Evidence-based Score Research Articles

The association between Lifelines Diet Score (LLDS) and Polycystic Ovary Syndrome (PCOS) in Iranian women: a case-control study

BackgroundAlthough adherence to a healthy dietary pattern is one of the primary recommendations for the prevention of polycystic ovary syndrome (PCOS), there is still no conclusive evidence of which specific dietary pattern is best. The Lifelines diet score (LLDS) is a new, evidence-based scoring system to determine diet quality, and its association with PCOS has not been investigated. The present study aimed to assess the association between LLDS and PCOS in Iranian women.Materials and methodsThis frequency-matched case-control study was carried out on 108 women with PCOS and 108 women without PCOS as a control group in Yazd, Iran. Healthy controls were matched to PCOS women based on age and BMI. The validated 178-item food frequency questionnaire was used to assess the usual dietary intake. Logistic regression was used to estimate the association between LLDS and PCOS.ResultsThe findings of the present study showed women in the highest tertile of LLDS compared with the participants in the lowest tertile had 90% lower odds of PCOS (Odds Ratio (OR): 0.10; 95% Confidence Interval (CI): 0.04 to 0.21, p for trend: <0.001). This association remained significant after adjustment for energy intake, marital status, pregnancy history, WC, chronic disease history, physical activity, and BMI (Odds Ratio (OR): 0.11; 95% (CI):0.05 to 0.27, p for trend: <0.001).ConclusionAlthough the present study found a significant protective association between adherence to LLDS and PCOS, more mechanism-based studies are needed to confirm these findings in the future.

Systematic Review of Platelet-Rich Plasma in Medical and Surgical Specialties: Quality, Evaluation, Evidence, and Enforcement.

Background: Platelet-rich plasma (PRP) is widely used in various medical and surgical specialties for its regenerative properties, including aesthetics (facial rejuvenation, hair restoration, and skin tightening) and orthopedics (treatment of tendinitis and osteoarthritis). However, the inconsistent literature on PRP's efficacy and safety leads to critical knowledge gaps. This systematic review evaluates quality control measures in PRP preparation and application and explores the regulatory environment governing its clinical use. Methods: Following PRISMA guidelines, a comprehensive search was conducted across multiple databases, including PubMed, EMBASE, and Web of Science, for studies published from January 2020 to April 2024. The review included randomized controlled trials (RCTs) involving human participants undergoing PRP treatment for aesthetic or regenerative purposes. Key parameters such as the PRP preparation methods, platelet concentration, and quality control measures were analyzed. The study protocol was registered with PROSPERO (ID: CRD42024557669). Results: Out of 75 RCTs involving 5726 patients, the review identified significant variability in PRP preparation methods and application techniques, including differences in centrifugation protocols and platelet concentration levels. A new evidence-based scoring system, the William-Eqram Scoring System for PRP Quality Reporting (WESS-PQR), was proposed to address these inconsistencies. Correlation analysis revealed a strong positive correlation (r = 0.79) between proper temperature control during preparation and PRP efficacy. Initial platelet count assessment showed a moderate positive correlation (r = 0.57) with efficacy. Conclusions: Standardized PRP preparation protocols and robust regulatory frameworks are urgently needed to ensure the safety and efficacy of PRP treatments. The proposed WESS-PQR scoring system can serve as a valuable tool for clinicians and researchers, promoting consistency and reliability in PRP applications.

Assessing the implementation of evidence-based alcohol policies on Atlantic Canadian post-secondary campuses: A comparative analysis.

This study assessed the quality of campus alcohol policies against best practice to assist campus decision-makers in strengthening their campus alcohol policies and reducing student alcohol use and harm. Drawing on empirical literature and expert opinion, we developed an evidence-based scoring rubric to assess the quality of campus alcohol policies across 10 alcohol policy domains. Campus alcohol policy data were collected from 12 Atlantic Canadian universities. All extracted data were verified by the institutions and then scored. On average, post-secondary institutions are implementing only a third of the evidence-based alcohol policies captured by the 10 domains assessed. The average campus policy score was 33% (range 15‒49%). Of the 10 domains examined, only enforcement achieved an average score above 50%, followed closely by leadership and surveillance at 48%. The two heaviest-weighted domains-availability and access, and advertising and sponsorship-had average scores of 27% and 24%, respectively. However, if post-secondary campuses adopted the highest scoring policies from across all 12 campuses, they could achieve a score of 74%, indicating improvement is possible. Atlantic Canadian universities are collectively achieving less than half their potential to reduce student alcohol-related harm. However, this study identifies opportunities where policies can be enhanced or modified. The fact that most policies are present at one or more campuses highlights that policy recommendations are an achievable goal for campuses. Campuses are encouraged to look to each other as models for improving their own policies.

