Investigating the Prevalence and Predictors of Uncontrolled Hypertension: A Cross-Sectional Study in Gujarat, India.

BACKGROUND: Uncontrolled hypertension is a major public health concern that contributes significantly to cardiovascular morbidity and mortality. Treatment of hypertension prevents and reduces cardiovascular morbidity, notably a 40% reduction in risk of stroke and a 15% reduction in risk of myocardial infarction. Understanding the prevalence and predictors of uncontrolled hypertension is crucial for developing targeted interventions. OBJECTIVE: This study aimed to determine the prevalence of uncontrolled hypertension and identify potential predictors among patients attending the Non-Communicable Disease (NCD) clinic of a tertiary care center in Gujarat, India. METHODS: A cross-sectional study involving 732 adult patients with hypertension was conducted. Sociodemographic data, lifestyle factors, anthropometric measurements, and comorbidities were assessed. Blood pressure was measured using standardized protocols, and uncontrolled hypertension was defined as a systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg. Univariate and multivariate logistic regression analyses were performed to identify predictors of uncontrolled hypertension. RESULTS: The prevalence of uncontrolled hypertension was 60.2% (95% CI: 56.7%-63.7%). In the multivariate analysis, increasing age (adjusted OR: 1.21, 95% CI: 1.05-1.39), increased body mass index (adjusted OR: 1.49, 95% CI: 1.27-1.75), diabetes (adjusted OR: 1.68, 95% CI: 1.20-2.35), chronic kidney disease (adjusted OR: 2.11, 95% CI: 1.22-3.65), and current smoking status (adjusted OR: 1.83, 95% CI: 1.14-2.93) were identified as independent predictors of uncontrolled hypertension. CONCLUSION: This study revealed a high prevalence of uncontrolled hypertension in this tertiary care setting. Age, obesity, diabetes, chronic kidney disease, and smoking were identified as significant predictors. Targeted interventions addressing these modifiable risk factors and comorbidities are crucial for improving blood pressure control and reducing the burden of hypertension-related complications.

Risk predictors of glycaemic control in children and adolescents with type 1 diabetes: A systematic review and meta-analysis.

OBJECTIVES: To conduct systematic evaluation of the risk predictors of glycaemic control in children and adolescents with type 1 diabetes mellitus. METHODS: Cohort studies on risk predictors of glycaemic control in children and adolescents with type 1 diabetes were retrieved from CNKI, PubMed, Web of Science, Embase databases, etc. from the construction of the repository to 3 February 2023. Literature screening was conducted according to inclusion and exclusion criteria, then data extraction of region, sample size, age, follow-up time, risk predictors, outcome indicators, etc., and quality evaluation of The Newcastle-Ottawa Scale were conducted by two researchers while the third researcher makes decisions if there are disagreements. Finally, Revman5.4 and StataMP17 were used for meta-analysis. RESULTS: A total of 29 studies were included, and the results showed that insulin pump [Weighed mean difference (WMD) = -.48, 95% CI (-.73, -.24), p < .01], high-frequency sensor monitoring, early use of insulin pumps, prospective follow-up male, white race, large body mass index-standardised scoring, conscientiousness, agreeableness of mothers, eicosapentaenoic acid, leucine and protein (p < .05) were beneficial for reducing HbA1c levels in children and adolescents with diabetes. Ketoacidosis [WMD = .39, 95% CI (.28, .50), p < .01], selective admission, higher HbA1c level at one time (p < .01), higher glutamate decarboxylase antibody at 1 month after diagnosis, lower socio-economic status, non-living with biological parents, non-two-parent family, family disorder, family history of diabetes and high carbohydrate intake (p < .05) increased HbA1c levels in children and adolescents with diabetes. CONCLUSION: For children and adolescents with type 1 diabetes mellitus, the use of insulin pump, high-frequency sensor monitoring, prospective follow-up, good family support and reasonable diet are conducive to blood glucose control, while selective admission and DKA are not. Disease characteristics and demographic characteristics of children are closely related to subsequent blood glucose control, and the relationship between diagnosis age and blood glucose control needs to be further explored.

Pre-treatment risk predictors of valproic acid-induced dyslipidemia in pediatric patients with epilepsy.

