AI and ICU Monitoring on the Wake of the COVID-19 Pandemic

The Intensive Care Unit (ICU) is a paradigmatic example of the potential reach of data-centred knowledge discovery. This is because the contemporary ICU heavily depends on medical devices for patient monitoring through electronic data acquisition. This poses a unique opportunity for multivariate data analysis to support evidence-based medicine (EBM), particularly in the form of Artificial Intelligence (AI) approaches. The COVID-19 pandemic has tested the limits of critical care management, often overwhelming ICUs. In this brief chapter, we sketch the role of AI, especially in the form of Machine Learning (ML), at the ICU and discuss what can it offer to address COVID-19 disruption in this environment. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Invasive aspergillosis in patients with COVID-19 in intensive care units: results of a multicenter study.

Objective. To study risk factors, clinical and radiological features and effectiveness of the treatment of invasive aspergillosis (IA) in adult patients with COVID-19 (COVID-IA) in intensive care units (ICU). Materials and methods. A total of 60 patients with COVID-IA treated in ICU (median age 62 years, male - 58%) were included in this multicenter prospective study. The comparison group included 34 patients with COVID-IA outside the ICU (median age 62 years, male - 68%). ECMM/ISHAM 2020 criteria were used for diagnosis of CAPA, and EORTC/MSGERC 2020 criteria were used for evaluation of the treatment efficacy. A case-control study (one patient of the main group per two patients of the control group) was conducted to study risk factors for the development and features of CAPA. The control group included 120 adult COVID-19 patients without IA in the ICU, similar in demographic characteristics and background conditions. The median age of patients in the control group was 63 years, male - 67%. Results. 64% of patients with COVID-IA stayed in the ICU. Risk factors for the COVID-IA development in the ICU: chronic obstructive pulmonary disease (OR = 3.538 [1.104-11.337], p = 0.02), and prolonged (> 10 days) lymphopenia (OR = 8.770 [4.177-18.415], p = 0.00001). The main location of COVID-IA in the ICU was lungs (98%). Typical clinical signs were fever (97%), cough (92%), severe respiratory failure (72%), ARDS (64%) and haemoptysis (23%). Typical CT features were areas of consolidation (97%), hydrothorax (63%), and foci of destruction (53%). The effective methods of laboratory diagnosis of COVID-IA were test for galactomannan in BAL (62%), culture (33%) and microscopy (22%) of BAL. The main causative agents of COVID-IA are A. fumigatus (61%), A. niger (26%) and A. flavus (4%). The overall 12-week survival rate of patients with COVID-IA in the ICU was 42%, negative predictive factors were severe respiratory failure (27.5% vs 81%, p = 0.003), ARDS (14% vs 69%, p = 0.001), mechanical ventilation (25% vs 60%, p = 0.01), and foci of destruction in the lung tissue on CT scan (23% vs 59%, p = 0.01). Conclusions. IA affects predominantly ICU patients with COVID-19 who have concomitant medical conditions, such as diabetes mellitus, hematological malignancies, cancer, and COPD. Risk factors for COVID-IA in ICU patients are prolonged lymphopenia and COPD. The majority of patients with COVID-IA have their lungs affected, but clinical signs of IA are non-specific (fever, cough, progressive respiratory failure). The overall 12-week survival in ICU patients with COVID-IA is low. Prognostic factors of poor outcome in adult ICU patients are severe respiratory failure, ARDS, mechanical ventilation as well as CT signs of lung tissue destruction.Copyright © 2022, Interregional Association for Clinical Microbiology and Antimicrobial Chemotherapy. All rights reserved.

Does COVID-19 Increase the Risk of Central-Line-Associated Bloodstream Infections?

