Clinical Test Data Research Articles

Optimal dose of misoprostol combined with oxytocin for preventing postpartum hemorrhage in cesarean section: A randomised controlled trial

BackgroundThe study analyzed an optimal misoprostol dosage in prevention of postpartum hemorrhage (PPH). Also evaluated the side effects that might be related to dose of misoprostol. Material and methodsA randomised study was performed in mothers who received cesarean section. Participants were divided into 3 groups of 400, 600 and 800 μg intrauterine misoprostol insertion combined with oxytocin. Clinical characteristics, laboratory testing and operative data were collected. The primary outcome was the amount of intra-operative blood loss and side effects were assigned as a secondary outcome. ResultsThere were 357 eligible cases, 119 cases in each group equally. Baseline characteristics were similar in between groups. Higher misoprostol dosage demonstrated lower blood loss. Mean blood loss was 509.1, 465.7 and 441.1 ml in the 400, 600 and 800 μg misoprostol groups respectively which were significant difference (p value 0.027). Post-hoc pairwise t-tests found that 800 μg group diminished blood loss than 400 μg group (p value 0.004). Intra-operative blood loss ≥500 ml occurred less frequently in patients receiving higher misoprostol dosage (p value 0.035). However, PPH was not identified difference between groups (p value 0.707). Nausea and vomiting were complained in less than 1% while none of the cases exhibited shivering. Pyrexia was identified in all groups, however, there was a trend towards lower dosage related to less percentage of pyrexia. ConclusionsEither 400, 600 or 800 μg of misoprostol can prevent PPH similarly. However, the study prefers 400 μg misoprostol because of minimization the side effects.

Invasive candidiasis among high prevalence neurological patients.

Invasive candidiasis is a severe form of infection. The incidence of invasive fungal infections has increased, due to the increasing number of patients with impaired immunity who are being treated through prolonged stay in hospital facilities. Neurological patient treatment methods such as antimicrobials, corticosteroid, central venous catheter (CVC), total parenteral nutrition, and mechanical ventilation use are associated with common risk factors for invasive candidiasis. Our study demonstrated invasive candidiasis prevalence among neurological patients. A cross-sectional study was done with consecutive sampling of neurological patients who were hospitalized from January 2017 to February 2020 at the Mahar Mardjono National Brain Center Hospital East Jakarta Indonesia. Patients with sepsis, septic shock, or fever (> 38.5 °C), and who had not received antifungals before culture were enrolled in the study. Clinical specimens were obtained from blood, liquor cerebrospinal or other sterile sites, CVC, respiratory tract specimens, and urine or other non-sterile sites. Socio-demographic data, potential risk factors based on previous studies, clinical, and other tests data were obtained from medical records. Classification of invasive candidiasis was according to the Paphitou classification criteria. One hundred and two subjects met the study criteria. The prevalence of invasive candidiasis in neurological patients was 13.7%. All of the isolates were C. parapsilosis. The prevalence of invasive candidiasis was high in the samples studied. The infection was associated with septic shock, tracheostomy, and duration of use of central venous catheter, ventilator, and steroids.

Population pharmacokinetics and Bayesian estimation of mycophenolate mofetil in patients with autoimmune hepatitis.

Mycophenolate mofetil (MMF) is the most widely used second-line agent in autoimmune hepatitis (AIH). Individual dose adjustment of MMF may avoid adverse outcomes while maximizing efficacy. The aim of the present study was to develop population pharmacokinetic (popPK) models and maximum a posteriori Bayesian estimators (MAP-BEs) to estimate mycophenolic acid interdose area under the curve in AIH patients administered MMF using nonlinear mixed effect modelling. We analysed 50 mycophenolic acid PK profiles from 34 different patients, together with some demographic, clinical, and laboratory test data. The median number of plasma samples per profile, immediately preceding and following the morning MMF dose, was 7. PopPK modelling was performed using parametric, top-down, nonlinear mixed effect modelling with NONMEM 7.3. MAP-BEs were developed based on the best popPK model and the best limited sampling strategy selected among several. The pharmacokinetic data were best described by a 2-compartment model, Erlang distribution to describe the absorption phase, and a proportional error. The mean (relative standard error) of popPK parameter estimates of clearance, intercompartmental clearance, central volume and absorption rate with the final model were: 21.6L h-1 (11%), 22.7L h-1 (19%), 35.9L (21%) and 8.7h-1 (9%), respectively. The peripheral volume was fixed to 300 L. The best MAP-BE relied on the limited sampling strategy at 0.33, 1 and 3hours after MMF dose administration and was very accurate (bias =5.6%) and precise (root mean squared prediction error <20%). The precise and accurate Bayesian estimator developed in this study for AIH patients on MMF can be used to improve the therapeutic management of these patients.