Background: Valproic acid (VPA) stands as one of the most frequently prescribed medications in children with newly diagnosed epilepsy. Despite its infrequent adverse effects within therapeutic range, prolonged VPA usage may result in metabolic disturbances including insulin resistance and dyslipidemia. These metabolic dysregulations in childhood are notably linked to heightened cardiovascular risk in adulthood. Therefore, identification and effective management of dyslipidemia in children hold paramount significance. Methods: In this retrospective cohort study, we explored the potential associations between physiological factors, medication situation, biochemical parameters before the first dose of VPA (baseline) and VPA-induced dyslipidemia (VID) in pediatric patients. Binary logistic regression was utilized to construct a predictive model for blood lipid disorders, aiming to identify independent pre-treatment risk factors. Additionally, The Receiver Operating Characteristic (ROC) curve was used to evaluate the performance of the model. Results: Through binary logistic regression analysis, we identified for the first time that direct bilirubin (DBIL) (odds ratios (OR) = 0.511, p = 0.01), duration of medication (OR = 0.357, p = 0.009), serum albumin (ALB) (OR = 0.913, p = 0.043), BMI (OR = 1.140, p = 0.045), and aspartate aminotransferase (AST) (OR = 1.038, p = 0.026) at baseline were independent risk factors for VID in pediatric patients with epilepsy. Notably, the predictive ability of DBIL (AUC = 0.690, p < 0.0001) surpassed that of other individual factors. Furthermore, when combined into a predictive model, incorporating all five risk factors, the predictive capacity significantly increased (AUC = 0.777, p < 0.0001), enabling the forecast of 77.7% of dyslipidemia events. Conclusion: DBIL emerges as the most potent predictor, and in conjunction with the other four factors, can effectively forecast VID in pediatric patients with epilepsy. This insight can guide the formulation of individualized strategies for the clinical administration of VPA in children.

The association of FRAX with predictors of falls in the assessment of postmenopausal osteoporosis in Turkey: the fracture study of Turkey (FRACT study).

Although FRAX is used for fracture risk evaluation, this tool does not include balance and fall risk. The association between the predictors of falls and high FRAX scores we found in this study suggests that risk indicators for falls may add substantial value to FRAX by improving fracture risk prediction. PURPOSE: This observational, descriptive, and cross-sectional study aimed to assess the fall risk predictors and explore their association with FRAX in Turkish patients with postmenopausal osteoporosis. METHODS: Two hundred and nine (209) women with postmenopausal osteoporosis referred to the Fracture Liaison Service (FLS) at Istanbul University-Cerrahpasa were enrolled in the FRACT study (The Fracture Study of Turkey). Clinical risk factors were assessed using the FRAX tool. Tandem stance, Tandem walking, Timed up and go (TUG), and Chair stand tests were performed to assess balance and fall risk. RESULTS: Among patients with a mean age of 67.6 (± 9.7) years, 66 patients (31.6%) had osteoporosis without fractures and 143 patients (68.4%) had fragility fractures. The proportion of patients with poor performance of fall prediction tests was significantly higher in patients with a fragility fracture than those with osteoporosis alone. There was an inverse relationship between dynamic balance tests and the reported number of prior falls in the past year. FRAX score was higher in patients with impaired Tandem stance, Tandem walking, and TUG tests (p = 0.008, p = 0.035, p = 0.001, respectively). CONCLUSION: Assessment of fall risk predictors should be one of the major pillars in the physical evaluation of osteoporotic patients in the FLS setting. FRAX is a useful tool to determine the fracture risk of patients with both static and dynamic balance impairments. Combining balance assessment with FRAX may be an important step to optimize osteoporosis risk assessment.

Two-year neurodevelopmental outcome in extremely preterm-born children: The Austrian Preterm Outcome Study Group.

AIM: The current study determined the neurodevelopmental outcome of extremely preterm infants at 2 years of age. METHODS: All live-born infants 23-27 weeks of gestation born between 2011 and 2020 in Austria were included in a prospective registry. Neurodevelopmental outcome at 2 years of corrected age was assessed using Bayley Scales of Infant Development for both motor and cognitive scores, along with a neurological examination and an assessment of neurosensory function. RESULTS: 2378 out of 2905 (81.9%) live-born infants survived to 2 years of corrected age. Follow-up data were available for 1488 children (62.6%). Overall, 43.0% had no, 35.0% mild and 22.0% moderate-to-severe impairment. The percentage of children with moderate-to-severe neurodevelopmental impairment decreased with increasing gestational age and was 31.4%, 30.5%, 23.3%, 19.0% and 16.5% at 23, 24, 25, 26 and 27 weeks gestational age (p < 0.001). Results did not change over the 10-year period. In multivariate analysis, neonatal complications as well as male sex were significantly associated with an increased risk of neurodevelopmental impairment. CONCLUSION: In this cohort study, a 22.0% rate of moderate-to-severe neurodevelopmental impairment was observed among children born extremely preterm. This national data is important for both counselling parents and guiding the allocation of health resources.

