EXPRESS: Predictive Modeling of Mortality in Carbapenem-Resistant Acinetobacter baumannii Bloodstream Infections Using Machine Learning.

Acinetobacter baumannii, a notable drug-resistant bacterium, often induces severe infections in healthcare settings, prompting a deeper exploration of treatment alternatives due to escalating carbapenem resistance. This study meticulously examined clinical, microbiological, and molecular aspects related to in-hospital mortality in patients with carbapenem-resistant A. baumannii (CRAB) bloodstream infections (BSI). From 292 isolates, 153 cases were scrutinized, reidentified through MALDI-TOF-MS, and evaluated for antimicrobial susceptibility and carbapenemase genes via multiplex PCR. Utilizing supervised machine learning, the study constructed models to predict 14-day and 30-day mortality rates, revealing the Naïve Bayes model's superior specificity (0.75) and area under the curve (AUC; 0.822) for 14-day mortality, and the Random Forest model's impressive recall (0.85) for 30-day mortality. These models delineated 8 and 9 significant features for 14-day and 30-day mortality predictions, respectively, with 'septic shock' as a pivotal variable. Additional variables such as neutropenia with neutropenic days prior to sepsis, mechanical ventilator support, chronic kidney disease, and heart failure were also identified as ranking features. However, empirical antibiotic therapy appropriateness and specific microbiological data had minimal predictive efficacy. This research offers foundational data for assessing mortality risks associated with CRAB BSI and underscores the importance of stringent infection control practices in the wake of the scarcity of new effective antibiotics against resistant strains. The advanced models and insights generated in this study serve as significant resources for managing the repercussions of A. baumannii infections, contributing substantially to the clinical understanding and management of such infections in healthcare environments.

Monogenic Hypertension Linked to the Renin-Angiotensin-Aldosterone System.

Mendelian forms of renin-angiotensin-aldosterone system (RAAS)-related hypertension, commonly referred to as monogenic hypertension, represent a rare but significant subset of hypertensive disorders characterized by genetic mutations that disrupt the normal physiological mechanisms of blood pressure regulation. This review focuses on elucidating the germline mutations affecting RAAS pathways that lead to distinct forms of heritable hypertension. By understanding the pathophysiological basis of conditions such as Gordon's syndrome, Liddle syndrome, congenital adrenal hyperplasia, and familial hyperaldosteronism types, this review aims to highlight the unique clinical features, diagnostic challenges, and therapeutic implications associated with these disorders. Recognizing specific clinical presentations and family histories indicative of monogenic hypertension is crucial for diagnosis, particularly as it often manifests as early-onset hypertension, abnormalities in potassium and blood pH, and occasionally, abnormal sexual development or related syndromes. Therefore, employing a targeted diagnostic approach through next-generation sequencing is essential to pinpoint the responsible genetic mutations, enabling accurate and individualized treatment plans. The critical importance of certain readily available specific channel blockers, such as thiazides or low-dose corticosteroids, in managing these disorders must be emphasized, as they play a key role in preventing serious complications, including cerebrovascular events. As advancements in genetic and molecular sciences continue to evolve, a deeper comprehension of the mechanisms underlying RAAS-related monogenic hypertension promises to revolutionize the management of this complex disorder, offering hope for more effective and individualized treatment options.

The Prognostic Significance of KIAA1522 Expression in Non-Small-Cell Lung Cancer Patients.

