Hospital-Acquired Blood Stream Infection in an Adult Intensive Care Unit

A Chronicle Review of In-Silico Approaches for Discovering Novel Antimicrobial Agents to Combat Antimicrobial Resistance

Antimicrobial resistance (AMR) poses a foremost threat to global health, necessitating innovative strategies for discovering antimicrobial agents. This review explores the role and recent advances of in-silico techniques in identifying novel antimicrobial agents and combating AMR giving few briefings of recent case studies of AMR. In-silico techniques, such as homology modeling, virtual screening, molecular docking, pharmacophore modeling, molecular dynamics simulation, density functional theory, integrated machine learning, and artificial intelligence, are systematically reviewed for their utility in discovering antimicrobial agents. These computational methods enable the rapid screening of large compound libraries, prediction of drug-target interactions, and optimization of drug candidates. The review discusses integrating in-silico approaches with traditional experimental methods and highlights their potential to accelerate the discovery of new antimicrobial agents. Furthermore, it emphasizes the significance of interdisciplinary collaboration and data-sharing initiatives in advancing antimicrobial research. Through a comprehensive discussion of the latest developments in in-silico techniques, this review provides valuable insights into the future of antimicrobial research and the fight against AMR.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s12088-024-01355-x.

Prevalence and clinical implications of bloodstream infections in intensive care patients with or without burn injury: a retrospective cohort study

PURPOSE

Severe burn injuries are often accompanied by infections and associated with high morbidity and mortality. This study aimed to compare the prevalence and clinical impact of bacteremia between patients receiving intensive care with and without burns.

METHODS

This single-center retrospective cohort study at the University Hospital Vienna, Austria, analyzed blood cultures from intensive care unit (ICU) patients with and without burns (2012-2022) to assess the prevalence of bacteremia, the associated pathogen distribution and the 60-day all-cause mortality.

RESULTS

In 1170 ICU patients, 303 with burns and 867 without, the prevalence of bacteremia was similar among patients with at least one blood culture (31/157 [19.7%] versus 44/213 [20.7%], OR [95%CI] = 0.95 [0.57-1.57]). Burn patients exhibited a significantly higher frequency of microbiological sampling (51.5% versus 24.5%, p < 0.001), resulting in a higher overall prevalence of bacteremia (10.2% versus 5.1%, p = 0.002). 16.2% of all identified pathogens were multidrug-resistant (MDR). The 60-day all-cause mortality was higher in patients with MDR pathogens than in patients without bacteremia (41.7% versus 10.6%, p = 0.026).

CONCLUSION

Bacteremia prevalence was similar in burn and non-burn patients, with high rates of multidrug-resistant Gram-negative pathogens. The 60-day all-cause mortality was significantly higher in patients with MDR pathogens than in patients without bacteremia.

Hospital-Acquired Bloodstream Infections in the Adult Intensive Care Unit at Prince Mohammed bin Abdulaziz Hospital, Riyadh, Saudi Arabia

Introduction Hospital-acquired infections, also called nosocomial infections, are infectious diseases acquired in healthcare facilities at least 48 hours after admission and can't be present at the time of admission. Nosocomial bloodstream infection is a serious medical complication from hospitalization, and it can be potentially preventable by taking certain precautions. Aim The aim of this study is to determine the prevalence of central line-related bloodstream infections (CLABSI) with different organisms between January 2022 and February 2024 at the intensive care unit (ICU) at Prince Mohammed bin Abdulaziz Hospital, Riyadh, Saudi Arabia. Patients and methods This retrospective cross-sectional study was conducted among ICU adult patients. The data were collected from medical and infection control records. All data for intensive care patients with positive blood cultures, except for the pediatric age group, were collected. Data were tabulated and cleaned in MS Excel, and subsequent data analyses were performed in IBM SPSS Statistics for Windows, Version 26 (Released 2019; IBM Corp., Armonk, New York, United States). Results Data from 21 patients were collected and analyzed. The mean age of the participants was 62.9 (SD 15.1) years. Female participants (61.9% (13)) were higher than males (38.1% (8)). All patients were inserted with a non-tunneled central venous catheter (CVC). The mortality rate was 76.2% (16). Vancomycin-resistant enterococci (VRE) was the most commonly detected organism in seven cultures (33.3%), followed by Candida species in six cultures (28.6%). Candida species were prevalent in younger patients (p=0.021) and those sensitive to medication (p=0.015). Survival analyses between age, gender, and organisms yielded insignificant results (p>0.05). Conclusion The major sources of bloodstream infection among adult ICU patients were VRE and Candida species. Mortality was common in this population, particularly among patients who were resistant to medication. Hence, strategies to reduce hospital-acquired bloodstream infections are warranted.

Clinical Characteristics and Nomogram for Predicting Mortality in Patients with Postoperative Bloodstream Infection in Surgical Intensive Care Unit

Background

Bloodstream infection is amongst the leading causes of mortality for critical postoperative patients. However, data, especially from developing countries, are scary. Clinical decision-making tools for predicting postoperative bloodstream infection-related mortality are important but still lacking.

Objective

To analyze the distribution of pathogens and develop a nomogram for predicting mortality in patients with postoperative bloodstream infection in the surgical intensive care unit.

Methods

The clinical data, infection and pathogen-related data, and prognosis of patients with PBSI in the SICU from January 2017 to January 2022 were retrospectively collected. The distribution of pathogens and clinical characteristics of patients with PBSI were analyzed. The patients were assigned to a died group and a survived group according to their survival status. Independent predictors for mortality were identified by univariate and multivariate analyses. A nomogram for predicting PBSI-related death was developed based on these independent predictors. Calibration and decision-curve analysis were established to evaluate the nomogram. We collected postoperative patients admitted to our center from February 2022 to June 2023 as external validation sets to verify the nomogram. We also add the Brier score to further validate the model.

Results

In the training set, 7128 patients admitted to the SICU after different types of surgery were collected. A total of 198 patients and 308 pathogens were finally enrolled. The mean age of patients with PBSI was 64.38 ± 16.22 (range 18-90) years, and 56.1% were male. Forty-five patients (22.7%) died in the hospital. Five independent predictors including BMI, APACHE II score, estimated glomerular filtration rate (eGFR), urine volume in the first 24 hours after surgery, and peak temperature before positive blood cultures were selected to establish the nomogram. The area under the receiver operating characteristic curve for the prediction model was 0.922. Calibration curve and decision curve analysis showed good performance of the nomogram. Seventy patients with PBSI were collected as an external validation set, and thirteen patients died in this set. The external validation set was used to validate the nomogram, and the results showed that the AUC was 0.930 which was higher than that in the training set indicating that the nomogram had a good discrimination. The brier score was 0.087 for training set and 0.050 for validation set.

Conclusions

PBSI was one of the key issues that clinicians were concerned and could be assessed with a good predictive model using simple clinical factors.