Early prediction of noninvasive ventilation failure in COPD patients: derivation, internal validation, and external validation of a simple risk score

Predictive value of diaphragm ultrasound for mechanical ventilation outcome in patients with acute exacerbation of chronic obstructive pulmonary disease

BACKGROUND

Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is often combined with respiratory failure, which increases the patient's morbidity and mortality. Diaphragm ultrasound (DUS) has developed rapidly in the field of critical care in recent years. Studies with DUS monitoring diaphragm-related rapid shallow breathing index have demonstrated important results in guiding intensive care unit patients out of the ventilator. Early prediction of the indications for withdrawal of non-invasive ventilator and early evaluation of patients to avoid or reduce disease progression are very important.

AIM

To explore the predictive value of DUS indexes for non-invasive ventilation outcome in patients with AECOPD.

METHODS

Ninety-four patients with AECOPD who received mechanical ventilation in our hospital from January 2022 to December 2023 were retrospectively analyzed, and they were divided into a successful ventilation group (68 cases) and a failed ventilation group (26 cases) according to the outcome of ventilation. The clinical data of patients with successful and failed noninvasive ventilation were compared, and the independent predictors of noninvasive ventilation outcomes in AECOPD patients were identified by multivariate logistic regression analysis.

RESULTS

There were no significant differences in gender, age, body mass index, complications, systolic pressure, heart rate, mean arterial pressure, respiratory rate, oxygen saturation, partial pressure of oxygen, oxygenation index, or time of inspiration between patients with successful and failed mechanical ventilation (P > 0.05). The patients with successful noninvasive ventilation had shorter hospital stays and lower partial pressure of carbon dioxide (PaCO₂) than those with failed treatment, while potential of hydrogen (pH), diaphragm thickening fraction (DTF), diaphragm activity, and diaphragm movement time were significantly higher than those with failed treatment (P < 0.05). pH [odds ratio (OR) = 0.005, P < 0.05], PaCO₂ (OR = 0.430, P < 0.05), and DTF (OR = 0.570, P < 0.05) were identified to be independent factors influencing the outcome of mechanical ventilation in AECOPD patients.

CONCLUSION

The DUS index DTF can better predict the outcome of non-invasive ventilation in AECOPD patients.

Analgesia and Sedation Use During Noninvasive Ventilation for Acute Respiratory Failure

OBJECTIVES

To describe U.S. practice regarding administration of sedation and analgesia to patients on noninvasive ventilation (NIV) for acute respiratory failure (ARF) and to determine the association of this practice with odds of intubation or death.

DESIGN

A retrospective multicenter cohort study.

SETTING

A total of 1017 hospitals contributed data between January 2010 and September 2020 to the Premier Healthcare Database, a nationally representative healthcare database in the United States.

PATIENTS

Adult (≥ 18 yr) patients admitted to U.S. hospitals requiring NIV for ARF.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We identified 433,357 patients on NIV of whom (26.7% [95% CI] 26.3%-27.0%) received sedation or analgesia. A total of 50,589 patients (11.7%) received opioids only, 40,646 (9.4%) received benzodiazepines only, 20,146 (4.6%) received opioids and benzodiazepines, 1.573 (0.4%) received dexmedetomidine only, and 2,639 (0.6%) received dexmedetomidine in addition to opioid and/or benzodiazepine. Of 433,357 patients receiving NIV, 50,413 (11.6%; 95% CI, 11.5-11.7%) patients underwent invasive mechanical ventilation on hospital days 2-5 or died on hospital days 2-30. Intubation was used in 32,301 patients (7.4%; 95% CI, 7.3-7.6%). Further, death occurred in 24,140 (5.6%; 95% CI, 5.5-5.7%). In multivariable analysis adjusting for relevant covariates, receipt of any medication studied was associated with increased odds of intubation or death. In inverse probability weighting, receipt of any study medication was also associated with increased odds of intubation or death (average treatment effect odds ratio 1.38; 95% CI, 1.35-1.40).

CONCLUSIONS

The use of sedation and analgesia during NIV is common. Medication exposure was associated with increased odds of intubation or death. Further investigation is needed to confirm this finding and determine whether any subpopulations are especially harmed by this practice.

Upper airway assessment and its implications for interventions by respiratory physiotherapists

BACKGROUND

When noninvasive interventions such as chest physiotherapy fail, then more aggressive interventions for airway secretion clearance with nasotracheal airway suctioning may be required. Clinicians however have to insert the nasotracheal suction catheter "blindly" and the success of being able to trigger a cough and pass through the vocal folds with a suction catheter is low.

CASE DESCRIPTION

The patient, a 48-year-old male underwent a heart and lung transplant. Following extubation, the patient developed secretion retention with a weak ineffective cough and swallow and required physiotherapy interventions with frequent "blind" passes of nasotracheal suctioning.

OUTCOMES

The patient required nasotracheal suction with frequent multiple failed attempts before successful passage of the suction catheter to trigger a cough reflex and clear secretions. A combined physiotherapist and speech and language therapist intervention during fiberoptic endoscopic evaluation of swallow (FEES) was recorded to both evaluate swallow and passage of the suction catheter. The video illustrated the successful passage of a suctioning catheter through the vocal folds leading to an effective cough and airway clearance.

DISCUSSION

We present a case report demonstrating that it is feasible to visualize the upper airways during nasotracheal suctioning as an objective means to guide the more accurate successful insertion of the suction catheter past the vocal folds. Rather than "blind" placement of nasotracheal suction catheters visualization using transnasal laryngoscopy should be useful to increase chances of passing through the vocal folds.

The role of ultrasound in predicting non-invasive ventilation outcomes: a systematic review

Purpose

To systematically review and compare ultrasonographic methods and their utility in predicting non-invasive ventilation (NIV) outcomes.

Methods

A systematic review was performed using the PubMed, Medline, Embase, and Cochrane databases from January 2015 to March 2023. The search terms included the following: ultrasound, diaphragm, lung, prediction, non-invasive, ventilation, and outcomes. The inclusion criteria were prospective cohort studies on adult patients requiring non-invasive ventilation in the emergency department or inpatient setting.

