Early-onset neonatal sepsis: Effectiveness of classification based on ante- and intrapartum risk factors and clinical monitoring.

INTRODUCTION: In 2017, the French public health authority HAS published new guidelines for the management of newborns at risk of early bacterial neonatal infection. These guidelines were based on ante- and intrapartum risk factors and clinical monitoring. In January 2021, we implemented a new protocol based on these guidelines in our tertiary maternity unit. OBJECTIVES: To assess the impact of the protocol implemented on neonates' antibiotic prescriptions. METHOD: An "old protocol" group comprising newborns hospitalized between July 1, 2020 and December 31, 2020, was compared to a "new protocol" group formed between January 14, 2021 and July 13, 2021. Data were collected on infectious risk factors, antibiotic prescriptions, and emergency room visits within 2 weeks for an infection or suspected infection. RESULTS: The "old protocol" population comprised 1565 children and the "new protocol" population 1513. Antibiotic therapy was prescribed for 29 newborns (1.85 %) in the old protocol group versus 15 (0.99 %) in the new one (p = 0.05). The median duration was 5 days and 2 days respectively (p = 0.08). With the new protocol, newborns in category B were about 20 times more likely (p = 0.01), and those in category C about 54 times more likely (p = 0.005) to have an infection than those classified in categories N or A. CONCLUSION: This study demonstrates that clinical monitoring criteria enable reduced use and duration of antibiotic therapy and are reliable.

Which Patients with Prostate Cancer and Lymph Node Uptake at Preoperative Prostate-specific Membrane Antigen Positron Emission Tomography/Computerized Tomography Scan Are at a Higher Risk of Prostate-specific Antigen Persistence After Radical Prostatectomy? Identifying Indicators of Systemic Disease by Integrating Clinical, Magnetic Resonance Imaging, and Functional Imaging Parameters.

BACKGROUND: The role of local therapies including radical prostatectomy (RP) in prostate cancer (PCa) patients with clinical lymphadenopathies on prostate-specific membrane antigen (PSMA) positron emission tomography/computerized tomography (PET/CT) has scarcely been explored. Limited data are available to identify men who would benefit from RP; on the contrary, those more likely to benefit already have systemic disease. OBJECTIVE: We aimed to assess the predictors of prostate-specific antigen (PSA) persistence in surgically managed PCa patients with lymphadenopathies on a PSMA PET/CT scan by integrating clinical, magnetic resonance imaging (MRI), and PSMA PET/CT parameters. DESIGN, SETTING, AND PARTICIPANTS: We identified 519 patients treated with RP and extended lymph node dissection, and who received preoperative PSMA PET between 2017 and 2022 in nine referral centers. Among them, we selected 88 patients with nodal uptake at preoperative PSMA PET (miTxN1M0). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The outcome was PSA persistence, defined as a PSA value of ≥0.1 ng/ml at the first measurement after surgery. Multivariable logistic regression models tested the predictors of PSA persistence. Covariates consisted of biopsy International Society of Urological Pathology (ISUP) grade group, clinical stage at MRI, and number of positive spots at a PET/CT scan. A regression tree analysis stratified patients into risk groups based on preoperative characteristics. RESULTS AND LIMITATIONS: Overall, lymph node invasion (LNI) was detected in 63 patients (72%) and 32 (36%) experienced PSA persistence after RP. At multivariable analyses, having more than two lymph nodal positive findings at PSMA PET, seminal vesicle invasion (SVI) at MRI, and ISUP grade group >3 at biopsy were independent predictors of PSA persistence (all p < 0.05). At the regression tree analysis, patients were stratified in four risk groups according to biopsy ISUP grade, number of positive findings at PET/CT, and clinical stage at MRI. The model depicted good discrimination at internal validation (area under the curve 78%). CONCLUSIONS: One out of three miN1M0 patients showed PSA persistence after surgery. Patients with ISUP grade 2-3, as well as patients with organ-confined disease at MRI and a single or two positive nodal findings at PET are those in whom RP may achieve the best oncological outcomes in the context of a multimodal approach. Conversely, patients with a high ISUP grade and extracapsular extension or SVI or more than two spots at PSMA PET should be considered as potentially affected by systemic disease upfront. PATIENT SUMMARY: Our novel and straightforward risk classification integrates currently available preoperative risk tools and should, therefore, assist physician in preoperative counseling of men candidates for radical treatment for prostate cancer with positive lymph node uptake at prostate-specific membrane antigen positron emission tomography.

Usefulness of PREDIC3T Case Type Risk Category in the CRISP Registry.

