OBJECTIVES: To validate the HACOR scale in predicting NIV failure among acute cardiogenic pulmonary oedema (ACPO) patients.
DESIGN, SETTINGS AND PARTICIPANTS: This is a prospective, observational study of consecutive ACPO patients requiring NIV admitted to the ED.
OUTCOME MEASURE AND ANALYSIS: Primary outcome was the ability of the HACOR score to predict NIV failure. Clinical, physiological, and HACOR score at baseline and at 1 h, 12 h and 24 h were analysed. Other potential predictors were assessed as secondary outcomes.
MAIN RESULTS: A total of 221 patients were included in the analysis. Fifty-four (24.4%) had NIV failure. Optimal HACOR score was >5 at 1 h after NIV initiation in predicting NIV failure (AUC 0.73, sensitivity 53.7%, specificity 83.2%). As part of the HACOR score, respiratory rate and heart rate were not found to be significant predictors. Other significant predictors of NIV failure in ACPO patients were acute coronary syndrome, acute kidney injury, presence of congestive heart failure as a comorbid, and the ROX index.
CONCLUSIONS: The HACOR scale measured at 1 h after NIV initiation predicts NIV failure among ACPO patients with acceptable accuracy. The cut-off level > 5 could be a useful clinical decision support tool in ACPO patient. However, clinicians should consider other factors such as the acute coronary and acute kidney diagnosis at presentation, presence of underlying congestive heart failure and the ROX index when clinically deciding on timely invasive mechanical ventilation.
MATERIALS AND METHODS: In this multicenter cross-sectional study, data on mechanical ventilation and clinical outcomes were collected. Predictors of mortality were analyzed by univariate and multivariable logistic regression. A scoring system was generated to predict 28-day mortality.
RESULTS: A total of 1408 patients were enrolled. In 138 patients with acute respiratory distress syndrome (ARDS), 65.9% were on a tidal volume ≤ 8 ml/kg predicted body weight (PBW), and 71.3% were on sufficient PEEP. In 1270 patients without ARDS, 88.8% were on a tidal volume ≤ 10 ml/kg PBW. A plateau pressure
METHODS: We recruited patients with CRDs from two hospitals in Klang Valley, Malaysia to a home-PR programme. Following centre-based assessment, patients performed the exercises at home (five sessions/week for eight weeks (total 40 sessions)). We monitored the patients via weekly telephone calls and asked about adherence to the programme. We measured functional exercise capacity (6-Minutes Walking Test (6MWT) and Health-Related Quality-of-Life (HRQoL) (COPD Assessment Test (CAT)) at baseline and post-PR at nine weeks. We conducted semi-structured interviews with 12 purposively sampled participants to explore views and feedback on the home-PR programme. The interviews were audio recorded, transcribed verbatim, and analysed thematically.
RESULTS: We included 30 participants; two withdrew due to hospitalisation. Although 28 (93%) adhered to the full programme, only 11 (37%) attended the post-PR assessment because COVID-19 movement restrictions in Malaysia at that time prevented attendance at the centre. Four themes emerged from the qualitative analysis: involvement of family and caregivers, barriers to home-PR programme, interactions with peers and health care professionals, and programme enhancement.
CONCLUSION: Despite the COVID-19 pandemic, the home-PR programme proved feasible for remote delivery, although centre-based post-PR assessments were not possible. Family involvement played an important role in the home-PR programme. The delivery of this programme can be further improved to maximise the benefit for patients.
OBJECTIVES: 1. To assess the effects of CPAP on AoP in preterm infants (this may be compared to supportive care or mechanical ventilation). 2. To assess the effects of different CPAP delivery systems on AoP in preterm infants.
SEARCH METHODS: Searches were conducted in September 2022 in the following databases: Cochrane Library, MEDLINE, Embase, and CINAHL. We also searched clinical trial registries and the reference lists of studies selected for inclusion.
SELECTION CRITERIA: We included all randomised and quasi-randomised controlled trials (RCTs) in which researchers determined that CPAP was necessary for AoP in preterm infants (born before 37 weeks). Cross-over studies were also included, provided sufficient data were available for analysis.
DATA COLLECTION AND ANALYSIS: We used the standard methods of Cochrane and Cochrane Neonatal, including independent assessment of risk of bias and extraction of data by at least two review authors. Discrepancies were resolved by involvement of a third author. We used the GRADE approach to assess the certainty of evidence for the following outcomes: 1) failed CPAP; 2) apnoea; 3) adverse effects of CPAP.