Results

Fifteen studies were analyzed, which comprised of 1,307 patients (n = 942 for lung ultrasound score studies; n = 365 patients for diaphragm dysfunction studies). Lung ultrasound scores (LUS) greater than 18 were associated with NIV failure with a sensitivity 62-90.5% and specificity 60-91.9%. Similarly, a diaphragm thickening fraction (DTF) of less than 20% was also associated with NIV failure with a sensitivity 80-84.6% and specificity 76.3-91.5%.

Conclusion

Predicting NIV failure can be difficult by routine initial clinical impression and diagnostic work up. This systematic review emphasizes the importance of using lung and diaphragm ultrasound, in particular the lung ultrasound score and diaphragm thickening fraction respectively, to accurately predict NIV failure, including the need for ICU-level of care, requiring invasive mechanical ventilation, and resulting in higher rates of mortality.

Acceptance and adherence to non-invasive positive pressure ventilation in people with chronic obstructive pulmonary disease: a grounded theory study

Introduction

Non-Invasive Positive Pressure Ventilation (NPPV) is an established treatment for people with Chronic Obstructive Pulmonary Disease (COPD), but it is often improperly used or rejected. The patterns of acceptance and adherence to NPPV, conceiving constraints, and strengths related to its adaptation have not been explored from a qualitative perspective yet.

Objectives

This study aims to qualitatively explore patterns of adaptation to NPPV in people affected by COPD and to identify the core characteristics and the specific adaptive challenges during the adaptation process.

Methods

Forty-two people with moderate or severe COPD were recruited and 336 unstructured interviews were conducted. A Constructivist Grounded Theory was used to gather and analyze data: the transcriptions were mutually gathered in open, selective, and theoretical phases, with open, selective, and theoretical coding, respectively.

Results

The analysis resulted in a non-linear and dynamic process, characterized by three phases: deciding, trying NPPV, and using NPPV. The patterns revealed that positive and negative NPPV experiences, together with beliefs, emotions, stressful mental states, and behaviors result in different acceptance and adherence rates.

Discussions

These findings may be helpful to implement new care strategies to promote acceptance and adherence to NPPV.

Noninvasive positive pressure in acute exacerbations of chronic obstructive pulmonary disease

PURPOSE OF REVIEW

Noninvasive positive pressure ventilation (NIV) is standard of care for patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD). We review the most current evidence and highlight areas of uncertainty and ongoing research. We highlight key concepts for the clinician caring for patients with AECOPD which require NIV.

RECENT FINDINGS

Implementation of NIV in AECOPD is not uniform in spite of the evidence and guidelines. Initiation of NIV should be done early and following protocols. Low-intensity NIV remains the standard of care, although research and guidelines are evaluating higher intensity NIV. Scores to predict NIV failure continue to be refined to allow early identification and interventions. Several areas of uncertainty remain, among them are interventions to improve tolerance, length of support and titration and nutritional support during NIV.

SUMMARY

The use of NIV in AECOPD is the standard of care as it has demonstrated benefits in several patient-centered outcomes. Current developments and research is related to the implementation and adjustment of NIV.

Timing of Treatment Outcomes and Risk Factors for Failure of BPAP in Patients Hospitalized for COPD Exacerbation

BACKGROUND

Patients hospitalized for COPD exacerbation have an increased risk of mortality, particularly among those who fail bi-level positive airway pressure (BPAP) for hypercapnic respiratory failure subsequently requiring invasive mechanical ventilation. Therefore, we sought to investigate the treatment course of BPAP and factors associated with BPAP treatment failure.

METHODS

We performed a retrospective cohort study using real-world evidence to investigate subjects with COPD who were treated with BPAP during a hospitalization for COPD exacerbation. Treatment outcomes were defined within 7 d from BPAP initiation as either failure, persistent, or success. Failure was defined as death or progression to invasive ventilation. Persistent was defined as receiving BPAP during hospital day 7. Success was defined as liberation from BPAP prior to hospital day 7 and not meeting criteria for failure. Unadjusted multinomial logistic regression models were used to examine the association between BPAP treatment outcomes and 17 recipient characteristics.

RESULTS

Among the 427 clinical encounters, 78% were successful, 10% were persistent, and 12% experienced failure. The median time to failure and success was 8 h and 16 h, respectively. Increasing age, body mass index (BMI), bicarbonate level, and creatinine level were significantly associated with either BPAP treatment failure, persistent treatment, or both.

CONCLUSIONS

The first 8 h following initiation of BPAP is a critical time period where patients are at high risk for life-threatening decompensation. Careful consideration should be given to increasing age, BMI, bicarbonate level, and creatinine level as these factors were associated with BPAP treatment failure or persistent treatment.

Clinical prediction models in hospitalized patients with COVID-19: A multicenter cohort study

Background

Clinical spectrum of novel coronavirus disease (COVID-19) ranges from asymptomatic infection to severe respiratory failure that may result in death. We aimed at validating and potentially improve existing clinical models to predict prognosis in hospitalized patients with acute COVID-19.

Methods

Consecutive patients with acute confirmed COVID-19 pneumonia hospitalized at 5 Italian non-intensive care unit centers during the 2020 outbreak were included in the study. Twelve validated prognostic scores for pneumonia and/or sepsis and specific COVID-19 scores were calculated for each study patient and their accuracy was compared in predicting in-hospital death at 30 days and the composite of death and orotracheal intubation.

Results

During hospital stay, 302 of 1044 included patients presented critical illness (28.9%), and 226 died (21.6%). Nine out of 34 items included in different prognostic scores were independent predictors of all-cause-death. The discrimination was acceptable for the majority of scores (APACHE II, COVID-GRAM, REMS, CURB-65, NEWS II, ROX-index, 4C, SOFA) to predict in-hospital death at 30 days and poor for the rest. A high negative predictive value was observed for REMS (100.0%) and 4C (98.7%) scores; the positive predictive value was poor overall, ROX-index having the best value (75.0%).