Procedural risk in Congenital Cardiac Catheterization (PREDIC3T) was recently reported as the contemporary procedure-type risk metric by the Congenital Cardiac Catheterization Project on Outcomes (C3PO) registry. The usefulness of this metric has not been evaluated elsewhere. The CRISP registry of Congenital Cardiovascular Interventional Study Consortium (CCISC) data set was analyzed. The study period was 14 years (2009 to 2022). The primary outcome was significant adverse event (SAE). Cases were assigned to the 6 PREDIC3T risk categories. Univariate and multivariable logistic regression models were used to evaluate the association between PREDIC3T and the primary outcome. The model discriminative performance was evaluated by the c-statistic. In a total of 64,419 enrolled cases, PREDIC3T case types were assigned in 59,822 cases (93%). The frequency for PREDIC3T category was 0 = 7,494 (12.5%), 1 = 16,932 (28.3%), 2 = 17,023 (28.5%), 3 = 9,885 (16.5%), 4 = 4,403 (7.4%), and 5 = 4,085 (6.8%). SAE was observed in 2,474 cases (4.1%). The SAE rates for category were 0 = 1.0%, 1 = 2.3%, 2 = 4.0%, 3 = 6.2%, 4 = 8.2%, and 5 = 9.0%. In a multivariable model, PREDIC3T case type risk category (odds ratios for category: 0 = 0.49, 1 = 1.00, 2 = 1.40, 3 = 2.06, 4 = 2.79, and 5 = 3.15; p <0.001) were significantly associated with SAE (c-statistic of 0.707) after adjusting for age, preprocedural inotropic support and systemic illness, low systemic saturation, high pulmonary vascular resistance, and the use of general anesthesia. The PREDIC3T case type risk category was associated with the risk of SAE in the CRISP registry data set and appeared to be a useful procedural risk classification tool.

Observational study on the evolution of systemic treatments for advanced renal cell carcinoma in Southwest Finland between 2010 and 2021.

Background: Novel receptor tyrosine kinase inhibitors and immune checkpoint inhibitors have been introduced to the treatment of advanced renal cell carcinoma (aRCC) during the past decade. However, the adoption of novel treatments into clinical practice has been unknown in Finland. Objectives: Our aim was to evaluate the use of systemic treatments and treatment outcomes of aRCC patients in Southwest Finland during 2010-2021. Design and Methods: Clinical characteristics, treatments for aRCC, healthcare resource utilization, and overall survival (OS) were retrospectively obtained from electronic medical records. Patients were stratified using the International Metastatic RCC Database Consortium (IMDC) risk classification. Results: In total, 1112 RCC patients were identified, 336 (30%) patients presented with aRCC, and 57% of them (n = 191) had received systemic treatment. Pre-2018, sunitinib (79%) was the most common first-line treatment, and pazopanib (17%), axitinib (17%), and cabozantinib (5%) were frequently used in the second-line. Post-2018, sunitinib (52%), cabozantinib (31%), and the combination of ipilimumab and nivolumab (10%) were most commonly used in the first-line, and cabozantinib (23%) in the second-line. Median OS for patients with favorable, intermediate, and poor risk were 61.9, 28.6, and 8.1 months, respectively. A total of 73%, 74%, and 35% of the patients with favorable, intermediate, and poor risk had received second-line systemic treatment. In poor-risk patients, the number of hospital inpatient days was twofold higher compared to intermediate and fourfold higher compared to favorable-risk patients. Conclusion: New treatment options were readily adopted into routine clinical practice after becoming reimbursed in Finland. OS and the need for hospitalization depended significantly on the IMDC risk category. Upfront combination treatments are warranted for poor-risk patients as the proportion of patients receiving second-line treatment is low. Registration: Clinical trial identifier: ClinicalTrials.gov NCT05363072.

Observational study on the evolution of systemic treatments for advanced renal cell carcinoma in Southwest Finland between 2010 and 2021 The aim of the study was to evaluate the use of novel medical treatments for advanced kidney cancer in routine clinical practice in Southwest Finland from 2010 to 2021 and to study the impact of IMDC risk factors on patients' survival and healthcare resource utilization. Before 2018, sunitinib (79%) was the most common first-line treatment for advanced kidney cancer, and pazopanib (17%), axitinib (17%), and cabozantinib (5%) were frequently used in the second-line. After 2018, sunitinib (52%), cabozantinib (31%), and the combination of ipilimumab and nivolumab (10%) were most commonly used in the first-line, and cabozantinib (23%) in the second-line treatment. The IMDC risk category predicted the patient's prognosis accurately as the median overall survival times for patients with favorable, intermediate, and poor risk were 61.9 months, 28.6 months, and 8.1 months, respectively. 73­74% of the patients with favorable and intermediate risk had received second-line medical treatment for advanced disease, whereas only 35% of the patients with poor risk had received second-line treatment after disease progression on the first-line treatment. Among patients with poor risk, the number of hospital inpatient days was twofold higher compared to intermediate and fourfold higher compared to favorable-risk patients. This study demonstrated that new treatment options for advanced kidney cancer were readily adopted into clinical practice and IMDC risk scoring was a valuable tool in determining patient prognosis and healthcare resource utilization.

