Symptoms predictive of Fusobacterium necrophorum pharyngotonsillitis - an observational study of cases presenting to hospitals in Southern Sweden.

OBJECTIVES: Fusobacterium necrophorum is a common cause of pharyngotonsillitis. However, no guidelines exist on when to diagnose or treat it. We aimed to investigate associations between clinical criteria and F. necrophorum-positivity in pharyngotonsillitis and assess the predictive potential of a simple scoring system. METHODS: Pharyngotonsillitis patients who were tested for F. necrophorum (PCR) and presented to hospitals in the Skåne Region, Sweden, between 2013-2020 were eligible. Data were retrieved from electronic chart reviews and registries. By logistic regression we investigated associations between F. necrophorum-positivity and pre-specified criteria: age 13-30 years, symptom duration ≤ 3 days, absence of viral symptoms (e.g. cough, coryza), fever, tonsillar swelling/exudate, lymphadenopathy and CRP ≥ 50 mg/L. In secondary analyses, associated variables were weighted by strength of association into a score and its predictive accuracy of F. necrophorum was assessed. RESULTS: Among 561 cases included, 184 (33%) had F. necrophorum, which was associated with the following criteria: age 13-30, symptom duration ≤ 3 days, absence of viral symptoms, tonsillar swelling/exudate and CRP ≥ 50 mg/L. Age 13-30 had the strongest association (OR5.7 95%CI 3.7-8.8). After weighting, these five variables had a sensitivity and specificity of 68% and 71% respectively to predict F. necrophorum-positivity at the proposed cut-off. CONCLUSION: Our results suggest that F. necrophorum cases presenting to hospitals might be better distinguished from other pharyngotonsillitis cases by a simple scoring system presented, with age 13-30 being the strongest predictor for F. necrophorum. Prospective studies, involving primary care settings, are needed to evaluate generalisability of findings beyond cases presenting to hospitals.

A scoring system to predict the technical difficulty of endoscopic resection for cardial submucosal tumors.

BACKGROUND AND AIM: Endoscopic resection has been successfully used for the removal of digestive submucosal tumors (SMTs). However, the cardia has been considered a challenging location for endoscopic resection due to its narrow lumen and sharp angle. The objective of this study was to establish a clinical scoring model to grade the technical difficulty of endoscopic resection for cardial SMTs. METHODS: A total of 246 patients who suffered cardial SMTs and received endoscopic resection were included in this retrospective study. All of them were randomized into the training cohort (n = 123) or internal validation cohort (n = 123). Potential predictors were analyzed using univariate analysis. Then, covariates with P < 0.05 were selected for the multivariate logistic regression model. The ß coefficients from the logistic regression model were used to create a scoring system for technical difficulty prediction by rounding the score to the nearest integer of the absolute ß coefficient value. RESULTS: The clinical score consisted of the following factors: male gender (2 points), extraluminal growth (3 points), and maximum diameter ≥3 cm (3 points). The scoring model demonstrated good discriminatory power, with an area under the receiver operating characteristic curve of 0.860 and a 95% confidence interval of 0.763-0.958. The model also showed a good goodness of fit in the Hosmer-Lemeshow test (P = 0.979). In the training cohort, the probability of encountering technical difficulty in the easy (score = 0), intermediate (score = 1-3), difficult (score = 4-6), and very difficult (score >6) categories was 0, 6.8%, 33.3%, and 100.0%, respectively; similarly, in the validation cohort, it was 0, 5.6%, 22.2%, and 50.0%, respectively. CONCLUSIONS: This scoring system could serve as a valuable tool for clinicians in predicting the technical difficulty of endoscopic resection for cardial SMTs.

The cotton swab method: an accurate and less invasive way to assess fecal consistency in weaned pigs.