The majority of lung cancers belong to the non-small-cell lung cancer (NSCLC) category, which is linked to a high mortality rate despite significant progress in diagnosis and treatment. Therefore, there is a need for novel prognostic NSCLC biomarkers to improve prognosis which currently remains poor. Recent studies and analyses of gene expression data of NSCLC revealed that high expression of KIAA1522 was significantly associated with poor prognosis and decreased overall survival. We identified 98 patients who underwent radical curative surgical resections or metastasectomy for pulmonary adenocarcinoma and squamous cell carcinoma at our institution or the pathological diagnosis confirmed by our pathologists. Following the latest data, we utilized immunohistochemistry to assess the expression of KIAA1522 and investigated its association with various clinic-demographic parameters, pathological stages, recurrence rates, overall survival, and disease-free survival in patients who achieved complete remission. Notably, there were no significant differences in the expression profiles of KIAA1522 between adenocarcinoma and squamous cell carcinoma samples (p=0.6). Survival analysis was conducted using log-rank tests and a multivariate Cox proportional hazard model. Of the 98 samples, 54 (55.1%) exhibited high expression of KIAA1522, and patients with high KIAA1522 expression had a significantly shorter overall survival than the low-expression group (p=0.01). Multivariate Cox proportional hazard models in which metastatic patients were included revealed that along with older age, higher TNM stage (tumor, node, metastasis system), and Eastern Cooperative Oncology Group (ECOG) performance status, high expression of KIAA1522 served as an independent prognostic factor. A high expression profile was not significantly associated with relapses in those whose complete remission had been achieved. Still, those patients with high expression of KIAA1522 tended to exhibit a shorter disease-free survival rate. In conclusion, our findings suggest that KIAA1522 expression is an independent factor for predicting overall survival and may serve as a valuable prognostic indicator for relapse and disease-free survival in NSCLC patients.

Evaluation of machine learning algorithms for renin-angiotensin-aldosterone system inhibitors associated renal adverse event prediction.

BACKGROUND: Renin-angiotensin-aldosterone system inhibitors (RAASi) are commonly used medications. Renal adverse events associated with RAASi are hyperkalemia and acute kidney injury. We aimed to evaluate the performance of machine learning (ML) algorithms in order to define event associated features and predict RAASi associated renal adverse events. MATERIALS AND METHODS: Data of patients recruited from five internal medicine and cardiology outpatient clinics were evaluated retrospectively. Clinical, laboratory, and medication data were acquired via electronic medical records. Dataset balancing and feature selection for machine learning algorithms were performed. Random forest (RF), k-nearest neighbor (kNN), naïve Bayes (NB), extreme gradient boosting (xGB), support vector machine (SVM), neural network (NN), and logistic regression (LR) were used to create a prediction model. RESULTS: 409 patients were included, and 50 renal adverse events occurred. The most important features predicting the renal adverse events were the index K and glucose levels, as well as having uncontrolled diabetes mellitus. Thiazides reduced RAASi associated hyperkalemia. kNN, RF, xGB and NN algorithms have the highest and similar AUC (≥ 98%), recall (≥ 94%), specifity (≥ 97%), precision (≥ 92%), accuracy (≥ 96%) and F1 statistics (≥ 94%) performance metrics for prediction. CONCLUSION: RAASi associated renal adverse events can be predicted prior to medication initiation by machine learning algorithms. Further prospective studies with large patient numbers are needed to create scoring systems as well as for their validation.

[Q Fever Endocarditis-Associated Immune Complex-Mediated Proliferative Glomerulonephritis: Fourth Case from Türkiye]. / Q Atesi Endokarditi Iliskili Immün Kompleks Aracili Proliferatif Glomerülonefrit: Türkiye'den Dördüncü Olgu.

Q fever is a zoonosis caused by the intracellular gram-negative bacterium Coxiella burnetii. Infection can be asymptomatic, acute or can cause chronic disease. Chronic disease often presents with infective endocarditis (IE). Diagnosis of IE is difficult because the agent does not grow easily in standard blood cultures and valve vegetations are difficult to detect. Glomerular involvement in patients with Q fever endocarditis is limited to the case reports. In addition, a total of three cases of Q fever endocarditis from Türkiye have been published so far. In this case report, a fourth case of Q fever endocarditis from Türkiye accompanied by immune complex-mediated glomerulonephritis was presented. A 35-year-old male patient with a history of mitral and aortic heart valve replacement was admitted with complaints of fever, night sweats and involuntary weight loss. Cervical lymphadenopathy and hepatosplenomegaly were found during the examination. Laboratory investigations revealed anemia inflammation, acute kidney injury (AKI), hematuria and proteinuria. While no causative agent was detected in blood and urine cultures, no diagnosis could be made as a result of bone marrow and cervical lymph node biopsies.Transesophageal echocardiography was performed for the etiology of fever and revealed 7 mm vegetation on the prosthetic mitral valve. C.burnetii phase 1 IgG tested with indirect immunofluorescent antibody method was reported positive at 1/16384 titer and doxycycline and hydroxychloroquine treatments were initiated. Kidney biopsy for the etiology of AKI revealed focal segmental endocapillary proliferative glomerulonephritis with C3, C1q and IgM immunocomplex deposition. After the addition of methylprednisolone to the treatment, the patient's symptoms improved and creatinine and proteinuria levels decreased dramatically. Although Q fever is endemic in our country, it is detected in fewer numbers than expected. In addition to the difficulties in microbiological and clinical diagnosis, the low awareness of physicians about the disease is one of the important reasons for this situation. When the disease comes to mind, the diagnosis can be easily reached by serological methods. Therefore, Q fever should be investigated in the presence of lymphoproliferative disease-like findings fever of unknown origin and culture-negative endocarditis.