MAIN RESULTS: We included four single-centre trials conducted in Malaysia, Spain, Germany, and North America, involving 138 infants with a mean/median gestation of 26 to 28 weeks. Two studies were parallel-group RCTs and two were cross-over trials. None of the studies compared CPAP with supportive care. All trials compared one form of CPAP with another. Two compared a variable flow device with ventilator CPAP, one compared two different variable flow devices, and one compared a variable flow device with bubble CPAP. Interventions were administered for periods ranging between six and 48 hours, with pressures between 4 and 6 cm H2O. We assessed all trials as having a high risk of bias for blinding of participants and personnel, and two studies for blinding of outcome assessors. We found a high risk of a carry-over effect in two studies where the washout period was not adequately described, and a high risk of bias in a study that appeared to use an analysis method not generally accepted for cross-over studies. Comparison 1. CPAP and supportive care compared to supportive care alone We did not identify any study for inclusion in this comparison. Comparison 2. CPAP delivered by different types of devices 2a. Variable flow compared to ventilator CPAP Two studies were included in this comparison. We are very uncertain whether there is any difference in the incidence of failed CPAP, defined as the need for mechanical ventilation (risk ratio (RR) 0.16, 95% confidence interval (CI) 0.01 to 2.90; 1 study, 26 participants; very low-certainty). We are very uncertain whether there is any difference in the frequency of apnoea events (mean difference (MD) per four-hour interval -0.10, 95% CI -1.30 to 1.10; 1 study, 26 participants; very low-certainty). We are uncertain whether there is any difference in adverse events. Neurodevelopmental outcomes were not reported. 2b. Variable flow compared to bubble CPAP We included one study in this comparison, but it did not report our pre-specified outcomes. 2c. Infant Flow variable flow CPAP compared to Medijet variable flow CPAP We are very uncertain whether there is any difference in the incidence of failed CPAP (RR 2.62, 95% CI 0.91 to 7.53; 1 study, 80 participants; very low-certainty). The frequency of apnoea was not reported, and we do not know whether there is any difference in adverse events. Neurodevelopmental outcomes were not reported. Comparison 3. CPAP compared to mechanical ventilation We did not identify any studies for inclusion in this comparison.
AUTHORS' CONCLUSIONS: Due to the limited available evidence, we are very uncertain whether any CPAP device is more effective than other forms of supportive care, other CPAP devices, or mechanical ventilation for the prevention and treatment of AoP. The devices used in these studies included two types of variable flow CPAP device: bubble CPAP and ventilator CPAP. For each comparison, data were only available from a single study. There are theoretical reasons why these devices might have different effects on AoP, therefore further trials are indicated.
METHODS: The present study was a descriptive-analytical study in which the records of 1361 patients who underwent cardiovascular surgery and were on a mechanical ventilator during 2019-2020 at the Imam Ali Heart Center in Kermanshah city were examined. The data collection tool was a three-part researcher-made questionnaire including demographic characteristics, health records, and clinical variables. Data analysis was done using descriptive and inferential statistical tests and SPSS Version 25 software.
RESULTS: In this study, of the 1361 patients, 953 (70%) were male. The results indicated that 78.6% of patients had short-term mechanical ventilation, and 21.4% had long-term mechanical ventilation. There was a statistically significant relationship between the history of smoking, drug use, and baking bread with the type of mechanical ventilation (P
METHODS: This international, investigator-initiated, pragmatic, registry-based, single-blinded, randomised trial was undertaken in 85 intensive care units (ICUs) across 16 countries. We enrolled nutritionally high-risk adults (≥18 years) undergoing mechanical ventilation to compare prescribing high-dose protein (≥2·2 g/kg per day) with usual dose protein (≤1·2 g/kg per day) started within 96 h of ICU admission and continued for up to 28 days or death or transition to oral feeding. Participants were randomly allocated (1:1) to high-dose protein or usual dose protein, stratified by site. As site personnel were involved in both prescribing and delivering protein dose, it was not possible to blind clinicians, but patients were not made aware of the treatment assignment. The primary efficacy outcome was time-to-discharge-alive from hospital up to 60 days after ICU admission and the secondary outcome was 60-day morality. Patients were analysed in the group to which they were randomly assigned regardless of study compliance, although patients who dropped out of the study before receiving the study intervention were excluded. This study is registered with ClinicalTrials.gov, NCT03160547.
