Scoring System For Prediction Research Articles

Prognostic Implications of Initial Radiological Findings of Pulmonary Fibrosis in Patients with Acute SARS-CoV-2 Infection: A Prospective Multicentric Study

Pulmonary fibrosis detected during the acute phase of SARS-CoV-2 infection may significantly influence patient prognosis. This study aimed to evaluate the prognostic value of initial high-resolution computed tomography (HRCT) findings of pulmonary fibrosis in hospitalized COVID-19 patients and to examine how these findings relate to disease severity and clinical outcomes, with a particular focus on the development and validation of predictive scoring systems. In this multicentric prospective cohort study from January 2023 to January 2024, 120 adult patients with confirmed SARS-CoV-2 infection requiring hospitalization were enrolled from two Romanian university hospitals. Patients were categorized based on the presence (n = 60) or absence (n = 60) of pulmonary fibrosis signs on admission HRCT scans, identified by reticular opacities, traction bronchiectasis, honeycombing, and architectural distortion. Biochemical analyses, severity scores (SOFA, APACHE II, NEWS 2), and novel compound scores combining clinical and radiological data were assessed. Patients with HRCT evidence of pulmonary fibrosis had significantly higher severity scores and worse clinical outcomes. The HRCT score alone was a strong predictor of severe COVID-19 (area under the ROC curve [AUC] = 0.885), with a best cutoff value of 9.72, yielding 85.7% sensitivity and 79.8% specificity. Compound Score 1, integrating SOFA, APACHE II, and HRCT scores, demonstrated excellent predictive performance with an AUC of 0.947, sensitivity of 92.5%, and specificity of 88.9%. Compound Score 2, combining systemic inflammation markers (SIRI, SII) and NEWS 2, also showed a strong predictive capability (AUC = 0.913), with 89.2% sensitivity and 85.7% specificity at the optimal cutoff. Regression analysis revealed that Compound Score 1 had the highest hazard ratio for severe COVID-19 outcomes (HR = 4.89; 95% CI: 3.40–7.05), indicating its superior prognostic value over individual markers and traditional severity scores. Initial HRCT findings of pulmonary fibrosis are significantly associated with increased disease severity in hospitalized COVID-19 patients. The HRCT score is a valuable prognostic tool, and, when combined with clinical severity scores into Compound Score 1, it enhances the prediction of severe COVID-19 outcomes with high sensitivity and specificity. These compound scores facilitate the early identification of high-risk patients, guiding clinical decision-making and optimizing patient management to improve outcomes.

Development and validation of the prediction score for augmented renal clearance in critically Ill Japanese adults.

Augmented renal clearance (ARC) decreases the therapeutic concentration of drugs excreted by the kidneys in critically ill patients. Several ARC prediction models have been developed and validated; however, their usefulness in Japan has not been comprehensively investigated. Thus, we developed a unique ARC prediction model for a Japanese mixed intensive care unit (ICU) population and compared it with existing models. This retrospective study enrolled a mixed ICU population in Japan from January 2019 and June 2022. The primary outcome was the development and validation of a model to predict ARC onset based on baseline information at ICU admission. Patients admitted until May 2021 were included in the training set, and external validation was performed on patients admitted thereafter. A multivariate logistic regression model was used to develop an integer-based predictive scoring system for ARC. The new model (the JPNARC score) was externally validated along with the ARC and Augmented Renal Clearance in Trauma Intensive Care (ARCTIC) scores. A total of 2,592 critically ill patients were enrolled initially, with 651 patients finally included after excluding 1,941 patients. The training and validation datasets comprised 456 and 195 patients, respectively. Multivariate analysis was performed to develop the JPNARC score, which incorporated age, sex, serum creatinine, and diagnosis upon ICU admission (trauma or central nervous system disease). The JPNARC score had a larger area under the receiver operating characteristic curve than the ARC and ARCTIC scores in the validation dataset (0.832, 0.633, and 0.740, respectively). An integer-based scoring system was developed to predict ARC onset in a critically ill Japanese population and showed high predictive performance. New models designed to predict the often-unrecognized ARC phenomenon may aid in the decision-making process for upward drug dosage modifications, especially in resource- and labor-limited settings.

