To identify urinary catheter (UC)–associated urinary tract infection (CAUTI) incidence and risk factors.

A prospective cohort study.

The study was conducted across 623 ICUs of 224 hospitals in 114 cities in 37 African, Asian, Eastern European, Latin American, and Middle Eastern countries.

The study included 169,036 patients, hospitalized for 1,166,593 patient days.

Data collection took place from January 1, 2014, to February 12, 2022. We identified CAUTI rates per 1,000 UC days and UC device utilization (DU) ratios stratified by country, by ICU type, by facility ownership type, by World Bank country classification by income level, and by UC type. To estimate CAUTI risk factors, we analyzed 11 variables using multiple logistic regression.

Participant patients acquired 2,010 CAUTIs. The pooled CAUTI rate was 2.83 per 1,000 UC days. The highest CAUTI rate was associated with the use of suprapubic catheters (3.93 CAUTIs per 1,000 UC days); with patients hospitalized in Eastern Europe (14.03) and in Asia (6.28); with patients hospitalized in trauma (7.97), neurologic (6.28), and neurosurgical ICUs (4.95); with patients hospitalized in lower–middle-income countries (3.05); and with patients in public hospitals (5.89).

The following variables were independently associated with CAUTI: Age (adjusted odds ratio [aOR], 1.01; P < .0001), female sex (aOR, 1.39; P < .0001), length of stay (LOS) before CAUTI-acquisition (aOR, 1.05; P < .0001), UC DU ratio (aOR, 1.09; P < .0001), public facilities (aOR, 2.24; P < .0001), and neurologic ICUs (aOR, 11.49; P < .0001).

CAUTI rates are higher in patients with suprapubic catheters, in middle-income countries, in public hospitals, in trauma and neurologic ICUs, and in Eastern European and Asian facilities.

Based on findings regarding risk factors for CAUTI, focus on reducing LOS and UC utilization is warranted, as well as implementing evidence-based CAUTI-prevention recommendations.

Rates of ventilator-associated pneumonia (VAP) in low- and middle-income countries (LMIC) are several times above those of high-income countries. The objective of this study was to identify risk factors (RFs) for VAP cases in ICUs of LMICs.

Prospective cohort study.

This study was conducted across 743 ICUs of 282 hospitals in 144 cities in 42 Asian, African, European, Latin American, and Middle Eastern countries.

The study included patients admitted to ICUs across 24 years.

In total, 289,643 patients were followed during 1,951,405 patient days and acquired 8,236 VAPs. We analyzed 10 independent variables. Multiple logistic regression identified the following independent VAP RFs: male sex (adjusted odds ratio [aOR], 1.22; 95% confidence interval [CI], 1.16–1.28; P < .0001); longer length of stay (LOS), which increased the risk 7% per day (aOR, 1.07; 95% CI, 1.07–1.08; P < .0001); mechanical ventilation (MV) utilization ratio (aOR, 1.27; 95% CI, 1.23–1.31; P < .0001); continuous positive airway pressure (CPAP), which was associated with the highest risk (aOR, 13.38; 95% CI, 11.57–15.48; P < .0001); tracheostomy connected to a MV, which was associated with the next-highest risk (aOR, 8.31; 95% CI, 7.21–9.58; P < .0001); endotracheal tube connected to a MV (aOR, 6.76; 95% CI, 6.34–7.21; P < .0001); surgical hospitalization (aOR, 1.23; 95% CI, 1.17–1.29; P < .0001); admission to a public hospital (aOR, 1.59; 95% CI, 1.35-1.86; P < .0001); middle-income country (aOR, 1.22; 95% CI, 15–1.29; P < .0001); admission to an adult-oncology ICU, which was associated with the highest risk (aOR, 4.05; 95% CI, 3.22–5.09; P < .0001), admission to a neurologic ICU, which was associated with the next-highest risk (aOR, 2.48; 95% CI, 1.78–3.45; P < .0001); and admission to a respiratory ICU (aOR, 2.35; 95% CI, 1.79–3.07; P < .0001). Admission to a coronary ICU showed the lowest risk (aOR, 0.63; 95% CI, 0.51–0.77; P < .0001).

Some identified VAP RFs are unlikely to change: sex, hospitalization type, ICU type, facility ownership, and country income level. Based on our results, we recommend focusing on strategies to reduce LOS, to reduce the MV utilization ratio, to limit CPAP use and implementing a set of evidence-based VAP prevention recommendations.

To identify risk factors for mortality in intensive care units (ICUs) in Asia.

