Multiple Scoring Systems Research Articles

UNNECESSARY USE OF ANTIMICROBIALS – COMPARISON OF THE PREDICTIVE PERFORMANCE OF QSOFA AND APACHE SCORE FOR EVALUATION OF DISEASE PROGNOSIS PATTERNS IN CRITICAL ILLNESS

In critical care, accurate prognosis assessment, including antimicrobial therapy, is vital for guiding treatment decisions. The Acute Physiology and Chronic Health Evaluation (APACHE) and quick Sequential Organ Failure Assessment (qSOFA) scores are widely used for predicting patient outcomes. Yet, their relative performance and potential implications for antimicrobial stewardship need further exploration. Objective: To evaluate the disease prognosis patterns in critically ill patients by comparing the predictive performance of APACHE and qSOFA scores and to explore their correlation with antimicrobial misuse. Methods: A comparative study was conducted at the National Hospital and Medical Center in Lahore from January to November 2023. The study included 138 critically ill patients. Demographic information, clinical parameters, and medical history were collected, explicitly focusing on APACHE and qSOFA scores recorded at admission and during follow-up. Statistical analysis, including Pearson's and Spearman's correlation coefficients and logistic regression models, was performed using RStudio to assess the predictive ability of these scores for disease progression and patient outcomes. Results: The analysis revealed a moderate positive correlation (r=0.51) between qSOFA and APACHE-II scores, suggesting that both scores align in assessing the severity of illness in critically ill patients. The predictive models indicated that combining qSOFA and APACHE-II scores enhanced the accuracy of predicting critical outcomes, such as shortness of breath (SOB), with a combined model AUC of 0.659 compared to 0.601 for the APACHE-II model alone. Conclusion: The findings underscore the value of integrating multiple clinical scoring systems in managing critically ill patients. Such integration can aid in more judicious use of antibiotics, potentially mitigating the risk of antimicrobial resistance. The study advocates incorporating these insights into clinical guidelines and decision-making processes in critical care settings.

Predictive Value of Multiple Scoring Systems in the Prognosis of Septic Patients with Different Infection Sites: Analysis of the Medical Information Mart for the Intensive Care IV Database.

The heterogeneity nature of sepsis is significantly impacted by the site of infection. This study aims to explore the predictive value of multiple scoring systems in assessing the prognosis of septic patients across different infection sites. Data for this retrospective cohort study were extracted from the Medical Information Mart for Intensive Care IV database (MIMIC-IV) (v2.2). Adult patients meeting the criteria for sepsis 3.0 and admitted to the intensive care unit (ICU) were enrolled. Infection sites included were pneumonia, urinary tract infection (UTI), cellulitis, abdominal infection, and bacteremia. The primary outcome assessed was 28-day mortality. The sequential Organ Failure Assessment (SOFA) score, Oxford Acute Severity of Illness Score (OASIS), and Logistic Organ Dysfunction System (LODS) score were compared. Binomial logistic regression analysis was conducted to evaluate the association between these variables and mortality. Additionally, differences in the area under the curve (AUC) of receiver operating characteristic (ROC) among the scoring systems were analyzed. A total of 4721 patients were included in the analysis. The average 28-day mortality rate was 9.4%. Significant differences were observed in LODS, OASIS, and SOFA scores between the 28-day survival and non-survival groups across different infection sites (p < 0.01). In the pneumonia group and abdominal infection group, both the LODS and OASIS scoring systems emerged as independent risk factors for mortality in septic patients (odds ratio [OR]: 1.165, 95% confidence interval [CI]: 1.109-1.224, p < 0.001; OR: 1.047, 95% CI: 1.028-1.065, p < 0.001) (OR: 1.200, 95% CI: 1.091-1.319, p < 0.001; OR: 1.060, 95% CI: 1.025-1.095, p < 0.001). For patients with UTI, the LODS, OASIS, and SOFA scoring systems were identified as independent risk factors for mortality (OR: 1.142, 95% CI: 1.068-1.220, p < 0.001; OR: 1.062, 95% CI: 1.037-1.087, p < 0.001; OR: 1.146, 95% CI: 1.046-1.255, p = 0.004), with the AUC of LODS score and OASIS significantly higher than that of the SOFA score (p = 0.006). Among patients with cellulitis, the OASIS and SOFA scoring systems were identified as independent risk factors for mortality (OR: 1.055, 95% CI: 1.007-1.106, p = 0.025; OR: 1.187, 95% CI: 1.005-1.403, p = 0.044), with no significant difference in prognosis prediction observed (p = 0.243). In the bacteremia group, the LODS scoring system was identified as an independent risk factor for mortality (OR: 1.165, 95% CI: 1.109-1.224, p < 0.001). The findings suggest that LODS scores offer better prognostic accuracy for predicting the mortality risk in septic patients with pneumonia, abdominal infections, bacteremia, and UTI compared to SOFA scores.

