Predictors for extubation failure in COVID-19 patients using a machine learning approach.

INTRODUCTION: Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. METHODS: We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. RESULTS: A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure. CONCLUSION: The most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records.

The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients.

BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. METHODS: A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract-transform-load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. RESULTS: Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. CONCLUSIONS: In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.

MicroRNAs expression profiles as biomarkers and therapeutic tools in Turkish patients with chronic myeloid leukemia.

AIM: In 95 % of Chronic myeloid leukemia (CML) patients, chromosomal translocation resulting in the formation of the Philadelphia (Ph) chromosome (t:9;22) is observed, which in turn leads to the formation of the BCR-ABL fusion gene. MicroRNAs (miRNAs) are a group of small and non-coding RNAs modulating gene expression via binding to the target mRNAs. We aimed to characterize the expression profiles of various miRNAs in different stages of Ph(+) CML patients. METHODS: This case-controlled study was conducted in 75 CML patients and 25 healthy controls. The subjects were categorized into 4 groups; newly diagnosed patients, treatment-response patients, treatment-failure patients, and healthy controls. Expressions of miRNAs was analyzed by RT-PCR. RESULTS: miR-150 expression was downregulated in the treatment failure patients compared to the control group (p = 0.003212) while miRNA 148b expression up-regulated in the treatment failure patients than the control group (p = 0.038016). miR-10a expression was up-regulated in newly diagnosed and treatment response patients compared to control group (p = 0.003934, p = 0.000292, respectively). It was found that miR-10a expression increased 11.17- fold in newly diagnosed patients and 9.82-fold in treatment response patients than in the control group. CONCLUSION: Our data suggest that expression profiles of miR-10a, miR-150, and miRNA 148b were correlated as biomarker and therapeutic tool in Turkish patients with CML (Tab. 2, Fig. 1, Ref. 30).

Epidemiology and cost of burns in emergency department during Syrian civil war.

BACKGROUND: We aimed to emphasize the importance of regional hospitals' capacities and emergency services for burn patients in war and disaster situations, in addition to assessing the costs and clinical situations of seriously burned patients who have come to the emergency service due to the bomb and heater burst during the Syrian civil war. METHODS: In this study, we analyzed these 217 burn patients and analyzed these patients' data for retrospective analysis. RESULTS: Burn patients were more often seen during the winter months. The majority of the patients were children, young adults and male (1‒16 age, 95 % burn, 44 %,17‒40 age 94 % burn, 44 %, ≥ 41‒65 age, 28 % burn, 12 %). The most common body surface burns ≥ 20 % body surface in surviving patients n = 184, 78 % were determined. 14 of the burned patients died within the first 24 hours. The total cost of the burned patients in the emergency unit was observed to be 33.4 ± 25.9 Turkish Lira (10.2‒6813.2). CONCLUSION: The present study showed that burn patients need much longer treatment time. The need for trained personnel in case of mass disasters and warfare, the identification of burn intensive care units and hospitals to be referred is important (Tab. 2, Fig. 4, Ref. 23).

Prognostic factors in elderly patients with advanced non-small cell lung cancer treated with first-line cisplatin-based chemotherapy: a retrospective analysis of single institution.

PURPOSE: Non-small cell lung cancer (NSCLC) makes up 80-85% of all lung cancers cases. Lung cancer in older individuals is frequently undertreated. Patients eligible for cisplatin- based chemotherapy should be selected carefully. The aim of this retrospective single-center study was to evaluate prognostic factors for overall survival (OS) in elderly (≥65 years) patients with advanced NSCLC who received first-line cisplatin-based chemotherapy. METHODS: We retrospectively reviewed 110 elderly patients with locally advanced or metastatic NSCLC who had been administered cisplatin-based first-line chemotherapy between December 2004 and November 2011. Seventeen potential prognostic variables were chosen for analysis. Univariate and multivariate analyses were conducted to identify prognostic factors associated with OS. RESULTS: Among the 17 variables of univariate analysis, 4 were identified to have prognostic significance for OS: comorbidities (p<0.001), Eastern Cooperative Oncology Group (ECOG) performance status (PS) (p=0.02), first-line chemotherapy cycles (p<0.001) and serum albumin level (p=0.04). Multivariate analysis showed that only ECOG PS (p=0.01) was independent prognostic factor for OS. CONCLUSION: PS was important prognostic factor in elderly patients with advanced NSCLC. The findings of this study may facilitate pretreatment prediction of OS and therefore can be used for selecting the most appropriate treatment for elderly patients.