Conclusions

Despite the growing interest in prognostic models, their performance in patients with COVID-19 is modest. The 4C, REMS and ROX-index may have a role to select high and low risk patients at admission. However, simple predictors as age and PaO2/FiO2 ratio can also be useful as standalone predictors to inform decision making.

Early prediction of noninvasive ventilation failure after extubation: development and validation of a machine-learning model

Background

Noninvasive ventilation (NIV) has been widely used in critically ill patients after extubation. However, NIV failure is associated with poor outcomes. This study aimed to determine early predictors of NIV failure and to construct an accurate machine-learning model to identify patients at risks of NIV failure after extubation in intensive care units (ICUs).

Methods

Patients who underwent NIV after extubation in the eICU Collaborative Research Database (eICU-CRD) were included. NIV failure was defined as need for invasive ventilatory support (reintubation or tracheotomy) or death after NIV initiation. A total of 93 clinical and laboratory variables were assessed, and the recursive feature elimination algorithm was used to select key features. Hyperparameter optimization was conducted with an automated machine-learning toolkit called Neural Network Intelligence. A machine-learning model called Categorical Boosting (CatBoost) was developed and compared with nine other models. The model was then prospectively validated among patients enrolled in the Cardiac Surgical ICU of Zhongshan Hospital, Fudan University.

Results

Of 929 patients included in the eICU-CRD cohort, 248 (26.7%) had NIV failure. The time from extubation to NIV, age, Glasgow Coma Scale (GCS) score, heart rate, respiratory rate, mean blood pressure (MBP), saturation of pulse oxygen (SpO₂), temperature, glucose, pH, pressure of oxygen in blood (PaO₂), urine output, input volume, ventilation duration, and mean airway pressure were selected. After hyperparameter optimization, our model showed the greatest accuracy in predicting NIV failure (AUROC: 0.872 [95% CI 0.82–0.92]) among all predictive methods in an internal validation. In the prospective validation cohort, our model was also superior (AUROC: 0.846 [95% CI 0.80–0.89]). The sensitivity and specificity in the prediction group is 89% and 75%, while in the validation group they are 90% and 70%. MV duration and respiratory rate were the most important features. Additionally, we developed a web-based tool to help clinicians use our model.

Conclusions

This study developed and prospectively validated the CatBoost model, which can be used to identify patients who are at risk of NIV failure. Thus, those patients might benefit from early triage and more intensive monitoring.

Trial registration: NCT03704324. Registered 1 September 2018, https://register.clinicaltrials.gov.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-02096-7.

Intelligent Volume-Assured Pressure Support vs. Spontaneous/Timed Mode as a Weaning Strategy in COPD-Evaluation of a New Ventilation Strategy

We thank Salama S et al [...].

Noninvasive ventilation in COVID-19 patients aged ≥ 70 years-a prospective multicentre cohort study

BACKGROUND

Noninvasive ventilation (NIV) is a promising alternative to invasive mechanical ventilation (IMV) with a particular importance amidst the shortage of intensive care unit (ICU) beds during the COVID-19 pandemic. We aimed to evaluate the use of NIV in Europe and factors associated with outcomes of patients treated with NIV.

METHODS

This is a substudy of COVIP study-an international prospective observational study enrolling patients aged ≥ 70 years with confirmed COVID-19 treated in ICU. We enrolled patients in 156 ICUs across 15 European countries between March 2020 and April 2021.The primary endpoint was 30-day mortality.

RESULTS

Cohort included 3074 patients, most of whom were male (2197/3074, 71.4%) at the mean age of 75.7 years (SD 4.6). NIV frequency was 25.7% and varied from 1.1 to 62.0% between participating countries. Primary NIV failure, defined as need for endotracheal intubation or death within 30 days since ICU admission, occurred in 470/629 (74.7%) of patients. Factors associated with increased NIV failure risk were higher Sequential Organ Failure Assessment (SOFA) score (OR 3.73, 95% CI 2.36-5.90) and Clinical Frailty Scale (CFS) on admission (OR 1.46, 95% CI 1.06-2.00). Patients initially treated with NIV (n = 630) lived for 1.36 fewer days (95% CI - 2.27 to - 0.46 days) compared to primary IMV group (n = 1876).

CONCLUSIONS

Frequency of NIV use varies across European countries. Higher severity of illness and more severe frailty were associated with a risk of NIV failure among critically ill older adults with COVID-19. Primary IMV was associated with better outcomes than primary NIV. Clinical Trial Registration NCT04321265 , registered 19 March 2020, https://clinicaltrials.gov .

Non-Invasive Ventilation as a Therapy Option for Acute Exacerbations of Chronic Obstructive Pulmonary Disease and Acute Cardiopulmonary Oedema in Emergency Medical Services

In this observational prospective multicenter study conducted between October 2016 and October 2018, we tested the hypothesis that the use of prehospital non-invasive ventilation (phNIV) to treat patients with acute respiratory insufficiency (ARI) caused by severe acute exacerbations of chronic obstructive pulmonary disease (AECOPD) and acute cardiopulmonary oedema (ACPE) is effective, time-efficient and safe. The data were collected at four different physician response units and three admitting hospitals in a German EMS system. Patients with respiratory failure due to acute exacerbation of chronic obstructive pulmonary disease and acute cardiopulmonary oedema were enrolled. A total of 545 patients were eligible for the final analysis. Patients were treated with oxygen supplementation, non-invasive ventilation or invasive mechanical ventilation. The primary outcomes were defined as changes in the clinical parameters and the in-hospital course. The secondary outcomes included time efficiency, peri-interventional complications, treatment failure rate, and side-effects. Oxygenation under phNIV improved equally to endotracheal intubation (ETI), and more effectively in comparison to standard oxygen therapy (SOT) (paO2 SOT vs. non-invasive ventilation (NIV) vs. ETI: 82 mmHg vs. 125 mmHg vs. 135 mmHg, p-value SOT vs. NIV < 0.0001). In a matched subgroup analysis phNIV was accompanied by a reduced time of mechanical ventilation (phNIV: 1.8 d vs. ETI: 4.2 d) and a shortened length of stay at the intensive care unit (3.4 d vs. 5.8 d). The data support the hypothesis that the treatment of severe AECOPD/ACPE-induced ARI using prehospital NIV is effective, time efficient and safe. Compared to ETI, a matched comparison supports the hypothesis that prehospital implementation of NIV may provide benefits for an in-hospital course.