BACKGROUND: Researchers and pig veterinarians are interested in assessing pigs' fecal consistency. This study developed a standardized protocol and scale for the cotton swab method, which is a way of assessing the fecal consistency in pigs. The accuracy of the cotton swab method was evaluated in weaned pigs using fecal dry-matter analysis as a golden standard. The study also proposed fecal dry-matter percentage thresholds for the categorization of fecal consistency on a four-point scale. RESULTS: The thresholds of 10.3%, 16.6%, and 21.9% fecal dry-matter were suggested for categorization of the consistency of fecal samples on a four-point scale. The accuracy of the cotton swab method was high. The agreement to the four-point fecal consistency score derived from the fecal dry-matter percentage was almost perfect (weighted Gwet's agreement coefficient = 0.87 [95% confidence interval: 0.84; 0.91]). The cotton swab method had a sensitivity of 85.0% (95% confidence interval: 76.5; 91.4) and a specificity of 95.2% (95% confidence interval: 92.0; 97.3) when used to diagnose whether pigs had diarrhea or not. For non-diarrheic pigs, the method almost always (n = 287/289) required less handling than the collection of a fecal sample by digital rectal manipulation. CONCLUSION: The cotton swab method is an accurate way to assess fecal consistency in pigs, both on a four-point scale and as a dichotomous diarrhea score. The method is quick to perform and less invasive than methods relying on the collection of fecal samples. New fecal dry-matter thresholds between feces of different consistencies were proposed.

Performance of various interpretations of clinical scoring systems for diagnosis of respiratory disease in dairy calves in a temperate climate using Bayesian latent class analysis.

Bovine respiratory disease (BRD) presents a challenge to farmers all over the globe not only because it can have significant impacts on welfare and productivity, but also because diagnosis can prove challenging. Several clinical scoring systems have been developed to aid farmers in making consistent early diagnosis, 2 examples being the Wisconsin (WCS) and the California (CALIF) systems. Neither of these systems were developed in or for use in a temperate environment. As environment may lead to changes in BRD presentation, the weightings and cut offs designed for one environmental presentation of BRD may not be appropriate when used in a temperate climate. Additionally, the interpretation of the scores recorded varies between studies; this may also influence conclusions. Hence, the objective of this work was to investigate the sensitivity (Se) and specificity (Sp) of these tests in a temperate climate and investigate the influence of varying the interpretation on the performance of the WCS. In this prospective study, 98 commercial spring calving dairy farms were recruited (40 randomly, 58 targeted) and visited. Thoracic ultrasound and WCS was performed on 20 randomly sampled calves between 4 and 6 weeks of age on each farm. On a subset of 32 farms, the CALIF score was also undertaken. The data were then used in a hierarchical Bayesian latent class model to estimate the Se and Sp of 5 different interpretations of the Wisconsin clinical score and one interpretation of the California clinical score. In total, 1,936 calves were examined. The Se of the Wisconsin score varied from 0.336 to 0.577 depending on the interpretation used and the Sp varied from 0.943 to 0.977. The Se of the California score was 0.529 (95% Bayesian credible interval (BCI); 0.403, 0.651) and the Sp was 0.903 (95% bci; 0.883, 0.922). In conclusion, the performance of the clinical scores in a temperate environment were similar to previously published work from more extreme climates, however the performance varied widely depending on the score interpretation. Authors should justify their usage of a particular clinical score interpretation to improve clarity in publications.

Accurate tibial tunnel position in transtibial pullout repair for medial meniscus posterior root tears delays the progression of medial joint space narrowing.

PURPOSE: This study aimed to evaluate the association between the progression of medial joint space (MJS) narrowing, medial meniscus extrusion (MME) and clinical scores and the tibial tunnel position in pullout repairs for medial meniscus posterior root tears (MMPRTs). METHODS: This retrospective study examined 54 patients. Changes in MJS (ΔMJS), MME (ΔMME) and clinical scores and their relationship with the tibial tunnel position were evaluated using correlation coefficients. The distance from the anatomical to technical attachment position in the tibial tunnel position was measured in the anterior and medial directions, and the direct distance was measured using the Pythagorean theorem. RESULTS: The mean ΔMJS and ΔMME were 0.6 ± 0.8 and 1.3 ± 1.3 mm, respectively, and the mean anterior, medial and direct distances were 1.4 ± 2.3, 2.2 ± 1.7 and 3.4 ± 1.7 mm, respectively. ΔMJS had a significant positive correlation with the medial (r = 0.580, p < 0.001) and direct (r = 0.559, p < 0.001) distances, while ΔMME had a significant positive correlation with direct distance (r = 0.295, p = 0.030). Several clinical scores were significantly negatively correlated with these distances. CONCLUSION: In transtibial pullout repair for MMPRTs, accurate tibial tunnel position delayed the progression of MJS narrowing and MME, leading to improved clinical outcomes. The progression of MJS narrowing was associated with the mediolateral direction of the tibial tunnel position, while the clinical scores were associated with the anteroposterior direction of the tibial tunnel position. These findings indicate the need to orient the tip of the guide in a more posterolateral direction when creating the tibial tunnel. LEVEL OF EVIDENCE: Level IV.