Prognostic value of fluorine-18 fluorodeoxyglucose positron emission tomography in patients with advanced non-small cell lung cancer: single center experience.

PURPOSE: The purpose of this retrospective single-center study was to evaluate the prognostic implication on overall survival (OS) of the F-18 FDG PET scan in locally advanced or metastatic non small cell lung cancer (NSCLC) patients. METHODS: We retrospectively reviewed 120 locally advanced or metastatic NSCLC patients (December 2004-November 2011) treated/followed at the Dicle University, School of Medicine, Department of Medical Oncology. SUVmax and other potential prognostic variables (n=18) were chosen for analysis. Univariate and multivariate analyses were conducted to identify prognostic factors for OS. RESULTS: Among 18 variables of univariate analysis, 6 were identified to bear prognostic significance: sex (p=0.01), performance status (PS) (p =0.03), stage (p=0.04), bone metastases (p=0.002), serum albumin (p=0.01) and blood glucose level (p=0.03). Multivariate analysis showed that PS, bone metastases and serum albumin level were independent prognostic factors for OS (p=0.01, p=0.004, p=0.003, respectively). CONCLUSION: PS, serum albumin levels and bone metastases were independent prognostic factors, while FDG uptake of the primary lesion was not associated with prognosis of OS in locally advanced or metastatic NSCLC patients.

Relationship between vitamin D deficiency and thrombus load in patients with ST-elevation myocardial infarction.

OBJECTIVE: Clinical studies detecting the increase in thrombotic events with vitamin D deficiency note the relationship between vitamin D and thrombosis. This study aims at evaluating the relationship between serum vitamin D levels and coronary thrombus burden. PATIENTS AND METHODS: We retrospectively evaluated 77 patients with ST-elevated myocardial infarction (STEMI). Serum vitamin D levels, degree of coronary thrombus, Thrombolysis in Myocardial Infarction (TIMI) frame count and the extent and severity of atherosclerosis in coronary arteries were also measured in all cases. Patients were divided into 2 groups, according to thrombus load. RESULTS: The rate of vitamin D deficiency in the study population was 79.22% (< 20 ng/mL). Vitamin D levels were significantly higher in patients with a mild thrombus load than in patients with a severe thrombus load (16 vs. 13.95 p = 0.018). Gensini scores were significantly higher in patients with a severe thrombus burden than in patients with a mild thrombus burden (42 vs. 54.5 p = 0.014). There was a low negative correlation between vitamin D levels and thrombus burden classification grades (r = -0.304, p = 0.007), Cx TIMI frame counts (r = -0.402, p < 0.001), and RCA TIMI frame counts (r = -0.479, p < 0.001). There was a moderate negative correlation between serum vitamin D levels and LAD TIMI frame count (r = -0.507, p < 0.001). CONCLUSIONS: The results of our study showed that low 25(OH)D3 levels are an independent predictor of high coronary artery thrombus load and post-procedural TIMI frame count increase in patients with STEMI undergoing primary percutaneous coronary intervention.

A novel intermediate coronary artery stenosis severity method: Fluoroscopy-Assisted Measurement of Coronary Volume Ratio (The FLAME FFR Trial).