Efficacy prediction of noninvasive ventilation failure based on the stacking ensemble algorithm and autoencoder

Background

Early prediction of noninvasive ventilation failure is of great significance for critically ill ICU patients to escalate or change treatment. Because clinically collected data are highly time-series correlated and have imbalanced classes, it is difficult to accurately predict the efficacy of noninvasive ventilation for severe patients. This paper aims to precisely predict the failure probability of noninvasive ventilation before or in the early stage (1–2 h) of using it on patients and to explain the correlation of the predicted results.

Methods

In this paper, we proposed a SMSN model (stacking and modified SMOTE algorithm of prediction of noninvasive ventilation failure). In the feature generation stage, we used an autoencoder algorithm based on long short-term memory (LSTM) to automatically extract time series features. In the modelling stage, we adopted a modified SMOTE algorithm to address imbalanced classes, and three classifiers (logistic regression, random forests, and Catboost) were combined with the stacking ensemble algorithm to achieve high prediction accuracy.

Results

Data from 2495 patients were used to train the SMSN model. Among them, 80% of 2495 patients (1996 patients) were randomly selected as the training set, and 20% of these patients (499 patients) were chosen as the testing set. The F1 of the proposed SMSN model was 79.4%, and the accuracy was 88.2%. Compared with the traditional logistic regression algorithm, the F1 and accuracy were improved by 4.7% and 1.3%, respectively.

Conclusions

Through SHAP analysis, oxygenation index, pH and H1FIO₂ collected after 1 h of noninvasive ventilation were the most relevant features affecting the prediction.

Predictors of Helmet CPAP Failure in COVID-19 Pneumonia: A Prospective, Multicenter, and Observational Cohort Study

Background

Continuous positive airway pressure (CPAP) can be beneficial in acute respiratory failure (ARF) due to coronavirus (COVID-19) pneumonia, but delaying endotracheal intubation (ETI) in nonresponders may increase mortality. We aimed at investigating the performance of composite respiratory indexes as possible predictors of CPAP failure in ARF due to COVID-19.

Methods

This was a multicenter, prospective, observational, and cohort study conducted in the respiratory units of three University hospitals in Milan and in a secondary care hospital in Codogno (Italy), on consecutive adult patients with ARF due to COVID-19 pneumonia that underwent CPAP between March 2020 and March 2021. ETI transfer to the intensive care unit or death is defined CPAP failure. Predictors of CPAP failure were assessed before T0 and 1 hour after T1 CPAP initiation and included mROX index (ratio of PaO2/FiO2 to respiratory rate), alveolar-to-arterial (A-a) O₂ gradient, and the HACOR (heart rate, acidosis, consciousness, oxygenation, and respiratory rate) score.

Results

Three hundred and fifty four patients (mean age 64 years, 73% males) were included in the study; 136 (38.4%) satisfied criteria for CPAP failure. A-a O₂ gradient, mROX, and HACOR scores were worse in patients who failed CPAP, both at T0 and T1 (p < 0.001 for all parameters). The HACOR score was associated with CPAP failure (odds ratio—OR—for every unit increase in HACOR = 1.361; 95%CI: 1.103–1.680; p=0.004; AUROC = 0.742; p < 0.001). CPAP failure was best predicted by a threshold of 4.50 (sensitivity = 53% and specificity = 87%).

Conclusions

The HACOR score may be a reliable and early predictor of CPAP failure in patients treated for ARF in COVID-19 pneumonia.

Hospital Variation in Non-Invasive Ventilation Use for Acute Respiratory Failure Due to COPD Exacerbation

Background

Non-invasive mechanical ventilation (NIV) use in patients admitted with acute respiratory failure due to COPD exacerbations (AECOPDs) varies significantly between hospitals. However, previous literature did not account for patients’ illness severity. Our objective was to examine the variation in risk-standardized NIV use after adjusting for illness severity.

Methods

We retrospectively analyzed AECOPD hospitalizations from 2011 to 2017 at 106 acute-care Veterans Health Administration (VA) hospitals in the USA. We stratified hospitals based on the percentage of NIV use among patients who received ventilation support within the first 24 hours of admission into quartiles, and compared patient characteristics. We calculated the risk-standardized NIV % using hierarchical models adjusting for comorbidities and severity of illness. We then stratified the hospitals by risk-standardized NIV % into quartiles and compared hospital characteristics between quartiles. We also compared the risk-standardized NIV % between rural and urban hospitals.

Results

In 42,048 admissions for AECOPD over 6 years, the median risk-standardized initial NIV % was 57.3% (interquartile interval [IQI]=41.9–64.4%). Hospitals in the highest risk-standardized NIV % quartiles cared for more rural patients, used invasive ventilators less frequently, and had longer length of hospital stay, but had no difference in mortality relative to the hospitals in the lowest quartiles. The risk-standardized NIV % was 65.3% (IQI=34.2–84.2%) in rural and 55.1% (IQI=10.8–86.6%) in urban hospitals (p=0.047), but hospital mortality did not differ between the two groups.

Conclusion

NIV use varied significantly across hospitals, with rural hospitals having higher risk-standardized NIV % rates than urban hospitals. Further research should investigate the exact mechanism of variation in NIV use between rural and urban hospitals.