Meniscal healing status after medial meniscus posterior root repair negatively correlates with a midterm increase in medial meniscus extrusion.

PURPOSE: The second-look arthroscopic score of pullout repair for medial meniscus posterior root tears (MMPRTs) is associated with contemporaneous clinical scores and progression of cartilage damage. However, the relationship among these scores, midterm clinical scores and magnetic resonance imaging (MRI) evaluations is unknown. The relationship between the second-look arthroscopic score at 1 year and the clinical scores or MRI at 3 years was evaluated. METHODS: Sixty-three patients were included. Medial meniscus extrusion (MME) was evaluated preoperatively and at 3 years postoperatively. Clinical scores were evaluated preoperatively, and 1 and 3 years postoperatively. Meniscal healing status was assessed using the semiquantitative second-look arthroscopic score at 1 year postoperatively. Correlation coefficients between patient characteristics, postoperative clinical scores or second-look arthroscopic score and the change in MME (ΔMME) were evaluated. Multiple regression analysis was performed on the ΔMME to evaluate the effects of patient characteristics and second-look arthroscopic scores. RESULTS: No significant correlation was observed between patient characteristics and ΔMME. In contrast, a significant correlation was found between the second-look arthroscopic score and ΔMME (p < 0.001) and visual analogue scale pain score (p = 0.016) at 3 years postoperatively. In the subitems of the second-look arthroscopic score, width (p < 0.001) and stability (p = 0.009) scores also showed significant correlations with ΔMME. Multiple regression analysis showed a significant association between the second-look arthroscopic score and ΔMME (p = 0.001). CONCLUSIONS: The second-look arthroscopic score at 1 year postoperatively correlated with the ΔMME and clinical score at 3 years postoperatively. Second-look arthroscopic scores predict midterm meniscal function after pullout repair of MMPRTs. LEVEL OF EVIDENCE: Level IV.

Reliability of the Harris Hip limping sub-score in patients undergoing total hip arthroplasty.

PURPOSE: In patients undergoing total hip arthroplasty, limping is a significant symptom, often assessed with the limping sub-score of the Harris Hip Score. However, the reliability of this sub-score has not been specifically investigated. The purpose of this study is to investigate the intra- and inter-rater reliability of this sub-score. METHODS: Thirty patients undergoing THA were recruited and performed a gait analysis before surgery and three months after surgery. In addition, 30 asymptomatic participants were included. In total, 90 visits were analysed in this study. The HHS limping sub-score was assessed for each visit using a video (front and back view side-by-side) of a ten metre walk at a self-selected speed. Two orthopaedic surgeons evaluated the limping of each video in two different grading sessions with a one week delay. To avoid recall bias, the patient's number identity was randomized and different for each grading session and each rater. The weighted Cohen's Kappa coefficient was used to quantify the intra- and inter-reliability. The reliability of three components was studied: the presence of limping, its severity, and the compensation type. RESULTS: For all components, the agreement for intra-rater reliability ranged from moderate to strong and from none to moderate for the inter-rater reliability. CONCLUSION: These results do not encourage the use of HHS-limping sub-score for data involving different raters in both clinical and research contexts. It calls for improved consensus on limping definitions or the creation of objective measures.

Unveiling the Complexity of Traumatic Brain Injury: Insights from Clinical Scoring Systems.

Krishnakumar M. Unveiling the Complexity of Traumatic Brain Injury: Insights from Clinical Scoring Systems. Indian J Crit Care Med 2024;28(3):193-195.

Longitudinal changes in medial meniscus extrusion and clinical outcomes following pullout repair for medial meniscus posterior root tears: a 3-year evaluation.