Prediction of CRT response using a novel CRT responder score in an Asian patient population

Abstract Introduction Cardiac Resynchronization Therapy (CRT) guidelines, derived from trials among U.S. and European patients, assign weaker recommendations to those with midrange QRS duration (<150ms). Patient height and body size may modulate CRT efficacy. Moreover, these factors may affect CRT utilization and efficacy in Asia. Aim The purpose of this analysis was to determine the prediction scoring system model for CRT responders in a Japanese patient population. Methods We analyzed the database of the Multicenter Prospective Pilot Study to Test LV Intracardiac Conduction Time as a Predictor of CRT Response (BIO|SELECT) which was a single-arm study conducted at 28 hospitals in Japan. This study enrolled patients eligible for a de-novo CRT-defibrillator (CRT-D) based on current guideline indications, who had no recent or planned cardiac surgery and were planned to receive a Sentus ProMRI OTW quadripolar LV lead and a BIOTRONIK CRT-D with multipole pacing feature. Patients were followed for 7 months after implantation. Four accepted parameters to define CRT response [LVESV (cut-off -15%), LVEF (+5%), BNP (-25%), and NYHA class (one class improvement)] were combined into a composite benefit index (CBI) by forming the normalized sum, with CBI = 4.0 meaning response. The CBI was found to be more robust than the individual 4 parameters due to the reduced influence of noise and measurement errors in single parameters. Several factors were studied to create the scoring tool. The CRT responder score was the sum of these individual scores (range 0-100). To construct a predictive scoring system, logistic regression analysis was performed with a backward selection procedure. In addition, the Akaike information criterion (AIC) was applied to determine the best model among those tested. The score was then assigned employing the β coefficient of each variable divided by the reference value. The model's calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test. Results A total of 196 patients were enrolled in this study (mean age 69 years, mean LVEF 30%, left bundle-branch block [LBBB] 58%). The Ooccurrence of CRT response during the 7-month follow-up was 54%. Future CRT responders were significantly predicted by low age (< 70 years)(18 points), female (19 points), prior heart failure hospitalization (16 points), body mass index (<20) (17 points), QRS/height (<0.858)(30 points). This score predicted CRT response well (area under curve 0.72; 95% CI 0.643-0.798). When the cut-off of 63 points or more was applied the sensitivity was 0.56, the specificity was 0.72, and the negative predictive value was 0.58. Conclusions The CRT responder score is a novel approach for the prediction of CRT response, but should be validated and further improved to increase its predictive value. This approach highlights the role of preventing the development of severe heart failure and could help to identify individuals who might benefit from CRT.

NEWS, SIRS and qSOFA criteria for predicting sepsis and sepsis with high risk of death in emergency room: A comparison study and improved predictive models based on local data from CETAT and MIMIC-IV databases

Early identification of sepsis in emergency room patients is critical for initiating timely interventions, highlighting the need for effective predictive scoring systems. A retrospective observational study was conducted using data from the CETAT database collected between December 2019 and October 2021. The study evaluated how well the SIRS, qSOFA, and NEWS scoring systems, along with logistic regression models, predict sepsis and high-risk sepsis in emergency room patients. The logistic regression models were further optimized by incorporating additional features based on local data.A total of 12,799 patients were analyzed, including 1,360 sepsis cases, of which 373 were classified as high-risk sepsis. The NEWS score demonstrated superior predictive performance compared to qSOFA and SIRS, with an AUC-ROC of 0.737 (95% CI 0.72–0.75) for sepsis and 0.653 (95% CI 0.62–0.69) for high-risk sepsis. After optimization, the NEWS-based model improved to an AUC-ROC of 0.756 (95% CI 0.74–0.77) for sepsis and 0.718 (95% CI 0.69–0.75) for high-risk sepsis. Further enhancement was observed with the inclusion of additional clinical variables, resulting in AUC-ROC values of 0.834 (95% CI 0.82–0.85) for sepsis and 0.756 (95% CI 0.73–0.78) for high-risk sepsis. Data from the MIMIC-IV database, which included sepsis status and relevant variables for SIRS, qSOFA, and NEWS score calculations, confirmed that the optimized NEWS-based model improved the sepsis prediction AUC-ROC from 0.690 (95% CI 0.68–0.70) to 0.708 (95% CI 0.70–0.72), and consistently outperformed qSOFA and SIRS in sepsis prediction.