Development and validation of a clinical prediction model for glioma grade using machine learning.

BACKGROUND: Histopathological evaluation is currently the gold standard for grading gliomas; however, this technique is invasive. OBJECTIVE: This study aimed to develop and validate a diagnostic prediction model for glioma by employing multiple machine learning algorithms to identify risk factors associated with high-grade glioma, facilitating the prediction of glioma grading. METHODS: Data from 1114 eligible glioma patients were obtained from The Cancer Genome Atlas (TCGA) database, which was divided into a training set (n= 781) and a test set (n= 333). Fifty machine learning algorithms were employed, and the optimal algorithm was selected to construct a prediction model. The performance of the machine learning prediction model was compared to the clinical prediction model in terms of discrimination, calibration, and clinical validity to assess the performance of the prediction model. RESULTS: The area under the curve (AUC) values of the machine learning prediction models (training set: 0.870 vs. 0.740, test set: 0.863 vs. 0.718) were significantly improved from the clinical prediction models. Furthermore, significant improvement in discrimination was observed for the Integrated Discrimination Improvement (IDI) (training set: 0.230, test set: 0.270) and Net Reclassification Index (NRI) (training set: 0.170, test set: 0.170) from the clinical prognostic model. Both models showed a high goodness of fit and an increased net benefit. CONCLUSION: A strong prediction accuracy model can be developed using machine learning algorithms to screen for high-grade glioma risk predictors, which can serve as a non-invasive prediction tool for preoperative diagnostic grading of glioma.

Venous Thromboembolism Risk Assessment in Hospitalized Cancer Patients: A Single Center Study.

This study aimed to identify predictors of venous thromboembolism (VTE) in hospitalized cancer patients and develop a predictive model using demographic, clinical, and laboratory data. Our analysis showed that patient groups categorized under a very high risk, and high risk, patients with low hemoglobin levels and renal disease were at a significantly increased risk of developing VTE. We developed a VTE risk-assessment model (RAM) with moderate discriminatory performance, high specificity, and negative predictive value, indicating its potential utility in identifying patients without VTE risk. However, the model's positive predictive value and sensitivity were low due to the low prevalence of VTE within the analyzed population. Future studies are needed to analyze additional predictive factors, and to validate the effectiveness of our VTE RAM to safely rule out VTE, compare it with other VTE RAMs in hospitalized cancer patients, and address any limitations of our study.

Risk Factors for Sudden Cardiac Arrest Among Hispanic or Latino Adults in Southern California: Ventura PRESTO and HCHS/SOL.

Background Out-of-hospital sudden cardiac arrest (SCA) is a leading cause of mortality, making prevention of SCA a public health priority. No studies have evaluated predictors of SCA risk among Hispanic or Latino individuals in the United States. Methods and Results In this case-control study, adult SCA cases ages 18-85 (n=1,468) were ascertained in the ongoing Ventura Prediction of Sudden Death in Multi-Ethnic Communities (PRESTO) study (2015-2021) in Ventura County, California. Control subjects were selected from 3033 Hispanic or Latino participants who completed Visit 2 examinations (2014-2017) at the San Diego site of the HCHS/SOL (Hispanic Community Health Survey/Study of Latinos). We used logistic regression to evaluate the association of clinical factors with SCA. Among Hispanic or Latino SCA cases (n=295) and frequency-matched HCHS/SOL controls (n=590) (70.2% men with mean age 63.4 and 61.2 years, respectively), the following clinical variables were associated with SCA in models adjusted for age, sex, and other clinical variables: chronic kidney disease (odds ratio [OR], 7.3 [95% CI, 3.8-14.3]), heavy drinking (OR, 4.5 [95% CI, 2.3-9.0]), stroke (OR, 3.1 [95% CI, 1.2-8.0]), atrial fibrillation (OR, 3.7 [95% CI, 1.7-7.9]), coronary artery disease (OR, 2.9 [95% CI, 1.5-5.9]), heart failure (OR, 2.5 [95% CI, 1.2-5.1]), and diabetes (OR, 1.5 [95% CI, 1.0-2.3]). Conclusions In this first population-based study, to our knowledge, of SCA risk predictors among Hispanic or Latino adults, chronic kidney disease was the strongest risk factor for SCA, and established cardiovascular disease was also important. Early identification and management of chronic kidney disease may reduce SCA risk among Hispanic or Latino individuals, in addition to prevention and treatment of cardiovascular disease.

