Scoring Systems to Evaluate the Mortality Risk of Patients with Emphysematous Cystitis: A Retrospective Observational Study

BACKGROUND

Emphysematous cystitis (EC) is a complicated urinary tract infection (UTI) characterized by gas formation within the bladder wall and lumen. Immunocompetent people are less likely to suffer from complicated UTIs, but EC usually occurs in women with poorly controlled diabetes mellitus (DM). Other risk factors of EC include recurrent UTI, neurogenic bladder disorder, blood supply disorders, and prolonged catheterization, but DM is still the most important of all aspects. Our study investigated clinical scores in predicting clinical outcomes of patients with EC. Our analysis is unique in predicting EC clinical outcomes by using scoring system performance.

MATERIALS AND METHODS

We retrospectively collected EC patient data from the electronic clinical database of Taichung Veterans General Hospital between January 2007 and December 2020. Urinary cultures and computerized tomography confirmed EC. In addition, we investigated the demographics, clinical characteristics, and laboratory data for analysis. Finally, we used a variety of clinical scoring systems as a predictor of clinical outcomes.

RESULTS

A total of 35 patients had confirmed EC, including 11 males (31.4%) and 24 females (68.6%), with a mean age of 69.1 ± 11.4 years. Their hospital stay averaged 19.9 ± 15.5 days. The in-hospital mortality rate was 22.9%. The Mortality in Emergency Department Sepsis (MEDS) score was 5.4 ± 4.7 for survivors and 11.8 ± 5.3 for non-survivors (p = 0.005). For mortality risk prediction, the AUC of ROC was 0.819 for MEDS and 0.685 for Rapid Emergency Medicine Score (REMS). The hazard ratio of univariate and multivariate logistic regression analyses of REMS for EC patients was1.457 (p = 0.011) and 1.374 (p = 0.025), respectively.

CONCLUSION

Physicians must pay attention to high-risk patients according to clinical clues and arrange imaging studies as soon as possible to confirm the diagnosis of EC. MEDS and REMS are helpful for clinical staff in predicting the clinical outcome of EC patients. If EC patients feature higher scores of MEDS (≥12) and REMS (≥10), they will have higher mortality.

Performance of Scoring Systems in Predicting Clinical Outcomes of Patients with Emphysematous Pyelonephritis: A 14-Year Hospital-Based Study

Background: Emphysematous pyelonephritis (EPN) is a rare but severe necrotizing infection causing there to be gas in the pelvicalyceal system, renal parenchyma, and perirenal or pararenal space. Physicians should attend to EPN because of its life-threatening septic complications. The overall mortality rate has been reported to be as high as 20−40%. In addition, most patients had diabetes mellitus (DM) and obstructive uropathy. The most common isolated microorganism is Escherichia coli. This study aims to analyze the risk factors and performance of scoring systems in predicting the clinical outcomes of patients with EPN. Materials and Methods: We collected the data of patients with EPN in this single hospital-based retrospective study from the electronic medical records of Taichung Veterans General Hospital between January 2007 and December 2020. Radiological investigations of abdominal computed tomography (CT) confirmed the diagnosis of EPN. In addition, we analyzed demographics, clinical characteristics, and laboratory data. Finally, we used various scoring systems to predict clinical outcomes. Results: A total of fifty patients with EPN, whose diagnoses were confirmed through CT, were enrolled in the study. There were 18 males (36%) and 32 females (64%), with a mean age of 64.3 ± 11.3 years. The in-hospital mortality rate was 16%. A DM of 34 (68%) patients was the most common comorbidity. Fever was the most common symptom, found in 25 (50%) patients. The Mortality in Emergency Department Sepsis (MEDS) score was 4.64 ± 3.67 for survivors and 14.25 ± 5.34 for non-survivors (p < 0.001). The National Early Warning Score (NEWS) was 3.64 ± 2.33 for survivors and 7.13 ± 4.85 for non-survivors (p = 0.046). The Rapid Emergency Medicine Score (REMS) was 5.81 ± 1.97 for survivors and 9.13 ± 3.87 for non-survivors (p = 0.024). Regarding performance of mortality risk prediction, the AUC of ROC was 0.932 for MEDS, 0.747 for REMS, and 0.72 for NEWS. Conclusions: MEDS, REMS, and NEWS could be prognostic tools for the prediction of the clinical outcomes of patients with EPN. MEDS showed the best sound performance. In those with higher scores in MEDS (≥12), REMS (≥10), and NEWS (≥8), we recommended aggressive management and appropriate antimicrobial therapy as soon as possible to reduce mortality. Further large-scale studies are required to gain a deep understanding of this disease and to ensure patient safety.