A retrospective validation of the effective and safe treatment of patients on general care wards with high velocity nasal insufflation therapy utilizing prognostic risk scores during COVID-19

Background Non-invasive positive pressure ventilation (NIPPV) has been a traditional therapy for acute respiratory failure (ARF). However, the use of NIPPV during the COVID-19 pandemic was challenging, while the use of invasive mechanical ventilation produced poor outcomes. An alternative to NIPPV, high velocity nasal insufflation (HVNI) has shown promise in treating ARF effectively. Objective This study evaluated whether HVNI can be used to treat ARF safely on the general care ward (GCW) during COVID-19 pandemic surges. Methods After introducing HVNI therapy to the facility, an evidence-based scoring system, Modified Early Warning Score (MEWS), was used to risk stratify patients and assist in assigning care level. Initial settings, demographic data, patient outcomes, and health care worker (HCW) virus conversion were measured throughout the study. Treatment failure was defined as the need for invasive mechanical ventilation (IMV) or NIPPV after HVNI therapy. MEWS and ROX index were compared retrospectively using the Pearson product-moment correlation coefficient to identify trends. The Welch two sample t-test (desired power of 90% with alpha=0.05) was used for demographic and outcome analysis. Results Two hundred thirty-four patients were treated with HVNI. The GCW failure rate of 18.56% (n=31/167) was lower than the ICU failure rate of 37.31% (n=25/67) but not statistically significant (P 0.175). No elevated risk to patients or HCW was observed. Respiratory rate (GCW 24.85 vs. ICU 30.14; P &lt;0.001), MEWS (GCW 2.34 vs. ICU 3.09; p=0.002), and ROX index (GCW 5.49 vs. ICU 4.68; P 0.002) assessments appear to be adequate predictors of HVNI failure. The Pearson product-moment coefficient comparing MEWS and ROX index identified a moderate negative correlation (-0.434; P &lt;0.001). Discussion HVNI therapy is an effective alternative to NIPPV for treating patients with COVID-19 associated ARF. Using measures such as MEWS and/or ROX, strict patient monitoring, and HCW surveillance, HVNI can be safely utilized on the GCW. This has a direct impact when dealing with patient surges where ICU beds and resources are limited. Additional studies are needed to further delineate these concepts. Keywords: COVID-19, Non-invasive Positive Pressure Ventilation, Acute Respiratory Failure, High Flow Nasal Oxygen, High Velocity Nasal Insufflation, ICU Admission, General Care Ward, MEWS, ROX

Initial development of an 'Orthodontic Care Index' involving treatment need,-complexity and-priority.

The aim of this study was to develop an evidence-based scoring system for prioritizing limited orthodontic resources based on orthodontic treatment need (OTN), orthodontic treatment complexity (OTC), and orthodontic treatment priority (OTP), which is not merely a scoring system for malocclusion but also a comprehensive classification of orthodontic issues incorporating patient- and treatment-related factors, called Orthodontic Care Index (OCI). The development of the OCI involved eight phases, starting with a systematic literature review to identify all possible parameters involved in determining OTN, OTC, and OTP. An eight-member orthodontic specialist panel then evaluated and scored the significance of each parameter, resulting in a parameter-score list. Subsequently, a retrospective convenience sample of 61 patients was scored with the parameter-score list, and using the same convenience sample a gold standard was established through the expert opinion of a third orthodontic panel. Linear regression analysis was used to estimate weights of importance and construct a formula to calculate index scores. Lastly, the expert opinion was compared to the index scores, to determine the index performance. The preliminary index separately calculates OTN, OTC, and OTP for a patient as the weighted sum of his/her domain scores. The sensitivity of the index for predicting OTN, OTC, and OTP was high (98.1%, 82.9%, and 92.7% respectively), while the variability of each was relatively low (52.1%, 31.2%, and 52.6% respectively). The OCI shows promise as a guideline for prioritizing orthodontic care. It will be further refined and validated to enhance its performance and usefulness.