Primary Central Nervous System Anaplastic Large Cell Lymphoma, ALK Positive.

Primary central nervous system anaplastic large cell lymphoma, anaplastic lymphoma kinase positive (primary CNS ALCL, ALK+) is a rare CNS lymphoma whose description is limited to case reports. These tumors have a variable clinical course, and prognosis is primarily determined by age. We present the largest case series to date of primary CNS ALCL, ALK+, with observational data. A retrospective search of multiple academic centers was performed to identify cases of primary CNS ALCL, ALK+. We also performed a review of published cases of primary CNS ALCL, ALK+. Clinical history, radiography, pathology, and genetic testing data were obtained to determine the prognostic implications in the context of clinical course. We identified three cases of primary CNS ALCL, ALK+ from our databases. A literature review identified 30 published reports of 31 individual cases. Clinical features for the combined 34 cases included a median age of 18.5 years, with a male to female ratio of 4.7:1, and the most common symptom was headache. Genetic studies demonstrated an ALK rearrangement by fluorescence in situ hybridization, and a gene fusion assay confirmed an NPM1-ALK gene fusion in one case. We present the largest case series to date of a rare primary CNS lymphoma with additional diagnostic and clinical information.

Functional Cognitive Disorder Presents High Frequency and Distinct Clinical Profile in Patients With Low Education.

IntroductionFunctional Cognitive Disorder (FCD) is a non-degenerative, common cause of memory complaint in patients with high educational levels. FCD has been insufficiently described in individuals with low education. Here, we investigated the frequency of FCD among individuals with low education.MethodsWe analyzed retrospectively all new referrals from primary care to a tertiary memory clinic from 2014 to 2021. Final diagnosis, diagnostic work-up, clinical and cognitive testing data were compared between FCD and other diagnoses, grouped as Neurodegenerative Disorders (NDD). A regression model was used to assess the effect of education on the diagnosis. Data is shown in Mean [SD].ResultsA total of 516 individuals (70.76 [10.3] years) with low educational attainment (4.5 [3.94] years) were divided into FCD (146, 28.3%) and NDD. Compared with NDD, FCD patients showed lower age at presentation (66.2 [9.4] vs. 72.6 [10.2], p < 0.001), higher Mini-Mental State Examination (MMSE) scores (22.4 [6.2] vs. 14.7 [7.8], p < 0.001) and Geriatric Depression Scale (GDS) scores (7.4 [5.4] vs. 5.3 [3.7], p = 0.0001).DiscussionSurprisingly, FCD was the most frequent diagnosis in a low educational setting. However, education was not associated with FCD. Individuals presenting FCD showed a distinct clinical profile, including younger age and higher depressive scores. Strategies to identify FCD in primary care settings may benefit both patients and healthcare systems.

Baseline neutrophil\u2013lymphocyte ratio can be associated with hematoma expansion in patients with intracerebral hemorrhage: a retrospective observational study