Development and validation of a predictive scoring system for hypoglycaemic agents for optimal control of blood glucose during glucocorticoid therapy.

Glucocorticoid (GC) treatments are often used. There is limited information on the prediction of hyperglycaemia after GC administration. This study aimed to identify the risk factors for hyperglycaemia after glucocorticoid (GC) administration and the need for hypoglycaemic agents to correct it and to develop and validate a novel scoring system for predicting GC-induced hyperglycaemia. In a development set, 508 adults receiving prednisolone (PSL) for the first time were divided into two groups based on treatment with or without hypoglycaemic agents. Clinical and laboratory parameters were compared, and risk factors were identified using logistic regression analysis after performing univariate analyses between the two groups. A point-addition scoring system with several categories and coefficients for each risk factor was constructed to predict the need for hypoglycaemic agents. The scoring system was then applied and validated on two validation sets: A and B. Older age, higher glycated haemoglobin percentage, body mass index and initial PSL dosage were identified as risk factors. The sensitivity, specificity and accuracy of the scoring system were 70.6%, 81.9% and 77.1% in the development set; 75.8%, 78.4% and 77.4% in validation set A; and 79.4%, 73.9% and 75.3% in validation set B respectively. By fitting the total score in the development set and the probability of hyperglycaemia to a logistic curve, a figure was created to show the probability of GC-induced hyperglycaemia in patients scheduled to receive GC. This scoring system is a novel, valid and reliable tool for predicting GC-induced hyperglycaemia and the need for hypoglycaemic agents to correct it.

Development of an intraductal papillary mucinous neoplasm malignancy prediction scoring system.

Despite the presence of various guidelines, diagnosing malignant intraductal papillary mucinous neoplasm (IPMN) continues to pose challenges. Furthermore, although endoscopic ultrasonography (EUS) offers high-resolution images, it has not yet recognized as the primary tool for malignancy diagnosis. The study objective was to develop a simplified and user-friendly scoring system to improve the diagnostic accuracy of malignant IPMNs. Additionally, the utility of EUS and its effect on diagnostic accuracy were assessed. We retrospectively collected the clinical data on 160 cases of resected IPMN at Tokyo Medical and Dental University Hospital from January 2008 to December 2022. We examined clinical features, computed tomography (CT) and magnetic resonance imaging (MRI) findings, and EUS results if available. We then calculated the odds ratio of malignancy for these factors and developed an IPMN malignancy prediction (IMAP) scoring system. There were 89 (55.6%) cases of benign IPMNs and 71 (44.4%) of malignant IPMNs. Eight clinical and imaging findings, including age, diabetes mellitus status, jaundice, CA19-9 level, enhancing mural nodules ≥5mm, thickened wall, and main duct dilatation, were significantly associated with malignancy. The IMAP score was calculated by assigning 0 to 2 points to these factors based on the odds ratio. The area under the receiver operating characteristic curve for the IMAP score was 0.78 [95% confidence interval (CI): 0.71-0.85] based on CT/MRI alone and improved to 0.81 (95% CI: 0.74-0.87) when EUS was added. When the total exceeds 5 points, the positive predictive value becomes 100% (95% CI: 95.9-100). In conclusion, the IMAP scoring system has demonstrated promise as a clinically useful tool, offering both simplicity and sufficient accuracy. It holds potential as an important decision criterion for determining the treatment approach for IPMN. Additionally, EUS contributes to enhancing the diagnostic accuracy of the IMAP scoring system, thereby enabling more precise decision-making.

CD36 cell surface expression as a surrogate marker to identify ABL/JAK-class kinase fusions in pediatric BCP-ALL.