OBJECTIVE: The fluoroscopy-assisted coronary volume measurement (FLASH) algorithm, based on contrast passage time and vessel size, is a simple and non-invasive method of assessing coronary blood volume. The present study evaluated the diagnostic performance of FLASH flow ratio-derived fractional flow reserve (FFRFLAME) compared to wire-based FFR (FFRWB). PATIENTS AND METHODS: FFRFLAME was defined as the ratio of FLASH at baseline to maximal hyperemia. Forty-eight patients with one intermediate coronary lesion (30-70% by angiographic visual estimation) were enrolled in this cross-sectional study. FFRFLAME and FFRWB measurements were collected in each patient. Intravenous administration of adenosine was used to achieve maximal hyperemia. The Pearson correlation coefficient and receiver operating characteristic analysis were performed to determine the predictive accuracy of FFRFLAME. RESULTS: The average age of the patients was 58 years, and 43% (21 of 48) were female. The predominant vessel assessed was the left anterior descending artery system (87.5%). The mean FFRWB was 0.91 ± 0.05 at baseline and 0.83 ± 0.07 at the hyperaemic level, with 27% (13 of 48) of patients having an FFRWB of ≤0.80. For each patient, the mean FFRFLAME was 0.668 ± 0.17. The mean FFRFLAME was 0.85 ± 0.16 for patients having an FFRWB of ≤0.80. A strong relationship existed between FFRFLAME and FFRWB (Pearson's r = - 0.765 p<0.001). The optimal cutoff value of the functional significance of coronary artery stenosis for FFRFLAME was determined to be > 0.84 (AUC: 0.899, 84% sensitivity and 97% specificity) when the FFRWB cutoff value for significant lesions was ≤ 0.80. CONCLUSIONS: FFRFLAME, applied to coronary angiography without the need for an invasive pressure wire, can be a beneficial index for appropriate lesion selection in coronary artery diseases.

Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning.

BACKGROUND: For mechanically ventilated critically ill COVID-19 patients, prone positioning has quickly become an important treatment strategy, however, prone positioning is labor intensive and comes with potential adverse effects. Therefore, identifying which critically ill intubated COVID-19 patients will benefit may help allocate labor resources. METHODS: From the multi-center Dutch Data Warehouse of COVID-19 ICU patients from 25 hospitals, we selected all 3619 episodes of prone positioning in 1142 invasively mechanically ventilated patients. We excluded episodes longer than 24 h. Berlin ARDS criteria were not formally documented. We used supervised machine learning algorithms Logistic Regression, Random Forest, Naive Bayes, K-Nearest Neighbors, Support Vector Machine and Extreme Gradient Boosting on readily available and clinically relevant features to predict success of prone positioning after 4 h (window of 1 to 7 h) based on various possible outcomes. These outcomes were defined as improvements of at least 10% in PaO2/FiO2 ratio, ventilatory ratio, respiratory system compliance, or mechanical power. Separate models were created for each of these outcomes. Re-supination within 4 h after pronation was labeled as failure. We also developed models using a 20 mmHg improvement cut-off for PaO2/FiO2 ratio and using a combined outcome parameter. For all models, we evaluated feature importance expressed as contribution to predictive performance based on their relative ranking. RESULTS: The median duration of prone episodes was 17 h (11-20, median and IQR, N = 2632). Despite extensive modeling using a plethora of machine learning techniques and a large number of potentially clinically relevant features, discrimination between responders and non-responders remained poor with an area under the receiver operator characteristic curve of 0.62 for PaO2/FiO2 ratio using Logistic Regression, Random Forest and XGBoost. Feature importance was inconsistent between models for different outcomes. Notably, not even being a previous responder to prone positioning, or PEEP-levels before prone positioning, provided any meaningful contribution to predicting a successful next proning episode. CONCLUSIONS: In mechanically ventilated COVID-19 patients, predicting the success of prone positioning using clinically relevant and readily available parameters from electronic health records is currently not feasible. Given the current evidence base, a liberal approach to proning in all patients with severe COVID-19 ARDS is therefore justified and in particular regardless of previous results of proning.

Dynamic prediction of mortality in COVID-19 patients in the intensive care unit: A retrospective multi-center cohort study.

