Impact of Serum Ferritin and Iron Overload on Acute Myeloid Leukemia Outcomes: A Systematic Review and Meta-Analysis.

OBJECTIVE: To evaluate the iron overload among individuals with acute myeloid leukemia (AML) who have not received red blood cell transfusions. METHODS: A comprehensive search was conducted in Embase, PubMed, PubMed Central, Web of Science, NIH, and Blood Library databases up to September 2023. The search strategy included keywords related to AML, iron overload, serum ferritin, survival, outcomes, and inflammation. Manual searches through included articles and relevant references were also performed. From 1650 initial articles, 16 studies involving 8752 patients met the inclusion criteria for systematic review. Statistical analysis used hazard ratios (HR) and confidence intervals (CI).  Results: The systematic review and meta-analysis revealed a statistically significant association between high serum ferritin (SF) levels and poor outcomes in AML patients before starting chemotherapy. Elevated SF levels (>1000 mg/L) were associated with lower overall survival (OS) and event-free survival (EFS) (HR for OS: 1.99, 95% CI: 1.48-2.66; HR for EFS: 2.29, 95% CI: 1.73-3.05). Elevated SF levels were inversely correlated with the gradual onset of infections, indicating an increased risk of early mortality (p<0.05). CONCLUSION: Elevated serum ferritin levels are significantly associated with poor outcomes in AML patients before treatment initiation. These findings highlight the importance of monitoring iron levels in these patients to improve prognostic assessments and treatment strategies.

Artificial Intelligence-Based Models for Prediction of Mortality in ICU Patients: A Scoping Review.

BACKGROUND AND OBJECTIVE: Healthcare professionals may be able to anticipate more accurately a patient's timing of death and assess their possibility of recovery by implementing a real-time clinical decision support system. Using such a tool, the healthcare system can better understand a patient's condition and make more informed judgements about distributing limited resources. This scoping review aimed to analyze various death prediction AI (Artificial Intelligence) algorithms that have been used in ICU (Intensive Care Unit) patient populations. METHODS: The search strategy of this study involved keyword combinations of outcome and patient setting such as mortality, survival, ICU, terminal care. These terms were used to perform database searches in MEDLINE, Embase, and PubMed up to July 2022. The variables, characteristics, and performance of the identified predictive models were summarized. The accuracy of the models was compared using their Area Under the Curve (AUC) values. RESULTS: Databases search yielded an initial pool of 8271 articles. A two-step screening process was then applied: first, titles and abstracts were reviewed for relevance, reducing the pool to 429 articles. Next, a full-text review was conducted, further narrowing down the selection to 400 key studies. Out of 400 studies on different tools or models for prediction of mortality in ICUs, 16 papers focused on AI-based models which were ultimately included in this study that have deployed different AI-based and machine learning models to make a prediction about negative patient outcome. The accuracy and performance of the different models varied depending on the patient populations and medical conditions. It was found that AI models compared with traditional tools like SAP3 or APACHE IV score were more accurate in death prediction, with some models achieving an AUC of up to 92.9%. The overall mortality rate ranged from 5% to more than 60% in different studies. CONCLUSION: We found that AI-based models exhibit varying performance across different patient populations. To enhance the accuracy of mortality prediction, we recommend customizing models for specific patient groups and medical contexts. By doing so, healthcare professionals may more effectively assess mortality risk and tailor treatments accordingly. Additionally, incorporating additional variables-such as genetic information-into new models can further improve their accuracy.

Diagnostic and prognostic value of Sepsis-Induced coagulopathy and International Society on Thrombosis and Hemostasis scoring systems in COVID-19-associated disseminated intravascular coagulopathy.