A Systematic Evaluation of Risk Predictors for COVID-19 Sequelae.

Background Multisystem involvement in coronavirus disease 2019 (COVID-19) is known since the beginning of the pandemic, and post-COVID-19 sequelae have often been reported. The term 'long Covid' encompasses these signs and symptoms. The aim of our study was to study different after-effects which patients endured within 12 months after recovery from acute COVID-19 and to study the various risk predictors. Methods This was a longitudinal observational study of a cohort of 146 patients who recovered from COVID-19 illness. Patients were enrolled during the first four weeks of the onset of their illness, and a monthly follow-up assessment was done for six months that included a detailed history of persistent or new symptoms, new illnesses diagnosed, and complete biochemical, pulmonary, cardiac, neurological and psychiatric evaluation, both objective and subjective. A final follow-up was also done at the end of one year of enrolment. Based on the patient's self-reported history and our multi-system assessment, recorded sequelae were classified according to the involved organ system. These were correlated with possible risk predictors and statistically significant associations were established. Results One hundred and twenty subjects out of 146 total subjects qualified for final analysis. Pulmonary sequelae (48/120; 40%) were the most followed by psychiatric (30/120; 25%), neurological (26/120; 21.7%), and opportunistic infections (7/120; 5.8%). A total of 39/120 (32.1%) cases complained of prolonged dyspnoea. Six out of 120 i.e. 5% of study participants had new-onset diabetes. Twenty-six out of 120 (21.7%) had radiological signs of pulmonary fibrosis. Patients with co-morbidities, older age, higher body mass index, and patients with severe disease were found to be at higher risk of developing these sequelae. Poor nutrition, female gender, and hospitalization were predictors of psychiatric sequelae. Diabetes and liberal steroid use during COVID-19 management were predictors of opportunistic fungal infections. Conclusion This study evaluated post-COVID-19 sequalae in-depth both objectively and subjectively. Some specific predictors for specific sequelae were confirmed on statistical correlation. Long-term follow-up of high-risk persons is therefore recommended after the cure of COVID-19.

Association of demographics, cardiovascular indicators and disability characteristics with 7-year coronary heart disease incident in persons with disabilities.

OBJECTIVE: Previous studies had demonstrated that disability increases mortality in patients with coronary heart disease (CHD). However, for people who had been disabled but do not have baseline cardiovascular disease, there is still limited data on how they might develop CHD. This study aimed to investigate the incidence and predictors of CHD in people with disabilities. METHODS: We conducted a 7-year retrospective study utilizing data from the Shanghai Comprehensive Information Platform for Persons with Disabilities Rehabilitation. Subjects aged over 18 years with at least four annual complete electronic health records were included. The primary outcome was CHD, defined as ischemic heart disease or myocardial infarction. Kaplan-Meier analysis and log-rank tests were used to compare cumulative CHD for sub-populations, stratified by age, gender, and the classification of disabilities. Cox regression was used to identify the potentially important factors. RESULTS: Out of 6419 persons with disabilities, 688 CHD cases (mean age 52.95 ± 7.17 years, male 52.2%) were identified, with a cumulative incidence of 10.72% and an incidence density of 15.15/1000 person-years. The incidence density of CHD is higher in the male gender, people over 45 years, and those with physical disabilities. Male (HR = 1.294, 95% CI, 1.111-1.506), hypertension (HR = 1.683, 95% CI, 1.405-2.009), diabetes mellitus (HR = 1.488, 95% CI, 1.140-1.934), total cholesterol (HR = 1.110, 95% CI, 1.023-1.204), and physical disabilities (HR = 1.122, 95% CI, 1.019-1.414) were independently associated with CHD. CONCLUSION: The findings indicate that the incidence of CHD differs across disability categories rather than the severity of disability. People with physical disabilities had significantly higher risks for the development of CHD. The underlying physiological and pathological factors need to be further studied.