Background: The COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among COVID-19 patients could assist decision making in the ICU setting. In this work, we report on the development and validation of a dynamic mortality model specifically for critically ill COVID-19 patients and discuss its potential utility in the ICU. Methods: We collected electronic medical record (EMR) data from 3222 ICU admissions with a COVID-19 infection from 25 different ICUs in the Netherlands. We extracted daily observations of each patient and fitted both a linear (logistic regression) and non-linear (random forest) model to predict mortality within 24 h from the moment of prediction. Isotonic regression was used to re-calibrate the predictions of the fitted models. We evaluated the models in a leave-one-ICU-out (LOIO) cross-validation procedure. Results: The logistic regression and random forest model yielded an area under the receiver operating characteristic curve of 0.87 [0.85; 0.88] and 0.86 [0.84; 0.88], respectively. The recalibrated model predictions showed a calibration intercept of -0.04 [-0.12; 0.04] and slope of 0.90 [0.85; 0.95] for logistic regression model and a calibration intercept of -0.19 [-0.27; -0.10] and slope of 0.89 [0.84; 0.94] for the random forest model. Discussion: We presented a model for dynamic mortality prediction, specifically for critically ill COVID-19 patients, which predicts near-term mortality rather than in-ICU mortality. The potential clinical utility of dynamic mortality models such as benchmarking, improving resource allocation and informing family members, as well as the development of models with more causal structure, should be topics for future research.

Assess and validate predictive performance of models for in-hospital mortality in COVID-19 patients: A retrospective cohort study in the Netherlands comparing the value of registry data with high-granular electronic health records.

PURPOSE: To assess, validate and compare the predictive performance of models for in-hospital mortality of COVID-19 patients admitted to the intensive care unit (ICU) over two different waves of infections. Our models were built with high-granular Electronic Health Records (EHR) data versus less-granular registry data. METHODS: Observational study of all COVID-19 patients admitted to 19 Dutch ICUs participating in both the national quality registry National Intensive Care Evaluation (NICE) and the EHR-based Dutch Data Warehouse (hereafter EHR). Multiple models were developed on data from the first 24 h of ICU admissions from February to June 2020 (first COVID-19 wave) and validated on prospective patients admitted to the same ICUs between July and December 2020 (second COVID-19 wave). We assessed model discrimination, calibration, and the degree of relatedness between development and validation population. Coefficients were used to identify relevant risk factors. RESULTS: A total of 1533 patients from the EHR and 1563 from the registry were included. With high granular EHR data, the average AUROC was 0.69 (standard deviation of 0.05) for the internal validation, and the AUROC was 0.75 for the temporal validation. The registry model achieved an average AUROC of 0.76 (standard deviation of 0.05) in the internal validation and 0.77 in the temporal validation. In the EHR data, age, and respiratory-system related variables were the most important risk factors identified. In the NICE registry data, age and chronic respiratory insufficiency were the most important risk factors. CONCLUSION: In our study, prognostic models built on less-granular but readily-available registry data had similar performance to models built on high-granular EHR data and showed similar transportability to a prospective COVID-19 population. Future research is needed to verify whether this finding can be confirmed for upcoming waves.

INCIDENCE, RISK FACTORS, AND OUTCOME OF SUSPECTED CENTRAL VENOUS CATHETER-RELATED INFECTIONS IN CRITICALLY ILL COVID-19 PATIENTS: A MULTICENTER RETROSPECTIVE COHORT STUDY.

ABSTRACT: Background: Aims of this study were to investigate the prevalence and incidence of catheter-related infection, identify risk factors, and determine the relation of catheter-related infection with mortality in critically ill COVID-19 patients. Methods: This was a retrospective cohort study of central venous catheters (CVCs) in critically ill COVID-19 patients. Eligible CVC insertions required an indwelling time of at least 48 hours and were identified using a full-admission electronic health record database. Risk factors were identified using logistic regression. Differences in survival rates at day 28 of follow-up were assessed using a log-rank test and proportional hazard model. Results: In 538 patients, a total of 914 CVCs were included. Prevalence and incidence of suspected catheter-related infection were 7.9% and 9.4 infections per 1,000 catheter indwelling days, respectively. Prone ventilation for more than 5 days was associated with increased risk of suspected catheter-related infection; odds ratio, 5.05 (95% confidence interval 2.12-11.0). Risk of death was significantly higher in patients with suspected catheter-related infection (hazard ratio, 1.78; 95% confidence interval, 1.25-2.53). Conclusions: This study shows that in critically ill patients with COVID-19, prevalence and incidence of suspected catheter-related infection are high, prone ventilation is a risk factor, and mortality is higher in case of catheter-related infection.

