Improving the clinical accuracy and flexibility of the Alkaptonuria severity score index
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ABSTRACT:
SUBMITTER: Cant H
PROVIDER: S-EPMC9259391 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:Alkaptonuria (AKU) is a rare disorder with no licensed treatment; nitisinone may reduce symptoms and progression. The All Alkaptonuria Severity Score Index (AKUSSI) measures disease severity in clinical, joint and spine domains, with 57 subcomponent feature scores. Our primary aim was to assess tools for validating scores such as the AKUSSI by detecting relationships between features both before and during nitisinone treatment. METHODS:AKUSSI measurements from nitisinone-treated patients visiting the National AKU Centre between 01-Jun-2012 and 31-May-2016 were analysed pre-treatment, at first treatment and annually to Year 3 post-treatment. Principal component analysis (PCA) and redundancy analysis assessed whether any AKUSSI features contributed little information to the overall score. RESULTS:65 AKU patients were included: 17 with a pre-treatment AKUSSI measurement (10 later received nitisinone) and 48 with a first measurement at their first treatment visit. In PCA, the first four principal components (PC1-PC4) explained ?50% of AKUSSI variance at all visits (54.1-87.3%). Some features regularly dominated their domain's PC1: ears, aortic sclerosis, and nasal/temporal eye scores (clinical), pain-related scores (joint) and cervical, lumbar and thoracic spine scores (spine). Only the right-hand/wrist score was consistently redundant. Right eye (nasal) and left ear scores were redundant pre-treatment, potentially correlating with other dominant clinical PC1 features. CONCLUSIONS:PCA and redundancy analysis supported the AKUSSI as a robust AKU disease severity measure, although some AKUSSI features could be removed for simplicity. For small patient populations and rare diseases, PCA and redundancy analysis together can aid validation of disease severity metrics.
| S-EPMC6122049 | biostudies-literature
Project description:BackgroundThe fatty liver index (FLI) is frequently used as a non-invasive clinical marker for research, prognostic and diagnostic purposes. It is also used to stratify individuals with hepatic steatosis such as non-alcoholic fatty liver disease (NAFLD), and to detect the presence of type 2 diabetes or cardiovascular disease. The FLI is calculated using a combination of anthropometric and blood biochemical variables; however, it reportedly excludes 8.5-16.7% of individuals with NAFLD. Moreover, the FLI cannot quantitatively predict liver fat, which might otherwise render an improved diagnosis and assessment of fatty liver, particularly in longitudinal studies. We propose FLI+ using predictive regression modelling, an improved index reflecting liver fat content that integrates 12 routinely-measured variables, including the original FLI.Methods and findingsWe evaluated FLI+ on a dataset from the UK Biobank containing 28,796 individual estimates of proton density fat fraction derived from magnetic resonance imaging across normal to severe levels and interpolated to align with the original FLI range. The results obtained for FLI+ outperform the original FLI by delivering a lower mean absolute error by approximately 47%, a lower standard deviation by approximately 20%, and an increased adjusted R2 statistic by approximately 49%, reflecting a more accurate representation of liver fat content.ConclusionsOur proposed model predicting FLI+ has the potential to improve diagnosis and provide a more accurate stratification than FLI between absent, mild, moderate and severe levels of hepatic steatosis.
| S-EPMC9469950 | biostudies-literature
Project description:BackgroundDespite the notoriety of Ebola virus disease (EVD) as one of the world's most deadly infections, EVD has a wide range of outcomes, where asymptomatic infection may be almost as common as fatality. With increasingly sensitive EVD diagnosis, there is a need for more accurate prognostic tools that objectively stratify clinical severity to better allocate limited resources and identify those most in need of intensive treatment.Methods/principal findingsThis retrospective cohort study analyses the clinical characteristics of 158 EVD(+) patients at the GOAL-Mathaska Ebola Treatment Centre, Sierra Leone. The prognostic potential of each characteristic was assessed and incorporated into a statistically weighted disease score. The mortality rate among EVD(+) patients was 60.8% and highest in those aged <5 or >25 years (p<0.05). Death was significantly associated with malaria co-infection (OR = 2.5, p = 0.01). However, this observation was abrogated after adjustment to Ebola viral load (p = 0.1), potentially indicating a pathologic synergy between the infections. Similarly, referral-time interacted with viral load, and adjustment revealed referral-time as a significant determinant of mortality, thus quantifying the benefits of early reporting as a 12% mortality risk reduction per day (p = 0.012). Disorientation was the strongest unadjusted predictor of death (OR = 13.1, p = 0.014) followed by hiccups, diarrhoea, conjunctivitis, dyspnoea and myalgia. Including these characteristics in multivariate prognostic scores, we obtained a 91% and 97% ability to discriminate death at or after triage respectively (area under ROC curve).Conclusions/significanceThis study proposes highly predictive and easy-to-use prognostic tools, which stratify the risk of EVD mortality at or after EVD triage.