Objectives: All over the world, there has been a rapid and significant increase in the number of critically ill patients requiring mechanical ventilation, which was over the capacity of the intensive care units (ICU). This resulted in an increased risk of healthcare-associated infections. The most significant increase was in central-line-associated bloodstream infections (CLABSI). Our study aimed to determine the effect of COVID-19 infection on CLABSI rates in patients in the COVID-ICU and the factors affecting it. Methods: Adult patients hospitalized in the ICU between January 01, 2021, and December 31, 2021, and diagnosed with CLABSI were evaluated retrospectively. Only the first infection data of patients diagnosed with more than one CLABSI during hospitalization were included in the study. The patients were divided into two groups COVID-ICU and general ICU patients and were compared in terms of infection rate, risk factors, and agent distributions. Results: Twenty-two patients in the COVID-ICU and 32 patients in the general ICUs were diagnosed with CLABSI, and the infection rates were 2.05 and 1.03, respectively. The patients in the COVID-ICU had a shorter length of stay in the ICU and a significantly shorter time from ICU admission to CLABSI diagnosis. There was no difference in mortality between the two groups. Infections caused by Gram-negative microorganisms developed most frequently in both groups, and Acinetobacter baumannii was the most frequent among them. Conclusion: CLABSI is seen more frequently and earlier in patients followed in the COVID-ICU. According to our study, this situation did not significantly affect mortality. To prevent CLABSI in COVID-ICUs and improve health care quality, additional management strategies must be determined, and close data monitoring is needed.

Survival Analysis of Delta versus Omicron Variants in COVID-19 Intensive Care Unit (ICU)

Objective: COVID-19 has presented numerous epidemiological and clinical pictures from its beginning and much effort has been paid to detect the behavior of disease and its new types. Therefore, in this study, we aimed to compare the in-hospital survival time of Delta and Omicron variant patients admitted to the intensive care unit. Methods: This was a secondary data analysis of the QCOVICU data registry of 200 COVID-19 patients admitted to the ICU of Shahid Beheshti-Amir Al-Momenin Hospital of Qom City, in 2021. Likewise, time to event data, demographics, and baseline laboratory data was collected. Time of transfer to ICU, survivals, and possible predictors of hazards of death was compared within the variants of Omicron and delta. Results: Two hundred patients (62.98±19.94 years old, 94 females/106 males;100 Delta and 100 Omicron variant) participated in this study. Fifty percent of the population had died. Cross-tabulation showed comparable death rates among variants of delta and omicron (50.5% vs. 51%;p=0.999). There was a statistically significant higher time to ICU admission in Delta variant victims than in Omicron variant victims. The mean survival time of delta variant patients was 21.52 days (95% CI: 17.96 – 25.09) which was statistically higher than the mean survival of omicron patients (17.15 days, 95% CI: 13.65-20.64, p=0.018). The mean survival time of delta variant patients was statistically higher than omicron patients (21.52 vs. 17.15 days, p=0.018). Gender, age (years), and lymphocyte count were significant predictors of mortality based on the Cox regression analysis (P>0.05). There was a 5.9 times higher risk of mortality in females compared with males' gender after adjusting for other variables and a 5.6% increase in death risk with a 1-year increase in age, and a 31.8% decrease in death risk with a 1% lymphocyte percentage increase. Conclusion: Critically patients with Delta variant are getting ICU admitted later and withstand more days at ICU than Omicron patients. It seems that Omicron variant causes sudden deterioration of the patient's condition. © 2023 by SPC (Sami Publishing Company).

The Importance of Neuropsychology in the Early Rehabilitation of Patients with Critical Illness after Acute COVID Infection

The current literature has insufficiently examined the potential benefits of implementing early neuropsychological interventions for critically ill patients who have experienced COVID-19. To address this research gap, we conducted a descriptive analysis of clinical and neuropsychological data from N = 29 critically ill patients with COVID-19 admitted to an early neurological rehabilitation facility. Most patients had been diagnosed with critical illness polyneuropathy (CIP), and one-third exhibited additional brain damage. Upon admission, all patients exhibited severe cognitive impairments, demonstrating significant improvement following neuropsychological therapy. Nonetheless, the neurocognitive outcomes at discharge displayed a high cognitive and psychoemotional status variability. This paper presents the neuropsychological treatment concept we employed and discusses challenges encountered while treating critically ill patients with cognitive impairments.