Genetic alterations are the cornerstone of risk stratification in B-cell precursor acute lymphoblastic leukemia (BCP-ALL), and their accurate identification is critical for optimal treatment. Most cases with ABL-class fusion are classified as high-risk yet display good responses to tyrosine kinase inhibitors (TKIs). Current clinical protocols recommend adding a TKI to chemotherapy as soon as possible, making it mandatory to rapidly identify these alterations. We investigated here whether the identification of immunophenotypic features associated with these molecular alterations could be a valuable screening tool. CD36 expression was shown to be a characteristic feature of ABL- or JAK-class kinase fusions. The main genetic subgroups clustering in the subset with Philadelphia (Ph)-like features were also found to display specific immunophenotypic characteristics. A predictive multiparameter scoring system was generated, segregating genetic subtypes with aberrant kinase activation (PAX5/CRLF2alt, BCR::ABL1, ABL/JAK-class). The most robust markers identified were the TSLPR with CD19/22/9/38/81/304 and CD49f. As TKI adjunction is currently limited to the ABL-class kinase fusions, immunophenotypes distinguishing ABL from JAK-class were also investigated. The flow cytometry method reported here, accessible to most hematology departments, is thus a new useful tool to quickly screen for Ph-like kinase fusion with a good sensitivity (95%) and specificity (96%).

Predictive factors and risk scoring system for acute kidney injury (aki) in sick neonates-a prospective cohort study.

Nearly half of sick neonates admitted to NICU have AKI, which is maximum in extremely preterm infants. Sepsis, invasive ventilation, acidosis, and perinatal asphyxia have good diagnostic accuracy in identifying neonates likely to develop AKI. • Asphyxia, prematurity, sepsis, shock, hypotension, drugs, congenital heart diseases contribute to neonatal AKI. • Our simple risk prediction model can be used in sick neonates to identify infants who are at risk for developing AKI.

Predictive value of clinico-radiological variables in the management of suspected foreign body aspiration in children: A ten-year retrospective cohort study

ABSTRACT Background: Definite history is not always present in children with foreign body aspiration (FBA), hence necessitating a high index of suspicion. Objective: To assess the predictive value of clinico-radiological variables among children presenting with features of suspected FBA and to document their course in a tertiary care teaching hospital. Materials and Methods: In this retrospective observational study, we included children aged below 15 years presenting with clinical features of suspected FBA. Data was obtained from case records. Multivariable binary logistic regression analysis (MVA) was performed to determine statistically significant predictors of FBA, and Weighted Risk Scores (WRS) were calculated to determine the significance of the model. Results: Of the 296 children included in the study and having undergone bronchoscopy, 84.5% were toddlers; 269 (90.87%) had a foreign body (FB) removed. Organic material was commonly found with 64.3% being peanut and right main bronchus, the commonest lodging site (50.6%). Of the 54 (18%) children with symptomatic but unwitnessed FBA, 45 (83.3%) had a FB retrieved. Choking with sudden onset cough, stridor, unilateral decreased breath sounds, abnormal chest radiograph, unilateral hyperinflation and mediastinal shift correlated with FBA (P < 0.05). MVA confirmed statistical significance with choking with sudden onset cough to predict FBA (P = 0.024) with overall sensitivity and specificity of 60.9% and 77.8%, respectively. Total WRS with cut-off >2 showed good power of discrimination with sensitivity, specificity and AUC of 60.2%, 77.8% and 0.704%, respectively. Conclusions: The proposed predictive value-based scoring system enhances accuracy in decision-making regarding bronchoscopy in children with suspected FBA.

Predicting the risk of colorectal cancer among diabetes patients using a random survival forest-guided approach.

Colorectal cancer (CRC) is the third most frequently diagnosed cancer worldwide. Diabetes and CRC share many overlapping lifestyle risk factors such as obesity, heavy alcohol use, and diet. This study aims to develop a risk scoring system for CRC prediction among diabetes patients using routine medical records. A retrospective cohort study was conducted using electronic health records of Hong Kong. Patients who received diabetes care in public general outpatient clinics between 2010 and 2019 and had no cancer history were identified, and followed up until December 2019. The outcome was diagnosis of CRC during follow-up. For model building, predictors were first selected using random survival forest, and weights were subsequently assigned to selected predictors using Cox regression. Of the 386,325 patients identified, 4,199 patients developed CRC during a median follow-up of 6.2 years. The overall incidence rate of CRC was 1.93 per 1000 person-years. In the final scoring system, age, waist-to-hip ratio, and serum creatinine were included as predictors. The C-index on test set was 0.651 (95%CI: 0.631-0.669). Elevated serum creatinine (≥127 µmol/L) could be a potential important predictor of increased CRC risk. While obesity is a well-known risk factor for CRC, renal dysfunction could be potentially linked to an elevated risk of CRC among diabetes patients. Further studies are warranted to explore whether renal function could be a potential parameter to guide screening recommendation for diabetes patients.