Predictive Modeling for Spinal Metastatic Disease.

Spinal metastasis is exceedingly common in patients with cancer and its prevalence is expected to increase. Surgical management of symptomatic spinal metastasis is indicated for pain relief, preservation or restoration of neurologic function, and mechanical stability. The overall prognosis is a major driver of treatment decisions; however, clinicians' ability to accurately predict survival is limited. In this narrative review, we first discuss the NOMS decision framework used to guide decision making in the treatment of patients with spinal metastasis. Given that decision making hinges on prognosis, multiple scoring systems have been developed over the last three decades to predict survival in patients with spinal metastasis; these systems have largely been developed using expert opinions or regression modeling. Although these tools have provided significant advances in our ability to predict prognosis, their utility is limited by the relative lack of patient-specific survival probability. Machine learning models have been developed in recent years to close this gap. Employing a greater number of features compared to models developed with conventional statistics, machine learning algorithms have been reported to predict 30-day, 6-week, 90-day, and 1-year mortality in spinal metastatic disease with excellent discrimination. These models are well calibrated and have been externally validated with domestic and international independent cohorts. Despite hypothesized and realized limitations, the role of machine learning methodology in predicting outcomes in spinal metastatic disease is likely to grow.

Scoring system related to retrograde percutaneous coronary intervention for coronary chronic total occlusion

AbstractThe retrograde approach is a principal procedure used in coronary chronic total occlusion percutaneous coronary intervention. However, the retrograde approach presents more challenges compared with the antegrade approach, as it is associated with a lower rate of success and a higher risk of complications. An accurate pre‐procedural evaluation of the complexity of a lesion could aid in the planning of the procedure, in estimating the procedure's duration, or in determining whether the patient should be referred to another center specializing in CTO‐PCI, as well as in a more precise evaluation of the risk‐benefit ratio. In recent years, multiple scoring systems have been created to forecast the success and efficiency of the retrograde procedure. However, each scoring system was developed independently, and comparative studies were lacking. This article provides a review of these scoring systems, offers an overview of the current state of the retrograde approach, and aims to stimulate further discussion on this topic.

Development of a Novel Comprehensive Hepatocellular Carcinoma Outcome Prognostic Scoring System With Integration of Imaging Features.

Accurate prognostic stratification of hepatocellular carcinoma (HCC) is vital for clinical trial enrollment and treatment allocation. Multiple scoring systems have been created to predict patient survival, but no standardized scoring systems account for radiologic tumor features. We sought to create a generalizable scoring system for HCC which incorporates standardized radiologic tumor features and more accurately predicts overall survival (OS) than established systems. Clinicopathologic parameters were collected from a prospectively collected cohort of patients with HCC treated at a single institution. Imaging studies were evaluated for tumor characteristics. Patients were randomly divided into a training set for identification of covariates that impacted OS and a validation set. Cox models were used to determine the association of various factors with OS and a scoring system was created. We identified 383 patients with HCC with imaging and survival outcomes, n = 255 in the training set and 128 in the validation cohort. Factors associated with OS on multivariate analysis included: tumor margin appearance on CT or MRI (hazard ratio [HR] 1.37, 95% CI, 1.01-1.88) with infiltrative margins portending worse outcomes than encapsulated margins, massive tumor morphology (HR 1.64, 95% CI, 1.06-2.54); >2 lesions (HR 2.06, 95% CI, 1.46-2.88), Child-Turcotte-Pugh class C (HR 3.7, 95% CI, 2.23-6.16), and portal vein thrombus (HR 2.41, 95% CI, 1.71-3.39). A new scoring system was developed and more predictive of OS than other well-established systems. Incorporation of standardized imaging characteristics to established clinical and lab predictors of outcome resulted in an improved predictive scoring system for patients with HCC.