BACKGROUND: The coronavirus disease 2019 (COVID-19) presents various phenotypes from asymptomatic involvement to death. Disseminated intravascular coagulopathy (DIC) is among the poor prognostic complications frequently observed in critical illness. To improve mortality, a timely diagnosis of DIC is essential. The International Society on Thrombosis and Hemostasis (ISTH) introduced a scoring system to detect overt DIC (score ≥5) and another category called sepsis-induced coagulopathy (SIC) to identify the initial stages of DIC (score ≥4). This study aimed to determine whether clinicians used these scoring systems while assessing COVID-19 patients and the role of relevant biomarkers in disease severity and outcome. MATERIALS AND METHODS: An exhaustive search was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses, using Medline, Embase, Cochrane, CINAHL, and PubMed until August 2020. Studies considering disease severity or outcome with at least two relevant biomarkers were included. For all studies, the definite, maximum, and minimum ISTH/SIC scores were calculated. RESULTS: A total of 37 papers and 12,463 cases were reviewed. Studies considering ISTH/SIC criteria to detect DIC suggested a higher rate of ISTH ≥5 and SIC ≥4 in severe cases and nonsurvivors compared with nonsevere cases and survivors. The calculated ISTH scores were dominantly higher in severe infections and nonsurvivors. Elevated D-dimer was the most consistent abnormality on admission. CONCLUSION: Higher ISTH and SIC scores positively correlate with disease severity and death. In addition, more patients with severe disease and nonsurvivors met the ISTH and SIC scores for DIC. Given the high prevalence of coagulopathy in COVID-19 infection, dynamic monitoring of relevant biomarkers in the form of ISTH and SIC scoring systems is of great importance to timely detect DIC in suspicious patients.

Modelling COVID-19 transmission in a hemodialysis centre using simulation generated contacts matrices.

The COVID-19 pandemic has been particularly threatening to patients with end-stage kidney disease (ESKD) on intermittent hemodialysis and their care providers. Hemodialysis patients who receive life-sustaining medical therapy in healthcare settings, face unique challenges as they need to be at a dialysis unit three or more times a week, where they are confined to specific settings and tended to by dialysis nurses and staff with physical interaction and in close proximity. Despite the importance and critical situation of the dialysis units, modelling studies of the SARS-CoV-2 spread in these settings are very limited. In this paper, we have used a combination of discrete event and agent-based simulation models, to study the operations of a typical large dialysis unit and generate contact matrices to examine outbreak scenarios. We present the details of the contact matrix generation process and demonstrate how the simulation calculates a micro-scale contact matrix comprising the number and duration of contacts at a micro-scale time step. We have used the contacts matrix in an agent-based model to predict disease transmission under different scenarios. The results show that micro-simulation can be used to estimate contact matrices, which can be used effectively for disease modelling in dialysis and similar settings.

Anticoagulation therapy in COVID-19 patients with chronic kidney disease.

Coagulopathy and derangements in the coagulation parameters are significant features of COVID-19 infection, which increases the risk of disseminated intravascular coagulation, thrombosis, and hemorrhage in these patients, resulting in increased morbidity and mortality. In times of COVID-19, special consideration should be given to patients with concurrent chronic kidney disease (CKD) and COVID-19 (CKD/COVID-19 patients) as renal dysfunction increases their risk of thrombosis and hemorrhage, and falsely affects some of the coagulation factors, which are currently utilized to assess thrombosis risk in patients with COVID-19. Hence, we believe extra attention should be given to determining the risk of thrombosis and bleeding and optimizing the timing and dosage of anticoagulant therapy in this unique population of patients. CKD/COVID-19 patients are considered a high-risk population for thrombotic events and hemorrhage. Furthermore, effects of renal function on paraclinical and clinical data should be considered during the evaluation and interpretation of thrombosis risk stratification. Individualized evaluation of clinical status and kidney function is necessary to determine the best approach and management for anticoagulant therapy, whereas there is a lack of studies about the population of CKD/COVID-19 patients who need anticoagulant therapy now.

White blood cell count and clustered components of metabolic syndrome: A study in western Iran.

BACKGROUND: White blood cell count (WBC) is one of the objective parameters of systemic inflammation. The aim of present study was to evaluate the relationship between WBC count and metabolic syndrome. METHODS: In this study on Lor population in Borujerd province (West of Iran), from 2011 to 2013, 800 persons were enrolled. MetS was defined based on ATP III criteria. Differences among the quartiles of WBC were examined by one-way analysis of variance. RESULTS: Only 14.7% did not have any of the five components and 43% of all subjects had metabolic syndrome. The means of WBC count in MetS group were significantly higher than the control group (p<0.0001). In subjects without any MetS components, the means of WBC was 5.321 /µL, and it was 5.664, 5.714, 5.961, 6.302, and 6.572 /µL in subjects with 1, 2, 3, 4, and 5 components, respectively. These differences show a significant increasing trend (p<0.0001). CONCLUSION: WBC count was associated with clustered components of metabolic syndrome. It seems that WBC counts could be considered as a predictive factor for metabolic syndrome in preventive medicine.

Blunted Overnight Blood Pressure Dipping in Second Trimester; A Strong Predictor of Gestational Hypertension and Preeclampsia.

