OBJECTIVES: To determine the HRQoL and developmental outcome of children on HMV.
METHODS: This cross-sectional study used the TNO-AZL Preschool children's Quality Of Life (TAPQOL; <5 years old) and Health Utilities Index (HUI) 2/3 (≥5 years old) to assess the quality of life and the Schedule of Growing Skills-II to assess development. Instruments were used on children currently or previously on HMV (≥3 months) and compared with age and sex-matched controls.
RESULTS: Sixty-five patients and 130 controls were recruited. Patients' median (interquartile range) age was 3.12 (1.65, 5.81) years. Patients had significantly lower TAPQOL scores in the domains of lung, liveliness, positive mood, social functioning, motor functioning, and communication, and lower HUI 2/3 scores in hearing, sensation, pain, speech, mobility, ambulatory, dexterity, and self-care domains. The developmental outcome of patients was poorer in all domains. However, patients had fewer behavioral problems. Those with respiratory tract disease and without comorbidities had better HRQoL and developmental scores. Having a parent as the primary caregiver was associated with better speech and language skills.
CONCLUSIONS: HRQoL and the developmental outcome are lower in children on HMV compared to controls. Children with respiratory tract disease and without comorbidities have a better outcome. Parents play a crucial role in the acquisition of speech.
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: This study presents an approach using a 1-dimensional (1D) of airway pressure data as an input to the convolutional long short-term memory neural network (CNN-LSTM) with a classifier method to classify AB types into three categories: 1) reverse Triggering (RT); 2) premature cycling (PC); and 3) normal breathing (NB), which cover normal breathing and 2 primary forms of AB. Three types of classifier are integrated with the CNN-LSTM model which are random forest (RF), support vector machine (SVM) and logistic regression (LR). Clinical data inputs include measured airway pressure from 7 MV patients in IIUM Hospital ICU under informed consent with a total of 4500 breaths. Model performance is first assessed in a k-fold cross-validation assessing accuracy in comparison to the proposed CNN-LSTM integrated with each type of classifier. Then, confusion matrices are used to summarize classification performance for the CNN without classifier, CNN-LSTM without classifier, and CNN-LSTM with each of the 3 classifiers (RF, SVM, LR).
RESULTS AND DISCUSSION: The 1D CNN-LSTM with classifier method achieves 100 % accuracy using 5-fold cross validation. The confusion matrix results showed that the combined CNN-LSTM model with classifier performed better, demostrating higher accuracy, sensitivity, specificity, and F1 score, all exceeding 83.5 % across all three breathing categories. The CNN model without classifier and CNN-LSTM model without classifier displayed comparatively lower performance, with average values of F1 score below 71.8 % for all three breathing categories.
CONCLUSION: The results validate the effectiveness of the CNN-LSTM neural network model with classifier in accurately detecting and classifying the different categories of AB and NB. Overall, this model-based approach has the potential to precisely classify the type of AB and differentiate normal breathing. With this developed model, a better MV management can be provided at the bedside, and these results justify prospective clinical testing.
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: Databases of MEDLINE, EMBASE and CENTRAL were systematically searched from inception until March 2021. Case reports and case series were excluded.
RESULTS: Eleven studies (n = 606 patients) were eligible. Prone ventilation significantly improved PaO2/FiO2 ratio (studies: 8, n = 579, mean difference 46.75, 95% CI 33.35‒60.15, p < 0.00001; evidence: very low) and peripheral oxygen saturation (SpO2) (studies: 3, n = 432, mean difference 1.67, 95% CI 1.08‒2.26, p < 0.00001; evidence: ow), but not the arterial partial pressure of carbon dioxide (PaCO2) (studies: 5, n = 396, mean difference 2.45, 95% CI 2.39‒7.30, p = 0.32; evidence: very low), mortality rate (studies: 1, n = 215, Odds Ratio 0.66, 95% CI 0.32‒1.33, p = 0.24; evidence: very low), or number of patients discharged alive (studies: 1, n = 43, Odds Ratio 1.49, 95% CI 0.72‒3.08, p = 0.28; evidence: very low).
CONCLUSION: Prone ventilation improved PaO2/FiO2 ratio and SpO2 in intubated COVID-19 patients. Given the substantial heterogeneity and low level of evidence, more randomized- controlled trials are warranted to improve the certainty of evidence, and to examine the adverse events of prone ventilation.
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.
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.
DESIGN: Harmonized data from prospective multicenter international longitudinal cohort studies SETTING:: Diverse mix of ICUs.
PATIENTS: Critically ill patients expected to be ventilated for longer than 24 hours.
INTERVENTIONS: Richmond Agitation Sedation Scale and pain were assessed every 4 hours. Delirium and mobilization were assessed daily using the Confusion Assessment Method of ICU and a standardized mobility assessment, respectively.
MEASUREMENTS AND MAIN RESULTS: Sedation intensity was assessed using a Sedation Index, calculated as the sum of negative Richmond Agitation Sedation Scale measurements divided by the total number of assessments. We used multivariable Cox proportional hazard models to adjust for relevant covariates. We performed subgroup and sensitivity analysis accounting for immortal time bias using the same variables within 120 and 168 hours. The main outcome was 180-day survival. We assessed 703 patients in 42 ICUs with a mean (SD) Acute Physiology and Chronic Health Evaluation II score of 22.2 (8.5) with 180-day mortality of 32.3% (227). The median (interquartile range) ventilation time was 4.54 days (2.47-8.43 d). Delirium occurred in 273 (38.8%) of patients. Sedation intensity, in an escalating dose-dependent relationship, independently predicted increased risk of death (hazard ratio [95% CI], 1.29 [1.15-1.46]; p < 0.001, delirium hazard ratio [95% CI], 1.25 [1.10-1.43]), p value equals to 0.001 and reduced chance of early extubation hazard ratio (95% CI) 0.80 (0.73-0.87), p value of less than 0.001. Agitation level independently predicted subsequent delirium hazard ratio [95% CI], of 1.25 (1.04-1.49), p value equals to 0.02. Delirium or mobilization episodes within 168 hours, adjusted for sedation intensity, were not associated with survival.
CONCLUSIONS: Sedation intensity independently, in an ascending relationship, predicted increased risk of death, delirium, and delayed time to extubation. These observations suggest that keeping sedation level equivalent to a Richmond Agitation Sedation Scale 0 is a clinically desirable goal.