Clinically relevant potential drug-drug interactions in intensive care patients: A large retrospective observational multicenter study.

PURPOSE: Potential drug-drug interactions (pDDIs) may harm patients admitted to the Intensive Care Unit (ICU). Due to the patient's critical condition and continuous monitoring on the ICU, not all pDDIs are clinically relevant. Clinical decision support systems (CDSSs) warning for irrelevant pDDIs could result in alert fatigue and overlooking important signals. Therefore, our aim was to describe the frequency of clinically relevant pDDIs (crpDDIs) to enable tailoring of CDSSs to the ICU setting. MATERIALS & METHODS: In this multicenter retrospective observational study, we used medication administration data to identify pDDIs in ICU admissions from 13 ICUs. Clinical relevance was based on a Delphi study in which intensivists and hospital pharmacists assessed the clinical relevance of pDDIs for the ICU setting. RESULTS: The mean number of pDDIs per 1000 medication administrations was 70.1, dropping to 31.0 when considering only crpDDIs. Of 103,871 ICU patients, 38% was exposed to a crpDDI. The most frequently occurring crpDDIs involve QT-prolonging agents, digoxin, or NSAIDs. CONCLUSIONS: Considering clinical relevance of pDDIs in the ICU setting is important, as only half of the detected pDDIs were crpDDIs. Therefore, tailoring CDSSs to the ICU may reduce alert fatigue and improve medication safety in ICU patients.

Some Patients Are More Equal Than Others: Variation in Ventilator Settings for Coronavirus Disease 2019 Acute Respiratory Distress Syndrome.

OBJECTIVES: As coronavirus disease 2019 is a novel disease, treatment strategies continue to be debated. This provides the intensive care community with a unique opportunity as the population of coronavirus disease 2019 patients requiring invasive mechanical ventilation is relatively homogeneous compared with other ICU populations. We hypothesize that the novelty of coronavirus disease 2019 and the uncertainty over its similarity with noncoronavirus disease 2019 acute respiratory distress syndrome resulted in substantial practice variation between hospitals during the first and second waves of coronavirus disease 2019 patients. DESIGN: Multicenter retrospective cohort study. SETTING: Twenty-five hospitals in the Netherlands from February 2020 to July 2020, and 14 hospitals from August 2020 to December 2020. PATIENTS: One thousand two hundred ninety-four critically ill intubated adult ICU patients with coronavirus disease 2019 were selected from the Dutch Data Warehouse. Patients intubated for less than 24 hours, transferred patients, and patients still admitted at the time of data extraction were excluded. MEASUREMENTS AND MAIN RESULTS: We aimed to estimate between-ICU practice variation in selected ventilation parameters (positive end-expiratory pressure, Fio2, set respiratory rate, tidal volume, minute volume, and percentage of time spent in a prone position) on days 1, 2, 3, and 7 of intubation, adjusted for patient characteristics as well as severity of illness based on Pao2/Fio2 ratio, pH, ventilatory ratio, and dynamic respiratory system compliance during controlled ventilation. Using multilevel linear mixed-effects modeling, we found significant (p ≤ 0.001) variation between ICUs in all ventilation parameters on days 1, 2, 3, and 7 of intubation for both waves. CONCLUSIONS: This is the first study to clearly demonstrate significant practice variation between ICUs related to mechanical ventilation parameters that are under direct control by intensivists. Their effect on clinical outcomes for both coronavirus disease 2019 and other critically ill mechanically ventilated patients could have widespread implications for the practice of intensive care medicine and should be investigated further by causal inference models and clinical trials.

Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse.