Long-term impact of add-on sequential triple combination therapy in pulmonary arterial hypertension: real world experience.

BACKGROUND: Sequential triple combination therapy is recommended for pulmonary arterial hypertension (PAH) patients who are not at therapeutic goal on dual therapy, but long-term data on efficacy and safety is scarce. OBJECTIVE: To assess the long-term impact of sequential triple combination therapy in patients with PAH who are not at goal on dual combination therapy. STUDY DESIGN AND METHODS: We performed a retrospective observational study in a racially/ethnically diverse cohort of consecutive PAH patients on a stable dual therapy regimen who remained in intermediate- or high-risk category and were subsequently initiated on sequential triple combination therapy. We studied interval change in functional, echocardiographic, and hemodynamic parameters, REVEAL 2.0 risk category and ERS/ESC 2022 simplified four-strata risk category. Multivariate logistic regression analysis was performed to identify independent predictors of successful risk reduction (achievement or maintenance of REVEAL 2.0 low-risk category). Kaplan-Meier survival curves were created to assess the effect of risk reduction on survival. RESULTS: Out of 414 PAH patients seen in our program, 55 patients received add-on sequential triple combination regimen and had follow-up hemodynamic data. The mean age was 57 years, with 85% women. The most common etiology of PAH was idiopathic/heritable (41.8%). Most patients were WHO functional class III (76.4%), and 34.5% of patients were in high-risk category (REVEAL 2.0). On a median follow-up of 68 weeks, there was a significant improvement in WHO Functional Class (p < 0.001), six-minute walk distance (35 m) with 61.8% of patients achieving low-risk status by REVEAL 2.0, and a 28% of patients' improvement in pulmonary vascular resistance. Female gender was identified as a strong predictor of successful risk reduction, whereas Hispanic ethnicity estimated right atrial pressure on echocardiogram and pericardial effusion predicted lower probability of risk reduction. Patients who achieved or maintained low-risk status had significantly improved survival. CONCLUSION: Add-on sequential triple combination therapy significantly increased functional, echocardiographic, and hemodynamic parameters with improvement in risk category and survival.

Assessment of risk factors and preventive measure compliance against COVID-19 among healthcare workers at tertiary care hospital: a retrospective study.

Introduction: SARS-CoV-2 has created a significant challenge to healthcare systems, since the disease has spread rapidly, outweighing hospital capacity and exposing Health Care Workers (HCWs) to the risk of infection. The main objective of this study shows the HCW's self-reported use of Personal Protective Equipment (PPE), symptoms, and exposure to revealed and suspected people during the pandemic, as well as the implementation of infection prevention and control (IPC) guidelines that effectively limit the spread of the infection among healthcare personnel. Method: A single-center retrospective cohort study has been done at a tertiary care hospital. There were 3,651 hospital employees of these 1,890 HCWs and 1,761 nonclinical staff among those who were proven or suspected COVID-19 cases and had symptoms were included. The data was gathered using a standardized self-assessment questionnaire. Information about quarantine protocol and line listing was collected through telephonic conversations. Result: The majority of the participants were males (66%). The average age was 32.1±7.62. Out of 432 HCWs, 32.9% with positive SARS-CoV-2 PCR findings were nurses, 19.2% were doctors, and 47.9% were non-clinical employees from the hospital's inpatient and outpatient departments. 31.5% had a higher-risk exposure, 64.1% had a moderate-risk exposure, and 4.4% of practitioners with COVID-19 had a lower-risk exposure. A statistically significant association was found between COVID-19 disease and adherence to PPE and risk exposure. Conclusion: This study represents the healthcare workers' experience with COVID-19 patients in the early stages of the pandemic and emphasizes the measures required to overcome the problems, however, this study highlights that HCWs are being progressively infected with COVID-19 as a result of inadequate/ inappropriate PPE wear.