Literature-based predictions of Mendelian disease therapies

In the effort to treat Mendelian disorders, correcting the underlying molecular imbalance may be more effective than symptomatic treatment. Identifying treatments that might accomplish this goal requires extensive and up-to-date knowledge of molecular pathways-including drug-gene and gene-gene relationships. To address this challenge, we present "parsing modifiers via article annotations" (PARMESAN), a computational tool that searches PubMed and PubMed Central for information to assemble these relationships into a central knowledge base. PARMESAN then predicts putatively novel drug-gene relationships, assigning an evidence-based score to each prediction. We compare PARMESAN's drug-gene predictions to all of the drug-gene relationships displayed by the Drug-Gene Interaction Database (DGIdb) and show that higher-scoring relationship predictions are more likely to match the directionality (up- versus down-regulation) indicated by this database. PARMESAN had more than 200,000 drug predictions scoring above 8 (as one example cutoff), for more than 3,700 genes. Among these predicted relationships, 210 were registered in DGIdb and 201 (96%) had matching directionality. This publicly available tool provides an automated way to prioritize drug screens to target the most-promising drugs to test, thereby saving time and resources in the development of therapeutics for genetic disorders.

Are chronic condition management visits translatable to telehealth? Analysis of in-person consultations in primary care

BackgroundTelehealth was rapidly adopted in primary care during COVID-19. However, there is a lack of research assessing how translatable in-person consultations are to telehealth. ObjectiveTo examine insights from in-person GP-Patient consultations for patients with chronic conditions, including 1/frequency, duration, conditions of physical examinations, and when they occur during consultations, 2/types of physical artefacts used, 3/clinical tasks performed, and 4/translatability of clinical tasks to telehealth. MethodsEligible consultations were extracted from a dataset archive named HaRI, which contains 281 in-person GP consultations in de-identified transcript and video format. 38 consultations were included for analysis meeting eligibility criteria in this study. A multi-method approach (using content analysis, visualisation, video and time analysis) was applied to eligible consultations, extracting clinical tasks that involve physical interactions. Finally, an evidence-based scoring system was used on each clinical task, determining the likelihood of whether each task could be translated into telehealth. ResultsNine chronic conditions were observed across 38 GP-Patient consultations, predominately diabetes (39 %, 15/38). Out of these 38 consultations, 76 % (29/38) featured physical examinations, where 68 % (26/38) were initiated by GPs (e.g., auscultation), and 26 % (10/38) were initiated by patients (e.g., self-palpation). The average percentage of time spent on physical examination(s) during consultations is low (13.6 %, SD = 9.4 %). A total of 24 clinical tasks were observed across these 38 consultations. Out of these 24 tasks, 92 % (22/24) were supported by physical artefacts. The average score of a task being translatable to Telehealth is 7/10 (where Score 1 = Not amenable to being replicated over telehealth at this stage, scoring 10 = Easily translatable over telehealth with almost no additional equipment being required). ConclusionAll tasks observed across chronic condition management visits were deemed translatable/potentially translatable to telehealth. However, physical interactions between GPs and patients are still essential. Future research in telehealth should focus on examining ways to support physical examination, reduce uncertainty, promote safety netting, and facilitate patients’ safety at home with effective technology and support.

Systematic Assessment of the Quality and Comprehensibility of YouTube Content on Ulnar Collateral Ligament Injury and Management.

Ulnar collateral ligament (UCL) reconstruction has received a unique level of attention in the press and social media. There has also been an increasing use of the internet by patients to seek medical information. Concern exists regarding the quality and comprehensibility of online information when used for patient education. To evaluate the quality and comprehensibility of the most-viewed YouTube videos related to the diagnosis and management of UCL injuries. Based on our new evidence-based scoring rubrics, we hypothesized that the quality and comprehensibility of these videos would be poor. Cross-sectional study. The YouTube platform was searched on September 7, 2021, with the terms "UCL injury," "ulnar collateral ligament injury," "UCL surgery," "ulnar collateral ligament surgery," and "Tommy John surgery," and the 50 most-viewed videos from each search were compiled, yielding 250 videos. After removal of duplicates and application of exclusion criteria, the 100 most-viewed videos remained. Basic attributes, including duration of video and number of views, were recorded. Each video was then analyzed by 2 independent reviewers and evaluated for 4 key parameters (quality of diagnostic content [QAR-D], quality of treatment content [QAR-T], presence of inaccurate information, and comprehensibility) and graded on a novel scale from 1 to 4 (4 being the most appropriate for patient education). The mean QAR-D was 4.83 ± 3.41 (fair quality), and the mean QAR-T was 2.76 ± 3.26 (poor quality). Physician-led educational videos had both the highest mean QAR-D (6.37) and the highest mean QAR-T (4.34). No correlation was observed between video quality and views/likes. A total of 12 videos included ≥1 inaccuracy. The mean comprehensibility score was 2.66 ± 1.12, with 39 videos falling below the acceptable comprehensibility threshold (score <3). The overall quality of UCL injury-related YouTube content was low. In addition, the absence of correlation between video quality and views/likes suggests that patients are not preferentially utilizing the limited high-quality content that does exist on the YouTube platform. In addition, inaccurate videos were prevalent (12%), and almost half of all videos were deemed inappropriate for patient education in terms of comprehensibility, as defined by our comprehensibility parameter.