FINDINGS: Between Jan 17, 2018, and Dec 3, 2021, 1329 patients were randomised and 1301 (97·9%) were included in the analysis (645 in the high-dose protein group and 656 in usual dose group). By 60 days after randomisation, the cumulative incidence of alive hospital discharge was 46·1% (95 CI 42·0%-50·1%) in the high-dose compared with 50·2% (46·0%-54·3%) in the usual dose protein group (hazard ratio 0·91, 95% CI 0·77-1·07; p=0·27). The 60-day mortality rate was 34·6% (222 of 642) in the high dose protein group compared with 32·1% (208 of 648) in the usual dose protein group (relative risk 1·08, 95% CI 0·92-1·26). There appeared to be a subgroup effect with higher protein provision being particularly harmful in patients with acute kidney injury and higher organ failure scores at baseline.
INTERPRETATION: Delivery of higher doses of protein to mechanically ventilated critically ill patients did not improve the time-to-discharge-alive from hospital and might have worsened outcomes for patients with acute kidney injury and high organ failure scores.
FUNDING: None.
MATERIALS AND METHODS: This study is a novel retrospective study in a tertiary centre in Malaysia. Case notes of COVID- 19 patients who underwent tracheostomy in Hospital Ampang were collected using the electronic Hospital Information System. Data were analysed using the SPSS system.
RESULTS: From a total of 30 patients, 15 patients survived. All patients underwent either open or percutaneous tracheostomy. The median age is 53 (range: 28-69) with a significant p-value of 0.02. Amongst comorbidities, it was noted that diabetes mellitus was significant with a p-value of 0.014. The median time from the onset of COVID-19 to tracheostomy is 30 days. The median duration of intensive care unit (ICU) stay is 30.5 days, with the median duration of hospital length of stay of 44 days (p = 0.009 and <0.001, respectively). No complications that contributed to patient death were found. Survivors had a median of 29.5 days from tracheostomy to oxygen liberation.
CONCLUSION: Tracheostomy in COVID-19 patients that requires prolonged ventilation is unavoidable. It is a safe procedure and mortality is not related to the procedure. Mortality is primarily associated with COVID-19.
METHODS: A retrospective, observational study was performed among infants aged 6 months and below hospitalized for COVID-19 in a tertiary state hospital in Malaysia between February 1 and April 30, 2022. The primary outcome was "serious disease," defined as pneumonia requiring respiratory support or dehydration with warning signs. Multivariate logistic regression was used to determine independent predictors for serious disease.
RESULTS: A total of 102 infants were included in the study; 53.9% were males with a median age of 11 weeks (interquartile range: 5-20 weeks). Sixteen patients (15.7%) had pre-existing comorbidities, including preterm birth. Fever was the most common presenting symptom (82.4%), followed by cough (53.9%), and rhinorrhea (31.4%). Forty-one infants (40.2%) presented with serious disease, warranting either respiratory support or intravenous fluid therapy for dehydration. Recent maternal COVID-19 vaccination was associated with a reduced risk of serious disease on univariate analysis but was not significant after multivariate adjustment (adjusted odds ratio [aOR] 0.39; 95% CI: 0.14-1.11; p = 0.08). Exclusive breastfeeding was protective against serious COVID-19 in young infants, independent of other confounding factors (aOR 0.21, 95% CI: 0.06-0.71; p = 0.01).
CONCLUSION: COVID-19 is a serious disease with non-specific clinical manifestations in young infants. Exclusive breastfeeding could play an important protective role.
METHODS: This is a systematic review and a meta-analysis evaluating the evidence from clinical trials on the effect of colchicine and corticosteroids against COVID-19. In this review, we have systematically searched five databases [(PubMed, Embase, clinicaltrials.gov, ICTRP, CINAHL (EBSCO)]. Cochrane's data extraction sheet was used to collect the required information, and RevMan-5.4.1 was used to conduct the meta-analysis and to assess the risk of bias. The review was registered in Prospero (CRD42022299718).