SCOPING REVIEW OF CLINICAL STUDIES EXPLORING THE ASSOCIATION BETWEEN EPIGENETIC AGE AND FRAILTY

Abstract An overall increase in life expectancy shines light on the complexity of human aging where some individuals seem to age at a faster pace than others, a phenomenon health care systems are already battling to identify. Multiple frailty scoring systems have been proposed as models for biological age estimations but their implementation within health care systems is time consuming and often deprioritized. Epigenetic clocks based on DNA methylation (DNAm) changes have been proposed as newer estimations of biological age, but there is conflicting data on the correlation between these two measures. We conducted a review of the literature to identify studies that have explored the correlation between frailty and epigenetic age. Our search strategy identified 37 articles, and after further screening we found 15 articles that directly compared frailty scores to epigenetic age. Most studies measured DNAm in whole blood (9/15), although there was great variability in the specific epigenetic clocks applied. Almost all studies measured frailty with either Fried’s frailty phenotype (4/15) or a Frailty Index (9/15). The studies were divided in their findings, with 7/15 showing moderate to strong associations and the other 8 studies showing no or weak associations. Interestingly, the associations with frailty were usually seen for epigenetic clocks predicting mortality or other phenotypes (eg GrimAge, PhenoAge), rather than epigenetic clocks predicting chronological age. More work is needed to understand the relationship between these biological age measures and their potential role in clinical risk assessment for older adults.

Evaluation of Multiple Liver Cancer Scoring Systems.

Liver cancer is one of the most common malignant tumors in the world, and its incidence and mortality are increasing year by year. The prognosis of liver cancer depends on the stage of liver cancer, the treatment method, the liver function, and individual differences. The prognosis of liver cancer mainly worsens with the progression of the stage. The prediction and staging system of liver cancer prognosis plays a very important role in the outcome of liver cancer prognosis, providing some guidance for clinical practice and bringing benefits for patients. This article reports on the prediction models and staging systems that have been applied in the field of liver cancer in the past 5 years, objectively analyzes the advantages and disadvantages, applicable population of each model and staging system, and searches for other patient and clinical characteristics that need to be considered for successfully establishing a prediction model, aiming to improve the specificity, sensitivity, and accuracy of liver cancer prediction and increase the overall survival rate of liver cancer.

Predictive value of ELWI combined with sRAGE/esRAGE levels in the prognosis of critically ill patients with acute respiratory distress syndrome

Acute respiratory distress syndrome (ARDS) is a life-threatening condition. Accurate judgement of the disease progression is essential for controlling the condition in ARDS patients. We investigated whether changes in the level of serum sRAGE/esRAGE could predict the 28-day mortality of ICU patients with ARDS. A total of 83 ARDS patients in the ICU of the Second Affiliated Hospital of Nantong University from January 2021 to June 2022 were consecutively enrolled in this study. Demographic data, primary diagnosis and comorbidities were obtained. Multiple scoring systems, real-time monitoring systems, and biological indicators were determined within 6 h of admission. The clinical parameters for survival status of the ARDS patients were identified by multivariate logistic regression. Receiver operating characteristic (ROC) curve analysis was employed to verify the accuracy of the prognosis of the related parameters. The admission level of sRAGE was significantly higher in the nonsurvival group than in the survival group (p < 0.05), whereas the serum esRAGE level showed the opposite trend. Multivariate logistic regression analysis showed that sRAGE (AUC 0.673, p < 0.05), esRAGE (AUC 0.704, p < 0.05), and ELWI (extravascular lung water index) (AUC 0.717, p < 0.05) were independent risk factors for the prognosis of ARDS. Model B (ELWI + esRAGE) could not be built as a valid linear regression model (ELWI, p = 0.079 > 0.05). Model C (esRAGE + sRAGE) was proven to have no significance because it had a predictive value similar to that of the serum levels of esRAGE (Z = 0.993, p = 0.351) or sRAGE (Z = 1.116, p = 0.265) alone. Subsequently, Model D (sRAGE + esRAGE + ELWI) showed the best 28-day mortality predictive value with a cut-off value of 0.426 (AUC 0.841; p < 0.001), and Model A (sRAGE + ELWI) had a cut-off value of 0.401 (AUC 0.820; p < 0.001), followed by sRAGE (AUC 0.704, p = 0.004), esRAGE (AUC 0.717, p = 0.002), and ELWI (AUC 0.637, p = 0.028). In addition, there was no statistically significant difference between Model A and Model D (Z = 0.966, p = 0.334). The admission level of sRAGE was higher in the nonsurvival group, while the serum esRAGE level showed the opposite trend. Model A and Model D could be used as reliable combined prediction models for predicting the 28-day mortality of ARDS patients.

