Background: Clinical profile of polyps in paediatric cases are less in South India. Juvenile Polyps were the most common polyps in paediatric cases described in literature, presenting as LGI bleed. The aim of the study is to describe the clinical profile of colorectal polyps in paediatric population in a single tertiary care centre in South India.Methods: Paediatric cases between 0 and 16 years of age who underwent colonoscopy in our department from January 2002 to July 2018 were included from database. These cases were retrospectively analysed for presence of polyps, clinical presentation, indication for colonoscopy, histopathology of the resected polyps and other demographic details. Incomplete procedures were excluded.Results: About 166 paediatric cases underwent colonoscopy in the study period. 21 cases (12.65%) had colorectal Polyps. 85.7% of the polyps were in recto sigmoid region. Most common histological type was Juvenile Polyp (51.6%). One infant had sessile polyp in descending colon which was reported as heterotrophic esophageal mucosa in histopathology. LGI bleed was the most common presentation in children with polyps (66.6%).Conclusions: The prevalence of polyps in our cohort was 12.65%. Solitary Juvenile Polyp was the most common polyp in children, with lower GI bleed as the most common presenting feature. Rare case of heterotrophic esophageal polyp was seen in descending colon.
Abstract Background—The risk of sudden cardiac death (SCD) is known to be dynamic. However, the accuracy of a dynamic SCD prediction is unknown. We aimed to measure the dynamic predictive accuracy of ECG biomarkers of SCD and competing non-sudden cardiac death (non-SCD). Methods—Atherosclerosis Risk In Community study participants with analyzable ECGs in sinus rhythm were included (n=15,716; 55% female, 73% white, age 54.2±5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity and traditional ECG metrics (heart rate, QRS, QTc) were measured. Adjudicated SCD was the primary outcome; non-SCD was competing outcome. Time-dependent area under the receiver operating characteristic curve (ROC(t) AUC) analysis was performed to assess the prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years using survival analysis framework. Reclassification improvement as compared to clinical risk factors (age, sex, race, diabetes, hypertension, coronary heart disease, stroke) was measured. Results—Over a median 24.4 y follow-up, there were 577 SCDs (incidence 1.76 (95%CI 1.63-1.91)/1,000 person-years), and 829 non-SCDs [2.55 (95%CI 2.37-2.71)]. No ECG biomarkers predicted SCD within 3 months after ECG recording. Within 6 months, spatial ventricular gradient (SVG) elevation predicted SCD (AUC 0.706; 95%CI 0.526-0.886), but not a non-SCD (AUC 0.527; 95%CI 0.303-0.75). SVG elevation more accurately predicted SCD if ECG was recorded 6 months before SCD (AUC 0.706; 95%CI 0.526-0.886) than 2 years before SCD (AUC 0.608; 95%CI 0.515-0.701). Within the first 3 months after ECG recording, only SVG azimuth improved reclassification of the risk beyond clinical risk factors: 18% SCD events were reclassified from low or intermediate risk to a high-risk category. Long-term, QRS-T angle was the strongest predictor of SCD (AUC 0.710; 95%CI 0.668-0.753 for ECG recorded within 10 years before SCD). Conclusion—Short-term and long-term predictive accuracy of ECG biomarkers of SCD differed, reflecting differences in transient vs. persistent SCD substrates. The dynamic predictive accuracy of ECG biomarkers should be considered for competing SCD risk scores. The distinction between markers predicting short-term and long-term events may represent the difference between markers heralding SCD (triggers or transient substrates) versus markers identifying persistent substrate.
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Patients with headache, transient neurological episodes, symptoms after minor head trauma, and neck and low back pain often present to general practitioners and emergency room physicians. The examining doctor may be uncertain whether neurological imaging is needed. In this article, we discuss indications for imaging and tests that would be most useful in these scenarios. Table 1⇓ summarises our approach to this problem. Figure 1⇓ provides a walk through of representative images from patients with headache or minor head trauma, showing normal and abnormal findings. Figure 2⇓ shows various examples of abnormal imaging findings relevant to the clinical scenarios described here.
Occasionally, imaging leads to the incidental discovery of a lesion of unknown importance. We will also discuss the management and interpretation of such findings.
Fig 1 (A) In acute headache or minor head trauma, head computed tomography may be recommended. All images are oriented axially. A normal head computed tomography is shown. The brain structures are evaluated for symmetry …
Additional file 1: Table S1. Time-dependent AUC with 95% Confidence Interval for prediction of SCD and non-SCD, for windows of prediction 3, 6, 9 months, 1, 2, 3, 5, 10, 15 years for traditional ECG markers, and GEH-ECG in five partitions of the study dataset. See separate excel file. _lb = lower bound; _ub = upper bound. HR = heart rate; qtc = QTc interval; qrs = QRS interval; pQRST = peak QRS-T angle; aQRST = area QRS-T angle; pSVGaz = peak SVG azimuth; aSVGaz = area SVG azimuth; pSVGel = peak SVG elevation; aSVGel = area SVG elevation; pSVGmag = peak SVG magnitude; aSVGmag = area SVG magnitude. SAI = Sum Absolute QRST Integral (SAI QRST).