| S-EPMC5289426 | biostudies-literature
Project description:BackgroundSeveral risk factors already have been determined for dogs with degenerative mitral valve disease (DMVD). Risk factors often have been considered in isolation and have not always taken into account additional information provided by the history and physical examination (PE).Hypothesis/objectivesData obtained from history and PE of dogs with DMVD provide prognostic information and can be used for risk stratification.AnimalsClient-owned dogs (n = 244) with DMVD recruited from first opinion practice.MethodsProspective longitudinal follow-up of dogs with DMVD. History and PE data were obtained at 6-month intervals and analyzed with time-dependent Cox models to derive relative risk of cardiac death. Independent hazard ratios were used to derive a clinical severity score (CSS), the prognostic value of which was evaluated by analyzing the median survival times for different risk groups and ROC analysis. Analysis of the progression of CSS over time also was undertaken.ResultsHistory of cough, exercise intolerance, decreased appetite, breathlessness (difficulty breathing) and syncope with PE findings of heart murmur intensity louder than III/VI and absence of respiratory sinus arrhythmia were independently associated with outcome and allowed development of the CSS. Clinical severity score distinguished groups of dogs with significantly different outcomes.Conclusions and clinical importanceRoutinely obtained clinical findings allow risk stratification of dogs with DMVD. Results of ancillary diagnostic tests may be complementary to history and PE findings and always should be interpreted in conjunction with these findings.
| S-EPMC4895509 | biostudies-literature
Project description:Background: The management of the moderate and severe forms of acute pancreatitis (AP) with necrosis and multiorgan failure remains a challenge. To predict the severity and mortality of AP multiple clinical, laboratory-, and imaging-based scoring systems are available. Aim: To investigate, if the computed tomography severity index (CTSI) can predict the outcomes of AP better than other scoring systems. Methods: A systematic search was performed in three databases: Pubmed, Embase, and the Cochrane Library. Eligible records provided data from consecutive AP cases and used CTSI or modified CTSI (mCTSI) alone or in combination with other prognostic scores [Ranson, bedside index of severity in acute pancreatitis (BISAP), Acute Physiology, and Chronic Health Examination II (APACHE II), C-reactive protein (CRP)] for the evaluation of severity or mortality of AP. Area under the curves (AUCs) with 95% confidence intervals (CIs) were calculated and aggregated with STATA 14 software using the metandi module. Results: Altogether, 30 studies were included in our meta-analysis, which contained the data of 5,988 AP cases. The pooled AUC for the prediction of mortality was 0.79 (CI 0.73-0.86) for CTSI; 0.87 (CI 0.83-0.90) for BISAP; 0.80 (CI 0.72-0.89) for mCTSI; 0.73 (CI 0.66-0.81) for CRP level; 0.87 (CI 0.81-0.92) for the Ranson score; and 0.91 (CI 0.88-0.93) for the APACHE II score. The APACHE II scoring system had significantly higher predictive value for mortality than CTSI and CRP (p = 0.001 and p < 0.001, respectively), while the predictive value of CTSI was not statistically different from that of BISAP, mCTSI, CRP, or Ranson criteria. The AUC for the prediction of severity of AP were 0.80 (CI 0.76-0.85) for CTSI; 0.79, (CI 0.72-0.86) for BISAP; 0.83 (CI 0.75-0.91) for mCTSI; 0.73 (CI 0.64-0.83) for CRP level; 0.81 (CI 0.75-0.87) for Ranson score and 0.80 (CI 0.77-0.83) for APACHE II score. Regarding severity, all tools performed equally. Conclusion: Though APACHE II is the most accurate predictor of mortality, CTSI is a good predictor of both mortality and AP severity. When the CT scan has been performed, CTSI is an easily calculable and informative tool, which should be used more often in routine clinical practice.
| S-EPMC6718714 | biostudies-literature
Project description:Protein-nucleic acid complexes are important for many cellular processes including the most essential functions such as transcription and translation. For many protein-nucleic acid complexes, flexibility of both macromolecules has been shown to be critical for specificity and/or function. The flexibility-rigidity index (FRI) has been proposed as an accurate and efficient approach for protein flexibility analysis. In this article, we introduce FRI for the flexibility analysis of protein-nucleic acid complexes. We demonstrate that a multiscale strategy, which incorporates multiple kernels to capture various length scales in biomolecular collective motions, is able to significantly improve the state of art in the flexibility analysis of protein-nucleic acid complexes. We take the advantage of the high accuracy and O(N) computational complexity of our multiscale FRI method to investigate the flexibility of ribosomal subunits, which are difficult to analyze by alternative approaches. An anisotropic FRI approach, which involves localized Hessian matrices, is utilized to study the translocation dynamics in an RNA polymerase.