Socio-economic and clinical drivers of COVID-19 mortality: An empirical analysis of the supply-side and demand-side moderators

The COVID-19 pandemic has disrupted everyday life globally, with severe consequences in several countries and regions. A key concern related to the COVID-19 pandemic is the wide variation in mortality across nations and sub-national locations such as states and counties. Anecdotal evidence, as well as evidence from CDC, indicates that the risk of spread as well as the risk of mortality from the pandemic is higher for regions with a population characterized by disadvantaged economic (income) and racial (underserved communities) and demographic profiles (age). Multiple studies have indicated that the most crucial step toward reducing mortality is expanding critical care capacity through procuring personal protective equipment (PPE) and ventilators and training critical care frontline employees. It is projected that with exponential growth in the pandemic spread, many regions would fall short of critical care capacity, increasing mortality.Furthermore, the pandemic has imposed high levels of constraints on resource availability, even in developed nations. Under resource constraints in critical care delivery, mitigation strategies need to account for the variation in observed cases and the disparity in mortality across locations. In my dissertation, I make a concerted effort to contribute toward understanding the sources of variation in mortality and propose a framework that enables pandemic preparedness and mitigation strategies that encapsulate the spatial and temporal variation in risk of mortality from COVID-19. The mitigation strategies are divided into supply-side and demand-side moderators of mortality. Accordingly, I focus on two mitigation strategies: (i) ICU capacity as a supply-side moderator and (ii) Vaccination coverage as a demand-side moderator. The overarching objective of my dissertation is to understand the role of supply-side and demand-side moderators of mortality, independently and jointly, of the association between socio-economic, demographic (henceforth referred to as social), and clinical risk factors and COVID-19 mortality. Much of the epidemiological literature on COVID-19 has focused on reducing the spread. However, the ultimate goal is to reduce mortality. There is a necessity in both practice and academic literature to understand actionable policies that can reduce mortality in general and spatial variation of mortality in specific. This dissertation research primarily leverages empirical methodology combining matching procedures with fixed effect modeling of panel data to test the hypothesized relationships of interest. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Predicting Intensive Care Unit Admission Using Machine and Deep Learning: COVID-19 Case Study

The COVID-19 pandemic has affected the entire world by causing widespread panic and disrupting normal life. Since the outbreak began in December 2019, the virus has killed thousands of people and infected millions more. Hospitals are struggling to keep up with large patient flows. In some situations, hospitals are lacking enough beds and ventilators to accommodate all of their patients or are running low on supplies such as masks and gloves. Predicting intensive care unit (ICU) admission of patients with COVID-19 could help clinicians better allocate scarce ICU resources. In this study, many machine and deep learning algorithms are tested over predicting ICU admission of patients with COVID-19. Most of the algorithms we studied are extremely accurate toward this goal. With the convolutional neural network (CNN), we reach the highest results on our metrics (90.09% accuracy and 93.08% ROC-AUC), which demonstrates the usability of these learning models to identify patients who are likely to require ICU admission and assist hospitals in optimizing their resource management and allocation during the COVID-19 pandemic or others. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

A review of some Covid-19 pandemic numbers in European Union, Canada, and Mexico

The rapidity and extent of Covid-19 infections have shown how a phenomenon that initially seemed geographically circumscribed quickly spread worldwide. In 2020, the spread of infection and the containment and management measures taken by local governments have been quite heterogeneous. Therefore, here we investigate the different ways of the spread of the infection in different areas, and specifically in Canada, Mexico, and the European Union states. For this purpose, for each area, official data on infection in 2020 are used to depict, analyze, and compare the monthly contagion's curves and the Rt index, both in absolute and relative terms. © Springer Nature Switzerland AG 2023. All rights reserved.

Association of d-dimer levels with in-hospital outcomes among COVID-19 positive patients: a developing country multicenter retrospective cohort.