The relationship between maternal anemia and electronic fetal monitoring patterns.

BACKGROUND: Anemia is a commonly diagnosed comorbidity in pregnancy that is associated with increased risk of maternal and neonatal complications. Recent data demonstrate that maternal anemia is associated with higher umbilical artery and umbilical vein O2 content at the time of delivery. OBJECTIVE: This study aimed to examine the relationship between maternal anemia and electronic fetal monitoring patterns associated with fetal hypoxia. STUDY DESIGN: This is a secondary analysis of a prospective cohort study of singleton term deliveries with cord gases and universal complete blood count collected on admission between 2010 and 2014. Maternal anemia was defined as hemoglobin ≤11.0 g/dL on admission. The primary outcome was a composite of high-risk category 2 electronic fetal monitoring features in the last 60 minutes before delivery (recurrent late and/or variable decelerations, minimal variability, tachycardia, or >1 prolonged deceleration); secondary outcomes were total deceleration area and total deceleration area >90th percentile. Of the 8580 patients in the original study, 8196 were included in the analysis. Outcomes were compared between patients with and without anemia. Multivariable logistic regression was used to adjust for potentially confounding factors, including hypertensive disorders of pregnancy and induction of labor. RESULTS: Of the 8196 patients with complete blood count on admission and fetal monitoring data, 2672 (32.6%; 2672/8196) were anemic and 5524 (67.4%; 5524/8196) were not. Patients with anemia were significantly less likely to have composite high-risk category 2 features on electronic fetal monitoring (34.2% vs 32.0%; adjusted risk ratio, 0.93; 95% confidence interval, 0.86-0.99). Women with anemia also had decreased total deceleration area and were less likely to have total deceleration area >90th percentile (18.7% vs 16.2%; adjusted risk ratio, 0.85; 95% confidence interval, 0.77-0.94). CONCLUSION: Patients with anemia are less likely to have high-risk category 2 electronic fetal monitoring features associated with fetal hypoxia. This finding is consistent with the association between maternal anemia and increased umbilical cord O2 content, and suggests that maternal anemia may be protective against intrapartum fetal hypoxia.

Myelofibrosis and Survival Prognostic Models: A Journey between Past and Future.

Among the myeloproliferative diseases, myelofibrosis is a widely heterogeneous entity characterized by a highly variable prognosis. In this context, several prognostic models have been proposed to categorize these patients appropriately. Identifying who deserves more invasive treatments, such as bone marrow transplantation, is a critical clinical need. Age, complete blood count (above all, hemoglobin value), constitutional symptoms, driver mutations, and blast cells have always represented the milestones of the leading models still used worldwide (IPSS, DIPSS, MYSEC-PM). Recently, the advent of new diagnostic techniques (among all, next-generation sequencing) and the extensive use of JAK inhibitor drugs have allowed the development and validation of new models (MIPSS-70 and version 2.0, GIPSS, RR6), which are continuously updated. Finally, the new frontier of artificial intelligence promises to build models capable of drawing an overall survival perspective for each patient. This review aims to collect and summarize the existing standard prognostic models in myelofibrosis and examine the setting where each of these finds its best application.

Prescription pattern and associated factors among pregnant women attending antenatal clinics in University of Gondar, North West Ethiopia.

Background: An inappropriate use of drug during pregnancy may harm the fetus. There is no enough study on drug use among pregnant women at the University of Gondar referral hospital. Most studies are carried out in developed countries but not in developing countries. Thus, the aim of this study was to evaluate prescription of drug and associated factors among pregnant women attending antenatal care service in University of Gondar referral hospital. Methods: Institution based cross sectional study was used among 334 pregnant women who attended antenatal care units of the University of Gondar referral hospital. Data were collected from the pregnant women medical records and registration logbook and analyzed using SPSS version 23. Multivariate logistic regression used to analyze the association of the independent variables with drug use. P-values <0.05 were considered significant. Result: A total of 334 pregnant women's medical records showed a total of 631 drugs prescribed. The average numbers of drugs per pregnant women was 1.88. All pregnant women (100%) were prescribed with iron folat. Most pregnant women 185 (55.2%) were in the third trimester followed by third trimester 91 (27.25%). Moreover, 23.77%, 42.95%, 33%, and 7% pregnant women encountered with drugs from category A, B, C and D respectively. From the bivariate regression analysis, Age of women, maternal illness, trimester at the first visit, and gravidity were significantly associated with exposure to prescribed drug use during pregnancy. Conclusion: The present study showed the deviation of drug use pattern from the WHO optimal levels proposing the hospitals had inappropriate use of drug. Implementing corrective measures are required to achieve the recommended standards of appropriate drug use.