A New Score to Assess the Perioperative Period of the Cancer Patient Undergoing Non-Palliative Elective Surgery: A Retrospective Evaluation of a Case Report by PERIDIA Score

The complexity of cancer patients and the use of advanced and demolitive surgical techniques frequently need post-operatory ICU hospitalization. To increase safety and to select the best medical strategies for the patient, a multidisciplinary team has performed a new peri-operatory assessment, arising from evidence-based literature data. Verifying that most of the cancer patients, admitted to the intensive care unit, undergo major surgery with localizations in the supramesocolic thoraco-abdominal area, the team focused the attention on supramesocolic peridiaphragmatic cancer surgery. Some scores already in use in clinical practice were selected for the peri-operatory evaluation process. None of them evaluate parameters relating to the entire peri-operative period. In detail, only a few study models were found that concern the assessment of the intra-operative period. Therefore, we wanted to see if using a mix of validated scores, it was possible to build a single evaluation score (named PERIDIAphragmatic surgery score or PERIDIA-score) for the entire peri-operative period that could be obtained at the end of the patient's hospitalization period in post-operative ICU. The main property sought with the creation of the PERIDIA-score is the proportionality between the score and the incidence of injuries, deaths, and the length of stay in the ward. This property could organize a tailor-made therapeutic path for the patient based on pre-rehabilitation, physiotherapy, activation of social assistance services, targeted counseling, collaborations with the continuity of care network. Furthermore, if the pre-operative score is particularly high, it could suggest different or less invasive therapeutic options, and if the intra-operative score is particularly high, it could suggest a prolongation of hospitalization in ICU. The retrospective prospective study conducted on 83 patients is still ongoing. The first data would seem to prove an increase of clinical complications in patients who were assigned a one-third score with respect to the maximum (16/48) of PERIDIA-score. Moreover, patients with a 10/16 score within each phase of the evaluation (pre, peri, and post) more frequently develop injuries. In the light of these evidence, the 29-point score assigned to our patient can be considered as predictive for the subsequent critical and fatal complications the patient faced up.

[Factors predicting the need for invasive mechanical ventilation in patients with chronic obstructive pulmonary disease (COPD)]

Introduction

the use of invasive mechanical ventilation (IMV) in acute exacerbations of chronic obstructive pulmonary disease (AECOPD) constitutes a negative turning point in the progression of the disease. The purpose of this study is to determine factors predicting the need for IMV in AECOPD.

Methods

we conducted a retrospective study by reviewing the medical records of patients with AECOPD hospitalized in our Department over a 18-year period (2000-2017). We compared 2 groups: G1: patients with AECOPD undergoing at least one IMV and G2: patients who had never undergone IMV following AECOPD.

Results

the study included 1152 patients with COPD: 133 in the G1 group (11.5%), and 1019 in the G2 group (88.5%). G1 patients were more symptomatic (p < 0.001), with more severe bronchial obstruction (p < 0.001). G1 patients had more exacerbations (p < 0.001), more hospitalizations and a higher need for non-invasive ventilation (NIV) (p < 0.001). Similarly, G1 patients more often developed chronic respiratory failure (p < 0.001) and had significantly lower survival rates. Independent risk factors associated with IMV were hypercapnia and decreased pH (in patients with severe AECOPD), a history of NIV, and chronic respiratory failure (CRF).

Conclusion

respiratory function impairment, the severity of exacerbation and the need for NIV in a previous episode are factors predicting the need for IMV and poor outcomes.

Dynamic prediction of late noninvasive ventilation failure in intensive care unit using a time adaptive machine model

BACKGROUND

Noninvasive ventilation (NIV) failure is strongly associated with poor prognosis. Nowadays, plenty of mature studies have been proposed to predict early NIV failure (within 48 hours of NIV), however, the prediction for late NIV failure (after 48 hours of NIV) lacks sufficient research. Late NIV failure delays intubation resulting in the increasing mortality of the patients. Therefore, it is of great significance to expeditiously predict the late NIV failure. In order to dynamically predict late NIV failure, we proposed a Time Updated Light Gradient Boosting Machine (TULightGBM) model.

MATERIAL AND METHODS

In this work, 5653 patients undergoing NIV over 48 hours were extracted from the database of Medical Information Mart for Intensive Care Ⅲ (MIMIC-Ⅲ) for model construction. The TULightGBM model consists of a series of sub-models which learn clinical information from updating data within 48 hours of NIV and integrates the outputs of the sub-models by the dynamic attention mechanism to predict late NIV failure. The performance of the proposed TULightGBM model was assessed by comparison with common models of logistic regression (LR), random forest (RF), LightGBM, eXtreme gradient boosting (XGBoost), artificial neural network (ANN), and long short-term memory (LSTM).

RESULTS

The TULightGBM model yielded prediction results at 8, 16, 24, 36, and 48 hours after the start of the NIV with dynamic AUC values of 0.8323, 0.8435, 0.8576, 0.8886, and 0.9123, respectively. Furthermore, the sensitivity, specificity, and accuracy of the TULightGBM model were 0.8207, 0.8164, and 0.8184, respectively. The proposed model achieved superior performance over other tested models.

CONCLUSIONS

The TULightGBM model is able to dynamically predict the late NIV failure with high accuracy and offer potential decision support for clinical practice.

Noninvasive respiratory support and patient self-inflicted lung injury in COVID-19: a narrative review

COVID-19 pneumonia is associated with hypoxaemic respiratory failure, ranging from mild to severe. Because of the worldwide shortage of ICU beds, a relatively high number of patients with respiratory failure are receiving prolonged noninvasive respiratory support, even when their clinical status would have required invasive mechanical ventilation. There are few experimental and clinical data reporting that vigorous breathing effort during spontaneous ventilation can worsen lung injury and cause a phenomenon that has been termed patient self-inflicted lung injury (P-SILI). The aim of this narrative review is to provide an overview of P-SILI pathophysiology and the role of noninvasive respiratory support in COVID-19 pneumonia. Respiratory mechanics, vascular compromise, viscoelastic properties, lung inhomogeneity, work of breathing, and oesophageal pressure swings are discussed. The concept of P-SILI has been widely investigated in recent years, but controversies persist regarding its mechanisms. To minimise the risk of P-SILI, intensivists should better understand its underlying pathophysiology to optimise the type of noninvasive respiratory support provided to patients with COVID-19 pneumonia, and decide on the optimal timing of intubation for these patients.