BackgroundHematoma expansion can be related to increased mortality and poor clinical outcomes in patients with intracerebral hemorrhage (ICH). So, early identification and prevention of hematoma expansion can be considered as an important therapeutic aim. This study aimed to evaluate the hypothesis that the neutrophil to lymphocyte ratio (NLR) is associated with hematoma expansion in ICH patients.MethodsWe retrospectively evaluated the clinical data of a total of 221 patients with ICH who were treated in our department between April 2018 and April 2021. The demographic, clinical, radiological, and laboratory test data including the NLR upon admission were investigated. A binary logistic regression analysis was used to assess the independent associations between different variables and hematoma expansion.ResultsA total of 221 patients with ICH were included. There were 122 (55.2%) males and 99 (44.8%) females. The mean age (years) at admission was 66.43 ± 8.28.The hematoma expansion occurred in 57 (25.8%) cases. The results of the multivariate analysis showed that hematoma volume at baseline (OR, 3.12; 95% CI 1.78–5.02; P < 0.001), admission systolic blood pressure (OR, 2.87; 95% CI 1.79–4.34; P = 0.013), Glasgow Coma Scale (GCS) (OR, 1.94; 95% CI 1.45–2.93; P = 0.020), and NLR (OR, 1.74; 95% CI 1.16–2.60; P = 0.032) were correlated with hematoma expansion in these patients.ConclusionsOur findings suggest that NLR can be a predictor of hematoma expansion in patients with ICH. This cost-effective and easily available biomarker could be used to early prediction of hematoma expansion in these patients.

Monitoring COVID-19 spread in Prague local neighborhoods based on the presence of SARS-CoV-2 RNA in wastewater collected throughout the sewer network

Many reports have documented that the presence of SARS-CoV-2 RNA in the influents of municipal wastewater treatment plants (WWTP) correlates with the actual epidemic situation in a given city. However, few data have been reported thus far on measurements upstream of WWTPs, i.e. throughout the sewer network. In this study, the monitoring of the presence of SARS-CoV-2 RNA in Prague wastewater was carried out at selected locations of the Prague sewer network from August 2020 through May 2021. Various locations such as residential areas of various sizes, hospitals, city center areas, student dormitories, transportation hubs (airport, bus terminal), and commercial areas were monitored together with four of the main Prague sewers. The presence of SARS-CoV-2 RNA was determined by reverse transcription – multiplex quantitative polymerase chain reaction (RT-mqPCR) after the precipitation of nucleic acids with PEG 8,000 and RNA isolation with TRIzol™ Reagent. The number of copies of the gene encoding SARS-CoV-2 nucleocapsid (N1) per liter of wastewater was compared with the number of officially registered COVID-19 cases in Prague. Although the data obtained by sampling wastewater from the major Prague sewers were more consistent than those obtained from the small sewers, the correlation between wastewater-based and clinical-testing data was also good for the residential areas with more than 7,000 registered inhabitants. It was shown that monitoring SARS-CoV-2 RNA in wastewater sampled from small sewers could identify isolated occurrences of COVID-19-positive cases in local neighborhoods. This can be very valuable while tracking COVID-19 hotspots within large cities.

Estimating SARS-CoV-2 prevalence from large-scale wastewater surveillance: insights from combined analysis of 44 sites in England

PurposeAccurate surveillance of the COVID-19 pandemic can be weakened by under-reporting of cases, particularly due to asymptomatic or pre-symptomatic infections, resulting in bias. Quantification of SARS-CoV-2 RNA in wastewater (WW) can be used to infer infection prevalence, but uncertainty in sensitivity and considerable variability has meant that accurate measurement remains elusive.Methods & MaterialsData from 44 sewage sites in England, covering 31% of the population, are used in this analysis where samples are available from July 2020 to present day. Samples include the raw SARS-CoV-2 gene copy number and associated meta-data. To establish the sensitivity and specificity of the WW data, we compare to population representative prevalence surveys available across England (the ONS Covid Infection Survey - CIS). The WW data were mapped to sub-regional data of the CIS and fitted using mathematical modelling. First, a phenomenological model was developed to model how infected individuals shed SARS-CoV-2 into WW and how the markers may degrade in time and compare this to the data. Second, we develop a model to estimate SARS-CoV-2 prevalence directly from WW data which is trained on the CIS data.ResultsData from 44 sewage sites in England, shows that SARS-CoV-2 prevalence is estimated to within 1.1% of estimates from representative prevalence surveys (with 95% confidence). Using machine learning and phenomenological models, differences between sampled sites, particularly the WW flow rate, influence prevalence estimation and require careful interpretation. SARS-CoV-2 signals in WW appear 4-5 days earlier in comparison to clinical testing data but are coincident with prevalence surveys suggesting that WW surveillance can be a leading indicator for asymptomatic viral infections.ConclusionWastewater-based epidemiology complements and strengthens traditional surveillance, with significant implications for public health. Using WW to quantify infection prevalence requires knowledge of additional meta-data and outbreak detection needs to account for unexplained aberrations in WW data to improve reliability

Gender Related Differences in the Clinical Presentation of Hypertrophic Cardiomyopathy-An Analysis from the SILICOFCM Database.