Serum Inflammatory Dynamics as Novel Biomarkers for Immune Checkpoint Inhibitors in Non-small-cell Lung Cancer With Bone Metastases.

The aim of the study was to develop a novel predictive scoring system based on the dynamics of serum inflammatory indicators in immune checkpoint inhibitor (ICI) treatment on non-small-cell lung cancer (NSCLC) with bone metastases. Sixty patients with NSCLC and bone metastases treated with ICIs between January 2016 and March 2021 were included in the development cohort. Serum neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) levels were assessed before (pre-value) and 6 weeks after (post-value) ICI treatment, and a novel predictive score was developed: pre-value ≥ post-value, 0 points; pre-value < post-value, 1 point; total score: 0-2 points. The associations of these dynamics and the score with clinical outcomes, including overall survival (OS), progression-free survival (PFS), response rate (RR) of bone metastases, and disease control rate (DCR), were evaluated. Furthermore, cross-validation was performed with 23 patients after April 2021 using the same inclusion criteria. The patients with decreased serum inflammation levels had significantly better OS, PFS, and RR than those with increased levels. Applying the developed score to the development cohort, the patients with 0 points had significantly better OS, PFS, and RR than others. In multivariable analysis, the score independently predicted treatment response to ICI for bone metastasis and prognosis. Cross-validation showed that OS, PFS, and RR were significantly better in the patients in the 0-point group. The early NLR and CRP dynamics were associated with therapeutic responses to ICIs in NSCLC with bone metastases. Our novel scoring system based on these dynamics is simple and has a high predictive accuracy.

Development of a predictive scoring system for vitamin D deficiency 'Vitamin D Deficiency Predicting Scoring (ViDDPreS)' based on the vitamin D status in young Japanese women: a nationwide cross-sectional study.

Vitamin D deficiency (VDD) is common among young women and causes various health problems, including those that occur during pregnancy and childbirth. Thus, we investigated the risk factors for VDD in young Japanese women and developed a simple risk scoring system called Vitamin D Deficiency Predicting Scoring (ViDDPreS). A cross-sectional study, using the following factors for multivariate logistic regression analysis to create the ViDDPreS score: residential area, season, cumulative ambient ultraviolet-B irradiation, BMI, vitamin D supplement use, sun exposure habits, frequency of habitual food intake and eating habits. The subjects were randomly divided into development and test sets for analysis. Serum 25-hydroxivitamin D concentration of less than 20 ng/ml was defined as VDD. Four regions (Hokkaido/Tohoku, Kanto, Chubu/Kinki/Shikoku and Kyushu/Okinawa) in Japan. Five hundred and eighty-three healthy women aged 18-40 years. In the development set, the VDD group (68·4 %) had higher proportions of the following variables than the non-VDD group: residential area outside the Kanto region; blood samples obtained in winter; low BMI (<18·5 kg/m2); vitamin D supplement non-users; short time regularly spent outside on weekdays; intake of fish, vitamin D-abundant fish, dried fish and redfish less than once a week. VDD risk was classified as low, medium or high according to the ViDDPreS scores including these contributing factors, with a test set C-index of 0·671. We identified the risk factors for VDD in young Japanese women and developed a simple risk scoring system that enables us to assess VDD risk and aid in the development of appropriate prevention and treatment strategies for this population.

Development of a Scoring System for Predicting the Difficulty of Bile Duct Cannulation and Selecting the Appropriate Cannulation Method.