PURPOSE: We aimed to evaluate the longitudinal changes in medial meniscus extrusion (MME) and clinical scores at multiple time points up to 3 years after pullout repair for medial meniscus posterior root tears (MMPRTs). METHODS: This retrospective case series study included 64 patients who underwent pullout repair for MMPRTs and four MRI evaluations (preoperatively and at 3 months, 1 year, and 3 years postoperatively). MME was measured during the same time points. Clinical scores were assessed four times: preoperatively and at 1, 2, and 3 years postoperatively. Additionally, a multivariate analysis was performed on the change in MME (ΔMME) from the preoperative measurement point to 3 years postoperatively. RESULTS: The ΔMME per month from the preoperative measurement point to 3 months postoperatively, from 3 months to 1 year postoperatively, and from 1 to 3 years postoperatively were 0.30, 0.05, and 0.01 mm/month, respectively. All clinical scores significantly improved 3 years postoperatively (p < 0.001). In a multiple regression analysis for ΔMME from the preoperative measurement point to 3 years postoperatively, sex significantly affected the outcome (p = 0.039). CONCLUSION: Following pullout repair for MMPRTs with well-aligned lower extremities, although MME progression could not be entirely prevented, the rate of progression decreased over time, and clinical scores improved. In particular, MME progressed markedly during the first 3 months postoperatively. Additionally, sex had a significant influence on MME progression, suggesting that males may be able to expand the indications of pullout repair for MMPRTs.

Predicting clinical outcome of sulfur mustard induced ocular injury using machine learning model.

The sight-threatening sulfur mustard (SM) induced ocular injury presents specific symptoms in each clinical stage. The acute injury develops in all exposed eyes and may heal or deteriorate into chronic late pathology. Early detection of eyes at risk of developing late pathology may assist in providing unique monitoring and specific treatments only to relevant cases. In this study, we evaluated a machine-learning (ML) model for predicting the development of SM-induced late pathology based on clinical data of the acute phase in the rabbit model. Clinical data from 166 rabbit eyes exposed to SM vapor was used retrospectively. The data included a comprehensive clinical evaluation of the cornea, eyelids and conjunctiva using a semi-quantitative clinical score. A random forest classifier ML model, was trained to predict the development of corneal neovascularization four weeks post-ocular exposure to SM vapor using clinical scores recorded three weeks earlier. The overall accuracy in predicting the clinical outcome of SM-induced ocular injury was 73%. The accuracy in identifying eyes at risk of developing corneal neovascularization and future healed eyes was 75% and 59%, respectively. The most important parameters for accurate prediction were conjunctival secretion and corneal opacity at 1w and corneal erosions at 72 h post-exposure. Predicting the clinical outcome of SM-induced ocular injury based on the acute injury parameters using ML is demonstrated for the first time. Although the prediction accuracy was limited, probably due to the small dataset, it pointed out towards various parameters during the acute injury that are important for predicting SM-induced late pathology and revealing possible pathological mechanisms.

Clinical prediction score for prolonged length of hospital stay in aneurysmal subarachnoid hemorrhage.

BACKGROUND: Length of stay (LOS) is an important indicator of the optimization of health services and hospital financing efficiency in aneurysmal subarachnoid hemorrhage (aSAH) patients. The purpose of this study was to develop a scoring model to predict the LOS of patients with aSAH. METHOD: A clinical scoring was developed based on retrospectively collected data from the cerebral aneurysm registry of the National Brain Center Hospital, Jakarta, from January 2019 to June 2022. Multivariate logistic regression was used to determine the odds ratio for risk-adjusted prolonged LOS. LOS predictors were obtained based on the regression coefficients and converted into a point score model. RESULTS: Of the 209 aSAH patients observed, 117 patients had prolonged LOS (> 14 days of hospital stay). A clinical score was developed with a range of 0-7 points. Four variables were chosen as predictors of prolonged LOS: the presence of high-grade aSAH (1 point), aneurysm treatment (endovascular coiling: 1 point; surgical clipping: 2 points), cardiovascular comorbidities (1 point), and hospital-acquired pneumonia (3 points). The score showed good discrimination with an area under the receiving operating characteristics curve (AUC) of 0.8183 (SE 0.0278) and a p-value for the Hosmer-Lemeshow (HL) goodness-of-fit of 0.9322. CONCLUSION: This simple clinical score reliably predicted prolonged LOS in aneurysmal subarachnoid hemorrhage cases and may aid clinicians in improving patient outcomes and decreasing healthcare costs.

Diagnostic approach and grading scheme for canine allergic conjunctivitis.