The Collateral Benefit of COVID Pandemic: Improved Pharmacological Venous Thromboembolism Prophylaxis Practices in Non-COVID Patients.

Background: COVID-19 creates a hypercoagulable state with a wide spectrum of clinical manifestations. Of those, venous thromboembolism (VTE) is prevalent, and numerous studies have highlighted the importance of VTE prophylaxis. Pre-pandemic VTE prophylaxis practices have already been poor, despite guidelines. We hypothesized that the gap between guidelines and practices might have been closed due to increased awareness. Materials and Methods: Non-COVID-19 patients hospitalized in the internal medicine ward of a university hospital between January 1st, 2021, and June 30th, 2021, were assessed. VTE risk and thromboprophylaxis requirements were assessed using the Padua Prediction Score (PPS). The results were compared with the findings of the study conducted in the same setting before the pandemic. Results: A total of 267 patients were included, and 81 patients (30.3%) received prophylaxis. A total of 128 patients' (47.9%) PPS was ≥ 4, and 69 patients (53.9%) received prophylaxis; 12 low-risk patients (8.6%) received prophylaxis although it was not indicated. Compared to the pre-pandemic figures, both appropriate prophylaxis use and overuse rates have risen. While the increment rate of appropriate prophylaxis was statistically significant, the increment rate of overuse did not reach statistical significance. Patients hospitalized for infectious diseases and respiratory failure were more likely to receive appropriate prophylaxis. Conclusion: We have demonstrated a significant increase in appropriate pharmacologic prophylaxis rates among high-risk patients. Besides all the collateral damage the pandemic has created, it might also have brought collateral benefits with regards to VTE prophylaxis.

Machine Learning Insights Into Uric Acid Elevation With Thiazide Therapy Commencement and Intensification.

Background Elevated serum uric acid, associated with cardiovascular conditions such as atherosclerotic heart disease, hypertension, and heart failure, can be elevated by thiazide or thiazide-like drugs (THZ), essential in hypertension management. Identifying clinical determinants affecting THZ-related uric acid elevation is critical. Methods In this retrospective cross-sectional study, we explored the clinical determinants influencing uric acid elevation related to THZ, focusing on patients where THZ was initiated or the dose escalated. A cohort of 143 patients was analyzed, collecting baseline and control uric acid levels, alongside basic biochemical studies and clinical data. Feature selection was conducted utilizing criteria based on mean squared error increase and enhancement in node purity. Four machine learning algorithms - Random Forest, Neural Network, Support Vector Machine, and Gradient Boosting regressions - were applied to pinpoint clinical influencers. Results Significant features include uncontrolled diabetes, index estimated Glomerular Filtration Rate (eGFR) level, absence of insulin, action of indapamide, and absence of statin treatment, with absence of Sodium-glucose cotransporter 2 inhibitors (SGLT2i), low dose aspirin exposure, and older age also being noteworthy. Among the applied models, the Gradient Boosting regression model outperformed the others, exhibiting the lowest Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE) values, and the highest R2 value (0.779). While Random Forest and Neural Network regression models were able to fit the data adequately, the Support Vector Machine demonstrated inferior metrics. Conclusions Machine learning algorithms are adept at accurately identifying the factors linked to uric acid fluctuations caused by THZ. This proficiency aids in customizing treatments more effectively, reducing the need to unnecessarily avoid THZ, and providing guidance on its use to prevent instances where uric acid levels could become problematic.