Correlating Quantitative MRI-based Apparent Diffusion Coefficient Metrics with 24-month Neurodevelopmental Outcomes in Neonates from the HEAL Trial.

Background Multiple qualitative scoring systems have been created to capture the imaging severity of hypoxic ischemic brain injury. Purpose To evaluate quantitative volumes of acute brain injury at MRI in neonates with hypoxic ischemic brain injury and correlate these findings with 24-month neurodevelopmental outcomes and qualitative brain injury scoring by radiologists. Materials and Methods In this secondary analysis, brain diffusion-weighted MRI data from neonates in the High-dose Erythropoietin for Asphyxia and Encephalopathy trial, which recruited participants between January 2017 and October 2019, were analyzed. Volume of acute brain injury, defined as brain with apparent diffusion coefficient (ADC) less than 800 × 10-6 mm2/sec, was automatically computed across the whole brain and within the thalami and white matter. Outcomes of death and neurodevelopmental impairment (NDI) were recorded at 24-month follow-up. Associations between the presence and volume (in milliliters) of acute brain injury with 24-month outcomes were evaluated using multiple logistic regression. The correlation between quantitative acute brain injury volume and qualitative MRI scores was assessed using the Kendall tau-b test. Results A total of 416 neonates had available MRI data (mean gestational age, 39.1 weeks ± 1.4 [SD]; 235 male) and 113 (27%) showed evidence of acute brain injury at MRI. Of the 387 participants with 24-month follow-up data, 185 (48%) died or had any NDI. Volume of acute injury greater than 1 mL (odds ratio [OR], 13.9 [95% CI: 5.93, 32.45]; P < .001) and presence of any acute injury in the brain (OR, 4.5 [95% CI: 2.6, 7.8]; P < .001) were associated with increased odds of death or any NDI. Quantitative whole-brain acute injury volume was strongly associated with radiologists' qualitative scoring of diffusion-weighted images (Kendall tau-b = 0.56; P < .001). Conclusion Automated quantitative volume of brain injury is associated with death, moderate to severe NDI, and cerebral palsy in neonates with hypoxic ischemic encephalopathy and correlated well with qualitative MRI scoring of acute brain injury. Clinical trial registration no. NCT02811263 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Huisman in this issue.

Utilizing the R.E.N.A.L Nephrometry Score to predict the Surgical Technique and Peri-operative Outcomes of Renal Masses

Background: despite the rise in the incidence of renal cell carcinoma attributed to availability of medical imaging, a considerable decline in mortality is an association. Morbidity-wise, the shift from radical nephrectomy to partial nephrectomy is the trend for now. Multiple scoring systems have been introduced over the past decades to help surgeons choose between radical and partial nephrectomy. One commonly used system is the RENAL nephrometry score that was first introduced by Kutikov and Uzzo in 2009. Objective: to evaluate the role of RENAL nephrometry scoring system in predicting the surgical technique to use to resect renal masses and associated perioperative outcomes. Subjects and methods: between December 2018 and December 2020, we prospectively recruited 88 patients with renal masses. Nephrometry scores of all patients were calculated by an experienced radiologist and a decision then was made by blinded treating surgeons to proceed to radical or partial nephrectomy. Patients then sub-grouped into low, moderate, and high nephrometry scores, and into radical and partial nephrectomy. Pre-, intra-, and post-operative data were collected and analyzed. Results: Eighty-three patients completed the study. Thirty-three had undergone radical nephrectomy and 50 had partial nephrectomy. Total nephrometry score differed significantly between the two groups. Mass radius and nearness to the renal hilum were the only influential components. The only complication that differed significantly among the three nephrometry groups was the estimated blood loss, being highest in the low complexity group. No significant difference was found in the total operation time, ischemia time, renal function and hospital stay. Major complications were seen only in the high complexity group. Conclusion: Total nephrometry score, mass radius and nearness to renal hilum can be regarded as good and reproducible predictors of type of surgery required to treat renal masses. They also can predict the perioperative complication to a good extent.

Risk factors and their interactive effects on severe acute pancreatitis complicated with acute gastrointestinal injury.