Background and Objectives: Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease that affects approximately 1 in 500 people. Due to an incomplete disease penetrance associated with numerous factors, HCM is not manifested in all carriers of genetic mutation. Although about two-thirds of patients are male, it seems that female gender is associated with more severe disease phenotype and worse prognosis. The objective of this study was to evaluate the gender related differences in HCM presentation. Materials and Methods: This study was conducted as a part of the international multidisciplinary SILICOFCM project. Clinical information, laboratory analyses, electrocardiography, echocardiography, and genetic testing data were collected for 362 HCM patients from four clinical centers (Florence, Newcastle, Novi Sad, and Regensburg). There were 33% female patients, and 67% male patients. Results: Female patients were older than males (64.5 vs. 53.5 years, p < 0.0005). The male predominance was present across all age groups until the age of 70, when gender distribution became comparable. Females had higher number of symptomatic individuals then males (69% vs. 52%, p = 0.003), most frequently complaining of dyspnea (50% vs. 30%), followed by chest pain (30% vs. 17%), fatigue (26% vs. 13%), palpitations (22% vs. 13%), and syncope (13% vs. 8%). The most common rhythm disorder was atrial fibrillation which was present in a similar number of females and males (19% vs. 13%, p = 0.218). Levels of N-terminal pro-brain natriuretic peptide were comparable between the genders (571 vs. 794 ng/L, p = 0.244). Echocardiography showed similar thickness of interventricular septum (18 vs. 16 mm, p = 0.121) and posterolateral wall (13 vs. 12 mm, p = 0.656), however, females had a lower number of systolic anterior motion (8% vs. 16%, p = 0.020) and other mitral valve abnormalities. Conclusions: Female patients are underrepresented but seem to have a more pronounced clinical presentation of HCM. Therefore, establishing gender specific diagnostic criteria for HCM should be considered.

The value of clinical-ultrasonographic feature model to predict the severity of secondary hyperparathyroidism

Objectives To analyze conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) features in patients with secondary hyperparathyroidism (SHPT) and to evaluate the clinical-ultrasonographic feature based model for predicting the severity of SHPT. Methods From February 2016 to March 2021, a total of 59 patients (age 51.3 ± 11.7 years, seCr 797.8 ± 431.7 μmol/L, iPTH 1535.1 ± 1063.9 ng/L) with SHPT (including 181 parathyroid glands (PTGs)) without the history of intact parathyroid hormone (iPTH)-reducing drugs using were enrolled. The patients were divided into the mild SHPT group (mSHPT, iPTH <800 ng/L) and the severe SHPT group (sSHPT, iPTH ≥ 800 ng/L) according to the serum iPTH level. The clinical test data of patients were collected and CUS and CEUS examinations were performed for every patient. Multivariable logistic regression model according to clinical-ultrasonographic features was adopted to establish a nomogram. We performed K-fold cross-validation on this nomogram model and nomogram performance was determined by its discrimination, calibration, and clinical usefulness. Results There were 19 patients in the mSHPT group and 40 patients in the sSHPT group. Multivariable logistic regression indicated serum calcium, serum phosphorus and total volume of PTGs were independent predictors related with serum iPTH level. Even though CEUS score of wash-in and wash-out were showed related to severity of SHPT in univariate logistic regression analysis, they were not predictors of SHPT severity (p = 0.539, 0.474 respectively). The nomogram developed by clinical and ultrasonographic features showed good calibration and discrimination. The accuracy and the area under the curve (AUC), positive predictive value (PPV), negative predictive value (NPV) and accuracy of this model were 0.888, 92.5%, 63.2% and 83.1%, respectively. When applied to internal validation, the score revealed good discrimination with stratified fivefold cross-validation in the cohort (mean AUC = 0.833). Conclusions The clinical-ultrasonographic features model has good performance for predicting the severity of SHPT.