D-dimer levels, which originate from the lysis of cross-linked fibrin, are serially measured during coronavirus disease 2019 illness to rule out hypercoagulability as well as a septic marker. Methods: This multicenter retrospective study was carried out in two tertiary care hospitals in Karachi, Pakistan. The study included adult patients admitted with a laboratory-confirmed coronavirus disease 2019 infection, with at least one measured d-dimer within 24 h following admission. Discharged patients were compared with the mortality group for survival analysis. Results: The study population of 813 patients had 68.5% males, with a median age of 57.0 years and 14.0 days of illness. The largest d-dimer elevation was between 0.51-2.00 mcg/ml (tertile 2) observed in 332 patients (40.8%), followed by 236 patients (29.2%) having values greater than 5.00 mcg/ml (tertile 4). Within 45 days of hospital stay, 230 patients (28.3%) died, with the majority in the ICU (53.9%). On multivariable logistic regression between d-dimer and mortality, the unadjusted (Model 1) had a higher d-dimer category (tertile 3 and tertile 4) associated with a higher risk of death (OR: 2.15; 95% CI: 1.02-4.54, P=0.044) and (OR: 4.74; 95% CI: 2.38-9.46, P<0.001). Adjustment for age, sex, and BMI (Model 2) yields only tertile 4 being significant (OR: 4.27; 95% CI: 2.06-8.86, P<0.001). Conclusion: Higher d-dimer levels were independently associated with a high risk of mortality. The added value of d-dimer in risk stratifying patients for mortality was not affected by invasive ventilation, ICU stays, length of hospital stays, or comorbidities.

Risk Factors in HIV-1 Positive Patients on the Intensive Care Unit: A Single Center Experience from a Tertiary Care Hospital.

HIV-positive patients with acquired immunodeficiency syndrome (AIDS) often require treatment on intensive care units (ICUs). We aimed to present data from a German, low-incidence region cohort, and subsequently evaluate factors measured during the first 24 h of ICU stay to predict short- and long-term survival, and compare with data from high-incidence regions. We documented 62 patient courses between 2009 and 2019, treated on a non-operative ICU of a tertiary care hospital, mostly due to respiratory deterioration and co-infections. Of these, 54 patients required ventilatory support within the first 24 h with either nasal cannula/mask (n = 12), non-invasive ventilation (n = 16), or invasive ventilation (n = 26). Overall survival at day 30 was 77.4%. While ventilatory parameters (all p < 0.05), pH level (c/o 7.31, p = 0.001), and platelet count (c/o 164,000/µL, p = 0.002) were significant univariate predictors of 30-day and 60-day survival, different ICU scoring systems, such as SOFA score, APACHE II, and SAPS 2 predicted overall survival (all p < 0.001). Next to the presence or history of solid neoplasia (p = 0.026), platelet count (HR 6.7 for <164,000/µL, p = 0.020) and pH level (HR 5.8 for <7.31, p = 0.009) remained independently associated with 30-day and 60-day survival in multivariable Cox regression. However, ventilation parameters did not predict survival multivariably.

Markers of liver function as potential prognostic indicators of SARS-CoV-2 infection: A retrospective analysis during the first and second waves of COVID-19 pandemic.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is known to cause a predominant respiratory disease, although extrapulmonary manifestations can also occur. One of the targets of Coronavirus disease 2019 (COVID-19) is the hepatobiliary system. The present study aims to describe the correlation between the increase of liver damage markers (i.e. alanine aminotransferase [ALT], aspartate aminotransferase [AST], total bilirubin [TB]) and COVID-19 outcomes (i.e., in-hospital mortality [IHM] and intensive care unit [ICU] transfer). Methods: All patients with confirmed SARS-CoV-2 infection admitted to the Infectious Diseases Unit of the St. Anna University-Hospital of Ferrara from March 2020 to October 2021 were retrospectively included in this single-centre study. ALT, AST and TB levels were tested in all patients and IHM or ICU transfer were considered as main outcomes. Co-morbidities were assessed using Charlson Comorbidity Index. Results: A total of 106 patients were retrieved. No hepatic marker was able to predict IHM, whereas all of them negatively predicted ICU transfer (ALT: OR 1.005, 95%CI 1.001-1.009, p= 0.011; AST: OR 1.018, 95%CI 1.006-1.030, p= 0.003; TB: OR 1.329, 95%CI 1.025-1.724, p= 0.032). Age was the only parameter significantly related to mortality. Conclusions: The present study, by correlating liver damage markers with COVID-19 outcome, showed that an increase of ALT, AST and TB predicted patients' severity, although not mortality.