BACKGROUND: In humans, allergic conjunctivitis is a well described disease. In contrast, allergic conjunctivitis has not received much attention from the veterinary community so far. Canine allergic conjunctivitis (cAC) is one of the possible manifestations associated with canine atopic dermatitis (cAD), being often underdiagnosed and undertreated. Our aim is to contribute to disease characterization and clinical stagingfor cAC severity. RESULTS: A retrospective observational study including 122 dogs that underwent a complete ophthalmological and dermatological examinations and diagnosed with allergic conjunctivitis was conducted. A total of six ophthalmic clinical signs were considered for disease characterization and clinical staging: conjunctival hyperemia, chemosis, ocular pruritus, epiphora, seromucoid to mucopurulent discharge and keratitis, classified from 0 (absent) to 3 (severe). Scores comprised between 1-5 were considered mild, 6-10 moderate and 11-18 severe. The majority of dogs (64%) presented with moderate cAC followed by 24% of mild stages and only 12% of severe presentations. The severity of allergic conjunctivitis was not correlated to sex or age at the time of diagnosis and all presented with a bilateral form of the disease. Chemosis (84%), hyperemia (83%) and ocular pruritus (79%) was observed in 55% of the cases. Seromucoid to mucopurulent discharge (62%) and epiphora (69%) were less frequent, with keratitis being the least encountered clinical sign (15%). The degree of keratitis showed a positive correlation with both severity and chronicity of cAC (rho = 0.21-0.29, p ≤ 0.02)). Severity of cAD and cAD were not significantly correlated (p-value = 0.4). DISCUSSION AND CONCLUSION: The triad hyperemia, chemosis and ocular pruritus, already known in human medicine to be a reliable way of diagnosing human allergic conjunctivitis, also proved to be important in cAC Mild forms of the disease may pass unnoticed, ocular pruritus being hard to assess in canine patients.The proposed standardized diagnostic approach and novel grading scheme for cAC may be of value for both veterinary ophthalmologists and dermatologists, as well as general practitioners.

Clinical score for early diagnosis of myotonic dystrophy type 2.

INTRODUCTION: Myotonic dystrophy type 2 (DM2) is a rare, multisystemic, autosomal dominant disease with highly variable clinical presentation. DM2 is considered to be highly underdiagnosed. OBJECTIVE: The aim of this study was to determine which symptoms, signs, and diagnostic findings in patients referred to neurological outpatient units are the most indicative to arouse suspicion of DM2. We tried to make a useful and easy-to-administer clinical scoring system for early diagnosis of DM2-DM2 early diagnosis score (DM2-EDS). PATIENTS AND METHODS: Two hundred ninety-one patients with a clinical suspicion of DM2 were included: 69 were genetically confirmed to have DM2, and 222 patients were DM2 negative. Relevant history, neurological, and paraclinical data were obtained from the electronic medical records. RESULTS: The following parameters appeared as significant predictors of DM2 diagnosis: cataracts (beta = 0.410, p < 0.001), myotonia on needle EMG (beta = 0.298, p < 0.001), hand tremor (beta = 0.211, p = 0.001), positive family history (beta = 0.171, p = 0.012), and calf hypertrophy (beta = 0.120, p = 0.043). In the final DM2-EDS, based on the beta values, symptoms were associated with the following values: cataracts (present 3.4, absent 0), myotonia (present 2.5, absent 0), tremor (present 1.7, absent 0), family history (positive 1.4, negative 0), and calf hypertrophy (present 1.0, absent 0). A cut-off value on DM2-EDS of 3.25 of maximum 10 points had a sensitivity of 84% and specificity of 81% to diagnose DM2. CONCLUSION: Significant predictors of DM2 diagnosis in the neurology outpatient unit were identified. We made an easy-to-administer DM2-EDS score for early diagnosis of DM2.

The NH-OSA score in prediction of clinically significant obstructive sleep apnea among the Thai population: derivation and validation studies.