Selective biliary cannulation in endoscopic retrograde cholangiopancreatography can be challenging due to factors like papillary morphology. Various patterns indicate cannulation difficulty, but the combinations causing difficulty and the optimal cannulation method for each scenario are unclear. This study aimed to identify cannulation difficulty patterns and develop a predictive scoring system for selecting the appropriate cannulation method. We retrospectively compared 776 patients with naïve papilla, dividing them into conventional contrast cannulation (N = 510) and salvage technique (N = 266) groups. The salvage group included patients using pancreatic duct guidewire placement and/or wire-guided cannulation due to difficulties with the contrast method. Papillary morphology (Haraldsson's classification), periampullary diverticulum (PAD), and scope operability were analyzed using multiple regression to identify risk factors for cannulation difficulties. Factors were scored based on hazard ratios to access combinations causing difficulties. The salvage group had more older patients and higher frequencies of type 2 (small), type 3 (protruding or pendulous), type 4 (creased or ridged) papillae, PAD, and poor scope operability. Significant risk factors in the multivariate analysis included type 2 [odds ratio (OR) 6.88], type 3 (OR 7.74), type 4 (OR 4.06) papillae, PAD (OR 2.26), and poor scope operability (OR 4.03). Pattern recognition scores were significantly higher in the salvage group (1.31 vs. 3.43, P < 0.0001). Type 2-4 papillae, PAD, and poor scope operability are significant risk factors for cannulation difficulty. Pattern recognition scores based on these factors can predict cannulation difficulty and aid in selecting between conventional and salvage methods.

Establishment and validation of a predictive model for spontaneous preterm birth in singleton pregnant women

IntroductionIn the current study, we screened for highly sensitive and specific predictors of premature birth, with the aim to establish an sPTB prediction model that is suitable for women in China and easy to operate and popularize, as well as to establish a sPTB prediction scoring system for early, intuitive, and effective assessment of premature birth risk.MethodsA total of 685 pregnant women with a single pregnancy during the second trimester (16–26 weeks) were divided into premature and non-premature delivery groups based on their delivery outcomes. Clinical and ultrasound information were collected for both groups, and risk factors that could lead to sPTB in pregnant women were screened and analyzed using a cut-off value. A nomogram was developed to establish a prediction model and scoring system for sPTB. In addition, 119 pregnant women who met the inclusion criteria for the modeling cohort were included in the external validation of the model. The accuracy and consistency of the model were evaluated using the area under the receiver operating characteristic (ROC) and C-calibration curves.ResultsMultivariate logistic regression analysis showed a significant correlation (P < 0.05) between the number of miscarriages in pregnant women, history of miscarriages in the first week of pregnancy, history of preterm birth, CL of pregnant women, open and continuous cervical opening, and the occurrence of sPTB in pregnant women. We drew a nomogram column chart based on the six risk factors mentioned above, obtained a predictive model for sPTB, and established a scoring system to divide premature birth into three risk groups: low, medium, and high. After validating the model, the Hosmer Lemeshow test indicated a good fit (p = 0.997). The modeling queue C calibration curve was close to diagonal (C index = 0.856), confirming that the queue C calibration curve was also close to diagonal (C index = 0.854). The AUCs of the modeling and validation queues were 0.850 and 0.881, respectively.ConclusionOur predictive model is consistent with China’s national conditions, as well as being intuitive and easy to operate, with wide applicability, thus representing a helpful tool to assist with early detection of sPTB in clinical practice, as well as for clinical management in assessing low, medium, and high risks of sPTB.

A new scoring system to predict survival in elderly advanced stage Hodgkin lymphoma patients

Predictive prognostic scoring (PS) systems are not primarily applicable to elderly patients with classical Hodgkin lymphoma (cHL). The objective of this study was to develop a PS system for these patients. The derivation cohort (DC) was utilized for model development, consisting of 97 variables. The resulting algorithm was named as Hodgkin’s Lymphoma Early Death in the Elderly within 12 months (HEDEL12). Internal and external validation cohorts (IVC and EVC) were employed for validation. A total of 286 patients were evaluated retrospectively. In DC 38 of 178 patients died within the first 12 months and overall survival (OS) at 12-month was 78.6%. Independent predictors of HEDEL12 were female sex, low albumin levels (<3.5 g/dL), and ECOG scores 2-4. According to HEDEL12 scores 0–1, OS at 12- months were 89.8% and 91.0% for IVC and EVC, respectively. The HEDEL12 scoring is useful in predicting the survival of advanced-stage cHL patients.