The Noninvasive Ventilation Outcomes (NIVO) score: prediction of in-hospital mortality in exacerbations of COPD requiring assisted ventilation

Introduction

Acute exacerbations of COPD (AECOPD) complicated by acute (acidaemic) hypercapnic respiratory failure (AHRF) requiring ventilation are common. When applied appropriately, ventilation substantially reduces mortality. Despite this, there is evidence of poor practice and prognostic pessimism. A clinical prediction tool could improve decision making regarding ventilation, but none is routinely used.

Methods

Consecutive patients admitted with AECOPD and AHRF treated with assisted ventilation (principally noninvasive ventilation) were identified in two hospitals serving differing populations. Known and potential prognostic indices were identified a priori. A prediction tool for in-hospital death was derived using multivariable regression analysis. Prospective, external validation was performed in a temporally separate, geographically diverse 10-centre study. The trial methodology adhered to TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) recommendations.

Results

Derivation cohort: n=489, in-hospital mortality 25.4%; validation cohort: n=733, in-hospital mortality 20.1%. Using six simple categorised variables (extended Medical Research Council Dyspnoea score 1–4/5a/5b, time from admission to acidaemia >12 h, pH <7.25, presence of atrial fibrillation, Glasgow coma scale ≤14 and chest radiograph consolidation), a simple scoring system with strong prediction of in-hospital mortality is achieved. The resultant Noninvasive Ventilation Outcomes (NIVO) score had area under the receiver operating curve of 0.79 and offers good calibration and discrimination across stratified risk groups in its validation cohort.

Discussion

The NIVO score outperformed pre-specified comparator scores. It is validated in a generalisable cohort and works despite the heterogeneity inherent to both this patient group and this intervention. Potential applications include informing discussions with patients and their families, aiding treatment escalation decisions, challenging pessimism and comparing risk-adjusted outcomes across centres.

The NIVO score was created to predict in-hospital mortality in exacerbations of COPD requiring assisted ventilation. Prospective validation under real-world conditions in 10 UK hospitals shows it easily outperforms existing alternative scores.https://bit.ly/3oKMZdI

The Neutrophil/Lymphocyte Ratio Could Predict Noninvasive Mechanical Ventilation Failure in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Retrospective Observational Study

Purpose

To determine the effectiveness of neutrophil/lymphocyte ratio (NLR), compared to traditional inflammatory markers, for predicting noninvasive mechanical ventilation (NIMV) failure in acute exacerbation of chronic obstructive pulmonary disease (AECOPD) patients.

Patients and Methods

We conducted this retrospective observational study including 212 AECOPD patients who required NIMV during hospitalization from January 2015 to December 2020 in the department of respiratory and critical care medicine of Beijing Chao-Yang Hospital (west campus). We reviewed the medical record to determine if NIMV succeeded or failed for each patient, and compared NLR with traditional markers (leukocyte, C-reactive protein [CRP] and procalcitonin [PCT]) between NIMV failure and NIMV success group. Receiver-operating characteristic (ROC) curve and multivariate logistic regression analysis were used to assess the accuracy of these markers for predicting NIMV failure.

Results

A total of 38 (17.9%) patients experienced NIMV failure. NLR was a more sensitive biomarker to predict NIMV failure (AUC, 0.858; 95% CI 0.785-0.931) than leukocyte counts (AUC, 0.723; 95% CI 0.623-0.823), CRP (AUC, 0.670; 95% CI 0.567-0.773) and PCT (AUC, 0.719; 95% CI 0.615-0.823). There was statistically positive correlation between NLR and leukocytes count (r=0.35, p<0.001), between NLR and CRP (r=0.258, p<0.001), between NLR and PCT (r=0.306, p<0.001). The cutoff value of NLR to predict NIMV failure was 8.9 with sensitivity 0.688, specificity 0.886 and diagnostic accuracy 0.868. NLR>8.9 (odds ratio, 10.783; 95% CI, 2.069-56.194; P=0.05) was an independent predictor of NIMV failure in the multivariate logistic regression model.

Conclusion

NLR may be an effective marker for predicting NIMV failure in AECOPD patients, and the patients with NLR>8.9 should be handled with caution since they are at higher risk of NIMV failure and require intubation. Further study with a larger sample size and with more data is necessary to confirm our study.

Admission SpO2 and ROX index predict outcome in patients with COVID-19

Background

This study aimed to evaluate the accuracy of pulse oximetry-derived oxygen saturation (SpO₂) on room air, determined at hospital admission, as a predictor for the need for mechanical ventilatory support in patients with Coronavirus Disease-2019 (COVID-19).

Methods

In this retrospective observational study, demographic and clinical details of the patients were obtained during ICU admission. SpO₂ and respiratory rate (RR) on room air were determined within the first 6 h of hospital admission. As all measurements were obtained on room air, we calculated the simplified respiratory rate‑oxygenation (ROX) index by dividing the SpO₂ by the RR. Based on the use of any assistance of mechanical ventilator (invasive or noninvasive), patients were divided into mechanical ventilation (MV) group and oxygen therapy group. The accuracy of the SpO₂, CT score, and ROX index to predict the need to MV were determined using the Area under receiver operating curve (AUC).

Results

We included 72 critically ill patients who tested COVID-19-positive. SpO₂ on the room air could predict any MV requirement (AUC [95% confidence interval]: 0.9 [0.8–0.96], sensitivity: 70%, specificity 100%, cut-off value ≤78%, P < 0.001). Within the MV group, the use of noninvasive ventilation (NIV) was successful in 37 (74%) patients, whereas 13 patients (26%) required endotracheal intubation. The cut-off ROX value for predicting early NIV failure was ≤1.4, with a sensitivity of 85%, a specificity of 86%, and an AUC of 0.86 (95% confidence interval of 0.73–0.94, P < 0.0001).

Conclusions

A baseline SpO₂ ≤78% is an excellent predictor of MV requirement with a positive predictive value of 100%. Moreover, the ROX index measured within the first 6 h of hospital admission is a good indicator of early NIV failure.