Unplanned Readmissions and Long-Term Mortality Risk After Incident Heart Failure Hospitalisation in Western Australia, 2001-2015.

AIMS: To investigate the frequency and predictors of unplanned readmissions after incident heart failure (HF) hospitalisation and the association between readmissions and mortality over two years. METHODS: We performed a retrospective cohort study using Western Australian morbidity and mortality data to identify all patients, aged 25-94 years, who survived an incident (first-ever) HF hospitalisation (principal diagnosis) between 2001-2015. Ordinal logistic regression models determined the covariates independently associated with unplanned readmission(s). Cox proportional hazards models with time-varying exposures determined the hazard ratios (HR) of one or more readmissions for mortality over two years after incident HF. RESULTS: Of 18,693 patients, 53.4% male, mean age 74.4 (standard deviation [SD] 13.6) years, 61.3% experienced 32,431 unplanned readmissions (39.7% cardiovascular-related) within two years. Leading readmission causes were HF (19.1%), respiratory diseases (12.6%), and ischaemic heart disease (9.6%). All-cause death occurred in 27.2% of the cohort, and the multivariable-adjusted mortality HR of 1 (versus 0) readmission was 2.5 (95% confidence interval [CI], 2.3-2.7) increasing to 5.0 (95% CI, 4.7-5.4) for 2+ readmissions. The adjusted mortality HR of 1 and 2+ (versus 0) HF-specific readmission was 2.0 (95% CI, 1.8-2.1) and 3.6 (95% CI, 3.2-3.9), respectively. Coexistent cardiovascular and other comorbidities were independently associated with increased readmission and mortality risk. CONCLUSION: This study underlines the high burden of recurrent unplanned cardiovascular and other readmissions within two years after incident HF hospitalisation, and their additive adverse impact on mortality. Integrated multidisciplinary management of concomitant comorbidities, in addition to HF-targeted treatments, is necessary to improve long-term prognosis in HF patients.

Pneumothorax in hospitalized COVID-19 patients with severe respiratory failure: Risk factors and outcome.

PNX was described as an uncommon complication in COVID-19 patients but clinical risk predictors and the potential role in patient's outcome are still unclear. We assessed prevalence, risk predictors and mortality of PNX in hospitalized COVID- 19 with severe respiratory failure performing a retrospective observational analysis of 184 patients admitted to our COVID-19 Respiratory Unit in Vercelli from October 2020 to March 2021. We compared patients with and without PNX reporting prevalence, clinical and radiological features, comorbidities, and outcomes. Prevalence of PNX was 8.1% and mortality was >86% (13/15) significantly higher than in patients without PNX (56/169) (P < 0.001). PNX was more likely to occur in patients with a history of cognitive decline (HR: 31.18) who received non-invasive ventilation (NIV) (p < 0.0071) and with low P/F ratio (HR: 0.99, p = 0.004). Blood chemistry in the PNX subgroup compared to patients without PNX showed a significant increase in LDH (420 U/L vs 345 U/L, respectively p = 0.003), ferritin (1111 mg/dl vs 660 mg/dl, respectively p = 0.006) and decreased lymphocytes (HR: 4.440, p = 0.004). PNX may be associated with a worse prognosis in terms of mortality in COVID patients. Possible mechanisms may include the hyperinflammatory status associated with critical illness, the use of NIV, the severity of respiratory failure and cognitive impairment. We suggest, in selected patients showing low P/F ratio, cognitive impairment and metabolic cytokine storm, an early treatment of systemic inflammation in association with high-flow oxygen therapy as a safer alternative to NIV in order to avoid fatalities connected with PNX.

Unplanned 30-day readmissions, comorbidity and impact on one-year mortality following incident heart failure hospitalisation in Western Australia, 2001-2015.