Evaluation of peripheral blood inflammation indexes as prognostic markers for colorectal cancer metastasis

The aim of this study was to evaluate the prognostic value of peripheral blood inflammation indexes in patients with metastatic Colorectal Cancer (CRC) and to establish a predictive scoring system. A total of 324 CRC patients diagnosed through pathological examination from January 2017 to July 2022 at the Third Affiliated Hospital of Kunming Medical University were included. The prognosis of patients with metastatic CRC was examined, and the correlation between IL-10 expression in pathological tissues and IL-10 expression in serum was analyzed. The results showed that the prognosis of CRC was poorer when metastasis occurred (P < 0.001). Additionally, IL-10 was highly expressed in the metastatic CRC group (P = 0.018), and the expression of IL-10 in pathological tissues of patients with metastatic CRC was positively correlated with the expression of IL-10 in serum (P = 0.037). The neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-white blood cell ratio (LWR), aggregate index of systemic inflammation (AISI), monocyte-to-lymphocyte ratio (MLR), systemic inflammatory response index (SIRI), prognostic nutritional index (PNI), advanced lung cancer inflammation index (ALI), and interleukin-10 (IL-10) were calculated and determined by ROC curve. The critical values were 2.135, 3.735, 353.745, 0.265, 1.025, 52.975, 353.635, and 11.25, respectively. Inflammatory indexes with an AUC of more than 0.6 were selected, and each colorectal cancer patient with any of these risk factors was assigned a score of one. The 324 patients were then divided into two groups: 0–4 for the low-risk group and 4–8 for the high-risk group. The occurrence of distant metastases in the two groups was statistically analyzed. The results showed that the OS and PFS of the low-risk group were significantly superior to those of the high-risk group (P < 0.05). These findings indicate that NLR, LWR, AISI, MLR, SIRI, PNI, ALI, and IL-10 are risk factors for distant metastasis in CRC patients. Therefore, the prediction scores of these indexes can be used to effectively evaluate the prognosis of patients with metastatic CRC.

A knowledge-transfer-based approach for combining ordinal regression and medical scoring system in the early prediction of sepsis with electronic health records

Objective:The prediction of sepsis, especially early diagnosis, has received a significant attention in biomedical research. In order to improve current medical scoring system and overcome the limitations of class imbalance and sample size of local EHR (electronic health records), we propose a novel knowledge-transfer-based approach, which combines a medical scoring system and an ordinal logistic regression model. Materials and Methods:Medical scoring systems (i.e. NEWS, SIRS and QSOFA) are generally robust and useful for sepsis diagnosis. With local EHR, machine-learning-based methods have been widely used for building prediction models/methods, but they are often impacted by class imbalance and sample size. Knowledge distillation and knowledge transfer have recently been proposed as a combination approach for improving the prediction performance and model generalization. In this study, we developed a novel knowledge-transfer-based method for combining a medical scoring system (after a proposed score transformation) and an ordinal logistic regression model. We mathematically confirmed that it was equivalent to a specific form of the weighted regression. Furthermore, we theoretically explored its effectiveness in the scenario of class imbalance. Results:For the local dataset and the MIMIC-IV dataset, the VUS (the volume under the multi-dimensional ROC surface, a generalization measure of AUC-ROC for ordinal categories) of the knowledge-transfer-based model (ORNEWS) based on the NEWS scoring system were 0.384 and 0.339, respectively, while the VUS of the traditional ordinal regression model (OR) were 0.352 and 0.322, respectively. Consistent analysis results were also observed for the knowledge-transfer-based models based on the SIRS/QSOFA scoring systems in the ordinal scenarios. Additionally, the predicted probabilities and the binary classification ROC curves of the knowledge-transfer-based models indicated that this approach enhanced the predicted probabilities for the minority classes while reducing the predicted probabilities for the majority classes, which improved AUCs/VUSs on imbalanced data. Discussion:Knowledge transfer, which combines a medical scoring system and a machine-learning-based model, improves the prediction performance for early diagnosis of sepsis, especially in the scenarios of class imbalance and limited sample size.