Standards for the interpretation of constitutional copy number gain: Recommendation from the American College of Medical Genetics and Genomics (ACMG) and Clinical Genome Resource (ClinGen)

Copy number variants (CNVs) are common causes of human genetic diseases. CNVs detection has become a routine component of genetic testing, especially for pediatric neurodevelopmental disorders, multiple congenital abnormalities, prenatal evaluation of fetuses with structural anomalies detected by ultrasound. Although the technologies for CNVs detection are continuously improving, the interpretation is still challenging, with significant discordance across different laboratories. In 2020, the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen) developed a guideline for the interpreting and reporting of constitutional copy number variants, which introduced a quantitative, evidence-based scoring framework. Here, we detailed the key points of interpreting the copy number gain based on the guideline, used six examples of different categories to illuminate the scoring process and principles. We encourage a professional understanding and application of this guideline for the detected copy number gains in China in order to further improve the clinical evaluation accuracy and consistency across different laboratories.

Measuring and Improving Evidence-Based Patient Care Using a Web-Based Gamified Approach in Primary Care (QualityIQ): Randomized Controlled Trial.

BackgroundUnwarranted variability in clinical practice is a challenging problem in practice today, leading to poor outcomes for patients and low-value care for providers, payers, and patients.ObjectiveIn this study, we introduced a novel tool, QualityIQ, and determined the extent to which it helps primary care physicians to align care decisions with the latest best practices included in the Merit-Based Incentive Payment System (MIPS).MethodsWe developed the fully automated QualityIQ patient simulation platform with real-time evidence-based feedback and gamified peer benchmarking. Each case included workup, diagnosis, and management questions with explicit evidence-based scoring criteria. We recruited practicing primary care physicians across the United States into the study via the web and conducted a cross-sectional study of clinical decisions among a national sample of primary care physicians, randomized to continuing medical education (CME) and non-CME study arms. Physicians “cared” for 8 weekly cases that covered typical primary care scenarios. We measured participation rates, changes in quality scores (including MIPS scores), self-reported practice change, and physician satisfaction with the tool. The primary outcomes for this study were evidence-based care scores within each case, adherence to MIPS measures, and variation in clinical decision-making among the primary care providers caring for the same patient.ResultsWe found strong, scalable engagement with the tool, with 75% of participants (61 non-CME and 59 CME) completing at least 6 of 8 total cases. We saw significant improvement in evidence-based clinical decisions across multiple conditions, such as diabetes (+8.3%, P<.001) and osteoarthritis (+7.6%, P=.003) and with MIPS-related quality measures, such as diabetes eye examinations (+22%, P<.001), depression screening (+11%, P<.001), and asthma medications (+33%, P<.001). Although the CME availability did not increase enrollment in the study, participants who were offered CME credits were more likely to complete at least 6 of the 8 cases.ConclusionsAlthough CME availability did not prove to be important, the short, clinically detailed case simulations with real-time feedback and gamified peer benchmarking did lead to significant improvements in evidence-based care decisions among all practicing physicians.Trial RegistrationClinicalTrials.gov NCT03800901; https://clinicaltrials.gov/ct2/show/NCT03800901

Hematemesis in Infants: The First Evidence-Based Score to Predict the Need for Timely Endoscopy.