RESULTS: The total number of included studies was 17, with 18,956 participants; the majority were male 12,001. Out of which, 8772 participants were on colchicine, 569 took methylprednisolone, and 64 patients received prednisolone. The meta-analysis has shown that colchicine had no significant effect on reducing the mortality rate among COVID-19 patients [OR 0.98(95% CI 0.90-1.08), p = .70), I2:1%)], corticosteroids have significantly reduced the mortality rates [OR 0.55 (95% CI 0.33-0.91), p = .02, I2:40]. Colchicine did not reduce the incidence of ICU admissions [OR 0.74 (95% CI 0.39-1.40), p = .35, I2:0%], while steroidal drugs significantly reduced the ICU admissions [OR 0.42 (95% CI 0.23-0.78), p = .005, I2:0%]. Unlike steroidal drugs [OR 0.53 (95% CI 0.30-0.95), p = .03, I2:61%], colchicine failed to reduce the need for mechanical ventilation [OR 0.73 (95% CI 0.48-1.10), p = .13, I2:76%]. Steroidal drugs significantly reduced the duration of hospitalization among COVID-19 patients [OR -0.50 (95% CI -0.79-0.21), p = .0007, I2:36%].
CONCLUSIONS: The use of colchicine did not significantly reduce the mortality rate, ICU admissions, and mechanical ventilation among COVID-19 patients. Conversely, corticosteroids significantly reduced the mortality rate, ICU admissions, mechanical ventilation, and hospitalization duration among COVID-19 patients.
DESIGN: Systematic review and meta-analysis.
SETTING: Electronic search for randomized controlled trials and observational studies (MEDLINE, EMBASE, CENTRAL).
PARTICIPANTS: Hospitalized adults ≥ 18 years old who were SARS-CoV-2 PCR positive.
INTERVENTIONS: High-dose and low-dose corticosteroids.
MEASUREMENTS AND MAIN RESULTS: A total of twelve studies (n=2759 patients) were included in this review. The pooled analysis demonstrated no significant difference in mortality rate between the high-dose and low-dose corticosteroids groups (n=2632; OR: 1.07 [95%CI 0.67, 1.72], p=0.77, I2=76%, trial sequential analysis=inconclusive). No significant differences were observed in the incidence of intensive care unit (ICU) admission rate (n=1544; OR: 0.77[95%CI 0.43, 1.37], p=0.37, I2= 72%), duration of hospital stay (n=1615; MD: 0.53[95%CI -1.36, 2.41], p=0.58, I2=87%), respiratory support (n=1694; OR: 1.51[95%CI 0.77, 2.96], p=0.23, I2=84%), duration of mechanical ventilation (n=419; MD: -1.44[95%CI -4.27, 1.40], p=0.32, I2=93%), incidence of hyperglycemia (n=516, OR: 0.91[95%CI 0.58, 1.43], p=0.68, I2=0%) and infection rate (n=1485, OR: 0.86[95%CI 0.64, 1.16], p=0.33, I2=29%).
CONCLUSION: The meta-analysis demonstrated high-dose corticosteroids did not reduce mortality rate. However, high-dose corticosteroids did not pose higher risk of hyperglycemia and infection rate for COVID-19 patients. Due to the inconclusive trial sequential analysis, substantial heterogeneity and low level of evidence, future large-scale randomized clinical trials are warranted to improve the certainty of evidence for the use of high-dose compared to low-dose corticosteroids in COVID-19 patients.
METHODS: Non-linear autoregressive (NARX) model is used to reconstruct missing airway pressure due to the presence of spontaneous breathing effort in mv patients. Then, the incidence of SB patients is estimated. The study uses a total of 10,000 breathing cycles collected from 10 ARDS patients from IIUM Hospital in Kuantan, Malaysia. In this study, there are 2 different ratios of training and validating methods. Firstly, the initial ratio used is 60:40 which indicates 600 breath cycles for training and remaining 400 breath cycles used for testing. Then, the ratio is varied using 70:30 ratio for training and testing data.
RESULTS AND DISCUSSION: The mean residual error between original airway pressure and reconstructed airway pressure is denoted as the magnitude of effort. The median and interquartile range of mean residual error for both ratio are 0.0557 [0.0230 - 0.0874] and 0.0534 [0.0219 - 0.0870] respectively for all patients. The results also show that Patient 2 has the highest percentage of SB incidence and Patient 10 with the lowest percentage of SB incidence which proved that NARX model is able to perform for both higher incidence of SB effort or when there is a lack of SB effort.
CONCLUSION: This model is able to produce the SB incidence rate based on 10% threshold. Hence, the proposed NARX model is potentially useful to estimate and identify patient-specific SB effort, which has the potential to further assist clinical decisions and optimize MV settings.