Analysis of Therapeutic Decisions for Infantile Hemangiomas: A Prospective Study Comparing the Hemangioma Severity Scale with the Infantile Hemangioma Referral Score

BACKGROUND

In view of the high incidence of infantile hemangioma (IH) in infants and young children, a comprehensive and reasonable evaluation scale for referral is urgently needed. This study compared the influence of the Hemangioma Severity Scale (HSS) and the Infantile Hemangioma Referral Score (IHReS) on treatment decisions for infantile hemangioma patients.

OBJECTIVE

We aimed to establish a reliable and effective evaluation method for referral.

METHODS

This was a prospective study to determine whether treatment was needed for IH patients after evaluation with the HSS and IHReS.

RESULTS

A total of 266 consecutive referred IH patients were evaluated for the risk of IH, and the treatment rate was 80.8%. The area under the curve (AUC) of the subject receiver operating characteristic curve (ROC) of treatment decision making after referral by the HSS was 0.703 (95% CI: 0.634-0.772), and after referral by the IHReS was 0.892 (95% CI: 0.824-0.960).

LIMITATIONS

This was a single-center study.

CONCLUSIONS

For decisions regarding the treatment of IH patients, the IHReS has a higher efficiency and sensitivity than the HSS. However, the specificity of the IHReS is lower than that of the HSS.

Groundwater Potential Zone Mapping Using Analytical Hierarchy Process and GIS in Muga Watershed, Abay Basin, Ethiopia

Groundwater is an important resource that contributes significantly to the total annual water supply. The purpose of the present study is to assess and delineate the groundwater recharge zone using geospatial technology through an analytical hierarchal process (AHP) method in to the Muga watershed, Abay Basin. Remote sensing satellite images and the corresponding data are used for the preparation of thematic layers, viz., geology, rainfall, slope, soil, curvature, topography wetness index, elevation, drainage density, land use land cover, and lineament density of the study watershed. All thematic layers are integrated with a multicriteria evaluation technique. Weighted overlay index analysis is carried out to give rank for each parameter. The weight is assigned for each thematic layer depending on the AHP technique. The reliability of the output is checked by the calculated consistency index and consistency ratio which is reasonably acceptable (0.044 < 0.1). Verification is done by considering the groundwater well locations in the validation datasets. The receiver operating characteristic curve and area under curve (=82.9%) are used to explore the prediction accuracy.

Prognostic Value of Cell-Surface Vimentin-Positive CTCs in Pediatric Sarcomas

BACKGROUND

Despite advances in care, the 5 year overall survival for patients with relapsed and or metastatic sarcoma remains as low as < 35%. Currently, there are no biomarkers available to assess disease status in patients with sarcomas and as such, disease surveillance remains reliant on serial imaging which increases the risk of secondary malignancies and heightens patient anxiety.

METHODS

Here, for the first time reported in the literature, we have enumerated the cell surface vimentin (CSV+) CTCs in the blood of 92 sarcoma pediatric and adolescent and young adult (AYA) patients as a possible marker of disease.

RESULTS

We constructed a ROC with an AUC of 0.831 resulting in a sensitivity of 85.3% and a specificity of 75%. Additionally, patients who were deemed to be CSV+ CTC positive were found to have a worse overall survival compared to those who were CSV+ CTC negative. We additionally found the use of available molecular testing increased the accuracy of our diagnostic and prognostic tests.

CONCLUSIONS

Our findings indicate that CSV+ CTCs have prognostic value and can possibly serve as a measure of disease burden.

Performance of Scoring Systems in Predicting Clinical Outcomes in Patients with Bacteremia of Listeria monocytogenes: A 9-Year Hospital-Based Study

BACKGROUND

Listeria monocytogenes (LM) is a facultative anaerobe, Gram-positive bacillus which is widely distributed in nature, and can be separated from soil, water, and rotten vegetables. Immunocompetent people are less likely to suffer from LM infection or may only show gastrointestinal symptoms. However, immunocompromised elderly people, pregnant women, and newborns may develop life-threatening invasive infections. The mortality rate of LM infection is as high as 25-30%. The aim of this study is to investigate clinical scores of patients with bacteremia of LM confirmed by one or more blood cultures. We analyzed their demographics and laboratory findings in relation to their clinical outcomes.

MATERIALS AND METHODS

This was a hospital-based retrospective study on patients with bacteremia of LM. Data were collected from the electronic clinical database of Taichung Veterans General Hospital between January 2012 and December 2020. Bacteremia of LM was confirmed by at least one blood culture. Demographics, clinical characteristics, and laboratory data were collected for analysis. A variety of clinical scoring systems were used to predict the clinical outcome.

