There is a paucity of data regarding initial bacterial colonization on admission to Intensive Care Units (ICUs) in low and middle-income countries (LMICs). Patients admitted to ICUs in LMICs are at high-risk of subsequent infection with antimicrobial-resistant organisms (AROs). We conducted a prospective, observational study at the Hospital for Tropical Diseases in Ho Chi Minh City, Vietnam from November 2014 to January 2016 to assess the colonization and antimicrobial susceptibility of Staphylococcus aureus, Escherichia coli, Klebsiella spp., Pseudomonas spp. and Acinetobacter spp. among adult patients within 48 hours of ICU admission. We found the admission colonization prevalence (with at least one of the identified organisms) was 93.7% (785/838) and that of AROs was 63.1% (529/838). The colonization frequency with AROs among patients admitted from the community was comparable to those transferred from other hospitals (62.2% vs 63.8%). Staphylococcus aureus was the most commonly isolated bacteria from nasal swabs (13.1%, 110/838) and the methicillin-resistant Staphylococcus aureus nasal colonization prevalence was 8.6% (72/838). We isolated Escherichia coli from rectal swabs from almost all enrolled patients (88.3%, 740/838) and 52.1% (437/838) of patients were colonized by extended spectrum β-lactamase producing Escherichia coli. Notably, Klebsiella pneumoniae was the most frequently isolated bacteria from the tracheal swabs (11.8%, 18/153). Vietnamese ICU patients have a high rate of colonization with AROs and are thus at risk of subsequent infections with these organisms if good infection control practices are not in place.

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Hand foot and mouth disease (HFMD) and tetanus are serious infectious diseases in low and middle income countries. Tetanus in particular has a high mortality rate and its treatment is resource-demanding. Furthermore, HFMD often affects a large number of infants and young children. As a result, its treatment consumes enormous healthcare resources, especially when outbreaks occur. Autonomic nervous system dysfunction (ANSD) is the main cause of death for both HFMD and tetanus patients. However, early detection of ANSD is a difficult and challenging problem. In this paper, we aim to provide a proof-of-principle to detect the ANSD level automatically by applying machine learning techniques to physiological patient data, such as electrocardiogram (ECG) and photoplethysmogram (PPG) waveforms, which can be collected using low-cost wearable sensors. Efficient features are extracted that encode variations in the waveforms in the time and frequency domains. A support vector machine is employed to classify the ANSD levels. The proposed approach is validated on multiple datasets of HFMD and tetanus patients in Vietnam. Results show that encouraging performance is achieved in classifying ANSD levels. Moreover, the proposed features are simple, more generalisable and outperformed the standard heart rate variability (HRV) analysis. The proposed approach would facilitate both the diagnosis and treatment of infectious diseases in low and middle income countries, and thereby improve overall patient care.

BackgroundIn many countries, in-hospital survival from tetanus is increasing, but long-term outcome is unknown. In high-income settings, critical illness is associated with muscle wasting and poor functional outcome, but there are few data from resource-limited settings. In this study we aimed to assess muscle wasting and long-term functional outcome in adults with tetanus.MethodsIn a prospective observational study involving 80 adults with tetanus, sequential rectus femoris ultrasound measurements were made at admission, 7 days, 14 days and hospital discharge. Functional outcome was assessed at hospital discharge using the Timed Up and Go test, Clinical Frailty Score, Barthel Index and RAND 36-item Short Form Health Survey (SF-36) and 3 and 6 months after discharge using the SF-36 and Barthel Index.ResultsSignificant muscle wasting occurred between hospital admission and discharge (p<0.01), particularly in severe disease, where a median 23.49% (interquartile range 10.01–26.07) reduction in rectus femoris cross-sectional area occurred in those with severe (Ablett grades 3 and 4) disease. Muscle mass at discharge was related to objective and subjective measures of physical and emotional function at discharge and 3 and 6 months after discharge. In patients >70 y of age, functional recovery at 6 months was reduced compared with younger patients. Hospital-acquired infection and age were risk factors for muscle wasting.ConclusionsSignificant muscle wasting during hospitalization occurred in patients with tetanus, the extent of which correlates with functional outcome.

Autonomic nervous system dysfunction (ANSD) is a significant cause of mortality in tetanus. Currently, diagnosis relies on nonspecific clinical signs. Heart rate variability (HRV) may indicate underlying autonomic nervous system activity and represents a potentially valuable noninvasive tool for ANSD diagnosis in tetanus. HRV was measured from three 5-minute electrocardiogram recordings during a 24-hour period in a cohort of patients with severe tetanus, all receiving mechanical ventilation. HRV measurements from all subjects-five with ANSD (Ablett Grade 4) and four patients without ANSD (Ablett Grade 3)-showed HRV was lower than reported ranges for healthy individuals. Comparing different severities of tetanus, raw data for both time and frequency measurements of HRV were reduced in those with ANSD compared with those without. Differences were statistically significant in all except root mean square SD, indicating HRV may be a valuable tool in ANSD diagnosis.