A Focus on Intermediate-Risk Acute Myeloid Leukemia: Sub-Classification Updates and Therapeutic Challenges.

Acute myeloid leukemia (AML) represents a heterogeneous group of hematopoietic neoplasms deriving from the abnormal proliferation of myeloid progenitors in the bone marrow. Patients with AML may have highly variable outcomes, which are generally dictated by individual clinical and genomic characteristics. As such, the European LeukemiaNet 2017 and 2022 guidelines categorize newly diagnosed AML into favorable-, intermediate-, and adverse-risk groups, based on their molecular and cytogenetic profiles. Nevertheless, the intermediate-risk category remains poorly defined, as many patients fall into this group as a result of their exclusion from the other two. Moreover, further genomic data with potential prognostic and therapeutic influences continue to emerge, though they are yet to be integrated into the diagnostic and prognostic models of AML. This review highlights the latest therapeutic advances and challenges that warrant refining the prognostic classification of intermediate-risk AML.

Feature Genes in Neuroblastoma Distinguishing High-Risk and Non-high-Risk Neuroblastoma Patients: Development and Validation Combining Random Forest With Artificial Neural Network.

There is a significant difference in prognosis among different risk groups. Therefore, it is of great significance to correctly identify the risk grouping of children. Using the genomic data of neuroblastoma samples in public databases, we used GSE49710 as the training set data to calculate the feature genes of the high-risk group and non-high-risk group samples based on the random forest (RF) algorithm and artificial neural network (ANN) algorithm. The screening results of RF showed that EPS8L1, PLCD4, CHD5, NTRK1, and SLC22A4 were the feature differentially expressed genes (DEGs) of high-risk neuroblastoma. The prediction model based on gene expression data in this study showed high overall accuracy and precision in both the training set and the test set (AUC = 0.998 in GSE49710 and AUC = 0.858 in GSE73517). Kaplan-Meier plotter showed that the overall survival and progression-free survival of patients in the low-risk subgroup were significantly better than those in the high-risk subgroup [HR: 3.86 (95% CI: 2.44-6.10) and HR: 3.03 (95% CI: 2.03-4.52), respectively]. Our ANN-based model has better classification performance than the SVM-based model and XGboost-based model. Nevertheless, more convincing data sets and machine learning algorithms will be needed to build diagnostic models for individual organization types in the future.

Lymph node ratio is superior to AJCC N stage for predicting recurrence in papillary thyroid carcinoma.

OBJECTIVE: Recently, lymph node ratio (LNR) has emerged as an alternative to American Joint Committee on Cancer (AJCC) N stage, with superior prognostic value. The utility of LNR in Middle Eastern papillary thyroid carcinoma (PTC) remains unknown. Therefore, we retrospectively analyzed a large cohort of 1407 PTC patients for clinicopathological associations of LNR. METHODS: Receiver operating characteristics (ROC) curve was used to determine the cut-off for LNR. We also performed multivariate logistic regression analysis to determine whether LNR or AJCC N stage was superior in predicting recurrence in PTC. RESULTS: Based on ROC curve analysis, a cut-off of 0.15 was chosen for LNR. High LNR was significantly associated with adverse clinicopathological characteristics such as male sex, extrathyroidal extension, lymphovascular invasion, multifocality, bilateral tumors, T4 tumors, lateral lymph node (N1b) involvement, distant metastasis, advanced tumor stage, American Thyroid Association (ATA) high-risk category and tumor recurrence. On multivariate analysis, we found that LNR was a better predictor of tumor recurrence than AJCC N stage (odds ratio: 1.96 vs 1.30; P value: 0.0184 vs 0.3831). We also found that LNR combined with TNM stage and ATA risk category improved the prediction of recurrence-free survival, compared to TNM stage or ATA risk category alone. CONCLUSIONS: The present study suggests LNR is an independent predictor of recurrence in Middle Eastern PTC. Integration of LNR with 8th edition AJCC TNM staging system and ATA risk stratification will improve the accuracy to predict recurrence in Middle Eastern PTC and help in tailoring treatment and surveillance strategies in these patients.

Risk Stratification of Patients Candidate to Radical Prostatectomy Based on Clinical and Multiparametric Magnetic Resonance Imaging Parameters: Development and External Validation of Novel Risk Groups.