[Longitudinal Assessment of Anti-Spike-1 antibody Responses in a Group of Hospitalized Patients with SARS-CoV-2 Infection]. / Hastaneye Yatan SARS-CoV-2 Enfeksiyonlu Bir Grup Hastanin Anti-Spike-1 Antikor Yanitlarinin Boylamsal Degerlendirilmesi.

The coronavirus disease-2019 (COVID-19) has become a global cause of death/injury, particularly for those with limited access to vaccination programs and healthcare systems. The risk of re-infection is not negligible due to the emergence of new variants and the decrease in immunity of those who have recovered COVID-19 before. In this study, it was aimed to show longitudinally the change in antibody levels of patients hospitalized for COVID-19 who had an antibody response in the early stages of their infection and to reveal a response pattern that would help to predict patients whose antibody responses decreased or persisted over time. This observational, single-center study included 38 non-critical patients admitted to COVID-19 wards. Anti-spike-1 IgG levels were investigated by the "enzyme-linked immunosorbent assay (ELISA)" method in two different samples taken at different times in each patient. Two distinct anti-spike-1 IgG antibody response patterns were detected in the study; the first pattern was that with low antibody production at first who had an increase in antibody levels after an average of six months, and the second pattern was that the initially high antibody levels decreased after an average of six months. This paradoxical kinetic may blur physicians' predictions of antibody response. In general, anti-spike-1 antibody levels showed a moderate decrease after six months, but production seems to continue (mean ∆IgG= -0.77; σ= 4; p= 0.24). Higher antibody levels were observed at the beginning in patients with concomitant bacterial pneumonia (mean initial IgG= 7.67; σ= 3.54) (p= 0.03). Although the production of S1-IgG in patients recovered from severe acute respiratory system coronavirus2 (SARS-CoV-2) was modestly reduced compared to the beginning measurements, the production in general persisted during the study period. It appears that IgG responses increase or remain constant in individuals with relatively low IgG index values when controlled after an average of 180 days, while IgG tends to decrease in individuals with high IgG index values.

Independent predictors of in-hospital mortality and the need for intensive care in hospitalized non-critical COVID-19 patients: a prospective cohort study.

One of the most helpful strategies to deal with ongoing coronavirus pandemics is to use some prudence when treating patients infected with SARS-CoV-2. We aimed to evaluate the clinical, demographic, and laboratory parameters that might have predictive value for in-hospital mortality and the need for intensive care and build a model based on them. This study was a prospective, observational, single-center study including non-critical patients admitted to COVID-19 wards. Besides classical clinic-demographic features, basic laboratory parameters obtained on admission were tested, and then new models for each outcome were developed built on the most significant variables. Receiver operating characteristics (ROC) analyses were performed by calculating each model's probability. A total of 368 non-critical hospitalized patients were recruited, the need for ICU care was observed in 70 patients (19%). The total number of patients who died in either ICU or wards was 39 (10.6%). The first two models (based on clinical features and demographics) were developed to predict ICU and death, respectively; older age, male sex, active cancer, and low baseline saturation were noted to be independent predictors. The area under the curve values of the first two models were noted 0.878 and 0.882 (p < .001; confidence interval [CI] 95% [0.837-0.919], p < .001; CI 95% [0.844-0.922]). Following two models, the third and fourth were based on laboratory parameters with clinic-demographic features. Initial lower sodium and lower albumin levels were determined as independent factors in predicting the need for ICU care; higher blood urea nitrogen and lower albumin were independent factors in predicting in-hospital mortality. The area under the curve values of the third and fourth model was noted 0.938 and 0.929, respectively (p < .001; CI 95% [0.912-0.965], p < .001; CI 95% [0.895-962]). By integrating the widely available blood tests results with simple clinic demographic data, non-critical patients can be stratified according to their risk level. Such stratification is essential to filter the patients' non-critical underlying diseases and conditions that can obfuscate the physician's predictive capacity.

'Anxiety is still ongoing!' Evaluation of the effect of the COVID-19 pandemic on anxiety severity of physicians working in the internal medicine department after 1 year: a collaborative cross-sectional study.