BACKGROUND: Preeclampsia is a global burden with 10 million incidences annually and 210 daily deaths worldwide. Diagnosis is mainly based on the features following full presentation. OBJECTIVE: This study explored whether early pregnancy circadian changes of ambulatory blood pressure monitoring (ABPM) could predict preeclampsia and hypertension. METHODS: In a prospective study, 294 pregnant women who were referred to Sarem Women's Hospital, Iran were recruited. Systolic, diastolic and mean arterial pressures (MAP) were recorded (diurnally and nocturnally) in each trimester. Dipping was defined as a minimum 10% decrease in blood pressure. RESULTS: Of the 251 women who completed the study, 25 percent (n=63) experienced blunted MAP dipping during sleep phases in the second trimester. Eighty-nine percent (n=56) experienced hypertensive disorder in the third trimester, one-third of which experienced preeclampsia. Of the women with normal MAP dipping (n=188), 5 percent (n=10) had gestational hypertension and 1 percent (n=2) became preeclamptic. (P<0.0001). CONCLUSION: This study clearly demonstrated blunted blood pressure dipping overnight during the second trimester which is a strong predictor of forthcoming pregnancy-induced hypertension and preeclampsia. A scoring system was developed to predict hypertensive disorder and it was significantly correlated with preeclampsia occurrence.

3D simulation of solutes concentration in urinary concentration mechanism in rat renal medulla.

In this work, a mathematical model was developed to simulate the urinary concentration mechanism. A 3-D geometry was derived based on the detail physiological pictures of rat kidney. The approximate region of each tubule was obtained from the volume distribution of structures based on Walter Pfaller's monograph and Layton's region-based model. Mass and momentum balances were applied to solve for the change in solutes concentration and osmolality. The osmolality of short and long descending nephrons at the end of the outer medulla was obtained to be 530 mOsmol/kgH2O and 802 mOsmol/kgH2O, respectively, which were in acceptable agreement with experimental data. The fluid osmolality of the short and long ascending nephrons was also compatible with experimental data. The osmolality of CD fluid at the end of the inner medulla was determined to be 1198 mOsmol/kgH2O which was close the experimental data (1216 ±â€¯118). Finally, the impact of the position of each tubule on the fluid osmolality and solutes concentration were obvious in the results; for example, short descending limb a1, which is the closest tubule to the collecting duct, had the highest urea concentration in all tubules. This reflects the important effect of the 3D modeling on the precise analysis of urinary concentration mechanism.

The Impact of Hemodialysis Frequency and Duration on Blood Pressure Management and Quality of Life in End-Stage Renal Disease Patients.

Cardiovascular complications are the most prominent causes of morbidity and mortality among chronic kidney disease (CKD) and end-stage renal disease (ESRD) patients undergoing standard hemodialysis (HD) therapy. Cardiovascular disease risk is increased significantly through persistent hypertension and blood pressure (BP) fluctuation, which are the most common complications of CKD. It was hypothesized that an extended approach with lengthier and more frequent dialysis sessions, referred to in this paper as "extended hemodialysis" (EHD), can potentially lower and stabilize blood pressure, and consequently reduce the rate of morbidity and mortality. A greater reduction of volume (salt and water) with higher frequency can improve patient quality of life (QOL). Eleven papers, including clinical trials and systematic reviews were chosen and analyzed. The extracted data was used to evaluate the change in blood pressure levels between standard HD and EHD. Overall, the studies showed that EHD resulted in improved blood pressure management; therefore, we concluded that there will be a decrease in cardiovascular disease risk, stroke, and morbidity and mortality rate. There will be also an improvement in patient QOL due to beneficial effects of the EHD.

Dermatologic Manifestations in End-stage Renal Disease.

End-stage renal disease (ESRD) is a rapidly growing global health problem within the past decades due to increased life expectancy, diabetes mellitus, hypertension, and vascular diseases. Since ESRD is not curable definitively, patients suffering from ESRD have a very low quality of life; therefore, symptomatic management is the cornerstone of medical treatment. Uremia affects almost all body organs, such as skin, through different mechanisms including biochemical, vascular, neurologic, immunologic, hematologic, endocrine, and electrolyte and volume balance disturbances. Some of these conditions are associated with significant morbidity, and patients with ESRD commonly present with a spectrum of dermatologic disorders. Each one has its own unique presentation and treatment approaches. In this review article, we discuss the clinical presentation, pathophysiology, and treatment of the most common skin disorders associated with ESRD.