BACKGROUND: Despite the key importance of magnetic resonance imaging (MRI) parameters, risk classification systems for biochemical recurrence (BCR) in prostate cancer (PCa) patients treated with radical prostatectomy (RP) are still based on clinical variables alone. OBJECTIVE: We aimed at developing and validating a novel classification integrating clinical and radiological parameters. DESIGN, SETTING, AND PARTICIPANTS: A retrospective multicenter cohort study was conducted between 2014 and 2020 across seven academic international referral centers. A total of 2565 patients treated with RP for PCa were identified. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Early BCR was defined as two prostate-specific antigen (PSA) values of ≥0.2 ng/ml within 3 yr after RP. Kaplan-Meier and Cox regressions tested time and predictors of BCR. Development and validation cohorts were generated from the overall patient sample. A model predicting early BCR based on Cox-derived coefficients represented the basis for a nomogram that was validated externally. Predictors consisted of PSA, biopsy grade group, MRI stage, and the maximum diameter of lesion at MRI. Novel risk categories were then identified. The Harrel's concordance index (c-index) compared the accuracy of our risk stratification with the European Association of Urology (EAU), Cancer of the Prostate Risk Assessment (CAPRA), and International Staging Collaboration for Cancer of the Prostate (STAR-CAP) risk groups in predicting early BCR. RESULTS AND LIMITATIONS: Overall, 200 (8%), 1834 (71%), and 531 (21%) had low-, intermediate-, and high-risk disease according to the EAU risk groups. The 3-yr overall BCR-free survival rate was 84%. No differences were observed in the 3-yr BCR-free survival between EAU low- and intermediate-risk groups (88% vs 87%; p = 0.1). The novel nomogram depicted optimal discrimination at external validation (c-index 78%). Four new risk categories were identified based on the predictors included in the Cox-based nomogram. This new risk classification had higher accuracy in predicting early BCR (c-index 70%) than the EAU, CAPRA, and STAR-CAP risk classifications (c-index 64%, 63%, and 67%, respectively). CONCLUSIONS: We developed and externally validated four novel categories based on clinical and radiological parameters to predict early BCR. This novel classification exhibited higher accuracy than the available tools. PATIENT SUMMARY: Our novel and straightforward risk classification outperformed currently available preoperative risk tools and should, therefore, assist physicians in preoperative counseling of men candidate to radical treatment for prostate cancer.

Risk Assessment for Diabetes Mellitus by Using Indian Diabetes Risk Score Among Office Workers of Health Institutions of South India.

BACKGROUND: Diabetes mellitus (DM) is one of the non-communicable diseases plaguing the world and contributes a major part to the total disease burden. Diabetes has been prevalent in all countries throughout the years, with the majority of diabetics living in low- and middle-income countries. Madras Diabetes Research Foundation developed the Indian Diabetes Risk Score (IDRS), a simple and cost-effective method to assess the chances of developing diabetes. OBJECTIVES: To assess the diabetes risk profile of office workers using IDRS and to determine the proportion of individual risk factors of diabetes among the participants. METHODS: This cross sectional study included 94 non-diabetic office workers working in two health care institutions situated in coastal South India. Data was collected by a study questionnaire consisting of three sections. Section A included details related to participant characteristics, Section B included anthropometric measurements, and Section C consisted of the Indian Diabetes Risk Score. The collected data were coded and entered into Statistical Package for Social Sciences. RESULTS: The mean age of the study participants was 40.88 (±9.761) years, and the mean BMI was 23.8 (±3.6) kg/m2. Majority (n=65, 67%) of the study participants did not have a family history of diabetes. One-third of the study participants had IDRS ≥ 60, which allocated them in the high risk category for type 2 diabetes (n=34, 35.1%). CONCLUSION: It has been conclusively shown from the study that most of the office workers have moderate to high risk of developing diabetes and are also overweight or obese.

Exposure risk and COVID-19 infection among frontline health-care workers: A single tertiary care centre experience.

BACKGROUND: There is limited data on frontline health-care workers and risk of COVID-19 from the developing nations. It is imperative to identify those at higher risk to prevent further transmission. We assessed the relationship between exposure risk and COVID-19 among front-line health-care workers who were primary contacts of a COVID-19 patient. METHODS: A retrospective cohort study was conducted among front-line health-care workers in a tertiary care hospital who were exposed to a COVID-19 patient. Information on demographic factors, medical history, exposure related factors and subsequently COVID-19 lab reports were collected. An exposure risk assessment designed collating various exposure related factors categorized the participants into those with high and low risk. We used logistic regression to estimate the odds ratio of our primary outcome, a positive COVID-19 test when the independent variables were exposure risk, age, gender and occupation. RESULTS: Among1858 frontline workers who were primary contacts of a COVID-19 patient at the hospital, 106 (5.7%) incident reports of a positive COVID-19 test were recorded. None of the exposure related factors had any significant association with a positive COVID-19 test. However, high exposure risk category was significantly associated with COVID-19 positive test at the end of quarantine. CONCLUSION: COVID-19 was more frequent among front-line health-care workers who belonged to high exposure category. Education at different levels of service delivery at hospitals is required for best practice in order to prevent COVID-19 among health care providers. There is need to develop additional strategies to ensure that the information is translated in to practice.