Impact of HACOR Score on Noninvasive Ventilation Failure in Non-COPD Patients with Acute-on-Chronic Respiratory Failure

Background

A rating scale that takes into account heart rate, acidosis, consciousness, oxygenation, and respiratory rate (the HACOR score) has been used to predict noninvasive ventilation (NIV) failure in patients with chronic obstructive pulmonary disease (COPD). However, the HACOR score has not been used to predict NIV failure in non-COPD patients with acute-on-chronic respiratory failure.

Methods

This study was performed in the respiratory intensive care unit of a teaching hospital. Data had been collected prospectively between June 2011 and January 2019. We enrolled non-COPD patients who received NIV due to acute-on-chronic respiratory failure, pH < 7.35, and PaCO₂ >45 mmHg. NIV failure was defined as requiring intubation or dying during NIV. The HACOR score was determined at initiation and after 1-2, 12, and 24 h of NIV. Scores can range from 0 to 27, with higher scores indicating a higher risk of NIV failure.

Results

A total of 148 patients were enrolled in the study, 52 with sleep apnea-hypopnea syndrome, 34 with chronic thoracic sequelae, 31 with bronchiectasis, 14 with chest wall deformity, 5 with obesity-hypoventilation syndrome, and 12 with other conditions. Of the patients, 19 (13%) experienced NIV failure. From initiation to 24 h of NIV, the HACOR scores of patients who experienced NIV failure were much higher than those of patients who received successful NIV. The area under the receiver operating characteristic curve was 0.69, 0.91, 0.91, and 0.94 when the HACOR score was tested at initiation and after 1-2, 12, and 24 h of NIV, respectively. To obtain the best sensitivity and specificity, the cutoff value at initiation was 7 with a sensitivity of 68% and a specificity of 61%. After 1-2 h of NIV, it was 5 with a sensitivity of 90% and a specificity of 85%. After 12 h of NIV, it was 4 with a sensitivity of 82% and a specificity of 91%. After 24 h of NIV, it was 2 with a sensitivity of 100% and a specificity of 76%.

Conclusions

The HACOR score has high sensitivity and specificity for predicting NIV failure among non-COPD patients who receive NIV due to acute-on-chronic respiratory failure with respiratory acidosis.

Noninvasive Respiratory Support

Despite its life-saving nature, invasive mechanical ventilation does not come without risk, and the avoidance of invasive mechanical ventilation is the primary goal of noninvasive respiratory support. Noninvasive respiratory support in the form of continuous or bi-level positive airway pressure were considered the only viable options to accomplish this for many years. Innovation and research have led to high-flow nasal cannula being added to the list of specialized therapies clinically shown to reduce escalation of care and intubation rates in patients presenting with acute respiratory failure. The amount of research being performed in this clinical space is impressive, to say the least, and it is rapidly evolving. It is the responsibility of the clinicians trained to use these therapies in the management of respiratory failure to understand the currently available evidence, benefits, and risks associated with the type of noninvasive respiratory support being used to treat our patients.

Noninvasive ventilation and high-flow nasal oxygen for acute respiratory failure: is less more?

PURPOSE OF REVIEW

High-flow nasal oxygen and noninvasive ventilation (NIV) are two strategies representing an alternative to standard oxygen in the management of respiratory failure.

RECENT FINDINGS

Although high-flow nasal oxygen has shown promising results in patients with de-novo acute respiratory failure, further large clinical trials are needed to determine the best oxygenation strategy. As NIV may have deleterious effects, especially in patients generating strong inspiratory efforts, protective NIV using higher levels of positive-end expiratory pressure, more prolonged sessions and additional interfaces such as helmets should be assessed in the future. Whereas NIV is the first-line ventilation strategy in patients with acute exacerbation of chronic lung diseases, high-flow nasal oxygen could be an alternative to NIV after partial reversal of respiratory acidosis. To prevent severe hypoxemia during intubation of hypoxemic patients or to prevent postextubation respiratory failure in patients at high-risk of reintubation, NIV is the best strategy for preoxygenation or immediately after extubation in ICUs.

SUMMARY

New large-scale clinical trials are needed to compare high-flow nasal oxygen with standard oxygen in patients with de-novo acute respiratory failure to determine the reference treatment. After which, more protective NIV could be assessed among the more severe patients.

Failure of Noninvasive Ventilation in Acute Respiratory Failure is Associated with Higher Mortality in Patients with Solid Tumors: A Retrospective Cohort Study

BACKGROUND

Noninvasive Ventilation (NIV) is a well-established treatment for Acute Respiratory Failure (ARF) in hematological cancer. However, the NIV impact on mortality in patients with solid tumors is unclear.

OBJECTIVE

To define the factors associated with NIV failure and mortality and to describe the mortality risk of patients with solid tumors requiring NIV for ARF treatment in the intensive care unit (ICU).

METHODS

A retrospective cohort study of patients with solid tumors admitted into an ICU between Jan 2016 and Dec 2017, for cancer treatment, with ARF diagnosis that had used the NIV as first-line treatment. Our primary outcome was ICU and in-hospital mortality. The secondary outcome was NIV failure. A Cox proportional hazards regression was used to identify variables associated with mortality and NIV failure. Kaplan-Meier analyses were performed to demonstrate cumulative survival.

RESULTS

A total of 226 patients with solid tumors were included. The ICU and hospital mortality rates were 57.5% and 69.5%, respectively. NIV failed in 52.2% of the patients. The use of vasopressors (HR 2.48 [95% CI: 1.43-4.30] p = 0.001), baseline lactate (HR 1.20 [95% CI: 1.07-1.35] p = 0.003), baseline PaO₂/FiO₂ ratio (HR1.33 [1.11-1.55] p = 0.002), and NIV success (HR0.17 [95% CI: 0.10-0.27] p = 0.005) was independently associated with hospital mortality. The use of vasopressors (HR 2.58 [95% CI: 1.41-4.73] p = 0.02), NIV duration (HR 0.93 [95% CI: 0.89-0.97] p = 0.003), and baseline lactate (HR 1.13 [95% CI: 1.06-1.20] p = 0.001) was associated with NIV failure.

