The coronavirus disease 2019 has rapidly evolved into a worldwide pandemic. Preparing intensive care units (ICU) is an integral part of any pandemic response. In this review, we discuss the key principles and strategies for ICU preparedness. We also describe our initial outbreak measures and share some of the challenges faced. To achieve sustainable ICU services, we propose the need to 1) prepare and implement rapid identification and isolation protocols, and a surge in ICU bed capacity; (2) provide a sustainable workforce with a focus on infection control; (3) ensure adequate supplies to equip ICUs and protect healthcare workers; and (4) maintain quality clinical management, as well as effective communication.

Background The ROX index (ratio of pulse oximetry/FIO2 to respiratory rate) has been validated to predict high flow nasal cannula therapy (HFNC) outcomes in patients with pneumonia. We evaluated a modified ROX index incorporating heart rate (HR) in patients initiated on HFNC for acute hypoxemic respiratory failure and as a preventative treatment following planned extubation. Methods We performed a prospective observational cohort study of 145 patients treated with HFNC. ROX-HR index was defined as the ratio of ROX index over HR (beats/min), multiplied by a factor of 100. Evaluation was performed using area under the receiving operating characteristic curve (AUROC) and cutoffs assessed for prediction of HFNC failure: defined as the need for mechanical ventilation. Results Ninety-nine (68.3%) and 46 (31.7%) patients were initiated on HFNC for acute hypoxemic respiratory failure and following a planned extubation, respectively. The majority (86.9%) of patients had pneumonia as a primary diagnosis, and 85 (56.6%) patients were immunocompromised. Sixty-one (42.1%) patients required intubation (HFNC failure). Amongst patients on HFNC for acute respiratory failure, HFNC failure was associated with a lower ROX and ROX-HR index recorded at time points between 1 and 48 h. Within the first 12 h, both indices performed with the highest AUROC at 10 h as follows: 0.723 (95% CI 0.605–0.840) and 0.739 (95% CI 0.626–0.853) for the ROX and ROX-HR index respectively. A ROX-HR index of > 6.80 was significantly associated with a lower risk of HFNC failure (hazard ratio 0.301 (95% CI 0.143–0.663)) at 10 h. This association was also observed at 2, 6, 18, and 24h, even with correction for potential confounding factors. For HFNC initiated post-extubation, only the ROX-HR index remained significantly associated with HFNC failure at all recorded time points between 1 and 24 h. A ROX-HR > 8.00 at 10 h was significantly associated with a lower risk of HFNC failure (hazard ratio 0.176 (95% CI 0.051–0.604)). Conclusion While validation studies are required, the ROX-HR index appears to be a promising tool for early identification of treatment failure in patients initiated on HFNC for acute hypoxemic respiratory failure or as a preventative treatment after a planned extubation.

BackgroundThe key aim of triage in chest pain patients is to identify those with high risk of adverse cardiac events as they require intensive monitoring and early intervention. In this study, we aim to discover the most relevant variables for risk prediction of major adverse cardiac events (MACE) using clinical signs and heart rate variability.MethodsA total of 702 chest pain patients at the Emergency Department (ED) of a tertiary hospital in Singapore were included in this study. The recruited patients were at least 30 years of age and who presented to the ED with a primary complaint of non-traumatic chest pain. The primary outcome was a composite of MACE such as death and cardiac arrest within 72 h of arrival at the ED. For each patient, eight clinical signs such as blood pressure and temperature were measured, and a 5-min ECG was recorded to derive heart rate variability parameters. A random forest-based novel method was developed to select the most relevant variables. A geometric distance-based machine learning scoring system was then implemented to derive a risk score from 0 to 100.ResultsOut of 702 patients, 29 (4.1%) met the primary outcome. We selected the 3 most relevant variables for predicting MACE, which were systolic blood pressure, the mean RR interval and the mean instantaneous heart rate. The scoring system with these 3 variables produced an area under the curve (AUC) of 0.812, and a cutoff score of 43 gave a sensitivity of 82.8% and specificity of 63.4%, while the scoring system with all the 23 variables had an AUC of 0.736, and a cutoff score of 49 gave a sensitivity of 72.4% and specificity of 63.0%. Conventional thrombolysis in myocardial infarction score and the modified early warning score achieved AUC values of 0.637 and 0.622, respectively.ConclusionsIt is observed that a few predictors outperformed the whole set of variables in predicting MACE within 72 h. We conclude that more predictors do not necessarily guarantee better prediction results. Furthermore, machine learning-based variable selection seems promising in discovering a few relevant and significant measures as predictors.

BackgroundSevere asthma is a largely heterogeneous disease with varying phenotypic profiles. The relationship between specific allergen sensitization and asthma severity, particularly in Asia, remains unclear. We aim to study the prevalence of specific allergen sensitization patterns and investigate their association with outcomes in a severe asthma cohort in an Asian setting.MethodsWe conducted a cross-sectional study of patients receiving step 4 or 5 Global Initiative for Asthma treatment. Univariate and multivariate analyses were performed to assess the association between sensitization to a specific identifiable allergen by skin prick test (SPT) and uncontrolled asthma (defined in our study as the use of ≥2 steroid bursts or hospitalization in the past year, a history of near-fatal asthma or evidence of airflow obstruction on spirometry).ResultsTwo hundred and six severe asthma patients (mean age 45±17 years, 99 [48.1%] male) were evaluated. Of them, 78.2% had a positive SPT to one or more allergens. The most common allergen to which patients were sensitized was house dust mites (Blomia tropicalis, Dermatophagoides pteronyssinus and Dermatophagoides farinae). Also, 11.7% were sensitized to Aspergillus species. On multivariate analysis, Aspergillus sensitization was associated with uncontrolled asthma (odds ratio 6.07, 95% confidence interval 1.80–20.51). In particular, Aspergillus sensitization was independently associated with the use of ≥2 steroid bursts in the past year (odds ratio 3.05, 95% confidence interval 1.04–8.95). No similar associations of uncontrolled asthma with sensitization to any other allergens were found.ConclusionHigh allergen, specifically Aspergillus sensitization was observed in the Asian population with severe asthma by SPT. Aspergillus sensitization was specifically associated with frequent exacerbations and a greater corticosteroid requirement. An improved understanding of the severe asthma with Aspergillus sensitization phenotype is warranted, which is likely a subgroup of severe asthma with fungal sensitization.

Cochlear otosclerosis is an uncommon cause of mixed and sensorineural hearing loss. This has a characteristic appearance on CT, producing a distinctive pericochlear hypodense double ring. However, its appearance on MRI is not as readily appreciated, producing a ring of intermediate signal in the pericochlear and perilabyrinthine regions on T(1) weighted images, demonstrating mild to moderate enhancement after gadolinium administration. Increased signal on T(2) weighted images may also be seen. Recognition of these MRI features is important as MRI may be the first modality of investigation, especially when patients present with symptoms indicative of sensorineural hearing loss. We review four patients who presented with sensoineural hearing loss, and who were imaged with MRI as the first line of investigation.

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