Prevalence of the Risk Factors of Delirium Among COVID-19 Patients in the Intensive Care Unit at King Abdullah Medical City, Makkah: A Single-Center Study.

Background Coronavirus disease 2019 (COVID-19) patients admitted to the intensive care unit (ICU) are at a higher risk of developing delirium. In this study, we estimated the incidence of delirium and its risk factors in ICU patients with COVID-19 at King Abdullah Medical City (KAMC), Makkah, Saudi Arabia. Methodology We conducted a retrospective, analytical, cohort study of adult COVID-19 patients admitted to the ICU of KAMC between May 2020 and July 2021. Data were collected from electronic medical records. Results Of the 406 examined patients with COVID-19 aged >18 years, 55 developed delirium in the ICU setting. The incidence rate was 0.59% per 100 ICU days in these 55 patients; the mean age was 62.36 ± 17.9 years, and 65.5% were men. Binary logistic regression showed that age (p = 0.027), nationality (p = 0.045), presence of infectious diseases other than COVID-19 (p = 0.047), and ICU outcome (p = 0.013) were significant risk factors for developing delirium. The clinical presentation and prognosis of patients who developed delirium were assessed using the Acute Physiology and Chronic Health Evaluation II and Sequential Organ Failure Assessment scores, and the mean scores were 16.13 ± 7.96 and 5.25 ± 3.48, respectively. The mean length of ICU stay was 22.2 ± 33.3 days; 39 (70.9%) patients were discharged and 16 (29.1%) died. Conclusions Older age, nationality, infections, and ICU outcomes were risk factors for developing delirium in hospitalized COVID-19 patients at KAMC. Early detection of cognitive comorbidities and delirium in these patients is important.

A Tale of Two Hospitals: Comparing CAPA Infections in Two ICUs During the Spanish Fourth Pandemic Wave.

PURPOSE: COVID-19 associated pulmonary aspergillosis (CAPA) is a new clinical entity linked to SARS-CoV-2 infection that is causing a rise on the risk of complications and mortality, particularly in critical patients. METHODS: We compared diagnostic and clinical features in two cohorts of patients with severe COVID-19 admitted in the intensive care units (ICU) of two different hospitals in Madrid, Spain, between February and June 2021. Clinical and microbiological relevant aspects for CAPA diagnosis were collected for further classification. CAPA was classified as colonization, possible, probable, proven, and tracheobronchial aspergillosis according to the ECMM/ISHAM consensus, with some modifications to consider tracheobronchial aspirate as sample comparable to non-bronchoscopic lavages (NBL). RESULTS: 56 patients admitted in HULP (Hospital Universitario La Paz) ICU and 61 patients admitted in HEEIZ (Hospital de Emergencias Isabel Zendal) ICU had clinical suspicion of invasive fungal disease in the context of COVID-19 infection. Cultures were positive for Aspergillus spp. in 32 patients. According to 2020 European Confederation of Medical Mycology and the International Society for Human and Animal Mycology (ECMM/ISHAM) consensus, 11 patients were diagnosed with possible CAPA and 10 patients with probable CAPA. Global incidence for CAPA was 6.3%. Global median days between ICU admission and diagnosis was 14 day. Aspergillus fumigatus complex was the main isolated species. Antifungal therapy was used in 75% of patients with CAPA suspicion, with inter-hospital differences in the administered antifungals. Global overall mortality rate for CAPA patients was 66.6% (14/21). All-cause mortality in non-CAPA cohorts were of 26.3% in HULP group (34/129) and 56.8% (104/183) in HEEIZ group. CONCLUSIONS: There were no significant differences in incidence between the two hospitals, and differences in antifungal therapy did not correlate with differences in mortality, reflecting that both first-line azoles and Amphotericin B could be effective in treating CAPA infections, according to the current guideline indications.