METHOD: The CAE model was trained using 12,170,655 simulated SB flow and normal flow data (NB). The paired SB and NB flow data were simulated using a Gaussian Effort Model (GEM) with 5 basis functions. When the CAE model is given a SB flow input, it is capable of predicting a corresponding NB flow for the SB flow input. The magnitude of SB effort (SBEMag) is then quantified as the difference between the SB and NB flows. The CAE model was used to evaluate the SBEMag of 9 pressure control/ support datasets. Results were validated using a mean squared error (MSE) fitting between clinical and training SB flows.
RESULTS: The CAE model was able to produce NB flows from the clinical SB flows with the median SBEMag of the 9 datasets being 25.39% [IQR: 21.87-25.57%]. The absolute error in SBEMag using MSE validation yields a median of 4.77% [IQR: 3.77-8.56%] amongst the cohort. This shows the ability of the GEM to capture the intrinsic details present in SB flow waveforms. Analysis also shows both intra-patient and inter-patient variability in SBEMag.
CONCLUSION: A Convolutional Autoencoder model was developed with simulated SB and NB flow data and is capable of quantifying the magnitude of patient spontaneous breathing effort. This provides potential application for real-time monitoring of patient respiratory drive for better management of patient-ventilator interaction.
METHODS: This is a retrospective review of all mechanically ventilated surgical patients in the wards, in a tertiary hospital, in 2020. Sixty-two patients out of 116 patients ventilated in surgical wards fulfilled the inclusion criteria. Demography, surgical diagnosis and procedures and physiologic, biochemical and survival data were analyzed to explore the outcomes and predictors of mortality.
RESULTS: Twenty-two out of 62 patients eventually gained ICU admission. Mean time from intubation to ICU entry and mean length of ICU stay were 48 h (0 to 312) and 10 days (1 to 33), respectively. Survival for patients admitted to ICU compared to ventilation in the acute surgery wards was 54.5% (12/22) vs 17.5% (7/40). Thirty-four patients underwent surgery, and the majority were bowel-related emergency operations. SAPS2 score validation revealed AUC of 0.701. More than half of patients with mortality risk
METHODS: A stochastic model of Ers is integrated into the VENT protocol from previous works to develop the SiVENT protocol, to account for both intra- and inter-patient variability. A cohort of 20 virtual MV patients based on retrospective patient data are used to validate the performance of this method for volume-controlled (VC) ventilation. A performance evaluation was conducted where the SiVENT and VENT protocols were implemented in 1080 instances each to compare the two protocols and evaluate the difference in reduction of possible MV settings achieved by each.
RESULTS: From an initial number of 189,000 possible MV setting combinations, the VENT protocol reduced this number to a median of 10,612, achieving a reduction of 94.4% across the cohort. With the integration of the stochastic model component, the SiVENT protocol reduced this number from 189,000 to a median of 9329, achieving a reduction of 95.1% across the cohort. The SiVENT protocol reduces the number of possible combinations provided to the user by more than 1000 combinations as compared to the VENT protocol.
CONCLUSIONS: Adding a stochastic model component into a model-based approach to selecting MV settings improves the ability of a decision support system to recommend patient-specific MV settings. It specifically considers inter- and intra-patient variability in respiratory elastance and eliminates potentially harmful settings based on clinically recommended pressure thresholds. Clinical input and local protocols can further reduce the number of safe setting combinations. The results for the SiVENT protocol justify further investigation of its prediction accuracy and clinical validation trials.
METHODS: The model-based method uses a single-compartment lung model (SCM) to simulate the resultant tidal volume of patient pairs at a set ventilation setting. If both patients meet specified safe ventilation criteria under similar ventilation settings, the actual mechanical ventilator settings for Co-MV are determined via simulation using a double-compartment lung model (DCM). This method allows clinicians to analyse Co-MV in silico, before clinical implementation.
RESULTS: The proposed method demonstrates successful patient matching and MV setting in a model-based simulation as well as good discrimination to avoid mismatched patient pairs. The pairing process is based on model-based, patient-specific respiratory mechanics identified from measured data to provide useful information for guiding care. Specifically, the matching is performed via estimation of MV delivered tidal volume (mL/kg) based on patient-specific respiratory mechanics. This information can provide insights for the clinicians to evaluate the subsequent effects of Co-MV. In addition, it was also found that Co-MV patients with highly restrictive respiratory mechanics and obese patients must be performed with extra care.
CONCLUSION: This approach allows clinicians to analyse patient matching in a virtual environment without patient risk. The approach is tested in simulation, but the results justify the necessary clinical validation in human trials.