BACKGROUND: The identification of risk factors for adverse outcomes and prolonged intensive care unit (ICU) stay in COVID-19 patients is essential for prognostication, determining treatment intensity, and resource allocation. Previous studies have determined risk factors on admission only, and included a limited number of predictors. Therefore, using data from the highly granular and multicenter Dutch Data Warehouse, we developed machine learning models to identify risk factors for ICU mortality, ventilator-free days and ICU-free days during the course of invasive mechanical ventilation (IMV) in COVID-19 patients. METHODS: The DDW is a growing electronic health record database of critically ill COVID-19 patients in the Netherlands. All adult ICU patients on IMV were eligible for inclusion. Transfers, patients admitted for less than 24 h, and patients still admitted at time of data extraction were excluded. Predictors were selected based on the literature, and included medication dosage and fluid balance. Multiple algorithms were trained and validated on up to three sets of observations per patient on day 1, 7, and 14 using fivefold nested cross-validation, keeping observations from an individual patient in the same split. RESULTS: A total of 1152 patients were included in the model. XGBoost models performed best for all outcomes and were used to calculate predictor importance. Using Shapley additive explanations (SHAP), age was the most important demographic risk factor for the outcomes upon start of IMV and throughout its course. The relative probability of death across age values is visualized in Partial Dependence Plots (PDPs), with an increase starting at 54 years. Besides age, acidaemia, low P/F-ratios and high driving pressures demonstrated a higher probability of death. The PDP for driving pressure showed a relative probability increase starting at 12 cmH2O. CONCLUSION: Age is the most important demographic risk factor of ICU mortality, ICU-free days and ventilator-free days throughout the course of invasive mechanical ventilation in critically ill COVID-19 patients. pH, P/F ratio, and driving pressure should be monitored closely over the course of mechanical ventilation as risk factors predictive of these outcomes.

Prevalence of ELISA-detected specific antibodies against Besnoitia besnoiti in cattle of the Eastern and Southeastern Anatolian regions, Turkey.

BACKGROUND: Besnoitiosis caused by Besnoitia besnoiti is regarded as a re-emerging disease in cattle because of the increased number of cases and geographical distribution in many European countries. AIMS: The present study was conducted to determine the presence of B. besnoiti in cattle in the Eastern and Southeastern Anatolia of Turkey. METHODS: Blood samples were collected from 450 cattle in the provinces of Mus, Van, Siirt, and Diyarbakir. PrioCHECK®Besnoitia Ab 2.0 enzyme-linked immunosorbent assay (ELISA) kit was used to detect specific anti-B. besnoiti antibodies in the serum samples. RESULTS: Twelve (2.7%) of the 450 asymptomatic cattle were seropositive against B. besnoiti. In cattle, the prevalence rates were 0%, 3.7%, 3.4%, and 1.1% in Mus, Siirt, Diyarbakir, and Van provinces (P>0.05), respectively. This study is the first to investigate the presence of B. besnoiti in cattle raised in the Eastern and Southeastern Anatolia of Turkey. CONCLUSION: Although the ELISA test revealed some positive cases, concrete evidence for the establishment of clinical B. besnoiti infection could not be verified. More comprehensive analysis would be necessary to determine the significance of the present observations.

Evaluation of sexual functions and marital adjustment of pregnant women in Turkey.

The aim of this study was to evaluate pregnant women's sexual function and marital adjustment. The sample of the study included 298 women, and it was evaluated using Golombok Rust Inventory of Sexual Satisfaction (GRISS) Scale and Marital Adjustment Scale. The most important reasons for decreasing the frequency of sexual intercourse included the fear of harming the fetus during intercourse (62.1%), fear of having miscarriage (47.8%) and decreased sexual desire (34.7%). It was found that women with sexual dysfunction had a significantly lower educational level, were living with three or more people in their home, were multiparious, had an unplanned pregnancy, reported pain during sexual intercourse and felt that their sexual life was very affected during pregnancy. The findings of the study showed that women had ⩾5 points for GRISS for the subscales as follows: infrequency (47.3%), non-communication (57.4%), dissatisfaction (15.4%), avoidance (6.4%), non-sensuality (19.1%), vaginismus (28.9%), anorgasmia (29.9%) and sexual dysfunction (17.4%). In conclusion, women who were living with three or more people at home, had lower income level, were smoking and had an unplanned pregnancy scored under 43.5 of MAS. It was found negative and there was a medium correlation between MAS score and total GRISS score.