Fungal Infections in the ICU during the COVID-19 Pandemic in Mexico.

Background: Invasive Fungal Infections (IFI) are emergent complications of COVID-19. In this study, we aim to describe the prevalence, related factors, and outcomes of IFI in critical COVID-19 patients. Methods: We conducted a nested case-control study of all COVID-19 patients in the intensive care unit (ICU) who developed any IFI and matched age and sex controls for comparison (1:1) to evaluate IFI-related factors. Descriptive and comparative analyses were made, and the risk factors for IFI were compared versus controls. Results: We found an overall IFI prevalence of 9.3% in COVID-19 patients in the ICU, 5.6% in COVID-19-associated pulmonary aspergillosis (CAPA), and 2.5% in invasive candidiasis (IC). IFI patients had higher SOFA scores, increased frequency of vasopressor use, myocardial injury, and more empirical antibiotic use. CAPA was classified as possible in 68% and 32% as probable by ECMM/ISHAM consensus criteria, and 57.5% of mortality was found. Candidemia was more frequent for C. parapsilosis Fluconazole resistant outbreak early in the pandemic, with a mortality of 28%. Factors related to IFI in multivariable analysis were SOFA score > 2 (aOR 5.1, 95% CI 1.5-16.8, p = 0.007) and empiric antibiotics for COVID-19 (aOR 30, 95% CI 10.2-87.6, p = <0.01). Conclusions: We found a 9.3% prevalence of IFIs in critically ill patients with COVID-19 in a single center in Mexico; factors related to IFI were associated with higher SOFA scores and empiric antibiotic use for COVID-19. CAPA is the most frequent type of IFI. We did not find a mortality difference.

CORONA (COre ultRasOund of covid in iNtensive care and Acute medicine) study: National service evaluation of lung and heart ultrasound in intensive care patients with suspected or proven COVID-19.

Background: Combined Lung Ultrasound (LUS) and Focused UltraSound for Intensive Care heart (FUSIC Heart - formerly Focused Intensive Care Echocardiography, FICE) can aid diagnosis, risk stratification and management in COVID-19. However, data on its application and results are limited to small studies in varying countries and hospitals. This United Kingdom (UK) national service evaluation study assessed how combined LUS and FUSIC Heart were used in COVID-19 Intensive Care Unit (ICU) patients during the first wave of the pandemic. Method: Twelve trusts across the UK registered for this prospective study. LUS and FUSIC Heart data were obtained, using a standardised data set including scoring of abnormalities, between 1st February 2020 to 30th July 2020. The scans were performed by intensivists with FUSIC Lung and Heart competency as a minimum standard. Data was anonymised locally prior to transfer to a central database. Results: 372 studies were performed on 265 patients. There was a small but significant relationship between LUS score >8 and 30-day mortality (OR 1.8). Progression of score was associated with an increase in 30-day mortality (OR 1.2). 30-day mortality was increased in patients with right ventricular (RV) dysfunction (49.4% vs 29.2%). Severity of LUS score correlated with RV dysfunction (p < 0.05). Change in management occurred in 65% of patients following a combined scan. Conclusions: In COVID-19 patients, there is an association between lung ultrasound score severity, RV dysfunction and mortality identifiable by combined LUS and FUSIC Heart. The use of 12-point LUS scanning resulted in similar risk score to 6-point imaging in the majority of cases. Our findings suggest that serial combined LUS and FUSIC Heart on COVID-19 ICU patients may aid in clinical decision making and prognostication.

Results from the first audit of an intensive care unit in Botswana.