CONCLUSIONS

NIV failure was independently associated with an increase in both ICU and hospital mortality rates. In patients with NIV therapy indication, the duration of this intervention was associated with NIV failure.

The prognostic value of chest X-ray in patients with COVID-19 on admission and when starting CPAP

OBJECTIVE

The objective was to explore if chest X-ray severity, assessed using a validated scoring system, predicts patient outcome on admission and when starting continuous positive pressure ventilation (CPAP) for COVID-19.

DESIGN

The study was a retrospective case-controlled study.

PARTICIPANTS

There were 163 patients with COVID-19 deemed candidates for CPAP on admission, including 58 who subsequently required CPAP.

OUTCOME MEASURES

On admission, we measured the proportion of patients meeting a composite 'negative' outcome of requiring CPAP, intubation or dying versus successful ward-based care. For those escalated to CPAP, 'negative' outcomes were intubation or death versus successful de-escalation of respiratory support.

RESULTS

Our results were stratified into tertiles, those with 'moderate' or 'severe' X-rays on admission had significantly higher odds of negative outcome versus 'mild' (odds ratio (OR) 2.32; 95% confidence interval (CI) 1.121-4.803; p=0.023; and OR 3.600; 95% CI 1.681-7.708; p=0.001, respectively). This could not be demonstrated in those commencing CPAP (OR 0.976; 95% CI 0.754-1.264; p=0.856).

CONCLUSIONS

We outline a scoring system to stratify X-rays by severity and directly link this to prognosis. However, we were unable to demonstrate this association in the patients commencing CPAP.

Head-To-Head Comparison of Treatment Failure and Costs among COPD Patients Who Used Noninvasive Ventilation in the Ward versus in the ICU: A Propensity-Matched Cohort Study

Background

Head-to-head comparison of treatment failure and costs among chronic obstruct pulmonary disease (COPD) patients who used noninvasive ventilation (NIV) in the ward versus in the ICU is lacking.

Methods

This retrospective study was performed in a department of respiratory and critical care medicine in a teaching hospital. COPD patients who used NIV in the respiratory ward or respiratory ICU were screened. We enrolled patients with PaCO₂ more than 45 mmHg and pH less than 7.35 before the use of NIV.

Results

We enrolled 83 patients who initiated NIV in the ward and 319 patients in the ICU. Only 5 (6%) patients in the ward were required to transfer to ICU for intensive care. The vital signs were worse but improved faster within 24 h of NIV among patients in the ICU than those in the ward. The NIV failure, hospital mortality, and the length of stay in hospital did not differ between the two groups. However, the duration of NIV was shorter (median 4.0 vs. 6.1 days, p < 0.01) and hospital costs were higher (median 4638 vs. 3093 $USD, p < 0.01) among patients in the ICU than those in the ward. After propensity matching, 42 patients were left in each group, and the baseline data were comparable between the two groups. The findings in the overall cohort were confirmed again in the propensity-matched cohort.

Conclusions

Among COPD patients, the use of NIV in the ward leads to longer duration of NIV, but lower hospital costs, and similar NIV failure and mortality compared with those in the ICU.

Multidimensional prognostic index (MPI) predicts non-invasive ventilation failure in older adults with acute respiratory failure

BACKGROUND

Acute respiratory failure (ARF) is a very common complication among hospitalized older adults. Non-invasive ventilation (NIV) may avoid admission to intensive care units, intubation and their related complication, but still lacks specific indications in older adults. Multidimensional Prognostic Index (MPI) based on comprehensive geriatric assessment (CGA) could have a role in defining the short-term prognosis and the best candidates for NIV among older adults with ARF.

METHODS

This is a retrospective observational study which enrolled patients older than 70 years, consecutively admitted to an acute geriatric unit with ARF. A standardized CGA was used to calculate the MPI at admission. Multivariate Cox regression models were used to test if MPI score could predict in-hospital mortality and NIV failure. Receiver operator curve (ROC) analysis was used to identify the discriminatory power of MPI for NIV failure.

RESULTS

We enrolled 231 patients (88.2 ± 5.9 years, 47% females). Mean MPI at admission was 0.76±0.16. In-hospital mortality rate was 33.8%, with similar incidence in patients treated with and without NIV. Among NIV users (26.4%), NIV failure occurred in 39.3%. Higher MPI scores at admission significantly predicted in-hospital mortality (β=4.46, p<0.0001) among patients with ARF and NIV failure (β=7.82, p = 0.001) among NIV users. MPI showed good discriminatory power for NIV failure (area under the curve: 0.72, 95% CI: 0.58-0.85, p<0.001) with optimal cut-off at MPI value of 0.84.

CONCLUSIONS

MPI at admission might be a useful tool to early detect patients more at risk of in-hospital death and NIV failure among older adults with ARF.

Early detection of non-invasive ventilation failure among acute respiratory failure patients in the emergency department

Background

Non-invasive mechanical ventilation (NIV) has become an alternative to an invasive artificial airway for the management of acute respiratory failure (ARF). NIV failure causes delayed intubation, which eventually has been associated with increased morbidity and mortality. This study aimed to develop the clinical scoring system of NIV failure in ARF patients.

Methods

This study was a diagnostic, retrospectively cross-sectional, and exploratory model at the Emergency Medicine Department in Ramathibodi Hospital between February 2017 and December 2017. We included all of the acute respiratory failure patients aged > 18 years and received non-invasive ventilation (NIV). Clinical factors associated with NIV failure were recorded. The predictive model and prediction score for NIV failure were developed by multivariable logistic regression analysis.

Result

A total of 329 acute respiratory failure patients have received NIV success (N = 237) and failure (N = 92). This study showed that NIV failure was associated with heart rate >  110 bpm, systolic BP <  110 mmHg, SpO2 < 90%, arterial pH < 7.30 and serum lactate. The clinical scores were classified into three groups: low, moderate, and high.

Conclusion

We suggested that the novel clinical scoring of the NIV failure in this study may use as a good predictor for NIV failure in the emergency room.