Abstract Echocardiography is commonly utilized in patients with acute respiratory distress syndrome (ARDS) for assessment of cardiac function, volume status, and the potential development of acute cor pulmonale. In severe ARDS, prone positioning is frequently used, which imposes technical challenges during transthoracic echocardiography (TTE) image acquisition. Moreover, prone positioning can affect cardiopulmonary function in ways that are reflected on the echocardiographic findings in this position. Historically, a transesophageal approach was recommended when a patient is prone, with few studies reporting utility of TTE in this setting. However, recent publications have begun to address this knowledge gap. This review explores recent literature addressing the use of TTE in prone patients with ARDS, with a special focus on the cardiopulmonary effects of proning and potential solutions to the technical difficulties that arise in this position.
Introduction: Acute respiratory distress syndrome (ARDS) is a common presentation of patients with COVID-19 that often requires the initial use of venovenous extracorporeal membrane oxygenation (VV-ECMO) for management, but its clinical course may necessitate conversion to alternative ECMO configurations as V-A (including VV-A), V-AV (including VV-AV), and V-PA. Our study aims to provide insights into the characteristics and outcomes associated with conversion. Methods: We performed a retrospective analysis from the ELSO registry on all adult patients (≥ 18 years old) diagnosed with COVID-19 based on ICD-10 coding who received VV-ECMO between 2020 and 2022. Descriptive statistics were performed for categorical and continuous variables in our study population, comparing patients with COVID-19 supported by VV-ECMO who did or did not require conversion to a VA or hybrid ECMO configuration at the time of data query. We also performed a 3:1 propensity score matching to further examine the all-cause mortality associated with conversion. Results: Out of 12,858 patients initially started on VV-ECMO, there was a 3% conversion rate to VA-ECMO or other hybrid configurations. There were no significant differences in baseline characteristics. Pre-ECMO arrest (5.1% vs 3.1%, p< 0.05) and renal replacement therapy (RRT) (45.6% vs 24.5%, p< 0.05) were more prevalent in the conversion group. The conversion group also had a higher in-hospital mortality (66.2% vs 48.7%, p< 0.05), and longer duration of ECMO support (1238 ± 63 hours vs 654 ± 5.9 hours, p< 0.05). After propensity matching, the conversion of VV-ECMO to an alternative mode is associated with a mortality rate of 22.7% (95% CI: 16.4 – 29.1, p< 0.001). There continues to be an increased incidence of CPR requirement, cardiac arrhythmias, pneumothorax, and gastrointestinal bleeding associated with the conversion group. Conclusions: In conclusion, this study provides valuable insights into the clinical factors, outcomes, treatment modalities, and complication rates associated with VV-ECMO and its conversion to other ECMO configurations. Further research is warranted to better understand the underlying mechanisms and optimize treatment strategies in this complex patient population.
Abstract Background The risk of sudden cardiac death (SCD) is known to be dynamic. However, an accuracy of a dynamic SCD prediction, and “expiration date” of ECG biomarkers is unknown. Our goal was to measure dynamic predictive accuracy of ECG biomarkers of SCD and competing outcomes. Methods Atherosclerosis Risk In Community study participants with analyzable digital ECGs were included (n=15,768; 55% female, 73% white, age 54.2±5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity (GEH) and traditional ECG metrics were measured. Adjudicated SCD served as the primary outcome; non-sudden cardiac death served as competing outcome. Time-dependent area under the (receiver operating characteristic) curve (AUC) analysis was performed to assess prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years, using survival analysis framework. Results Over a median 24.4 y follow-up, there were 581 SCDs (incidence 1.77 (95%CI 1.63-1.92)/1,000 person-years), and 838 nonSCDs [2.55 (95%CI 2.39-2.73)]. Resting heart rate was the strongest (AUC 0.930) short-term (3-month) non-specific SCD predictor, whereas spatial peak QRS-T angle predicted specifically SCD 15 years after ECG recording (AUC 0.719). QRS duration (AUC 0.885) and QTc (AUC 0.711) short-term predicted advanced structural heart disease better than SCD. “Expiration date” for most ECG biomarkers was two years after ECG recording. GEH significantly improved reclassification of SCD risk beyond age, sex, race, diabetes, hypertension, coronary heart disease and stroke. Conclusion Short-term predictors of SCD, nonSCD, and biomarkers of long-term SCD risk differed, reflecting differences in transient vs. persistent SCD substrates.
The risk of sudden cardiac death (SCD) is known to be dynamic. However, the accuracy of a dynamic SCD prediction is unknown. We aimed to measure the dynamic predictive accuracy of ECG biomarkers of SCD and competing non-sudden cardiac death (non-SCD).
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