BACKGROUND: Readmissions within 30 days after heart failure (HF) hospitalisation is considered an important healthcare quality metric, but their impact on medium-term mortality is unclear within an Australian setting. We determined the frequency, risk predictors and relative mortality risk of 30-day unplanned readmission in patients following an incident HF hospitalisation. METHODS: From the Western Australian Hospitalisation Morbidity Data Collection we identified patients aged 25-94 years with an incident (first-ever) HF hospitalisation as a principal diagnosis between 2001 and 2015, and who survived to 30-days post discharge. Unplanned 30-day readmissions were categorised by principal diagnosis. Logistic and Cox regression analysis determined the independent predictors of unplanned readmissions in 30-day survivors and the multivariable-adjusted hazard ratio (HR) of readmission on mortality within the subsequent year. RESULTS: The cohort comprised 18,241 patients, mean age 74.3 ± 13.6 (SD) years, 53.5% males, and one-third had a modified Charlson Comorbidity Index score of ≥ 3. Among 30-day survivors, 15.5% experienced one or more unplanned 30-day readmission, of which 53.9% were due to cardiovascular causes; predominantly HF (31.4%). The unadjusted 1-year mortality was 15.9%, and the adjusted mortality HR in patients with 1 and ≥ 2 cardiovascular or non-cardiovascular readmissions (versus none) was 1.96 (95% confidence interval (CI) 1.80-2.14) and 3.04 (95% CI, 2.51-3.68) respectively. Coexistent comorbidities, including ischaemic heart disease/myocardial infarction, peripheral arterial disease, pneumonia, chronic kidney disease, and anaemia, were independent predictors of both 30-day unplanned readmission and 1-year mortality. CONCLUSION: Unplanned 30-day readmissions and medium-term mortality remain high among patients who survived to 30 days after incident HF hospitalisation. Any cardiovascular or non-cardiovascular readmission was associated with a two to three-fold higher adjusted HR for death over the following year, and various coexistent comorbidities were important associates of readmission and mortality risk. Our findings support the need to optimize multidisciplinary HF and multimorbidity management to potentially reduce repeat hospitalisation and improve survival.

A nomogram to predict preterm birth in twin pregnancies.

PURPOSE: To investigate risk factors for preterm birth in twin pregnancies, and to establish a nomogram model for predicting preterm birth and verify its application value. METHODS: Data from 266 twin pregnancies between January 2015 and December 2020 were analyzed in this retrospective study. According to the gestational weeks of delivery, the included subjects were divided into a preterm birth group (gestational age < 37 weeks) and a full-term group (gestational age ≥ 37 weeks). The general situation and pregnancy complications of the two groups were analyzed by univariate analysis, and the factors with statistical significance were entered into multivariate logistic regression analysis. Furthermore, the nomogram model for predicting the risk of preterm birth was established by using R. The predictive effect of the model was evaluated by the area under the ROC curve, C-index, and decision curve analysis. RESULTS: Demographic characteristics and their associations with preterm birth and full-term birth in twin pregnancies were summarized and analyzed. After validation, we identified the following significant predictors of preterm birth: chorionic status, inconsistent development of twins, premature rupture of membranes, fetal distress, scar uterus, and preeclampsia. Overall, we constructed preterm risk nomogram model with C-index of 0.783. A nomogram using a 0-100 scale illustrated our final model for predicting preterm birth in twin pregnancies. CONCLUSIONS: We developed and validated a clinical nomogram to predict preterm birth in twin pregnancy. Chorionic status, inconsistent development of twins, premature rupture of membranes, fetal distress, scar uterus, and preeclampsia were independent risk predictors for preterm birth in twin pregnancy.

Predictive Risk Modeling for Recurrence of Child Maltreatment Using Cases from the National Child Maltreatment Data System in Korea: Exploratory Data Analysis Using Data Mining Algorithm.