RESULTS

A total of 39 patients had confirmed bacteremia of LM. Among them, 1 neonatal patient was excluded. The remaining 38 patients were studied. They included 16 males (42.1%) and 22 females (57.9%), with a mean age of 59.9 ± 19.6 years. Their hospital stay averaged 23.3 ± 20.9 days. The in-hospital mortality rate was 36.8%. Mortality in Emergency Department Sepsis (MEDS) Score was 6.6 ± 4.0 for survivors and 12.4 ± 4.4 for non-survivors (P < 0.001). The National Early Warning Score (NEWS) was 3.9 ± 2.8 for survivors and 7.8 ± 3.1 for non-survivors (P = 0.001). Regarding the prediction of mortality risk, the AUC of ROC was 0.829 for MEDS and 0.815 for NEWS.

CONCLUSIONS

MEDS and NEWS were both good predictors of the clinical outcome in LM bacteremic patients. In those with higher scores of MEDS (≥10) and NEWS (≥8), we recommended an early goal-directed therapy and appropriate antibiotic treatment as early as possible to reduce mortality. Further large-scale studies are required to gain a deeper understanding of this disease and to ensure patient safety.

The relationship between severity of varus osteoarthritic knees and contracture of the medial structures

BACKGROUND

Severe varus osteoarthritic knee has possibility of medial structure contracture. There is no report concerning the relationship between severity of varus deformity and contracture of medial structure. We aimed to reveal a threshold angle that could be corrected in proportion to the width of medial osteophyte removal, and to examine correction differences between larger and smaller than the threshold angle in total knee arthroplasty.

METHODS

This study included 27 varus osteoarthritic knees scheduled for total knee arthroplasty (TKA). Each knee was measured the hip-knee-ankle angles (HKA) using a navigation system, at maximum extension, 30˚ and 60˚ flexion before and after osteophyte removal, with and without external 10 N-m valgus torque loads. Subsequently, resected osteophyte widths were measured. Mean correction angle per 1 mm osteophyte removal was calculated, and the threshold angle was calculated using the receiver operating characteristic curve. HKA differences were compared against larger and smaller deformity than the threshold angle.

RESULTS

Mean osteophyte width was 7.1±2.20 mm. Osteophyte removal produced a mean 3.1° correction, which equaled a 0.4° correction per 1 mm osteophyte width removal. The varus deformity threshold angle was 9.5°, however, when comparing the groups larger and smaller than the threshold, there were no significant differences in HKA differences between each step and flexion angle.

CONCLUSIONS

The threshold angle for expected correction with medial osteophyte removal was 9.5˚. However, with no differences in correction between those with larger or smaller than this angle, medial structure contracture seemed to be unrelated to severity of deformity.

Quantitative immunohistochemistry (IHC) analysis of biomarker combinations for human esophageal squamous cell carcinoma

Background

Esophageal squamous carcinoma (ESCC) is one of the most common cancers in developing countries. However, currently there are no specific biomarkers for ESCC. This study evaluated the expression of proliferating cell nuclear antigen (PCNA), tumor suppressor protein p53, epidermal growth factor receptor (EGFR), and vascular endothelial growth factor (VEGF) as biomarkers for ESCC.

Methods

This study included 60 clinical cases (30 ESCC and 30 non-ESCC cases that were confirmed pathologically). The expression of PCNA, p53, EGFR, and VEGF were investigated using a quantitative computerized immunohistochemistry (IHC) method. The expression level of each protein was indicated by a H-score from the quantitative analysis. Receiver operating characteristic curve (ROC) and area under curve (AUC) analyses were performed. The sensitivity and specificity of each individual protein and combinations of the proteins were calculated.

Results

The H-score analysis indicated that expressions of EGFR, PCNA, and VEGF were statistically significantly higher in ESCC than non-ESCC patients; however, p53 was not. The panels of combinations of these proteins were more sensitive than that of any single protein. In the triplicate combination, the AUC prediction probability increased to 0.86, while the single protein AUC prediction probabilities were 0.74 (EGFR), 0.80 (PCNA), and 0.70 (VEGF).

Conclusions

The high expression of PCNA, EGFR, and VEGF suggests that they are potential biomarkers for ESCC. The combination of these biomarkers may provide targets for molecular therapy and molecular imaging.

Diagnostic Utility of IGF2BP1 and Its Targets as Potential Biomarkers in ETV6-RUNX1 Positive B-Cell Acute Lymphoblastic Leukemia

Around 85% of childhood Acute Lymphoblastic Leukemia (ALL) are of B-cell origin and characterized by the presence of different translocations including BCR-ABL1, ETV6-RUNX1, E2A-PBX1, and MLL fusion proteins. The current clinical investigations used to identify ETV6-RUNX1 translocation include FISH and fusion transcript specific PCR. In the current study we assessed the utility of IGF2BP1, an oncofetal RNA binding protein, that is over expressed specifically in ETV6-RUNX1 translocation positive B-ALL to be used as a diagnostic marker in the clinic. Further, public transcriptomic and Crosslinked Immunoprecipitation (CLIP) datasets were analyzed to identify the putative targets of IGF2BP1. We also studied the utility of using the mRNA expression of two such targets, MYC and EGFL7 as potential diagnostic markers separately or in conjunction with IGF2BP1. We observed that the expression of IGF2BP1 alone measured by RT-qPCR is highly sensitive and specific to be used as a potential biomarker for the presence of ETV6-RUNX1 translocation in future.