Prospective cohort study.

The study included 317 ICUs of 96 hospitals in 44 cities in 9 countries of Asia: China, India, Malaysia, Mongolia, Nepal, Pakistan, Philippines, Sri Lanka, Thailand, and Vietnam.

Patients aged >18 years admitted to ICUs.

In total, 157,667 patients were followed during 957,517 patient days, and 8,157 HAIs occurred. In multiple logistic regression, the following variables were associated with an increased mortality risk: central-line–associated bloodstream infection (CLABSI; aOR, 2.36; P < .0001), ventilator-associated event (VAE; aOR, 1.51; P < .0001), catheter-associated urinary tract infection (CAUTI; aOR, 1.04; P < .0001), and female sex (aOR, 1.06; P < .0001). Older age increased mortality risk by 1% per year (aOR, 1.01; P < .0001). Length of stay (LOS) increased mortality risk by 1% per bed day (aOR, 1.01; P < .0001). Central-line days increased mortality risk by 2% per central-line day (aOR, 1.02; P < .0001). Urinary catheter days increased mortality risk by 4% per urinary catheter day (aOR, 1.04; P < .0001). The highest mortality risks were associated with mechanical ventilation utilization ratio (aOR, 12.48; P < .0001), upper middle-income country (aOR, 1.09; P = .033), surgical hospitalization (aOR, 2.17; P < .0001), pediatric oncology ICU (aOR, 9.90; P < .0001), and adult oncology ICU (aOR, 4.52; P < .0001). Patients at university hospitals had the lowest mortality risk (aOR, 0.61; P < .0001).

Some variables associated with an increased mortality risk are unlikely to change, such as age, sex, national economy, hospitalization type, and ICU type. Some other variables can be modified, such as LOS, central-line use, urinary catheter use, and mechanical ventilation as well as and acquisition of CLABSI, VAE, or CAUTI. To reduce mortality risk, we shall focus on strategies to reduce LOS; strategies to reduce central-line, urinary catheter, and mechanical ventilation use; and HAI prevention recommendations.

Literature investigating the change in psychological problems of the health care workers (HCWs) throughout the coronavirus disease (COVID-19) pandemic is lacking. We aimed at comparing the psychological problems and attitudes toward work among HCWs over two waves of the COVID-19 pandemic in India.

A survey was conducted involving HCWs (n = 305, first wave, 2020; n = 325, second wave, 2021). Participants’ demographic and professional and psychological characteristics (using attitude toward COVID-19 questionnaire [ATCQ]; Depression, Anxiety, and Stress Scale – 21 Items and impact of event scale – 22) were recorded. The unpaired t-test/chi-squared test was used for comparison.

Significant improvements (χ2(1) = 7.3 to 45.6, P < 0.05) in level of depression (42.2% vs 9.6%), anxiety (41.3% vs 16.3%), stress (30.1% vs 6.7%), event-related stress symptoms (31.2% vs 27%), work-related stress (89.8% vs 76.8%), and stigma (25.9% vs 22.8, though marginally significant) were found among the participants of the second wave (vs first wave). However, on subgroup analysis, allied-HCWs (housekeeping staff and security personnel) reported lesser concerns over the domains of the ATCQ vis-a-viz frontline-HCWs (doctors and nurses).

This improvement could be attributed to greater awareness about the illness, better coping skills, vaccination, and so forth; however, more research is warranted to investigate these determinants.

Despite significant advancements in healthcare technology, digital health solutions – especially those for serious mental illnesses – continue to fall short of their potential across both clinical practice and efficacy. The utility and impact of medicine, including digital medicine, hinges on relationships, trust, and engagement, particularly in the field of mental health. This paper details results from Phase 1 of a two-part study that seeks to engage people with schizophrenia, their family members, and clinicians in co-designing a digital mental health platform for use across different cultures and contexts in the United States and India.

Each site interviewed a mix of clinicians, patients, and their family members in focus groups (n = 20) of two to six participants. Open-ended questions and discussions inquired about their own smartphone use and, after a demonstration of the mindLAMP platform, specific feedback on the app's utility, design, and functionality.

Our results based on thematic analysis indicate three common themes: increased use and interest in technology during coronavirus disease 2019 (COVID-19), concerns over how data are used and shared, and a desire for concurrent human interaction to support app engagement.

People with schizophrenia, their family members, and clinicians are open to integrating technology into treatment to better understand their condition and help inform treatment. However, app engagement is dependent on technology that is complementary – not substitutive – of therapeutic care from a clinician.