The purpose of this study was to explore and identify patterns of risk predictors of maltreatment recurrence using predictive risk modeling (PRM). This study used the administrative dataset from the National Child Maltreatment Information System recorded by Korean CPS (Child Protective Service) workers. The information, including recurrent maltreatment, was collected in 2012; then, those reported cases were followed for 2 years through 2014. The data included information about child, family, caregiver, maltreatment, and service characteristics and consisted of male (50.22%) and female (49.78%) children with an average age of 9 years (n = 4319). We examined the association of risk factors with recurrence using conditional inference trees (CTREE): a tree-based data mining algorithm for classification that allows the exploration of the interconnection between hypothesized risk factors. Study findings showed that a history of prior CPS involvement was the first decision point in the decision tree structure of recurrence. The effect of other risk factors depended on the presence of prior CPS involvement. In the absence of prior CPS involvement, cases with (a) a single-parent status and (b) a caregiver's alcohol abuse living in other types of households (two-parent households, kinship care, and children without parents) were associated with recurrence. In the presence of prior CPS involvement, cases with out-of-home care or others (long- or short-term foster care and emergency placement) in the final decision of child placement (a) where in-home care in the initial decision of child placement within the presence of physical abuse and (b) where social isolation without physical abuse was related to recurrence. Cases with (a) a male caregiver and (b) a female caregiver with social isolation and without social isolation yet employed were at high risk for recurrence under the circumstance of in-home care in the final decision of child placement. This exploratory study found multiple connections among the factors in the prediction of recurrence. The CTREE helps unravel the complexity embedded in maltreatment recurrence by capturing its patterns. This information can deepen our knowledge of associations between risk factors in the prediction of recurrence and be used as a reference to inform child maltreatment policy and prevention.

Risk factors for early neurological deterioration in acute isolated pontine infarction without any causative artery stenosis.

BACKGROUND: This study aimed to investigate the risk predictors for early neurological deterioration (END) in isolated acute pontine infarction without any causative artery stenosis. METHODS: In this retrospective study, patients with isolated acute pontine infarction within 72 h of symptom onset were enrolled between October 2017 and December 2021. END was defined as an increase in the National Institutes of Health Stroke Scale (NIHSS) score ≥ 2 points within the first week postadmission. Patients were divided into the END and the non-END groups. Multiple logistic regression analysis was used to evaluate independent predictors of END in patients with isolated acute pontine infarction. RESULTS: A total of 153 patients were included in the final study (62 females; mean age, 67.27 ± 11.35 years), of whom 28.7% (47 of 153) experienced END. Multiple logistic regression analyses showed that infarct volume (adjusted odds ratio [aOR], 1.003; 95% CI, 1.001-1.005; P = 0.002) and basilar artery branch disease  (aOR, 3.388; 95% CI, 1.102-10.417; P = 0.033) were associated with END. The combined ROC analysis of the infarct volume and basilar artery branch disease for predicting END showed that the sensitivity and specificity were 80.9% and 72.6%, respectively. CONCLUSION: Basilar artery branch disease and infarct volume were associated with END in acute isolated pontine infarction and may be useful prognostic factors for neurological progression.

Development and validation of a nomogram to predict recurrence in children with Henoch-Schönlein purpura.

BACKGROUND: To screen risk factors for the recurrence in children with Henoch-Schönlein Purpura (HSP) and to develop and validate a nomogram for recurrence in children with HSP. METHODS: During September 2019 and September 2021, 212 children with HSP were selected in this study. The children were divided into two sets in a proportion of 7:3 using R language, with the first group as the training sets and the second as the internal validation sets. The related variables were analyzed by univariate and multivariate logistic regression analyses, and a nomogram for predicting the recurrence in HSP children was established. The nomogram was evaluated by ROC curve, calibration curve and decision curve, and 1000 times bootstrap resampling method was used to verify the model internally. RESULTS: Univariate and multivariate regression analyses identified respiratory infection, without preventive medication and diet restriction, age, allergen positive and abnormal urine routine as risk factors for the recurrence in children with HSP. Those risk factors were used to construct a predictive nomogram. The calibration curves revealed excellent accuracy of the predictive nomogram model, internally and externally. CONCLUSIONS: We constructed and validated a clinical nomogram to predict the recurrence in children with HSP. We confirmed that respiratory tract infection, without preventive medication and diet restriction, age, allergen positive and abnormal urine routine were independent recurrence risk factors. This nomogram had a good performance in clinical decision-making.

Does implant location influence the risk of peri-implantitis?

Peri-implantitis is characterized by nonreversible and progressive loss of supporting bone and is associated with bleeding and/or suppuration on probing. Peri-implant disease is considered as the main etiologic factor related to implant failure. Peri-implant disease has a pathogenesis similar to that of periodontal disease, both being triggered by an inflammatory response to the biofilm accumulation. Although the prevalence of peri-implantitis has been evaluated by several clinical studies with different follow-ups, there are currently little data on the impact of implant location and the prevalence of peri-implantitis. The aim of this review, therefore, was to summarize the evidence concerning the prevalence of peri-implantitis in relation to implant location and associated risk predictors. Even though most studies evaluating the prevalence of peri-implantitis in relation to implant location are cross-sectional or retrospective, they suggest that the occurrence of peri-implantitis is most prevalent in the anterior regions of the maxilla and mandible. Moreover, it seems that there is a higher prevalence of peri-implantitis in the maxilla than in the mandible.