Lymphocyte percentage and hemoglobin as a joint parameter for the prediction of severe and nonsevere COVID-19: a preliminary study

Background

Coronavirus disease 2019 (COVID-19) has spread rapidly around the world since December, 2019. This study aimed to identify parameters in routine blood tests that could be used to evaluate the severity of coronavirus disease 2019 (COVID-19) and, thus, assist with the clinical prediction of the extent of progression.

Methods

This retrospective study analyzed the epidemiological, clinical symptom, and laboratory examination data of 159 patients diagnosed with COVID-19. The percentage of lymphocytes (Lym%) and hemoglobin (HGB) were integrated into a joint parameter, Lym% & HGB, through binary logistic regression.

Results

Individually, Lym% and HGB decreased gradually with disease progression whereas the joint parameter Lym% & HGB increased gradually with disease progression. When Lym%, HGB, and Lym% & HGB were used to predict the severity of COVID-19, the area under the receiver operating characteristic (ROC) curve (AUC) was 0.89, 0.79, and 0.92, respectively. The dynamic change curves showed that Lym% and HGB continued to decline while Lym% & HGB continued to increase with disease progression in patients with severe COVID. The change in Lym% & HGB was more prominent than those in Lym% and HBG.

Conclusions

The joint parameter Lym% & HGB could serve as an effective tool for differentiating severe and nonsevere COVID-19, and its sensitivity and specificity are higher than those of Lym% or HGB alone.

Association Analysis of Peripheral and CSF Biomarkers in Late Mild Cognitive Impairment

Research shows that late mild cognitive impairment (LMCI) has a high risk of turning into Alzheimer's disease (AD). Due to the invasion of detection methods and physical damage to the patients, it is not a convenient way to diagnose and detect early AD and LMCI by cerebrospinal fluid (CSF) data. So there is an urgent need to find the correlation between peripheral biological data and CSF data in the brain, and to find new diagnostic methods through changes in the peripheral biological data. Studies have shown that during the pathogenesis of LMCI and AD, peripheral immune cells specifically infiltrate into the brain through the blood-brain barrier, causing an imbalance in the brain's immune response and dysregulating the clearance of Aβ in CSF. Therefore, in this paper, canonical correlation analysis (CCA) algorithm is presented to derive the correlation between peripheral and CSF biomarkers based on LMCI peripheral gene expression data and plasma marker information. Firstly, to explore the influence of the infiltration of peripheral blood immune cells on the brain, the abundance of 28 immune cells were calculated by using the gene set enrichment analysis algorithm of LMCI samples. Then, to identify the correlation between biomarkers inside and outside of the brain, we performed CCA to calculate the relationship between CSF and peripheral biomarkers. Results of CCA showed significant correlations between the variable sets of 8 peripheral biomarkers and the variable sets of CSF biomarkers (at 0.794). Finally, according to Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analysis, it was found that the obtained peripheral biomarkers are involved in many immune-related pathways and functions which can be activated in peripheral blood of LMCI patients. Most related genes enriched in immune-related pathways and functions were up-regulated. Through receiver operating characteristic curve (ROC) analysis, it was also found that FP40/FP42 and type 1 T helper can accurately predict the pathological changes of LMCI (at 0.747).

Identifying Potential miRNAs-Disease Associations With Probability Matrix Factorization

In recent years, miRNAs have been verified to play an irreplaceable role in biological processes associated with human disease. Discovering potential disease-related miRNAs helps explain the underlying pathogenesis of the disease at the molecular level. Given the high cost and labor intensity of biological experiments, computational predictions will be an indispensable alternative. Therefore, we design a new model called probability matrix factorization (PMFMDA). Specifically, we first integrate miRNA and disease similarity. Next, the known association matrix and integrated similarity matrix are utilized to construct a probability matrix factorization algorithm to identify potentially relevant miRNAs for disease. We find that PMFMDA achieves reliable performance in the frameworks of global leave-one-out cross validation (LOOCV) and 5-fold cross validation (AUCs are 0.9237 and 0.9187, respectively) in the HMDD (V2.0) dataset, significantly outperforming a few state-of-the-art methods including CMFMDA, IMCMDA, NCPMDA, RLSMDA, and RWRMDA. In addition, case studies show that PMFMDA has good predictive performance for new associations, and the evidence can be identified by literature mining.