Monitoring SARS-CoV-2 in wastewater during New York City's second wave of COVID-19: sewershed-level trends and relationships to publicly available clinical testing data

SARS-CoV-2 viral loads in New York City were significantly correlated with clinical case rates in corresponding sewersheds.

Serum NLRP3: A biomarker for identifying high-risk septic patients

Over-activation of the NLRP3 inflammasome can lead to sepsis. NLRP3 is an essential protein in the classical pathway of pyroptosis. This study assessed the use of serum NLRP3 level as a potential inflammatory biomarker in septic patients. Patients were categorized into five groups: healthy controls (n=30), ICU controls (n=22), infection (n=19), septic non-shock (n=33), and septic shock (n=83). Serum NLRP3 levels were measured by enzyme-linked immunosorbent assay for all patients upon enrollment. Clinical parameters and laboratory test data (APACHE II, SOFA, and lactate) were also assessed. Moreover, the ability of serum NLRP3 levels to predict sepsis was determined by the area under the curve (AUC) analysis. The NLRP3 levels in the septic shock group was significantly higher (431.89, 386.61-460.21pg/mL) than that in the healthy control group (23.24, 9.38-49.73pg/mL), ICU control group (74.82, 62.71-85.93pg/mL), infection group (114.34, 99.21-122.56pg/mL), and septic non-shock group (136.99, 128.80-146.98pg/mL; P＜0.001 for all comparisons). Additionally, the AUC indicated that the ability of serum NLRP3 levels to predict sepsis and septic shock incidences was not lower than that of the SOFA score. Patients with higher NLRP3 serum levels (>147.72pg/mL) had significantly increased 30-day mortality rate. NLRP3 is useful for the early identification of high-risk septic patients, particularly septic shock patients. Moreover, elevated NRLP3 levels could result in poor septic prediction outcomes.

Development and Validation of a Nomogram Model for Lung Cancer Based on Radiomics Artificial Intelligence Score and Clinical Blood Test Data

Development and Validation of a Nomogram Model for Lung Cancer Based on Radiomics Artificial Intelligence Score and Clinical Blood Test Data

Abnormal Sodium and Chlorine Level Is Associated With Prognosis of Lung Cancer Patients

Objective: The imbalance of sodium and chloride ions occurs frequently in patients with lung cancer. However, the correlation between ion concentration change and patients prognosis have not been studied thoroughly. Our research will fill the gap, especially for high ion concentration. Methods: We retrospectively studied inpatients diagnosed with primary NSCLC and treated between May 2015 and July 2017. The basic clinical information and blood test data before and after treatment were collected. According to the clinical reference range of normal ion concentration, the patients were divided into three groups: low, normal and high level. Kaplan-Meier curve was used to analyze the difference of overall survival (OS) prognosis among each group. The correlation between ion concentration and other clinical parameters was further analyzed. Finally, a prognostic nomogram model was established by LASSO-COX method. Results: In the 1237 patients cohort, the median follow-up period was 861 days (range 3-2128 days). Firstly, 6 serum ions were included in the study, and only sodium (Na) and chloride (cl) ions were significantly associated with OS. Low level patients were found nearly just in III-IV stage patients, in contrast, high level patients distribute evenly in all stages. Then, correlation analysis showed that increased Na and cl concentrations were associated with decreased neutrophil number and elevated lymphocyte proportion. Finally, prognostic model analysis showed that cl is a crucial parameter. Conclusion: Serum Na and cl ion concentrations are closely related to the OS of lung cancer patients, and should be considered as clinical prognostic factors.

Pleuroparenchymal fibroelastosis in systemic sclerosis-associated interstitial lung disease.

To explore the frequency and clinical associations of radiologic pleuroparenchymal fibroelastosis (PPFE) in patients with systemic sclerosis-associated interstitial lung disease (SSc-ILD). In this single-center retrospective study, high resolution computed tomography (HRCT) images of 105 patients with SSc-ILD were examined for the presence of PPFE. Demographic, clinical, laboratory, and pulmonary function test (PFT) data of patients with and without PPFE were compared. PPFE was detected in 19 (18.1%) patients ('definite PPFE' in 13 and 'consistent with PPFE' in 6 patients). Patients with PPFE had higher age and longer disease duration than PPFE (-) patients (p < 0.05 for both). Radiologic usual interstitial pneumoniae (UIP) pattern was more frequent (26.3% vs. 4.7%, p = 0.01) and median force vital capacity (FVC) was lower in patients with PPFE (64% vs. 82%, p = 0.005). Spontaneous pneumothorax developed in one patient with PPFE. More deaths occured in PPFE (+) group during follow-up (31% vs. 11%, p = 0.04).