| S-EPMC5844491 | biostudies-literature
Project description:ImportancePolygenic risk scores comprising millions of single-nucleotide polymorphisms (SNPs) could be useful for population-wide coronary heart disease (CHD) screening.ObjectiveTo determine whether a polygenic risk score improves prediction of CHD compared with a guideline-recommended clinical risk equation.Design, setting, and participantsA retrospective cohort study of the predictive accuracy of a previously validated polygenic risk score was assessed among 4847 adults of white European ancestry, aged 45 through 79 years, participating in the Atherosclerosis Risk in Communities (ARIC) study and 2390 participating in the Multi-Ethnic Study of Atherosclerosis (MESA) from 1996 through December 31, 2015, the final day of follow-up. The performance of the polygenic risk score was compared with that of the 2013 American College of Cardiology and American Heart Association pooled cohort equations.ExposuresGenetic risk was computed for each participant by summing the product of the weights and allele dosage across 6 630 149 SNPs. Weights were based on an international genome-wide association study.Main outcomes and measuresPrediction of 10-year first CHD events (including myocardial infarctions, fatal coronary events, silent infarctions, revascularization procedures, or resuscitated cardiac arrest) assessed using measures of model discrimination, calibration, and net reclassification improvement (NRI).ResultsThe study population included 4847 adults from the ARIC study (mean [SD] age, 62.9 [5.6] years; 56.4% women) and 2390 adults from the MESA cohort (mean [SD] age, 61.8 [9.6] years; 52.2% women). Incident CHD events occurred in 696 participants (14.4%) and 227 participants (9.5%), respectively, over median follow-up of 15.5 years (interquartile range [IQR], 6.3 years) and 14.2 (IQR, 2.5 years) years. The polygenic risk score was significantly associated with 10-year CHD incidence in ARIC with hazard ratios per SD increment of 1.24 (95% CI, 1.15 to 1.34) and in MESA, 1.38 (95% CI, 1.21 to 1.58). Addition of the polygenic risk score to the pooled cohort equations did not significantly increase the C statistic in either cohort (ARIC, change in C statistic, -0.001; 95% CI, -0.009 to 0.006; MESA, 0.021; 95% CI, -0.0004 to 0.043). At the 10-year risk threshold of 7.5%, the addition of the polygenic risk score to the pooled cohort equations did not provide significant improvement in reclassification in either ARIC (NRI, 0.018, 95% CI, -0.012 to 0.036) or MESA (NRI, 0.001, 95% CI, -0.038 to 0.076). The polygenic risk score did not significantly improve calibration in either cohort.Conclusions and relevanceIn this analysis of 2 cohorts of US adults, the polygenic risk score was associated with incident coronary heart disease events but did not significantly improve discrimination, calibration, or risk reclassification compared with conventional predictors. These findings suggest that a polygenic risk score may not enhance risk prediction in a general, white middle-aged population.
| S-EPMC7042849 | biostudies-literature
Project description:BackgroundCompared with children and immunocompromised patients, Adenovirus pneumonia in immunocompetent adults is less common. Evaluation of the applicability of severity score in predicting intensive care unit (ICU) admission of Adenovirus pneumonia is limited.MethodsWe retrospectively reviewed 50 Adenovirus pneumonia inpatients in Xiangtan Central Hospital from 2018 to 2020. Hospitalized patients with no pneumonia or immunosuppression were excluded. Clinical characteristics and chest image at the admission of all patients were collected. Severity scores, including Pneumonia severity index (PSI), CURB-65, SMART-COP, and PaO2/FiO2 combined lymphocyte were evaluated to compare the performance of ICU admission.ResultsFifty inpatients with Adenovirus pneumonia were selected, 27 (54%) non-ICU and 23 (46%) ICU. Most patients were men (40 [80.00%]). Age median was 46.0 (IQR 31.0-56.0). Patients who required ICU care (n = 23) were more likely to report dyspnea (13[56.52%] vs 6[22.22%]; P = 0.002) and have lower transcutaneous oxygen saturation ([90% (IQR, 90-96), 95% (IQR, 93-96)]; P = 0.032). 76% (38/50) of patients had bilateral parenchymal abnormalities, including 91.30% (21/23) of ICU patients and 62.96% (17/27) of non-ICU patients. 23 Adenovirus pneumonia patients had bacterial infections, 17 had other viruses, and 5 had fungi. Coinfection with virus was more common in non-ICU patients than ICU patients (13[48.15%]VS 4[17.39%], P = 0.024), while bacteria and fungi not. SMART-COP exhibited the best ICU admission evaluation performance in Adenovirus pneumonia patients (AUC = 0.873, p < 0.001) and distributed similar in coinfections and no coinfections (p = 0.26).ConclusionsIn summary, Adenovirus pneumonia is not uncommon in immunocompetent adult patients who are susceptible to coinfection with other etiological illnesses. The initial SMART-COP score is still a reliable and valuable predictor of ICU admission in non-immunocompromised adult inpatients with adenovirus pneumonia.