Isolated brain stem edema in a pediatric patient with head trauma: a case report.

Brain stem is the most vital part of our body and is a transitional region of the brain that connects the cerebrum with the spinal cord. Though, being small in size, it is full of indispensible functions such as the breathing, heart beat. Injury to the brain stem has similar effects as a brain injury, but it is more fatal. Use of the Glasgow Coma Score as a prognostic indicator of outcome in patients with head injuries is widely accepted in clinical practice. Traumatic brain stem edema in children is rare, but is associated with poor outcome. The question is that whether it is being aware of computerized tomography appearance of the posterior fossa when initial evaluating pediatric patients with head trauma at emergency clinics. Normal and edematous brain stem without an additional pathology are slightly different and not distinguished easily. On the other hand, brain stem edema should be promptly identified and appropriately treated in a short time.

Serum uric acid and inflammation in patients with immune thrombocytopenic purpura: preliminary results.

OBJECTIVE: The purpose of this study was to evaluate the uric acid (UA) and C-reactive protein (CRP) levels in patients with immune thrombocytopenic purpura (ITP). PATIENTS AND METHODS: Forty patients with newly diagnosed ITP and 40 healthy individuals were enrolled in the study. The patients were divided into two groups; group 1 (n = 40) consisted of patients with ITP, and group 2 (n = 40) consisted of healthy subjects. UA and CRP levels were measured in the blood samples from them. RESULTS: There were no statistical differences in gender, age and body mass index between two groups (p > 0.05 for all). Compared to group 2, group 1 had significantly higher UA levels (p = 0.002), whereas CRP levels were not significantly different (p > 0.05). In ITP patients, serum UA and CRP levels significantly correlated with low platelet count (r = -0.362, p = 0.022; r = -0.383, p = 0.015, respectively); and UA levels significantly correlated with CRP levels (r = 0.436, p = 0.005). CONCLUSIONS: The present study showed that UA levels increased in patients with ITP and negatively correlated with platelet counts. UA levels might be a mediator of inflammation via enhanced production of inflammatory cytokines; they might also be a potential mediator of low platelet count, and could play a pathophysiological role in the development of ITP.

Usage of whey protein may cause liver damage via inflammatory and apoptotic responses.

The purpose of this study was to investigate the long- and short-term inflammatory and apoptotic effects of whey protein on the livers of non-exercising rats. Thirty rats were divided into three groups namely (1) control group, (2) short-term whey (WS) protein diet (252 g/kg for 5 days), and (3) long-term whey (WL) protein diet (252 g/kg for 4 weeks). Interleukin 1ß (IL-1ß), IL-6, tumor necrosis factor α (TNF-α), and cytokeratin 18 (CK-18-M30) were assessed using enzyme-linked immunosorbent assay and immunohistochemical methods. Apoptosis was evaluated using the terminal transferase-mediated deoxyuridine triphosphate nick-end labeling (TUNEL) method. Hepatotoxicity was evaluated by quantitation of serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT). Based on the biochemical levels and immunohistochemical results, the highest level of IL-1ß was identified in the WL group (p < 0.01). The IL-6 and TNF-α results were slightly lower in the WS group than in the control group and were highest in the WL group (p < 0.01). The CK-18-M30 and TUNEL results were highest in the WS group and exhibited medium intensity in the WL group (p < 0.01). AST results were statistically significant for all groups, while our ALT groups were particularly significant between the WL and control groups (p < 0.01). The results showed that when whey protein is used in an uninformed manner and without exercising, adverse effects on the liver may occur by increasing the apoptotic signal in the short term and increasing inflammatory markers and hepatotoxicity in the long term.