There are many risk factors for severe acute pancreatitis (SAP) complicated with acute gastrointestinal injury (AGI), but few reports on the interaction between these risk factors. To analyze the risk factors for SAP complicated with AGI and their interactive effects. We selected 168 SAP patients admitted to our hospital between December 2019 and June 2022. They were divided into AGI group and non-AGI group according to whether AGI was present. Demographic data and laboratory test data were compared between the two groups. The risk factors for SAP with concomitant AGI were analyzed using multifactorial logistic regression, and an analysis of the interaction of the risk factors was performed. The percentage of patients with multiple organ dysfunction syndrome, acute physiological and chronic health scoring system II (APACHE II) score, white blood cell count and creatinine (CRE) level was higher in the AGI group than in the non-AGI group. There was a statistically significant difference between the two groups (P < 0.05). Logistic regression analysis indicated that an APACHE II score > 15 and CRE > 100 µmol/L were risk factors for SAP complicating AGI. The interaction index of APACHE II score and CRE level was 3.123. An APACHE II score > 15 and CRE level > 100 µmol/L are independent risk factors for SAP complicated with AGI, and there is a positive interaction between them.

Comparison of different prognostic scores in estimating short- and long-term mortality in COVID-19 patients above 60years old in a university hospital in Belgium.

Multiple scoring systems were used for risk stratification in COVID-19 patients. The objective was to determine among 6 scores which performed the best in predicting short-and long-term mortality in hospitalized COVID-19 patients ≥ 60years. An observational, retrospective cohort study conducted between 21/10/2020 and 20/01/2021. 6 scores were calculated (Clinical Frailty Scale (CFS), Charlson Comorbidity Index (CCI), 4C Mortality Score (4CMS), NEWS score (NEWS), quick-SOFA score (qSOFA), and Quick COVID-19 Severity Index (qCSI)). We included unvaccinated hospitalized patients with COVID-19 ≥ 60years old in Brugmann hospital, detected by PCR and/or suggestive CT thorax images. Old and nosocomial infections, and patients admitted immediately at the intensive care unit were excluded. 199 patients were included, mean age was 76.2years (60-99). 47.2% were female. 56 patients (28%) died within 1year after the first day of hospitalization. The 4CMS predicted the best intrahospital, 30days and 6months mortality, with area under the ROC curve (AUROC) 0.695 (0.58-0.81), 0.76 (0.65-0.86) and 0.72 (0.63-0.82) respectively. The CCI came right after with respectively AUROC of 0.69 (0.59-0.79), 0.74 (0.65-0.83) and 0.71 (0.64-0.8). To predict mortality at 12months after hospitalization, the CCI had the highest AUROC with 0.77 (0.69-0.85), before the 4CMS with 0.69 (0.60-0.79). Among 6 scores, the 4CMS was the best to predict intrahospital, 30-day and 6-month mortality. To predict mortality at 12months, CCI had the best performance before 4CMS. This reflects the importance of considering comorbidities for short- and long-term mortality after COVID 19. This study was approved by the ethical committee of Brugmann University Hospital (reference CE 2020/228).

Comparing Visual-Only and Visual-Palpation Post-Mortem Lung Scoring Systems in Slaughtering Pigs.

Respiratory diseases continue to pose significant challenges in pig production, and the assessment of lung lesions at the abattoir can provide valuable data for epidemiological investigations and disease surveillance. The evaluation of lung lesions at slaughter is a relatively simple, fast, and straightforward process but variations arising from different abattoirs, observers, and scoring methods can introduce uncertainty; moreover, the presence of multiple scoring systems complicates the comparisons of different studies, and currently, there are limited studies that compare these systems among each other. The objective of this study was to compare validated, simplified, and standardized schemes for assessing surface-related lung lesions in slaughtered pigs and analyze their reliability under field conditions. This study was conducted in a high-throughput abattoir in Italy, where two different scoring methods (Madec and Blaha) were benchmarked using 637 plucks. Statistical analysis revealed a good agreement between the two methods when severe or medium lesions were observed; however, their ability to accurately identify healthy lungs and minor injuries diverged significantly. These findings demonstrate that the Blaha method is more suitable for routine surveillance of swine respiratory diseases, whereas the Madec method can give more detailed and reliable results for the respiratory and welfare status of the animals at the farm level.