| S-EPMC9934457 | biostudies-literature
Project description:nasosinus polyposis (=PNS) is a chronic inflammatory disease of the nasal cavity and sinus cavity with a prevalence of 2 to 4% in the general population. The functional impact of PNS has a major impact on one’s quality of life.Medical treatment, nasal irrigations and local glucocorticoids as well as short treatment of oral glucocorticoids have shown a short-term benefit versus placebo. Surgery improves the efficacy of local treatments, but 40% of patients have a recurrence of polyps at 18 months and 20% of patients require a surgery recovery at 5 years. The development of monoclonal antibodies directly targeting the inflammatory way is a real public health issue. Bachert C. et al recently demonstrated the efficacy of Dupilumab (anti-IL-4/13 antibody) injected subcutaneously on the overall symptomatology of PNS. The marketing authorization (AMM) for the first biotherapy to be available soon includes PNS’s severe nature and resistance to treatment, although there is no consensus definition or score to characterize this severity. This study aims at developping a score for assessing severity in PNS. We suggest that this assessment strategy could be applied to the PNS. The originality and the innovative character of this project is the statistical modeling behind the creation of the score. Thus, the importance of symptoms, anatomical and biological factors, the estimation of the quality of life of the patients, the level of care use and the number of surgeries all become measurable indicators that are a direct reflexion of the severity and the control of PNS, called latent variables because they cannot be directly measured. To consider this detail, modeling using structural equations seems optimal to develop a severity score (PSI score) of PNS in order to personalize the therapeutic care of patients. Main Objective: To develop a severity score for PNS using latent variable modeling: Polyps Severity Index (PSI)
| 2390596 | ecrin-mdr-crc
Project description:Protein structural fluctuation, typically measured by Debye-Waller factors, or B-factors, is a manifestation of protein flexibility, which strongly correlates to protein function. The flexibility-rigidity index (FRI) is a newly proposed method for the construction of atomic rigidity functions required in the theory of continuum elasticity with atomic rigidity, which is a new multiscale formalism for describing excessively large biomolecular systems. The FRI method analyzes protein rigidity and flexibility and is capable of predicting protein B-factors without resorting to matrix diagonalization. A fundamental assumption used in the FRI is that protein structures are uniquely determined by various internal and external interactions, while the protein functions, such as stability and flexibility, are solely determined by the structure. As such, one can predict protein flexibility without resorting to the protein interaction Hamiltonian. Consequently, bypassing the matrix diagonalization, the original FRI has a computational complexity of O(N(2)). This work introduces a fast FRI (fFRI) algorithm for the flexibility analysis of large macromolecules. The proposed fFRI further reduces the computational complexity to O(N). Additionally, we propose anisotropic FRI (aFRI) algorithms for the analysis of protein collective dynamics. The aFRI algorithms permit adaptive Hessian matrices, from a completely global 3N × 3N matrix to completely local 3 × 3 matrices. These 3 × 3 matrices, despite being calculated locally, also contain non-local correlation information. Eigenvectors obtained from the proposed aFRI algorithms are able to demonstrate collective motions. Moreover, we investigate the performance of FRI by employing four families of radial basis correlation functions. Both parameter optimized and parameter-free FRI methods are explored. Furthermore, we compare the accuracy and efficiency of FRI with some established approaches to flexibility analysis, namely, normal mode analysis and Gaussian network model (GNM). The accuracy of the FRI method is tested using four sets of proteins, three sets of relatively small-, medium-, and large-sized structures and an extended set of 365 proteins. A fifth set of proteins is used to compare the efficiency of the FRI, fFRI, aFRI, and GNM methods. Intensive validation and comparison indicate that the FRI, particularly the fFRI, is orders of magnitude more efficient and about 10% more accurate overall than some of the most popular methods in the field. The proposed fFRI is able to predict B-factors for ?-carbons of the HIV virus capsid (313 236 residues) in less than 30 seconds on a single processor using only one core. Finally, we demonstrate the application of FRI and aFRI to protein domain analysis.
| S-EPMC4098052 | biostudies-literature