The COVID-19 pandemic has increased anxiety in society and particularly in healthcare workers, as shown with a questionnaire in our centre at the beginning of the pandemic. In this collaborative study, we aimed to evaluate the effects of the pandemic on anxiety 1 year later by applying the same questionnaire to the physicians working in the same department. A total of 77 participants consented to the study. The median age was 28 (interquartile range = 4) years and 55.8% were male. As in the first survey, female gender, having family members over 65 years of age, and having family members with chronic diseases were significantly associated with high anxiety scores and levels. There were no statistically significant differences between the first and second survey participants in any of the anxiety scales, which means anxiety persists.

"COVID-19: The final nail in the coffin for physical examination" Evaluation of the effects of COVID-19 pandemic on physical examination habits of residents in a university hospital: A cross-sectional survey.

AIMS: It is evident that the COVID-19 pandemic has affected the medical practice and training of residents. In this study, we evaluated the physical examination (PE) habits of residents working in a university hospital and how their PE practices did change during the pandemic. METHODS: This single-centre, non-interventional, cross-sectional descriptive study was conducted in a university hospital using an online survey questionnaire between 5 and 20 October 2020. RESULTS: Of the 308 residents who participated in the study, 172 of them (55.8%) were female and the median age was 27 (IQR (3) = Q1 (29)-Q3 (26)). Amongst all, 263 participants (85.4%) declared that they have worked in the areas where suspected/confirmed COVID-19 patients were being served. A total of 262 (85%) residents stated that PE habits have changed generally during the pandemic. There was a significant difference with regards to the change in PE habits between those residents who have worked in the COVID-19 areas (n = 230, 87.5%) and those who have not (n = 32, 71.1%) (P = .004). PE habits of Internal Medicine Residents were changed more than others (P < .001). The main reason for the change in PE habits in general (77.9%) and during the examination of suspected/confirmed COVID-19 patients (89.7%) were "self-protection." Independent factors for limited PE in suspected/confirmed COVID-19 patients were found as "Avoiding performing physical examination to be exposed less/to protect (adjusted ORs = 13.067)," "relying on laboratory and radiological investigations during practice (adjusted ORs = 4.358)," and "not having a thought that reduced physical examination will render the diagnosis and course of COVID-19 (adjusted ORs = 2.244)." CONCLUSIONS: This study clearly demonstrated that the COVID-19 pandemic has had a serious impact on the PE habits of the residents while examining patients in general and with COVID-19.

Quality gap in venous thromboembolism prophylaxis practices in inpatients: Assessment of prophylaxis practices in a University Hospital.

BACKGROUND: Venous thromboembolism (VTE) is a prevalent complication of inpatient care, causing high burden of morbidity and mortality. Prophylaxis reduces the events; thus, these practices are promoted. We aimed to assess the VTE prophylaxis practices in the general internal medicine wards of a tertiary-care university hospital and utilize these data to propose quality improvement projects. OBJECTIVE: Assess the pharmacological venous thromboembolism prophylaxis utilization by using the Padua Prediction Score and demonstrate the main determinants of inappropriate prophylaxis use. METHODS: Electronic medical records were used to collect data cross-sectionally from 1 January 2019 to 30 June 2019. Padua Prediction Score was used to assess the appropriateness of VTE prophylaxis. Underlying health conditions, hospitalization causes, anti-platelets and use of glucocorticoids were also assessed as confounding factors. RESULTS: A total of 295 patients were included. Higher proportion of patients who received VTE prophylaxis were obese and had higher rates of diabetes and coronary artery disease. Prophylaxis was more commonly utilized among patients who were elderly, obese, having an acute infection and/or rheumatologic disorder and prolonged bed rest (P ≤ 0.001, P = 0.01, P = 0.22 and P ≤ 0.001, respectively). Thirty-five patients (11.8%) received VTE prophylaxis, despite 89 patients (30.2%) were high-risk patients. In the high-risk group (n = 89), 27 patients (30.3%) received appropriate pharmacological prophylaxis, while 8 patients (3.9%) received VTE prophylaxis in the low-risk group (total n = 206). A considerable percentage of the high-risk population (69.6%) did not receive VTE prophylaxis. DISCUSSION: Underuse constitutes a major challenge in our hospital but differing from other institutions, overuse is not a significant issue. Further studies are needed whether VTE prophylaxis improvement implementations uniformly increase appropriate VTE use.