Quick-SOFA score ≥ 2 predicts prolonged hospital stay in geriatric patients with influenza infection.

PURPOSE: The quick Sepsis-Related Organ Failure Assessment (qSOFA) score was designed to predict mortality among sepsis patients. However, it has never been used to identify prolonged length of hospital stay (pLOS) in geriatric patients with influenza infection. We conducted this study to clarify this issue. METHODS: We conducted a retrospective case-control study, including geriatric patients (aged ≥ 65 years) with influenza infection visiting the emergency department (ED) of a medical center between January 01, 2010 and December 31, 2015. The included patients were divided into two groups on the basis of their qSOFA score: qSOFA < 2, and qSOFA ≥ 2. Data regarding demographics, vital signs, qSOFA score, underlying diseases, subtypes of influenza, and outcomes were included in the analysis. We investigated the association between qSOFA score ≥ 2 and pLOS (>9 days) via logistic regression. RESULTS: Four hundred and nine geriatric patients were included in this study with a mean age of 79.5 (standard deviation [SD], 8.3) years. The median length of stay (LOS) was 7.0 (interquartile range [IQR], 4-12) days, while the rate of pLOS (> 9 days) was 32%. The median LOS in the qSOFA ≥ 2 group, 11.0 (7-15) days, was longer than the qSOFA < 2 group, 6.0 (4-10) days (p-value <0.01). Logistic regression showed that qSOFA ≥ 2 predicts pLOS with an odds ratio of 3.78 (95% confidence interval, 2.04-6.97). CONCLUSION: qSOFA score ≥ 2 is a prompt and simple tool to predict pLOS in geriatric patients with influenza infection.

Utilization of systemic inflammatory response syndrome criteria in predicting mortality among geriatric patients with influenza in the emergency department.

BACKGROUND: Systemic Inflammatory Response Syndrome (SIRS) criteria are often used to evaluate the risk of sepsis and to identify in-hospital mortality among patients with suspected infection. However, utilization of the SIRS criteria in mortality prediction among geriatric patients with influenza in the emergency department (ED) remains unclear. Therefore, we conducted a research to delineate this issue. METHODS: This is a retrospective case-control study including geriatric patients (age ≥ 65 years) with influenza, who presented to the ED of a medical center between January 1, 2010 and December 31, 2015. Vital signs, past history, subtype of influenza, demographic data, and outcomes were collected from all patients and analyzed. We calculated the accuracy for predicting 30-days mortality using the SIRS criteria. We also performed covariate adjustment of the area under the receiver operating characteristic curve (AUROC) via regression modeling. RESULTS: We recruited a total of 409 geriatric patients in the ED, with mean age 79.5 years and an equal sex ratio. The mean SIRS criteria score was 1.9 ± 1.1. The result of a Hosmer-Lemeshow goodness-of-fit test was 0.34 for SIRS criteria. SIRS criteria score ≥ 3 showed better mortality prediction, with odds ratio (OR) 3.37 (95% confidence interval (CI), 1.05-10.73); SIRS score ≥ 2 showed no statistical significance, with p = 0.85 (OR, 1.15; 95% CI, 0.28-4.69). SIRS score ≥ 3 had acceptable 30-days mortality discrimination, with AUROC 0.77 (95% CI, 0.68-0.87) after adjustment. SIRS score ≥ 3 also had a notable negative predictive value of 0.97 (95% CI, 0.94-0.99). CONCLUSION: The presence of a higher number of SIRS criteria (≥ 3) showed greater accuracy for predicting mortality among geriatric patients with influenza.

Advancements in Artificial Intelligence in Emergency Medicine in Taiwan: A Narrative Review.

The rapid progression of artificial intelligence (AI) in healthcare has greatly influenced emergency medicine, particularly in Taiwan-a nation celebrated for its technological innovation and advanced public healthcare. This narrative review examines the current status of AI applications in Taiwan's emergency medicine and highlights notable achievements and potential areas for growth. AI has wide capabilities encompass a broad range, including disease prediction, diagnostic imaging interpretation, and workflow enhancement. While the integration of AI presents promising advancements, it is not devoid of challenges. Concerns about the interpretability of AI models, the importance of dataset accuracy, the necessity for external validation, and ethical quandaries emphasize the need for a balanced approach. Regulatory oversight also plays a crucial role in ensuring the safe and effective deployment of AI tools in clinical settings. As its footprint continues to expand in medical education and other areas, addressing these challenges is imperative to harness the full potential of AI for transforming emergency medicine in Taiwan.

Epidemiology of Emergency Department Sepsis: A National Cohort Study Between 2001 and 2012.

The aim of this study is to examine the incidence trend of sepsis over 11 years and compared mortality outcomes among Taiwanese patients with sepsis admitted from emergency department (ED) and non-ED routes. We used a nationwide health insurance database from Taiwan, which comprise of 23 million beneficiaries. Patients with sepsis were identified by ICD-9 CM codes for infection and organ dysfunction from 2001 to 2012. We performed propensity score matching and compared mortality rates between ED-admitted and non ED-admitted patients.During the 11-year study period, we identified 1,256,684 patients with sepsis. 493,397 (29.3%) were admitted through the ED, and 763,287 (70.7%) were admitted directly to the floor. For patients with sepsis, mortality in ED-admitted patients decreased from 27.2% in 2002 to 21.1% in 2012 while that in non-ED admitted patients decreased from 35.3% in 2002 to 30.7% in 2012. Although patients with sepsis admitted through the ED had a higher incidence of organ dysfunction than patients who were directly admitted, they had more favorable outcomes in mortality, length of intensive care unit stay, and hospital stay. After propensity score matching, ED-admitted patients had a 7% lower risk of 90-day mortality (HR, 0.93, 95% CI, 0.89-0.97) compared with directly admitted patients. During the study period, mortality declined faster among ED admitted sepsis patients than directly admitted sepsis patients. Results of this study should be interpreted in light of limitations. Like other administrative database studies, treatment details are not available. Further clinical studies evaluating the treatment and outcome difference between ED and non-ED admitted sepsis patients are warranted.

Quick-SOFA score to predict mortality among geriatric patients with influenza in the emergency department.

The quick sequential organ failure assessment (qSOFA) score is widely used to assess the risk of sepsis and predict in-hospital mortality in patients with suspected infection. However, its ability to predict mortality among geriatric patients with influenza in the emergency department (ED) remains unclear. Therefore, this study was conducted to delineate this issue.A retrospective case-control study was conducted on geriatric patients (age ≥65 years) with influenza who visited the ED of a medical center between January 01, 2010, and December 31, 2015. Demographic data, vital signs, past histories, influenza subtypes, and treatment outcomes were included in the analysis. We assessed the accuracy of the qSOFA score in predicting 30-day mortality via logistic regression. Covariate adjustment of the area under the receiver operating characteristic curve (AUROC) via regression modeling was performed too.In total, 409 geriatric ED patients with mean age of 79.5 years and nearly equal sex ratio were recruited. The mean qSOFA score was 0.55 ±â€Š0.7. The Hosmer-Lemeshow goodness-of-fit test was 0.79 for qSOFA score. Patients with qSOFA score of ≥2 (odds ratio, 4.21; 95% confidence interval [CI], 1.56-11.40) had increased in-hospital mortality. qSOFA score of ≥2 also had excellent in-hospital mortality discrimination with an adjusted AUROC of 0.81 (95% CI, 0.71-0.90). A qSOFA of ≥2 had prominent specificity of 0.89 (95% CI, 0.86-0.92).An increase in qSOFA score of 2 greatly predicts mortality in geriatric patients with influenza.