Infantile acute upper gastrointestinal bleeding involves a decision for therapeutic intervention that most pediatricians first coming into contact with the patient are, not unreasonably, unable to objectively provide. Therefore, some objective tools of individual risk assessment would seem to be crucial. The principal aim of the present study was to investigate the anamnestic and clinical parameters of infants with hematemesis, together with laboratory and instrumental findings, to create a scoring system that may help identify those infants requiring an appropriate and timely application of upper gastrointestinal (GI) endoscopy. Clinical data of infants admitted for hematemesis to the participating centers over the study period were systematically collected. According to the outcome dealing with rebleeding, need for blood transfusion, mortality, finding of GI bleeding lesions, or need for surgical intervention, patients were blindly divided into a group with major clinical severity and a group with minor clinical severity. Univariate and multivariate logistic regressions were conducted to investigate significant prognostic factors for clinical severity. According to our findings, we drafted a practical diagnostic algorithm and a clinical score able to predict the need for timely upper GI endoscopy (BLOVO infant score). Our clinical scoring system was created by incorporating anamnestic factors, clinical parameters, and laboratory findings that emerged as predictors of a worst outcome. We provided the first objective tool of individual risk assessment for infants with hematemesis, which could be very useful for pediatricians first coming into contact with the patient in the emergency department.

Perioperative risk prediction.

Predicting outcomes for surgical patients accurately can be challenging preoperatively. Fortunately, there is an array of evidence-based scoring systems which can guide perioperative decision making and discussions of risk with patients.

An evidence-based scoring system to diagnose acute rheumatic fever with carditis in children

BackgoundAcute rheumatic fever (ARF) with carditis and chronic rheumatic heart disease (RHD) may be difficult to differentiate and may lead to missed diagnosis of carditis. We aimed to determine differences between these groups and to develop a new scoring system for this purpose. MethodsChildren (N = 514; mean age 11.6 ± 2.8, range 5–18 years; 65% males) enrolled in a RHD registry at a tertiary care centre were studied. Clinical, laboratory and echocardiographic features of acute rheumatic carditis group (N = 126) were compared with chronic RHD group (N = 388). We performed multiple regression analysis and then developed a new scoring system using independent predictors. Accuracy of this scoring system was assessed using receiver operating characteristic (ROC) curve analysis. ResultsPatients with ARF and carditis were younger, more commonly had history of fever, arthritis/arthralgias and had worse NYHA class. On echocardiography, severity of mitral regurgitation, presence of mitral leaflet nodules, mitral valve prolapse and pericardial effusion were more common in ARF group. On multiple regression analysis, following features were found to be independently predictive of ARF with carditis: age -negative association, NYHA class, severity of mitral regurgitation, mitral leaflet nodules, erythrocyte sedimentation rate and antistreptolysin titer. Based on these 6 variables, a new scoring system (0−13) was developed. A score of 5 or more was found to be best threshold for diagnosis of carditis (ROC AUC 0.87, sensitivity 76%, specificity 79%). ConclusionA new scoring system based on independent statistical associations appears promising for differentiating ARF with carditis from chronic RHD.

The usefulness of a trauma probability of survival model for forensic life-threatening danger assessments

Clinical forensic medical examinations constitute an increasing proportion of our institution’s tasks, and, concomitantly, the authorities are now requesting forensic life-threatening danger assessments based on our examinations. The aim of this retrospective study was to assess if a probability of survival (PS) trauma score could be useful for these forensic life-threatening danger assessments and to identify a cut-off PS score as a supporting tool for the forensic practice of assessing life-threatening danger. We compared a forensic database and a trauma database and identified 161 individuals (aged 15 years or older) who had both a forensic life-threatening danger assessment and a PS score. The life-threatening danger assessments comprised the following statements: was not in life-threatening danger (NLD); could have been in life-threatening danger (CLD); or was in life-threatening danger (LD). The inclusion period was 2012–2016. A statistically significant difference was found in the PS scores between NLD, CLD and LD (chi-square test: p < 0.0001). The usefulness of the PS score for categorizing life-threatening danger assessments was determined by a receiver-operator characteristic (ROC) curve. The area under the curve was 0.76 (95% CI, 0.69 to 0.84) and the ROC curve revealed that a cut-off PS score of 95.8 would appropriately identify LD. Therefore, a PS score below 95.8 would indicate life-threatening danger. We propose a further exploration of how the evidence-based PS score, including a cut-off value, might be implemented in clinical forensic medical statements to add to the scientific strength of these statements.