BACKGROUND: Diagnosis of obstructive sleep apnea requires polysomnography which has limited availability. We aimed to develop and validate a risk score in predicting clinically significant OSA among the Thai population. METHODS: We reviewed polysomnographic studies performed in adults diagnosed with OSA in King Chulalongkorn Memorial Hospital from 2017 to 2019. 1798 and 450 patients were randomly enrolled in development and validation cohorts, respectively. A risk score was developed using multiple factor analysis and logistic regression. The NH-OSA score was externally validated at the Bangkok Christian Hospital. We compared its performance to existing screening scores (STOP-BANG, Berlin Questionnaire, Epworth Sleepiness Scale (ESS), and NoSAS score). RESULT: The NH-OSA score allocates 1 point for having neck circumference ≥ 13 inches (in women) or 15 inches (in men), 4 points for the presence of hypertension, 3 or 5 or 7 points for having a body mass index of 23-24.9, 25-30, ≥ 30 kg/m2, respectively, 9 points for the presence of moderate or severe snoring, and 5 points for age ≥ 40 years. With a cutoff value at 14 points, the sensitivity and specificity were 82.1% and 68.7%, respectively. The AUC was 0.75 (0.73-0.78). Both internal and external validation study revealed high AUC of 0.74 (0.68-0.80) and 0.75 (0.60-0.90), respectively. These were greater when compared to STOP-BANG, Berlin Questionnaire, ESS, and NoSAS score. CONCLUSION: NH-OSA is a newly developed tool which has good performance in predicting clinically significant OSA with high validity among the Thai population. It could help screen patients at risk of OSA for further investigation.

Determining clinical predictors to identify non-specific abdominal pain and the added value of laboratory examinations: A prospective derivation study in a paediatric emergency department.

AIM: To develop a model to discriminate non-specific abdominal pain (NSAP) from organic pain in the paediatric emergency department (PED) and evaluate the added value of laboratory markers. METHODS: Prospective cohort study in an urban French PED including all patients aged ≥4 years with abdominal pain between November 2020 and May 2021. The outcome was the discrimination between NSAP (patients coded to have only "pain" or "constipation") and organic pain (all other diagnoses) using stepwise backward multivariate logistic regression method with bootstrap resampling. RESULTS: The study enrolled 246 patients. Overall, 163 patients (66.2%) had NSAP. Four variables associated with organic pain: pain in the epigastric region (OR 0.48 [0.23-0.99]), worsening pain (0.57 [0.32-0.99]), pain migration (0.42 [0.17-0.99]) and vomiting (0.47 [0.26-0.84]) were integrated in a clinical model. To discriminate NSAP with a probability of 65%, model sensitivity was 71.8% (64.9-78.7), specificity was 53.0% (42.3-63.7), and the Net Benefit (NB) was 15.4%. White Blood Count and C-reactive protein results improved discriminative capacity of the model (AUC 0.708 [0.643-0.773] vs. 0.654 [0.585-0.723], p = 0.01) with a supplementary NB of 12%. Patient follow-up showed 95% diagnostic accuracy. CONCLUSION: This study reveals a four-clinical predictor model with a NB of 15% in predicting NSAP. Validation studies are necessary.

Increased quadriceps muscle strength after medial meniscus posterior root repair is associated with decreased medial meniscus extrusion progression.

BACKGROUND: This study aimed to assess quadriceps muscle strength after medial meniscus (MM) posterior root repair and determine its relationship with clinical scores and MM extrusion (MME). METHODS: Thirty patients who underwent pullout repair for MM posterior root tear and were evaluated for quadriceps muscle strength preoperatively and at 1 year postoperatively were included in this study. Quadriceps muscle strength was measured using the Locomo Scan-II instrument (ALCARE, Tokyo, Japan). MME and clinical scores (i.e., Knee Injury and Osteoarthritis Outcome Score [KOOS], International Knee Documentation Committee score, Lysholm score, Tegner score, and visual analog scale pain score) were evaluated preoperatively and at 1 year postoperatively, and second-look arthroscopy was performed at 1 year postoperatively. Wilcoxon's signed-rank test was used to compare each measure pre- and postoperatively. Pearson's correlation coefficient was used to assess the correlation with quadriceps muscle strength values. Multiple regression analysis was performed to identify factors associated with the change in MME (ΔMME). RESULTS: Second-look arthroscopy confirmed continuity of the posterior root in all patients. The quadriceps muscle strength measured at 1 year postoperatively (355.1 ± 116.2 N) indicated significant improvement relative to the quadriceps muscle strength measured preoperatively (271.9 ± 97.4 N, p < 0.001). The MME at 1 year postoperatively (4.59 ± 1.24 mm) had progressed significantly relative to the MME preoperatively (3.63 ± 1.01 mm, p < 0.001). The clinical scores at 1 year postoperatively were improved significantly relative to the scores preoperatively (p < 0.001). The postoperative quadriceps muscle strength was correlated with ΔMME (correlation coefficient = -0.398, p = 0.030), and the change in quadriceps muscle strength was correlated with the KOOS-Quality of Life (correlation coefficient = 0.430, p = 0.018). Multiple regression analysis showed that the postoperative quadriceps muscle strength had a significant effect on ΔMME even when the body mass index and time from injury to surgery were included. CONCLUSIONS: After MM posterior root repair, patients with greater quadriceps muscle strength showed less MME progression. In addition, patients with greater improvement in quadriceps muscle strength had better clinical scores; therefore, continued rehabilitation aimed at improving quadriceps muscle strength after MM posterior root repair is recommended. LEVEL OF EVIDENCE: IV.