Role of Revised Baux Score in Burns

Burns is one of the risk factors contributing to the mortality and morbidity burden of developing countries. Even though advancements in burn patient management have significantly decreased the mortality. Predicting the outcome of severe burns patient at presentation plays a paramount role in guiding clinical judgment. Multiple scoring systems are available to predict mortality in burns patients in developed countries. In this article, the Revised Baux score has been applied in predicting mortality in burns patients.

Risk Factors for Coronary Artery Aneurysm in a Chinese Pediatric Population with Kawasaki Disease at Low Risk of Intravenous Immunoglobulin Resistance: A Retrospective Cohort Study

Introduction: Multiple scoring systems for predicting intravenous immunoglobulin (IVIG) resistance have been developed. Although low-scoring patients with Kawasaki disease (KD) have a favorable prognosis, many develop coronary artery aneurysms (CAAs). Herein, we determined the risk factors for CAA development among patients with KD with low risk of IVIG resistance. Methods: We compared 14 scoring systems for predicting IVIG resistance among patients with KD hospitalized from 2003 to 2022. Patients were risk stratified using an optimal scoring system. Association between baseline characteristics and CAA development was assessed within the low-risk group. Results: Overall, 664 pediatric patients with KD were included; 108 (16.3%) had IVIG resistance, and the Liping scoring system had the highest area under the curve (0.714). According to this system, 444 (66.9%) patients with KD were classified as having low risk of developing IVIG resistance (<5 points). CAA development was significantly associated with male sex (odds ratio [OR], 1.946; 95% CI: 1.015–3.730), age <6 months at fever onset (OR, 3.142; 95% CI: 1.028–9.608), and a baseline maximum Z score of ≥2.72 (OR, 3.451; 95% CI: 2.582–4.612). CAA incidence increased with the number of risk factors, and comparisons with a Kobayashi score of <5 points among patients with KD revealed similar results. Conclusions: Predicting the response to IVIG might help further reduce CAA development in patients with KD.

An Assessment of the Three Popular Prognostic Scoring Systems for Chronic Myelomonocytic Leukemia (CMML) in an Indian Context

Abstract Introduction: Chronic myelomonocytic leukemia (CMML) is a rare clonal hematopoietic neoplasm with a prevalence of 1.05 to 1.94 cases per 1,00,000 population. There are multiple prognostic scoring system used in practice for CMML, which include both cytogenetic and next-generation sequencing based. Objective This study assesses the clinicohematological profile of CMML patients, along with comparison of three widely used prognostic scoring systems for CMML (CMML-specific prognostic scoring system, MD Anderson prognostic score, Mayo prognostic model). Materials and Methods: This study is an 8-year retrospective study. All relevant data had been retrieved and reviewed by the authors. Inclusion and exclusion criteria: All the cases that were diagnosed before 2016 as per 2008 criteria were reclassified, (2) all the cases that were positive for the mutations associated with myeloproliferative neoplasms were excluded, and (3) cases with more than or equal to 20% blast/blast equivalents were excluded. A univariate analysis was done followed by a multivariate analysis for all the parameters constituting each scoring system. Lastly, a receiver operating characteristic curve was plotted for all the three scoring systems. Result: There were total 23 patients, with a median age of 63 years and a male to female ratio of 2.3:1. Cytogenetic aberration and genetic mutation were observed in 6 and 3 cases, respectively. The median overall survival (OS) was 48 months and the median leukemia-free survival was 12 months. Post-multivariate analysis, the parameters with significant impact on OS were absolute monocyte count more than 10 × 10^9/L, myeloid precursors in peripheral blood, hemoglobin less than 10g/dL, platelet less than 100 × 10^9/L, hemoglobin less than 12g/dL, and absolute lymphocyte count more than 2.5 × 10^9/L. Conclusion: To summarize, we discovered CPSS to be a better prognostic tool for a setup like ours, since molecular investigations are not always readily available for each case. More such researches are needed in the near future so that we can design better prognostic tools and see for their usefulness in real life.