How to predict early clinical outcomes and evaluate the quality of primary total knee arthroplasty: a new scoring system based on lower-extremity angles of alignment

BackgroundA method that can accurately predict the outcome of surgery can give patients timely feedback. In addition, to some extent, an objective evaluation method can help the surgeon quickly summarize the patient’s surgical experience and lessen dependence on the long wait for follow-up results. However, there was still no precise tool to predict clinical outcomes of total knee arthroplasty (TKA). This study aimed to develop a scoring system to predict clinical results of TKA and then grade the quality of TKA.MethodsWe retrospectively reviewed 98 primary TKAs performed between April 2013 and March 2017 to determine predictors of clinical outcomes among lower-extremity angles of alignment. Applying multivariable linear-regression analysis, we built Models (i) and (ii) to predict detailed clinical outcomes which were evaluated using the Knee Society Score (KSS). Multivariable logistic-regression analysis was used to establish Model (iii) to predict probability of getting a good clinical outcome (PGGCO) which was evaluated by Knee Injury and Osteoarthritis Outcome Score (KOOS) score. Finally, we designed a new scoring system consisting of 3 prediction models and presented a method of grading TKA quality. Thirty primary TKAs between April and December 2017 were enrolled for external validation.ResultsWe set up a scoring system consisting of 3 models. The interpretations of Model (i) and (ii) were good (R2 = 0.756 and 0.764, respectively). Model (iii) displayed good discrimination, with an area under the curve (AUC) of 0.936, and good calibration according to the calibration curve. Quality of surgery was stratified as follows: “A” = PGGCO ≥0.8, “B” = PGGCO ≤0.6 but < 0.8, and “C” = PGGCO < 0.6. The scoring system performed well in external validation.ConclusionsThis study first developed a validated, evidence-based scoring system based on lower-extremity angles of alignment to predict early clinical outcomes and to objectively evaluate the quality of TKA.

Assessing the Mechanical Weakness of Vertebrae Affected by Primary Tumors: A Feasibility Study.

Patients spend months between the primary spinal tumor diagnosis and the surgical treatment, due to the need for performing chemotherapy and/or radiotherapy. During this period, they are exposed to an unknown risk of fracture. The aim of this study was to assess if it is possible to measure the mechanical strain in vertebrae affected by primary tumors, so as to open the way to an evidence-based scoring or prediction tool. We performed biomechanical tests on three vertebrae with bone tumor removed from patients. The tests were designed so as not to compromise the standard surgical and diagnostic procedures. Non-destructive mechanical tests in combination with state-of-the-art digital image correlation allowed to measure the distribution of strain on the surface of the vertebra. Our study has shown that the strains in the tumor region is circa 3 times higher than in the healthy bones, with principal strain peaks of 40,000/−20,000 microstrain, indicating a stress concentration potentially triggering vertebral fracture. This study has proven it is possible to analyze the mechanical behavior of primary tumor vertebrae as part of the clinical treatment protocol. This will allow building a tool for quantifying the risk of fracture and improving decision making in spine tumors.

Vetrivel trauma score – An evidence-based scoring system to predict limb salvage and outcomes in gustilo anderson grade III B and C compound fractures of lower extremities

Background: Open fractures with severe soft-tissue injuries are clinically challenging to treat. While several scoring systems are available to grade these clinical conditions, the Gustilo Anderson grading system is most commonly used. This grading system neither offers any clue regarding salvaging open fractures of Grade III B and above, nor does it help the surgeon to assess the outcomes in such injuries. Hence, a new system of grading was assessed to address this deficiency. Materials and Methods: Five hundred and twelve open fracture cases were analyzed for this study. Two hundred and twenty-seven patients sustained Grade III injuries according to the Gustilo Anderson classification; Of these, 175 patients had Grade III A open fractures and 52 patients were of Grade III B and above. The 52 patients with open fractures of Grade III B and above were scored using mangled extremity severity score (MESS), Ganga score, and our novel scoring system. The accuracy in deciding amputation and predict outcomes were measured. Results: The scores assessed by the new scoring system were compared with MESS, Gustilo grading, and Ganga score system. Binary logistic regression analysis indicated our scoring system to be more accurate compared to all other scoring systems (P = 0.02). A receiver operating characteristic curve was plotted to compare all other scoring systems. The area under the curve (0.996 ± 0.003) for our scoring system was significantly higher with the less standard error of the mean than other scoring systems compared. Conclusions: Our new scoring system was more accurate in predicting limb salvage and outcomes compared to the existing scoring systems for open fractures of Grade III B and above.