A new clinical score to predict the possibility of stroke patients receiving intravenous thrombolysis.

BACKGROUND: We aimed to develop and validate a clinical score to identify the factors which contribute to variation in, and influence clinician's decision-making about treating acute ischemic stroke (AIS) patients with Intravenous thrombolysis (IVT). METHODS: We retrospectively included consecutive AIS patients within 4.5 hours after onset in the emergency department (ED), who were admitted to a comprehensive stroke center in Jiangsu province, China. The patients were randomly divided into derivation (60%) and validation data sets (40%) to develop and validate the clinical score. Multivariable stepwise forward logistic regression was performed to identify the independent predictors of IVT offering in the derivation data. RESULTS: Out of 526 included patients, 418 patients received thrombolytic therapy. Nine patient factors were associated with the likelihood of thrombolysis (age, time to hospital, National Institute of Health stroke scale (NIHSS) score, great vessel, facial paralysis, dizziness, headache, history of stroke, and neutrophil ratio). The c-statistics of the Intravenous Thrombolysis Score in the derivation cohort (n= 316) and validation cohort(n = 210) were 0.795 and 0.751, respectively. The performance of the scoring model was validated with a calibration plot showing good predictive accuracy for the scores in the derivation data (calibrated P = 0.861) and validation data (calibrated P = 0.876). CONCLUSIONS: The Intravenous Thrombolysis Score for predicting the possibility of offering IVT to AIS patients indicates that clinicians differ in their thresholds for the treatment across a number of patient-related factors, which will be linked to training professional development programmes and address the impact of non-medical influences on decision-making using evidence-based strategies.

Pre-Test Probability Assessment and d-Dimer Based Evaluation in Patients with Previous Acute Aortic Syndrome.

Background and Objectives. Acute aortic syndromes (AASs) are emergencies burdened by high morbidity and mortality. Guideline-recommended diagnostic workup is based on pre-test probability assessment (PPA) and d-dimer testing. However, the performance of PPA and d-dimer has never been studied in individuals with previous AAS (pAAS), which represent a challenging population. Materials and Methods. We analyzed a registry of patients with pAAS evaluated in two Emergency Departments (EDs) for suspected novel AAS (nAAS). Enrolment criteria were history of pAAS and the presence of truncal pain, syncope or perfusion deficit. All patients underwent advanced imaging. Clinical data were registered prospectively and PPA was performed by applying the aortic dissection detection (ADD) and an aorta simplified (AORTAs) score. Results. A total of 128 patients were enrolled, including 77 patients with previous Stanford type A aortic dissection and 45 patients with previous Stanford type B aortic dissection. The final diagnosis was nAAS in 40 (31%) patients. Clinical variables associated with nAAS were: aortic valve disease, thoracic aortic aneurysm, severe pain, sudden pain, ripping/tearing pain and hypotension/shock. ADD score ≥ 2 had a sensitivity of 65% and a specificity of 83% for nAAS; AORTAs score ≥ 2 had a sensitivity of 48% and a specificity of 88%. d-dimer (cutoff ≥ 500 ng/mL or age-adjusted cutoff) had a sensitivity of 97% and a specificity of 13%/14.7%, for diagnosis of nAAS. Patients that were candidates for guideline-compliant PPA/d-dimer integrated rule-out were: 5 (4.9%) with ADD ≤ 1/d-dimer and 8 (7.8%) with AORTAs ≤ 1/d-dimer < age-adjusted cutoff. None of them had a nAAS. Conclusions. Patients with pAAS evaluated in the ED for red-flag symptoms showed intermediate-to-high pre-test probability of nAAS. The ADD score had lower sensitivity and specificity than in unselected patients. d-dimer, alone and integrated with PPA, was highly sensitive for nAAS, but very unspecific. PPA/d-dimer integrated strategies are unlikely to significantly reduce the number of patients with pAAS undergoing advanced imaging.