Association of the KDIGO Risk Classification with the Prevalence of Heart Failure in Patients with Type 2 Diabetes.

The objectives of this study were to determine the main characteristics associated with the presence of heart failure (HF) in patients with type 2 diabetes (T2DM), and specifically to assess the association of the risk classification proposed by the Kidney Disease Improving Global Outcomes (KDIGO) guidelines with HF. The DIABET-IC study is a multicentre, observational, prospective and analytical study in T2DM patients recruited in Spanish hospitals. This work, which features a cross-sectional design, has been conducted with the data obtained at the inclusion visit. The main dependent variable analysed was the presence of HF. The predictive variables evaluated were the demography, clinic, laboratory testing (including natriuretic peptides) and echocardiography. Patients were classified according to the number of vascular territories with atherosclerotic involvement and the KDIGO risk category. Multivariate logistic regression models were performed to determine the risk posed by the various baseline variables to present HF at the time of study inclusion. The study included 1517 patients from 58 hospitals, with a mean age of 67.3 (standard deviation (SD): 10) years, out of which 33% were women. The mean DM duration was 14 (SD: 11) years. The prevalence of HF was 37%. In a multivariate analysis, the independent predictors of HF were increased age (odds ratio (OR) per 1 year = 1.02; p = 0.006), decreased systolic blood pressure (OR per 1 mmHg = 0.98; p < 0.001), decreased haemoglobin (OR per 1 g/dL = 0.86; p < 0.001), the presence of obstructive sleep apnoea (OR = 1.61; p = 0.006), the absence of hepatic steatosis (OR = 0.59; p = 0.016), the severity of atherosclerotic involvement (OR 1 territory = 1.38 and OR > 1 territory = 2.39; p = 0.02 and p < 0.001 respectively) and the KDIGO risk classification (high-risk OR = 2.46 and very high-risk OR = 3.39; p < 0.001 for both). The KDIGO risk classification is useful to screen for the presence of HF in T2DM patients. Therefore, we believe that it is necessary to carry out a systematic screening for HF in the high- and very high-risk KDIGO categories.

Prognosis and Outcome of Fit Patients with Acute Myeloid Leukemia in Kuwait.

PURPOSE: Acute myeloid leukemia (AML) data from the Middle East are limited to single-center studies. We report leukemia-free survival (LFS) and overall survival (OS) of young (≤70 years) patients with AML treated in Kuwait. PATIENTS AND METHODS: This study investigated prognostic markers among 172 young and fit patients with de novo nonacute promyelocytic leukemia AML treated with intensive induction protocols from a tertiary cancer center. RESULTS: The median age was 44 years (interquartile range, 32-51) and 67% of cases were Arab. A greater proportion of males was found in the 2017 European Leukemia Net-defined unfavorable-risk group (20% vs 9%, respectively; P = .02). Most patients (94%) were treated by a standard 7 × 3 regimen; 72.5% of cases achieved complete remission. The 24-month LFS was 44% (95% confidence interval, 30-65), 36% (95% confidence interval, 26-50), and 23% (95% confidence interval, 10-53) for the favorable-, intermediate-, and adverse-risk groups, respectively (P = .018). The 24-month OS was 70% (95% confidence interval, 60-90), 65% (95% confidence interval, 53-79), and 49% (95% confidence interval, 31-78), respectively (P = .05). Multivariable factor analysis identified male gender (hazard ratio [HR], 1.66; P = .029) and older age (HR, 1.02; P = .05) with poor LFS outcome, whereas favorable-risk classification predicated better outcome (HR, 0.49; P = .03). Favorable-risk classification was the only predictor of OS (HR, 0.39; P = .029). CONCLUSION: Fit patients with AML in the favorable-risk group treated with intensive chemotherapy fare well, whereas patients in the adverse-risk group have poor survival.

Discrete-Time Markov Chain Modelling of the Ontario Air Quality Health Index.