Effect of medical treatment on eradication of biofilms in chronic rhinosinusitis

Background: Long-term macrolides and intranasal corticosteroids have evidence-based recommendations. It has been reported that macrolide therapy caused objective and subjective improvements which correlated to the duration of therapy. Topical nasal steroids are the mainstay of treatment in CRS. It is proposed that intranasal steroid may increase the restoration of normal epithelium. Methods: Sample size of 24 in each group is sufficient to detect the difference between positivity rate with 80% power and 5% level of significance clinically diagnosed cases of CRS with nasal polyps in age group of 18-60 years were taken. Outcome was measured with multiple scoring systems like SNOT-20, CT scoring, endoscopic scoring system. Results: Significant improvement was seen in the SNOT-20 scores with p value of 0.011 and endoscopic scores with p value of 0.001 in group having macrolides along with steroids pre-operatively however the scores post-surgery didn’t show any significant change in both groups. The efficacy of macrolide with nasal steroidal spray or nasal spray alone showed no further benefit in the subjective outcome measures post operatively. Also, no statistically significant eradication of biofilms or decrease in density could be appreciated in both groups. Furthermore, there was no significant difference in recurrence rate. Conclusions: Our result demonstrated the subjective improvement in patients of macrolide group post treatment which could be attributed to its anti-inflammatory effect. Even though macrolides in combination with nasal spray reflected some improvement in the secondary outcomes but the primary outcome of eradication of biofilms couldn’t be achieved.

Predictors for Hemorrhagic Transformation among Patients with Ischemic Stroke Admitted in a Tertiary Hospital in the Philippines from July 2018-July 2019.

Among the multiple scoring systems for hemorrhagic transformation, only few of these address spontaneous hemorrhagic transformation after an ischemic stroke, with most done with Western population data. This study aims to identify the predictors for hemorrhagic transformation among patients with ischemic stroke admitted in a tertiary hospital in Cebu City, Philippines. This is a retrospective cohort study of patients with ischemic stroke admitted in a tertiary hospital in Cebu City. Patients' baseline characteristics, clinical, and radiologic data were collected. Chi square test and t-test were used to determine which variables were significantly different between patients with and without hemorrhagic transformation. Odds ratio (OR) and 95% confidence interval (CI) were determined to measure the association between the different variables and hemorrhagic transformation. A total of 500 ischemic stroke patients were included in the study. There were 28 (6%) ischemic stroke patients with Hemorrhagic Transformation. The mean age of these patients is 66.93 ± 12.42 years, 48.8% male, 10.8% had atrial fibrillation, and 2.4% had myocardial infarction. Controlling for the effect of confounders, white blood cell count (OR 1.11; 95% CI 1.03-1.19), myocardial infarction (OR 5.25; 95% CI 1.13-24.34), and presence of brain edema (OR 2.86; 95% CI 1.05-7.80) were significant predictors of hemorrhagic transformation. White blood cell count, presence of brain edema, and myocardial infarction were significantly associated with hemorrhagic transformation among ischemic stroke patients.

Talar Arthroscopic Reduction and Internal Fixation (TARIF): A Novel All-Inside Soft-Tissue-Preserving Technique.

Talar Arthroscopic Reduction and Internal Fixation (TARIF): A Novel All-Inside Soft-Tissue-Preserving Technique.

Application of Deep Learning Models to Improve Ulcerative Colitis Endoscopic Disease Activity Scoring Under Multiple Scoring Systems.

Lack of clinical validation and inter-observer variability are two limitations of endoscopic assessment and scoring of disease severity in patients with ulcerative colitis [UC]. We developed a deep learning [DL] model to improve, accelerate and automate UC detection, and predict the Mayo Endoscopic Subscore [MES] and the Ulcerative Colitis Endoscopic Index of Severity [UCEIS]. A total of 134 prospective videos [1550 030 frames] were collected and those with poor quality were excluded. The frames were labelled by experts based on MES and UCEIS scores. The scored frames were used to create a preprocessing pipeline and train multiple convolutional neural networks [CNNs] with proprietary algorithms in order to filter, detect and assess all frames. These frames served as the input for the DL model, with the output being continuous scores for MES and UCEIS [and its components]. A graphical user interface was developed to support both labelling video sections and displaying the predicted disease severity assessment by the artificial intelligence from endoscopic recordings. Mean absolute error [MAE] and mean bias were used to evaluate the distance of the continuous model's predictions from ground truth, and its possible tendency to over/under-predict were excellent for MES and UCEIS. The quadratic weighted kappa used to compare the inter-rater agreement between experts' labels and the model's predictions showed strong agreement [0.87, 0.88 at frame-level, 0.88, 0.90 at section-level and 0.90, 0.78 at video-level, for MES and UCEIS, respectively]. We present the first fully automated tool that improves the accuracy of the MES and UCEIS, reduces the time between video collection and review, and improves subsequent quality assurance and scoring.