(1) Background: Sepsis is a life-threatening condition, and most patients with sepsis first present to the emergency department (ED) where early identification of sepsis is challenging due to the unavailability of an effective diagnostic model. (2) Methods: In this retrospective study, patients aged ≥20 years who presented to the ED of an academic hospital with systemic inflammatory response syndrome (SIRS) were included. The SIRS, sequential organ failure assessment (SOFA), and quick SOFA (qSOFA) scores were obtained for all patients. Routine complete blood cell testing in conjugation with the examination of new inflammatory biomarkers, namely monocyte distribution width (MDW), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), was performed at the ED. Propensity score matching was performed between patients with and without sepsis. Logistic regression was used for constructing models for early sepsis prediction. (3) Results: We included 296 patients with sepsis and 1184 without sepsis. A SIRS score of >2, a SOFA score of >2, and a qSOFA score of >1 showed low sensitivity, moderate specificity, and limited diagnostic accuracy for predicting early sepsis infection (c-statistics of 0.660, 0.576, and 0.536, respectively). MDW > 20, PLR > 9, and PLR > 210 showed higher sensitivity and moderate specificity. When we combined these biomarkers and scoring systems, we observed a significant improvement in diagnostic performance (c-statistics of 0.796 for a SIRS score of >2, 0.761 for a SOFA score of >2, and 0.757 for a qSOFA score of >1); (4) Conclusions: The new biomarkers MDW, NLR, and PLR can be used for the early detection of sepsis in the current sepsis scoring systems.

The coronavirus disease 2019 (COVID-19) has become a pandemic. Rapidly distinguishing COVID-19 from other respiratory infections is a challenge for first-line health care providers. This retrospective study was conducted at the Taipei Medical University Hospital, Taiwan. Patients who visited the outdoor epidemic prevention screening station for respiratory infection from February 19 to April 30, 2020, were evaluated for blood biomarkers to distinguish COVID-19 from other respiratory infections. Monocyte distribution width (MDW) ≥ 20 (odds ratio [OR]: 8.39, p = 0.0110, area under curve [AUC]: 0.703) and neutrophil-to-lymphocyte ratio (NLR) < 3.2 (OR: 4.23, p = 0.0494, AUC: 0.673) could independently distinguish COVID-19 from common upper respiratory tract infections (URIs). Combining MDW ≥ 20 and NLR < 3.2 was more efficient in identifying COVID-19 (AUC: 0.840). Moreover, MDW ≥ 20 and NLR > 5 effectively identified influenza infection (AUC: 0.7055). Thus, MDW and NLR can distinguish COVID-19 from influenza and URIs.

Posterior circulation acute ischemic stroke constitutes one-fourth of all ischemic strokes and can be efficiently quantified using the posterior circulation Alberta stroke program early computed tomography score (PC-ASPECTS) through diffusion-weighted imaging. We investigated whether the PC-ASPECTS and National Institutes of Health Stroke Scale (NIHSS) facilitate functional outcome prediction among Chinese patients with posterior circulation acute ischemic stroke. Participants were selected from our prospective stroke registry from January 1, 2015, to December 31, 2016. The baseline NIHSS score was assessed on the first day of admission, and brain magnetic resonance imaging was performed within 36 h after stroke onset. Simple and multiple logistic regressions were conducted to determine stroke risk factors and the PC-ASPECTS. Receiver operating characteristics (ROC) curve analysis was performed to compare the NIHSS and PC-ASPECTS. Of 549 patients from our prospective stroke admission registry database, 125 (22.8%) had a diagnosis of posterior circulation acute ischemic stroke. The optimal cutoff for the PC-ASPECTS in predicting outcomes was 7. The odds ratios of the PC-ASPECTS (≤ 7 vs > 7) in predicting outcomes were 6.33 (p = 0.0002) and 8.49 (p = 0.0060) in the univariate and multivariate models, respectively, and 7.52 (p = 0.0041) in the aging group. On ROC curve analysis, the PC-ASPECTS demonstrated more reliability than the baseline NIHSS for predicting functional outcomes of minor posterior circulation stroke. In conclusion, both the PC-ASPECTS and NIHSS help clinicians predict functional outcomes. PC-ASPECTS > 7 is a helpful discriminator for achieving favorable functional outcome prediction in posterior circulation acute ischemic stroke.

Objectives: This study aims to investigate whether combining scoring systems with monocyte distribution width (MDW) improves early sepsis detection in older adults in the emergency department (ED). Methods: In this prospective observational study, we enrolled older adults aged ≥60 years who presented with confirmed infectious diseases to the ED. Three scoring systems—namely quick sepsis-related organ failure assessment (qSOFA), Modified Early Warning Score (MEWS), and National Early Warning Score (NEWS), and biomarkers including MDW, neutrophil-to-lymphocyte ratio (NLR), and C-reactive protein (CRP), were assessed in the ED. Logistic regression models were used to construct sepsis prediction models. Results: After propensity score matching, we included 522 and 2088 patients with and without sepsis in our analysis from January 1, 2020, to September 30, 2021. NEWS ≥5 and MEWS ≥3 exhibited a moderate-to-high sensitivity and a low specificity for sepsis, whereas qSOFA score ≥2 demonstrated a low sensitivity and a high specificity. When combined with biomarkers, the NEWS-based, the MEWS-based, and the qSOFA-based models exhibited improved diagnostic accuracy for sepsis detection without CRP inclusion (c-statistics=0.842, 0.842, and 0.826, respectively). Of the three models, MEWS ≥3 with white blood cell (WBC) count ≥11 × 10⁹/L, NLR ≥8, and MDW ≥20 demonstrated the highest diagnostic accuracy in all age subgroups (c-statistics=0.886, 0.825, and 0.822 in patients aged 60–74, 75–89, and 90–109 years, respectively). Conclusions: Our novel scoring system combining MEWS with WBC, NLR, and MDW effectively detected sepsis in older adults.

Although a lower level of non-high-density lipoprotein cholesterol (HDL-C) was reported to be inversely associated with spontaneous intracranial hemorrhage (ICH), no enough evidence has verified whether lipid profiles modify hemorrhagic transformation and functional outcomes in patients with acute ischemic treated with thrombolysis. This multicenter cohort study included 2373 patients with acute ischemic stroke treated with intravenous thrombolysis between December 2004 and December 2016. Of these, 1845 patients were categorized into either the hyperlipidemia or non-hyperlipidemia group. Symptomatic ICH (SICH) rates within 24-36 h of thrombolytic onset and functional outcomes at 30 and 90 days were longitudinally surveyed. Models of predicting hemorrhagic transformation were used to validate our findings. For enrolled 1845 patients, SICH rates were ≥2-fold reduced for the hyperlipidemia group by the NINDS (adjusted RR: 0.488 [0.281-0.846], p=0.0106), the ECASS II (adjusted RR: 0.318 [0.130-0.776], p=0.0119), and SITS-MOST standards (adjusted RR: 0.214 [0.048-0.957], p=0.0437). The favorable functional rates between the two groups were not significantly different. Lower levels of LDL-C were showed in robust association with SICH. With a cut-off LDL-C value of ＜130 mg/dL, new models are more robust and significant in predicting hemorrhagic transformation within 24-36 h. This study supports the strong association between reduced LDL-C and increased SICH, but not for functional outcomes in patients with acute ischemic stroke treated with intravenous thrombolysis. LDL-C level of ＜130 mg/dL is supposed to a candidate marker for predicting SICH within 24-36 h.