The Air Quality Health Index (AQHI) is an aggregate indicator of air pollution used to communicate to Canadians the health impact of short-term exposure to current air pollutant levels. Understanding the stochastic behaviour of the AQHI can aid public health officials in predicting air pollution levels, determining the likelihood and duration of air quality advisories, and planning for increased strain on the health care system during periods of higher air pollution. Previous research has applied discrete-time Markov chains to investigate stochastic behaviour of air pollution indices but only in a handful of regions and none with the same climatic characteristics as Canadian regions. In this study, we investigated the stochastic behaviour of AQHI risk categories in Ontario (34 air monitoring stations) for 5 years from 2015 to 2019. We employed discrete-time Markov chains using three of the AQHI risk categories (Low Risk, Moderate Risk, High Risk) as states to determine (1) the transition probabilities between these states, (2) the long-run proportion of time spent in each state, and (3) the mean persistence time of each state. These results were then used to assess spatial trends in the stochastic behaviour of AQHI risk categories and the likelihood and duration of air quality advisories. Overall, the air quality (as characterised by the AQHI) in Ontario tends to decrease as population density increases. Urban areas spent a greater proportion of time in higher risk categories, and tended to remain in the higher risk categories for longer before transitioning.

Actualized inventory of medicinal plants used in traditional medicine in Oaxaca, Mexico.

BACKGROUND: Oaxaca is one of the most diverse states in Mexico from biological and cultural points of view. Different ethnic groups living there maintain deep and ancestral traditional knowledge of medicinal plants as well as traditional practices and beliefs about diseases/illnesses and cures. Previous ethnobotanical research in this state has helped document this knowledge, but with the addition of more studies, more records appear. We updated the inventory of medicinal knowledge between the different ethnic groups that inhabit the Oaxacan territory. METHODS: A database was constructed from two sources: (1) original data from a 3-year project in 84 municipalities of Oaxaca inhabited by eight ethnic groups and (2) different electronic databases. RESULTS: Records of 1032 medicinal plants were obtained; 164 families were registered, with Asteraceae, Fabaceae, and Rubiaceae being the most commonly used. A total of 770 species were reported in 14 vegetation types; the most important species came from temperate forests. Only 144 species corresponded to introduced species, and 272 were listed in a risk category. Illnesses of the digestive and genitourinary systems as well as culture-bound syndromes were treated with high numbers of medicinal plants. The Mestizo, Mixe, Mixtec, and Zapotec ethnic groups exhibited the greatest number of recorded medicinal plants. The 17 species that were used among almost all ethnic groups in Oaxaca were also used to cure the highest number of diseases. DISCUSSION: Inventories of medicinal plants confirm the persistence of traditional knowledge and reflect the need to recognize and respect this cosmovision. Many species are gathered in wild environments. The most important illnesses or diseases recorded in the present inventory are also mentioned in different studies, suggesting that they are common health problems in the rural communities of Mexico. CONCLUSIONS: Medicinal plants are essential for ethnic groups in Oaxaca. It is necessary to recognize and understand the complex ancestral processes involved in the human-nature interaction and the role of these processes in the conservation of biodiversity and in the survivorship of ethnic groups that have persisted for centuries. Finally, this study serves as a wake-up call to respect those worldviews.

A drug-biomarker interaction model to predict the key targets of Scutellaria barbata D. Don in adverse-risk acute myeloid leukaemia.

A poor prognosis, relapse and resistance are burning issues during adverse-risk acute myeloid leukaemia (AML) treatment. As a natural medicine, Scutellaria barbata D. Don (SBD) has shown impressive antitumour activity in various cancers. Thus, SBD may become a potential drug in adverse-risk AML treatment. This study aimed to screen the key targets of SBD in adverse-risk AML using the drug-biomarker interaction model through bioinformatics and network pharmacology methods. First, the adverse-risk AML-related critical biomarkers and targets of SBD active ingredient were obtained from The Cancer Genome Atlas database and several pharmacophore matching databases. Next, the protein-protein interaction network was constructed, and topological analysis and pathway enrichment were used to screen key targets and main pathways of intervention of SBD in adverse-risk AML. Finally, molecular docking was implemented for key target verification. The results suggest that luteolin and quercetin are the main active components of SBD against adverse-risk AML, and affected drug resistance, apoptosis, immune regulation and angiogenesis through the core targets AKT1, MAPK1, IL6, EGFR, SRC, VEGFA and TP53. We hope the proposed drug-biomarker interaction model provides an effective strategy for the research and development of antitumour drugs.