Background: Botswana is an economically stable middle-income country with a developing health system and a large HIV and infectious disease burden. Princess Marina Hospital (PMH) is the largest referral and teaching hospital with a mixed eight-bed intensive care unit (ICU). Objectives: To conduct an audit of PMH ICU in order to investigate major admission categories and quantify morbidity and mortality figures using a validated scoring system for quality improvement, education and planning purposes. Methods: PMH medical records and laboratory data were accessed to record demographics, referral patterns, diagnoses, HIV status, Acute Physiologic Assessment and Chronic Health Evaluation (APACHE) II scores and mortality rates. Results: A total of 182 patients >14 years of age were enrolled over a 12-month period from April 2017 - March 2018. Patient's mean age was 42.9 years, males represented 56.6% of the study population and surgical conditions accounted for 46% of diagnostic categories. Sixty percent of the patients were HIV-negative and 12% had no HIV status recorded. The mean APACHE II score was 25 and the mean length of stay in ICU was 10.3 days. Higher APACHE II scores were associated with higher mortality regardless of HIV status. The overall mortality was 42.8% and there was no difference in mortality rates in ICU or at 30 days between HIV-positive and HIV-negative ICU patient groups. Conclusion: The PMH ICU population is young with a high mean APACHE II score, significant surgical and HIV burdens and a high mortality rate. PMH ICU has significant logistical challenges making comparison with international ICUs challenging, and further research is warranted. Contributions of the study: This study is the first published audit for an intensive care unit in Botswana. The findings are especially relevant for the development of critical care capacity in the country during the current COVID-19 pandemic. We advocate for the establishment of an ICU registry in the country to allow ongoing accurate research in the field of critical care medicine and to improve healthcare for all critically ill patients in Botswana.

Critical Care 1950 to 2022: Evolution of Medicine, Nursing, Technology, and Design.

Critical care units-designed for concentrated and specialized care-came from multiple parallel advances in medical, surgical, and nursing techniques and training taking advantage of new therapeutic technologies. Regulatory requirements and government policy impacted design and practice. After WWII, medical practice and education promoted further specialization. Hospitals offered newer, more extreme, and specialized surgeries and anesthesia enabled more complex procedures. ICUs developed in the 1950s, providing a recovery room's level of observation and specialized nursing to serve the critically ill, whether medical or surgical.

The Price of Hospital Reshaping: Nasal Myiasis Caused by Flesh Fly (Diptera: Sarcophagidae) in Reallocated COVID-19 Intensive Care Unit.

Myiasis is a condition characterized by fly larvae infestation, most common in tropical regions, but with a risk of occurring anywhere in the world. Here, we report a case of nasal myiasis caused by a sarcophagid fly in a critically ill COVID-19 patient hospitalized in a reallocated ICU department in Serbia and discuss procedures that could prevent the occurrence of similar incidents in reallocated ICU departments worldwide.

Predictors of Pneumothorax in People With COVID-19 Pneumonia: A Multicenter Retrospective Investigation.

This multicenter retrospective investigation aimed to identify predictors of pneumothorax (PTX), pneumomediastinum (PM), and subcutaneous emphysema (SE) in patients with COVID-19 pneumonia admitted to the ICU. A total of 256 patients were included, with 128 in the case group and 128 in the control group. The study sample consisted of predominantly male patients with a mean age of around 53 years and a high prevalence of comorbidities. Significant predictors of PTX, PM, and SE included the presence of coronary artery disease, non-rebreather mask usage, high-flow oxygen therapy, mechanical ventilation, pressor usage, inpatient dialysis, steroid usage, sedative usage, narcotic usage, paralytic usage, elevated C-reactive protein levels, increased lung infiltration, the presence of PM and SE, mode of ventilation, duration of various respiratory support interventions, and severity of illness as indicated by APACHE and SOFA scores. These findings have important implications for the clinical management of patients with COVID-19 pneumonia, as they may help identify and closely monitor at-risk individuals, allowing for timely intervention and potentially improving clinical outcomes. Future research should focus on validating these predictors in larger cohorts and investigating the underlying mechanisms to develop targeted preventive and therapeutic strategies.