Lactate Levels as a Predictor of Emergency Department Revisits in Infants With Acute Bronchiolitis.

OBJECTIVE: This study aimed to identify predictive biomarkers for unscheduled emergency department (ED) revisits within 24 hours of discharge in infants diagnosed with acute bronchiolitis (AB). METHODS: A retrospective observational study was conducted on infants diagnosed with AB who visited 3 emergency medical centers between January 2020 and December 2022. The study excluded infants with comorbidities, congenital diseases, and prematurity and infants who revisited the ED after 24 hours of discharge. Demographic data, vital signs, and laboratory results were collected from the medical records. Univariable and multivariable logistic regression analyses were performed on factors with P of less than 0.1 in univariable analysis. Receiver operator curve analysis was used to assess the accuracy of lactate measurements in predicting ED revisits within 24 hours of discharge. RESULTS: Out of 172 participants, 100 were in the revisit group and 72 in the discharge group. The revisit group was significantly younger and exhibited higher lactate levels, lower pH values, and higher pCO2 levels compared to the discharge group. Univariable logistic regression identified several factors associated with revisits. Multivariable analysis found that only lactate was a variable correlated with predicting ED revisits (odds ratio, 18.020; 95% confidence interval [CI], 5.764-56.334). The receiver operator curve analysis showed an area under the curve of 0.856, with an optimal lactate cutoff value of 2.15. CONCLUSION: Lactate value in infants diagnosed with AB were identified as a potential indicator of predicting unscheduled ED revisits within 24 hours of discharge. The predictive potential of lactate levels holds promise for enhancing prognosis prediction, reducing health care costs, and alleviating ED overcrowding. However, given the study's limitations, a more comprehensive prospective investigation is recommended to validate these findings.

Reliability of the DI-60 Digital Image Analyzer for Detecting Platelet Clumping and Obtaining Accurate Platelet Counts.

Pseudothrombocytopenia caused by platelet clumping (PC) can lead to unnecessary platelet transfusions or underdiagnosis of hematologic neoplasms. To overcome these limitations, we assessed the capacity of the Sysmex DI-60 digital morphology analyzer (Sysmex, Kobe, Japan) for detecting PC and determining an accurate platelet count in the presence of PC. For this purpose, 135 samples with or without PC (groups Y and N, respectively) were processed by an examiner (a hematologic specialist) using both the Sysmex XN-9000 and DI-60 analyzers. Although the platelet aggregate (PA) and giant platelet (GP) counts reported by the DI-60 and the examiner exhibited strong correlations, they proved inadequate as effective indicators for screening samples containing PC. Between the PA and GP counts and four platelet indices (the platelet distribution width [PDW], mean platelet volume [MPV], platelet large cell ratio [P_LCR], and plateletcrit [PCT]) reported by the XN-9000, we observed statistically significant correlations (both overall and with group Y), but they were relatively weak. The platelet counts determined using the DI-60 and light microscopy in group Y showed substantial variations. Although the performance of the DI-60 was reliable for detecting PA and GP in smear images, such fixed areas are not representative of whole samples. Further, in the presence of PC, the resulting platelet counts determined using the DI-60 were not sufficiently accurate to be accepted as the final count.

High-Volume Hospital Had Lower Mortality of Severe Intracerebral Hemorrhage Patients.

Objective: Intracerebral hemorrhage (ICH) accompanies higher mortality rates than other type of stroke. This study aimed to investigate the association between hospital volume and mortality for cases of ICH. Methods: We used nationwide data from 2013 to 2018 to compare high-volume hospitals (≥32 admissions/year) and low-volume hospitals (<32 admissions/year). We tracked patients' survival at 3-month, 1-year, 2-year, and 4-year endpoints. The survival of ICH patients was analyzed at 3-month, 1-year, 2-year, and 4-year endpoints using Kaplan-Meier survival analysis. Multivariable logistic regression analysis and Cox regression analysis were performed to determine predictive factors of poor outcomes at discharge and death. Results: Among 9,086 ICH patients who admitted to hospital during 18-month period, 6,756 (74.4%) and 2,330 (25.6%) patients were admitted to high-volume and low-volume hospitals. The mortality of total ICH patients was 18.25%, 23.87%, 27.88%, and 35.74% at the 3-month, 1-year, 2-year, and 4-year, respectively. In multivariate logistic analysis, high-volume hospitals had lower poor functional outcome at discharge than low-volume hospitals (odds ratio, 0.80; 95% confidence interval, 0.72-0.91; p < 0.001). In the Cox analysis, high-volume hospitals had significantly lower 3-month, 1-year, 2-year, and 4-year mortality than low-volume hospitals (p < 0.05). Conclusion: The poor outcome at discharge, short- and long-term mortality in ICH patients differed according to hospital volume. High-volume hospitals showed lower rates of mortality for ICH patients, particularly those with severe clinical status.

Kidney biopsy can help to predict renal outcomes of patients with type 2 diabetes mellitus.

Background: In patients with type 2 diabetes mellitus (T2DM), diabetic kidney disease (DKD) is diagnosed based on clinical features. A kidney biopsy is used only in selected cases. This study aimed to reconsider the role of a biopsy in predicting renal outcomes. Methods: Clinical and laboratory parameters and renal biopsy results were obtained from 237 patients with T2DM who underwent renal biopsies at Soonchunhyang University Cheonan Hospital between January 2000 and March 2020 and were analyzed. Results: Of 237 diabetic patients, 29.1% had DKD only, 61.6% had non-DKD (NDKD), and 9.3% had DKD with coexisting NDKD (DKD/NDKD). Of the patients with DKD alone, 43.5% progressed to end-stage kidney disease (ESKD), while 15.8% of NDKD patients and 36.4% of DKD/NDKD patients progressed to ESKD (p < 0.001). In the DKD-alone group, pathologic features like ≥50% global sclerosis (p < 0.001), tubular atrophy (p < 0.001), interstitial fibrosis (p < 0.001), interstitial inflammation (p < 0.001), and the presence of hyalinosis (p = 0.03) were related to worse renal outcomes. The Cox regression model showed a higher risk of progression to ESKD in the DKD/NDKD group compared to the DKD-alone group (hazard ratio [HR], 2.73; p = 0.032), ≥50% global sclerosis (HR, 3.88; p < 0.001), and the degree of mesangial expansion (moderate: HR, 2.45; p = 0.045 and severe: HR, 6.22; p < 0.001). Conclusion: In patients with T2DM, a kidney biopsy can help in identifying patients with NDKD for appropriate treatment, and it has predictive value.