recommendations for Developing Precision Medicine in the ICU.

Critical care uses syndromic definitions to describe patient groups for clinical practice and research. There is growing recognition that a "precision medicine" approach is required and that integrated biologic and physiologic data identify reproducible subpopulations that may respond differently to treatment. This article reviews the current state of the field and considers how to successfully transition to a precision medicine approach. To impact clinical care, identification of subpopulations must do more than differentiate prognosis. It must differentiate response to treatment, ideally by defining subgroups with distinct functional or pathobiological mechanisms (endotypes). There are now multiple examples of reproducible subpopulations of sepsis, acute respiratory distress syndrome, and acute kidney or brain injury described using clinical, physiological, and/or biological data. Many of these subpopulations have demonstrated the potential to define differential treatment response, largely in retrospective studies, and that the same treatment-responsive subpopulations may cross multiple clinical syndromes (treatable traits). To bring about a change in clinical practice, a precision medicine approach must be evaluated in prospective clinical studies requiring novel adaptive trial designs. Several such studies are underway, but there are multiple challenges to be tackled. Such subpopulations must be readily identifiable and be applicable to all critically ill populations around the world. Subdividing clinical syndromes into subpopulations will require large patient numbers. Global collaboration of investigators, clinicians, industry, and patients over many years will therefore be required to transition to a precision medicine approach and ultimately realize treatment advances seen in other medical fields.

Dyssynchronous diaphragm contractions impair diaphragm function in mechanically ventilated patients.

BACKGROUND: Pre-clinical studies suggest that dyssynchronous diaphragm contractions during mechanical ventilation may cause acute diaphragm dysfunction. We aimed to describe the variability in diaphragm contractile loading conditions during mechanical ventilation and to establish whether dyssynchronous diaphragm contractions are associated with the development of impaired diaphragm dysfunction. METHODS: In patients receiving invasive mechanical ventilation for pneumonia, septic shock, acute respiratory distress syndrome, or acute brain injury, airway flow and pressure and diaphragm electrical activity (Edi) were recorded hourly around the clock for up to 7 days. Dyssynchronous post-inspiratory diaphragm loading was defined based on the duration of neural inspiration after expiratory cycling of the ventilator. Diaphragm function was assessed on a daily basis by neuromuscular coupling (NMC, the ratio of transdiaphragmatic pressure to diaphragm electrical activity). RESULTS: A total of 4508 hourly recordings were collected in 45 patients. Edi was low or absent (≤ 5 µV) in 51% of study hours (median 71 h per patient, interquartile range 39-101 h). Dyssynchronous post-inspiratory loading was present in 13% of study hours (median 7 h per patient, interquartile range 2-22 h). The probability of dyssynchronous post-inspiratory loading was increased with reverse triggering (odds ratio 15, 95% CI 8-35) and premature cycling (odds ratio 8, 95% CI 6-10). The duration and magnitude of dyssynchronous post-inspiratory loading were associated with a progressive decline in diaphragm NMC (p < 0.01 for interaction with time). CONCLUSIONS: Dyssynchronous diaphragm contractions may impair diaphragm function during mechanical ventilation. TRIAL REGISTRATION: MYOTRAUMA, ClinicalTrials.gov NCT03108118. Registered 04 April 2017 (retrospectively registered).

Clinical implications of frailty assessed in hospitalized patients with acute-exacerbation of interstitial lung disease.

BACKGROUND: Approximately 50% of patients with interstitial lung disease (ILD) experience frailty, which remains unexplored in acute exacerbations of ILD (AE-ILD). A better understanding may help with prognostication and resource planning. We evaluated the association of frailty with clinical characteristics, physical function, hospital outcomes, and post-AE-ILD recovery. METHODS: Retrospective cohort study of AE-ILD patients (01/2015-10/2019) with frailty (proportion ≥0.25) on a 30-item cumulative-deficits index. Frail and non-frail patients were compared for pre- and post-hospitalization clinical characteristics, adjusted for age, sex, and ILD diagnosis. One-year mortality, considering transplantation as a competing risk, was analysed adjusting for age, frailty, and Charlson Comorbidity Index (CCI). RESULTS: 89 AE-ILD patients were admitted (median: 67 years, 63% idiopathic pulmonary fibrosis). 31 were frail, which was associated with older age, greater CCI, lower 6-min walk distance, and decreased independence pre-hospitalization. Frail patients had more major complications (32% vs 10%, p = .01) and required more multidisciplinary support during hospitalization. Frailty was not associated with 1-year mortality (HR: 0.97, 95%CI: [0.45-2.10]) factoring transplantation as a competing risk. CONCLUSIONS: Frailty was associated with reduced exercise capacity, increased comorbidities and hospital complications. Identifying frailty may highlight those requiring additional multidisciplinary support, but further study is needed to explore whether frailty is modifiable with AE-ILD.

Combined frequency domain near-infrared spectroscopy and diffuse correlation spectroscopy system for comprehensive metabolic monitoring of inspiratory muscles during loading.

Significance: Mechanical ventilation (MV) is a cornerstone technology in the intensive care unit as it assists with the delivery of oxygen in critically ill patients. The process of weaning patients from MV can be long and arduous and can lead to serious complications for many patients. Despite the known importance of inspiratory muscle function in the success of weaning, current clinical standards do not include direct monitoring of these muscles. Aim: The goal of this project was to develop and validate a combined frequency domain near-infrared spectroscopy (FD-NIRS) and diffuse correlation spectroscopy (DCS) system for the noninvasive characterization of inspiratory muscle response to a load. Approach: The system was fabricated by combining a custom digital FD-NIRS and DCS system. It was validated via liquid phantom titrations and a healthy volunteer study. The sternocleidomastoid (SCM), an accessory muscle of inspiration, was monitored during a short loading period in fourteen young, healthy volunteers. Volunteers performed two different respiratory exercises, a moderate load and a high load, which consisted of a one-minute baseline, a one-minute load, and a six-minute recovery period. Results: The system has low crosstalk between absorption, reduced scattering, and flow when tested in a set of liquid titrations. Faster dynamics were observed for changes in blood flow index (BFi), and metabolic rate of oxygen (MRO2) compared with hemoglobin + myoglobin (Hb+Mb) based parameters after the onset of loads in males. Additionally, larger percent changes in BFi, and MRO2 were observed compared with Hb+Mb parameters in both males and females. There were also sex differences in baseline values of oxygenated Hb+Mb, total Hb+Mb, and tissue saturation. Conclusions: The dynamic characteristics of Hb+Mb concentration and blood flow were distinct during loading of the SCM, suggesting that the combination of FD-NIRS and DCS may provide a more complete picture of inspiratory muscle dynamics.