Combination of Neutrophil-to-Lymphocyte Ratio and Red Cell Distribution Width With Serum Tumor Markers for the Differential Diagnosis of Breast Cancer and its Association With Pathological Features and Molecular Types

ObjectiveTo explore the neutrophil-to-lymphocyte ratio (NLR), red cell distribution width (RDW) and serum tumor markers as differential diagnostic markers of breast cancer (BC) and breast fibroadenoma (FA) and their associations with histopathological indicators and molecular typing in BC patients. MethodsWe collected pathological and routine clinical test data [NLR, RDW, serum tumor markers (CEA, CA15-3, CA125, CA19-9)] of 653 patients with BC and 100 patients with FA. After identifying indicators with significant inter-group differences, we used ROC curves to determine clinically significant cutoff values. Binary logistic regression analyses and ROC curves were used to analyze combined models for the differential diagnosis of BC and FA. Ordinal multinomial logistic regression analysis was used to explore correlations between routine clinical test indicators and pathological BC features. ResultsThe BC and FA groups had significantly different CEA, NLR, and CA19-9 levels (P < .05), with respective areas under the curve (AUC) of 0.799, 0.747, and 0.711 for differentiating BC from FA and respective optimal cutoff values of 1.35 ng/mL, 1.58, and 8.55 U/mL. Binary logistic regression and ROC curve analysis showed that CEA was superior to the other 2 factors for the differential diagnosis of BC and FA. whereas the combined use of all three indicators was diagnostically most effective (AUC = 0.886; 95% confidence interval: 0.838–0.933, P = .000; sensitivity and/or specificity: 76.5%/88.9%). Ordered multinomial logistic regression analysis showed that NLR, CEA, and CA15-3 correlated positively with BC TNM staging; RDW was negatively correlated with BC histological grade; RDW, CA15-3 and CA125 were obviously associated with BC molecular typing. ConclusionThe combination of CEA, NLR, and CA19-9 may be used to screen and diagnose BC. NLR, CEA and CA15-3 are related to the TNM staging of BC. RDW is related to BC histological grading. RDW, CA15-3 and CA125 are related to BC molecular typing.

A Data Analytics Approach for Revealing Influencing Factors of HPV-Related Cancers From Population-Level Statistics Data

Human papillomavirus (HPV) is considered as one of the major causes of multiple cancers, including cervical, anal, and vaginal cancers. Some studies analyzed the infection patterns of cancers caused by HPV using individual clinical test data, which is resource and time expensive. In order to facilitate the understanding of cancers caused by HPV, we propose to use data analytics methods to reveal the influencing factors from the population-level statistics data, which is available more easily. Particularly, we demonstrate the effectiveness of data analytics approach by introducing a predictive analytics method in studying the risk factors of cervix cancer in the United States. Besides accurate prediction of the number of infections, the predictive analytics method discovers the population statistic factors that most affect the cervical cancer infection pattern. Furthermore, we discuss the potential directions in developing more advanced data analytics approaches in studying cancers caused by HPV.

A Colorectal Cancer 3D Bioprinting Workflow as a Platform for Disease Modeling and Chemotherapeutic Screening.