Predictive Factors and Scoring System for Delayed Symptomatic Hyponatremia Following Endoscopic Endonasal Surgery: A Single-Center Retrospective Study

BackgroundsDelayed symptomatic hyponatremia (DSH) is one of the common complications following endoscopic endonasal surgery (EES). Currently, published studies have predominantly focused on delayed postoperative hyponatremia, while there is relatively limited research on DSH. MethodsWe analyzed 175 consecutive cases from a single center between 2019 and 2023, involving patients who underwent endoscopic endonasal surgery (EES) for pituitary adenoma or Rathke's cleft cyst (RCC), all histopathologically confirmed. We collected preoperative, intraoperative, and postoperative data, and performed statistical analysis to determine the incidence of postoperative diabetes insipidus (DI) and identify significant predictive factors. Based on these factors, we developed a simplified scoring system. ResultsThere were 29 cases (16.6%) of DSH occurrence. In the binary logistic regression analysis, Knosp grade ≥3 (OR, 4.19; 95% CI, 1.26-13.92; P=0.019), intraoperative cerebrospinal fluid leaks (OR, 3.93; 95% CI, 1.49-10.34; P=0.006), serum sodium on the second day after surgery (OR, 0.88; 95% CI, 0.78-1.00; P=0.049), and postoperative diabetes insipidus (OR, 2.88; 95% CI, 1.10-7.53; P=0.031) were factors with independent predictive value for DSH. The scoring system achieved a maximum area under the ROC curve (AUC) of 0.789 (95% CI, 0.697-0.881), with a cutoff value of 1, sensitivity of 86.2%, and specificity of 59.6%. ConclusionThe incidence rate of DSH after EES in patients was 16.8%. Knosp grade ≥3, intraoperative cerebrospinal fluid leaks, serum sodium concentration on the second day after surgery, and postoperative diabetes insipidus were associated with the occurrence of DSH.

Evaluation of different scoring systems for repeating Transarterial Chemoembolization in Egyptian patients with Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) patients undergoing transarterial chemoembolization (TACE) have a diverse range of outcomes due to their high degree of heterogeneity. Therefore, different predictive scoring systems have been created to assist in decision-making regarding retreatment with TACE. We compared the predictive capabilities of different scoring systems, such as ART, ABCR, and SNACOR, for prediction of the outcome of subsequent TACE in HCC patients. In this retrospective study, the three scoring systems were compared for their capability of predicting the outcome of repeating TACE in 149 HCC patients treated at the National Liver Institute, Egypt, between January 2017 and December 2019. We used the likelihood ratio to select the model with the highest predictive capability for overall survival (OS). According to our data, the amount of tumor, the change in Barcelona Clinic Liver Cancer (BCLC) stage following TACE, and the SNACOR score (with a 95% confidence range for HR 1.0305-1.256 and p-value = 0.0106) were the most predictive variables. It was also shown that the ABCR score was a good predictor of survival (90 patients had an ABCR score ≤ 0 with a P- value <0.0001, 56 patients had 0 < ABCR < 4 with a P-value <0.0001, and the ART score was not useful in predicting OS (P-value = 0.18). The SNACOR score is the most predictive score for OS and would be the most helpful scoring system in decision-making regarding retreatment with TACE.

Acute phase optimization in burn care: Online tools and comprehensive predictive models for adult and pediatric patients

BackgroundSevere burn injuries significantly challenge acute medical care, particularly in resource-limited environments. Current predictive scoring systems, often impractical and adult-focused, neglect crucial aspects like mechanical ventilation and length of hospital stay (LOS). MethodsThis study analyzed 2,618 severe burn patients, developing new predictive models for survival, mechanical ventilation, and LOS, based on promptly accessible factors applicable in any setting. ResultsWe observed significant seasonality and clear age- and gender-specific patterns, highlighting the necessity for targeted interventions. We developed and publicly released new predictive models for mortality, mechanical ventilation, and LOS for both adult and pediatric populations. DiscussionTargeting deficiencies in existing scoring systems, this study potentially advances acute burn management, with a particular focus on resource-limited settings. It provides crucial insights into the epidemiology, etiology, and prognostic factors of severe burn injuries, encapsulated in 10 actionable points. We also present an innovative freely accessible online assessment tool: https://burn-scores.com. ConclusionBy bridging gaps in current scoring methodologies and improving acute phase management, our research offers insights to improve clinical outcomes for severe burn patients globally. The integration of tailored predictive models and technology-driven solutions, especially relevant in resource-constrained settings, represents a major stride in enhancing the quality of burn care.