A susceptibility putative haplotype within NLRP3 inflammasome gene influences ischaemic stroke risk in the population of Punjab, India.

Despite strong genetic implications of NLRP3 inflammasome, its examination as genetic determinant of ischaemic stroke (IS) remains to be done in Punjab, which has been investigated in this study. In this case control study, 400 subjects (200 IS patients, 200 stroke free controls) were included. Contributions of 5 single nucleotide polymorphisms (SNPs) including a functional SNP within NLRP3 gene (rs10754558, rs4612666, rs2027432, rs3738488 and rs1539019) for the risk of IS were investigated through genetic models after correcting the effect of significant variables. Plasma levels of three pro-inflammatory markers, that is, C-reactive protein (CRP), interleukin-1beta (IL-1ß) and interleukin-18 (IL-18) were measured by enzyme-linked immunosorbent assays (ELISA). Minor alleles of 3 out of 5 SNPs (rs10754558, rs4612666 and rs1539019) exhibited association with IS risk in additive, recessive and multiplicative models. Multivariable regression analysis confirmed that higher levels of systolic blood pressure (ß ± SE: 1.42 ± 0.57, p = .013), CRP (ß ± SE: 1.22 ± 0.41, p = .003), IL-1ß (ß ± SE: 1.78 ± 0.88, p = .043) and IL-18 (ß ± SE: 1.13 ± 0.49, p = .021) were independent risk predictors for IS. Haplotype analysis revealed a susceptibility putative haplotype GTGTA, which approximately doubled the IS risk (OR: 1.98, 95% CI: 1.12-3.78, p = .04) in dominant mode after adjusting the effect with confounding variables. This susceptibility putative haplotype GTGTA was significantly associated with increased concentrations of CRP (ß = 1.21, p = .014) and IL-1ß (ß = 1.53, p = .034) in dose-dependent manner (less in carriers of 1 copy than those who had 2 copies of GTGTA). The present study has revealed a susceptibility putative haplotype GTGTA within NLRP3 gene, carriers of which have double the risk of IS by having increased plasma levels of CRP and IL-1ß in a dose-dependent manner.

Clonal heterogeneity and rates of specific chromosome gains are risk predictors in childhood high-hyperdiploid B-cell acute lymphoblastic leukemia.

B-cell acute lymphoblastic leukemia (B-ALL) is the commonest childhood cancer. High hyperdiploidy (HHD) identifies the most frequent cytogenetic subgroup in childhood B-ALL. Although hyperdiploidy represents an important prognostic factor in childhood B-ALL, the specific chromosome gains with prognostic value in HHD-B-ALL remain controversial, and the current knowledge about the hierarchy of chromosome gains, clonal heterogeneity and chromosomal instability in HHD-B-ALL remains very limited. We applied automated sequential-iFISH coupled with single-cell computational modeling to identify the specific chromosomal gains of the eight typically gained chromosomes in a large cohort of 72 primary diagnostic (DX, n = 62) and matched relapse (REL, n = 10) samples from HHD-B-ALL patients with either favorable or unfavorable clinical outcome in order to characterize the clonal heterogeneity, specific chromosome gains and clonal evolution. Our data show a high degree of clonal heterogeneity and a hierarchical order of chromosome gains in DX samples of HHD-B-ALL. The rates of specific chromosome gains and clonal heterogeneity found in DX samples differ between HHD-B-ALL patients with favorable or unfavorable clinical outcome. In fact, our comprehensive analyses at DX using a computationally defined risk predictor revealed low levels of trisomies +18+10 and low levels of clonal heterogeneity as robust relapse risk factors in minimal residual disease (MRD)-negative childhood HHD-B-ALL patients: relapse-free survival beyond 5 years: 22.1% versus 87.9%, P < 0.0001 and 33.3% versus 80%, P < 0.0001, respectively. Moreover, longitudinal analysis of matched DX-REL HHD-B-ALL samples revealed distinct patterns of clonal evolution at relapse. Our study offers a reliable prognostic sub-stratification of pediatric MRD-negative HHD-B-ALL patients.