Colorectal cancer (CRC) is the third most common malignancy and has recently moved up to the second leading cause of death among carcinomas. Prognosis, especially for advanced diseases or certain molecular subtypes of CRC, remains poor, which highlights the urgent need for better therapeutic strategies. However, currently, as little as 0.1% of all drugs make it from bench to bedside because of the inherently high false-positive and false-negative rates of current preclinical and clinical drug testing data. Therefore, the success of developing novel treatment agents lies in the introduction of improved preclinical disease models which resemble in vivo carcinomas closer, possess higher predictive properties, and offer opportunities for individualized therapies. Aiming to address these needs, we have established an affordable, flexible, and highly reproducible 3D bioprinted CRC model. The histological assessment of Caco-2 cells in 3D bioprints revealed the formation of glandular-like structures which show greater pathomorphological resemblance to tumors than monolayer cultures do. RNA expression profiles in 3D bioprinted cells were marked by upregulation of genes involved in cell adhesion, hypoxia, EGFR/KRAS signaling, and downregulation of cell cycle programs. Testing this 3D experimental platform with three of the most commonly used chemotherapeutics in CRC (5-fluoruracil, oxaliplatin, and irinotecan) revealed overall increased resistance compared to 2D cell cultures. Last, we demonstrate that our workflow can be successfully extended to primary CRC samples. Thereby, we describe a novel accessible platform for disease modeling and drug testing, which may present an innovative opportunity for personalized therapeutic screening.

Concomitant genetic alterations are associated with plasma D-dimer level in patients with non-small-cell lung cancer.

Objective: D-dimer is correlated to the poor prognosis of non-small-cell lung cancer. The study aimed to investigate the association between plasma D-dimer and concomitant mutations in non-small-cell lung cancer. Methods: A total of 517 non-small-cell lung cancer patients were recruited and tested for ALK, BRAF, EGFR, HER2/ERBB2, KRAS, MET, PIK3CA, RET and ROS1 mutationby next-generation sequencing. Multiple gene mutation information, clinical baseline data and laboratory test data were analyzed statistically. Results: All patients were divided into three groups: wild-type group, single-gene mutation group and concomitant mutation group. The analysis of D-dimer, uric acid, gender, family history, smoking history, histology and distant metastasis all showed significant differences in the three groups (p<0.05). D-dimer was considered as a risk factor for concomitant mutations according to the unordered multiple logistic regression analysis. The receiver operating characteristic curve analysis indicated that D-dimer had an important predictive value for the occurrence of concomitant mutations (area under the curve [AUC]: 0.94; sensitivity: 88.71%; specificity: 86.46). There was significantly shorter median progression-free survival in the concomitant mutation group compared with the single mutation group (7.70 months vs 14.00 months; p=0.0133). Conclusion: Plasma D-dimer is significantly associated with concomitant mutations and may be regarded as a potent predictor of concomitant mutations for non-small-cell lung cancer patients.

The significant impact of Coronavirus disease 2019 (COVID-19) on in-hospital mortality of elderly patients with moderate to severe traumatic brain injury: A retrospective observational study

BackgroundTraumatic brain injury (TBI) is one of the main causes of death and disability among the elderly patient population. This study aimed to assess the predictors of in-hospital mortality of elderly patients with moderate to severe TBI who presented during the Coronavirus disease 2019 (COVID-19) pandemic. MethodsIn this retrospective analytical study, all elderly patients with moderate to severe TBI who were referred to our center between March 2nd, 2020 to August 1st, 2020 were investigated and compared against the TBI patients receiving treatment during the same time period within the year 2019. Patients were followed until discharge from the hospital or death. The demographic, clinical, radiological, and laboratory test data were evaluated. Data were analyzed using SPSS-21 software. FindingsIn this study, 359 elderly patients were evaluated (n = 162, Post-COVID-19). Fifty-four patients of the cohort had COVID-19 disease with a mortality rate was 33.3%. The patients with COVID-19 were 5.45 times more likely to expire before discharge (P < 0.001) than the TBI patients who were not COVID-19 positive. Other variables such as hypotension (OR, 4.57P < 0.001), hyperglycemia (OR, 2.39, P = 0.002), and use of anticoagulant drugs (OR, 2.41P = 0.001) were also associated with in-hospital death.According to the binary logistic regression analysis Age (OR, 1.72; 95% CI: 1.26–2.18; P = 0.033), Coronavirus infection (OR, 2.21; 95% CI: 1.83–2.92; P = 0.011) and Glasgow Coma Scale (GCS) (OR, 3.11; 95% CI: 2.12–4.53; P < 0.001) were independent risk factors correlated with increased risk of in-hospital mortality of elderly patients with moderate to severe TBI. ConclusionOur results showed that Coronavirus infection could increase the risk of in-hospital mortality of elderly patients with moderate to severe TBI significantly.