AutoScore-Ordinal: an interpretable machine learning framework for generating scoring models for ordinal outcomes.

BACKGROUND: Risk prediction models are useful tools in clinical decision-making which help with risk stratification and resource allocations and may lead to a better health care for patients. AutoScore is a machine learning-based automatic clinical score generator for binary outcomes. This study aims to expand the AutoScore framework to provide a tool for interpretable risk prediction for ordinal outcomes. METHODS: The AutoScore-Ordinal framework is generated using the same 6 modules of the original AutoScore algorithm including variable ranking, variable transformation, score derivation (from proportional odds models), model selection, score fine-tuning, and model evaluation. To illustrate the AutoScore-Ordinal performance, the method was conducted on electronic health records data from the emergency department at Singapore General Hospital over 2008 to 2017. The model was trained on 70% of the data, validated on 10% and tested on the remaining 20%. RESULTS: This study included 445,989 inpatient cases, where the distribution of the ordinal outcome was 80.7% alive without 30-day readmission, 12.5% alive with 30-day readmission, and 6.8% died inpatient or by day 30 post discharge. Two point-based risk prediction models were developed using two sets of 8 predictor variables identified by the flexible variable selection procedure. The two models indicated reasonably good performance measured by mean area under the receiver operating characteristic curve (0.758 and 0.793) and generalized c-index (0.737 and 0.760), which were comparable to alternative models. CONCLUSION: AutoScore-Ordinal provides an automated and easy-to-use framework for development and validation of risk prediction models for ordinal outcomes, which can systematically identify potential predictors from high-dimensional data.

AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data.

BACKGROUND: Medical decision-making impacts both individual and public health. Clinical scores are commonly used among various decision-making models to determine the degree of disease deterioration at the bedside. AutoScore was proposed as a useful clinical score generator based on machine learning and a generalized linear model. However, its current framework still leaves room for improvement when addressing unbalanced data of rare events. METHODS: Using machine intelligence approaches, we developed AutoScore-Imbalance, which comprises three components: training dataset optimization, sample weight optimization, and adjusted AutoScore. Baseline techniques for performance comparison included the original AutoScore, full logistic regression, stepwise logistic regression, least absolute shrinkage and selection operator (LASSO), full random forest, and random forest with a reduced number of variables. These models were evaluated based on their area under the curve (AUC) in the receiver operating characteristic analysis and balanced accuracy (i.e., mean value of sensitivity and specificity). By utilizing a publicly accessible dataset from Beth Israel Deaconess Medical Center, we assessed the proposed model and baseline approaches to predict inpatient mortality. RESULTS: AutoScore-Imbalance outperformed baselines in terms of AUC and balanced accuracy. The nine-variable AutoScore-Imbalance sub-model achieved the highest AUC of 0.786 (0.732-0.839), while the eleven-variable original AutoScore obtained an AUC of 0.723 (0.663-0.783), and the logistic regression with 21 variables obtained an AUC of 0.743 (0.685-0.801). The AutoScore-Imbalance sub-model (using a down-sampling algorithm) yielded an AUC of 0.771 (0.718-0.823) with only five variables, demonstrating a good balance between performance and variable sparsity. Furthermore, AutoScore-Imbalance obtained the highest balanced accuracy of 0.757 (0.702-0.805), compared to 0.698 (0.643-0.753) by the original AutoScore and the maximum of 0.720 (0.664-0.769) by other baseline models. CONCLUSIONS: We have developed an interpretable tool to handle clinical data imbalance, presented its structure, and demonstrated its superiority over baselines. The AutoScore-Imbalance tool can be applied to highly unbalanced datasets to gain further insight into rare medical events and facilitate real-world clinical decision-making.