The EUTOS long-term survival (ELTS) score is superior to the Sokal score for predicting survival in chronic myeloid leukemia

Prognostic scores support clinicians in selecting risk-adjusted treatments and in comparatively assessing different results. For patients with chronic-phase chronic myeloid leukemia (CML), four baseline prognostic scores are commonly used. Our aim was to compare the prognostic performance of the scores and to arrive at an evidence-based score recommendation. In 2949 patients not involved in any score development, higher hazard ratios and concordance indices in any comparison demonstrated the best discrimination of long-term survival with the ELTS score. In a second step, of 5154 patients analyzed to investigate risk group classification differences, 23% (n = 1197) were allocated to high-risk by the Sokal score. Of the 1197 Sokal high-risk patients, 56% were non-high-risk according to the ELTS score and had a significantly more favorable long-term survival prognosis than the 526 high-risk patients according to both scores. The Sokal score identified too many patients as high-risk and relatively few (40%) as low-risk (versus 60% with the ELTS score). Inappropriate risk classification jeopardizes optimal treatment selection. The ELTS score outperformed the Sokal score, the Euro, and the EUTOS score regarding risk group discrimination. The recent recommendation of the European LeukemiaNet for preferred use of the ELTS score was supported with significant statistical evidence.

Evaluation of a computational decision support system for molecularly targeted treatment planning by the clinical outcome data of the randomized trial SHIVA01.

3642 Background: Precision oncology requires the identification of individual molecular pathomechanisms to find optimal personalized treatment strategies for every cancer patient. Incorporation of complex molecular information into routine clinical practice remains a significant challenge due to the lack of a reproducible, standardized process of clinical decision making. Methods: To provide a standardized process for molecular interpretation, we develop a precision oncology decision support system, the Realtime Oncology Molecular Treatment Calculator (MTC). MTC is a rule-based medical knowledge engine that dynamically aggregates and ranks relevant scientific and clinical evidence using currently 26,000 evidence-based associations and reproducible algorithm scoring of drivers, molecular targets to match molecular alterations to efficient therapies. To validate this novel method and system, we used data of the SHIVA01 trial of molecularly targeted therapy (Lancet Oncol 2015 16:1324-34). Molecular profiles of participants were uploaded to MTC and aggregated evidence level (AEL) values of associated targeted treatments were calculated, including those used in the SHIVA01 trial. Results: The MTC output provided a prioritized list of drugs associated with the driver alterations in the patient molecular profile, where ranking is based on AEL values. Of 113 patients who received targeted therapy with available clinical best response data, disease control was experienced in 63 cases (PR: 5, SD: 58), while disease progression occurred in 50 cases. The average AEL score for the therapies applied was significantly higher in the responsive group than in the non-responsive group (1512 and 614, respectively (p = 0.049)). In 94 cases, drugs other than those used for therapy were ranked higher by the MTC. The average AEL difference between the top-ranked and the used drugs was in an inverse correlation with clinical response, i.e. smaller differences associated with a better outcome. Conclusions: Results indicate that the aggregation of evidence-based tumor-driver-target-drug associations using standardized mathematical algorithms of this computational tool is a promising novel approach to improve clinical decisions in precision oncology. Further validation based on the results of other targeted clinical trials and real-life data using more detailed molecular profiles is warranted to explore the full clinical potential of this novel medical solution.

ScCATCH: Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data.

SummaryRecent advancements in single-cell RNA sequencing (scRNA-seq) have facilitated the classification of thousands of cells through transcriptome profiling, wherein accurate cell type identification is critical for mechanistic studies. In most current analysis protocols, cell type-based cluster annotation is manually performed and heavily relies on prior knowledge, resulting in poor replicability of cell type annotation. This study aimed to introduce a single-cell Cluster-based Automatic Annotation Toolkit for Cellular Heterogeneity (scCATCH, https://github.com/ZJUFanLab/scCATCH). Using three benchmark datasets, the feasibility of evidence-based scoring and tissue-specific cellular annotation strategies were demonstrated by high concordance among cell types, and scCATCH outperformed Seurat, a popular method for marker genes identification, and cell-based annotation methods. Furthermore, scCATCH accurately annotated 67%–100% (average, 83%) clusters in six published scRNA-seq datasets originating from various tissues. The present results show that scCATCH accurately revealed cell identities with high reproducibility, thus potentially providing insights into mechanisms underlying disease pathogenesis and progression.