Cut-off Value Research Articles

Association between Hematological Parameters and Severity of COVID-19 disease

Background This study aimed to determine the relationships between hematological parameters- hemoglobin, Total Leucocyte Counts (TLC), platelet counts, Absolute Neutrophil Counts (ANC), Absolute Lymphocyte Counts (ALC), Neutrophil Lymphocyte Ratio (NLR), Systemic Immune Inflammatory Index (SII), Neutrophil Monocyte Ratio (NMR), Platelet Lymphocyte Ratio (PLR) and the severity of COVID-19 disease and their use in predicting severity of COVID-19 disease. Methods and Material This was a prospective, observational, single-center study of 573 symptomatic adult inpatients of COVID 19 admitted to our tertiary care center. Statistical analysis used The above-mentioned hematological parameter levels were noted and compared between the two categories of COVID-19 disease, namely non-severe and severe COVID-19 using logistic regression methods. Their cut-off values were detected using the ROC curve. Results The median TLC, ANC, NLR, SII, NMR, PLR were notably higher in patients with severe COVID-19 than in those with non-severe COVID-19. Logistic regression analysis showed that NMR (OR=1.029, p=0.006) and ALC (OR=0.999, p=0.002) were statistically significant independent predictors of COVID-19 severity. Conclusions The hematological parameters mentioned, can be used for predicting severe COVID-19 disease at admission. ALC and NMR levels could be used as hematological markers to predict severity of COVID-19 in adult patients with their cut off values being < 1105 cells/cubic millimeter and > 10.434 respectively.

Hypernatremia is associated with mortality in severe elderly sepsis patients

Objective To explore the relationship between hypernatremia and 28-day mortality in elderly sepsis patients. Methods A total of 179 elderly patients (age ≥65 years) with elevated serum sodium admitted to the Department of Critical Care Medicine of Nanjing Hospital affiliated with Nanjing Medical University from September 2021 to September 2022 were included in this retrospective observational study. The clinical data of all patients were collected, and the patients were divided into septic group and nonseptic groups according to the Sepsis 3.0 definition. The clinical features, acute physiological and chronic health II score (APACHE II score), mechanical ventilation time, serum sodium value and duration of serum sodium elevation were compared between the two groups. ROC curves were drawn to evaluate the predictive value of each index on the prognosis of sepsis patients, and Kaplan‒Meier survival analysis was carried out on patients with different serum sodium peaks. Results (1) The changes in serum sodium within 48 hours after admission in the sepsis group were small and statistically significant compared with those in the nonsepsis group (P = 0.039); however, the serum sodium elevation duration was longer (P = 0.018). (2) Compared with nonseptic patients, the 7-day mortality of septic patients was higher (15.8 vs. 7.7, P<0.001). The 28-day mortality of septic patients was higher than that of nonseptic patients, but there was no significant difference between the two groups (P = 0.086). (3) The serum sodium level in the sepsis group was higher than that in the nonsepsis group on the 1st, 3rd, 5th and 7th days (P<0.001). There was no significant difference in mechanical ventilation time or duration of stay in the ICU between the two groups. (4) The ROC curve analysis showed that the peak value of serum sodium had predictive value for the prognosis severity of elderly patients with sepsis. The area under the curve (AUC) was 0.753, the 95% confidence interval (95% CI) was 0.639~0.867, and the best cut-off value was 154.9 mmol/L. (5) According to the best cut-off value of the serum sodium peak, the septic patients were divided into two groups: the peak value of serum sodium was ≥154.9 mmol/L (group A), and the peak value of serum sodium was <154.9 mmol/L (group B). Among them, the case fatality rate was higher at 7 days and 28 days when the peak value of serum sodium was ≥154.9 mmol/L (group A) (22.0% vs. 8.6%); the χ2 value was 35.379, P<0.05; 75.6% vs. 37.1%, χ2 = 14.21, P = 0.003). There was no significant difference in mechanical ventilation time or duration of stay in the ICU between the two groups. (6) Kaplan‒Meier survival analysis showed that the median survival time of patients with a serum sodium peak ≥154.9 mmol/L (group A) was significantly shorter than that of patients with a serum sodium peak < 154.9 mmol/L (group B) (16.7±1.4 d vs. 24.8±1.2 d, P <0.05). Conclusions The serum sodium increase in elderly sepsis patients lasts for a long time, and the serum sodium fluctuation is relatively small. The serum sodium peak value has predictive value for 28-day mortality.

Machine learning for epithelial ovarian cancer platinum resistance recurrence identification using routine clinical data

BackgroundMost epithelial ovarian cancer (EOC) eventually develops recurrence. Identification of high-risk patients can prompt earlier intervention and improve long-term outcomes. We used laboratory and clinical data to create models based on machine learning for EOC platinum resistance recurrence identification.MethodsThis study was designed as a retrospective cohort analysis. Initially, we identified 1,392 patients diagnosed with epithelial ovarian cancer who underwent platinum-based chemotherapy at Yunnan Cancer Hospital between January 1, 2012, and June 30, 2022. We collected data on the patients’ clinicopathologic characteristics, routine laboratory results, surgical information, details of chemotherapy regimens, and survival outcomes. Subsequently, to identify relevant variables influencing the recurrence of platinum resistance, we screened thirty potential factors using two distinct variable selection methods: Lasso regression and multiple logistic regression analysis. Following this screening process, five machine learning algorithms were employed to develop predictive models based on the selected variables. These included decision tree analysis (DTA), K-Nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and eXtreme gradient boosting (XGBoost). The performance of these models was compared against that of traditional logistic regression. To ensure robust internal validation and facilitate comparison among model performance metrics, a five-fold cross-validation method was implemented. Key performance indicators for the models included the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and average accuracy. Finally, we will visualize these models through nomograms, decision tree diagrams, variable importance plots, etc., to assist clinicians in their practice.ResultsMultiple logistic regression analysis identified eight variables associated with platinum resistance recurrence. In the lasso regression, seven variables were selected. Based on the findings from both Lasso regression and multiple logistic regression analysis, models were developed using these 7 and 8 factors. Among these, the XGBoost model derived from multiple logistic regression exhibited superior performance and demonstrated good discrimination during internal validation, achieving an AUC of 0.784, a sensitivity of 0.735, a specificity of 0.713, an average accuracy of 80.4%, with a cut-off value set at 0.240. Conversely, the LR model based on lasso regression yielded commendable results as well; it achieved an AUC of 0.738, a sensitivity of 0.541, a specificity of 0.836, with a cut-off value established at 0.154 and an accuracy rate of 79.6%. Finally, we visualized both models through nomograms to illustrate the significance of each variable involved in their development.ConclusionsWe have successfully developed predictive models for platinum-resistant recurrence of epithelial ovarian cancer, utilizing routine clinical and laboratory data. Among these models, the XGBoost model—derived from variables selected through multiple logistic regression—demonstrated the best performance. It exhibited high AUC values and average accuracy during internal validation, making it a recommended tool for clinical use. However, due to variations in time and context, influencing factors may change over time; thus, continuous evolution of the model is necessary. We propose a framework for this ongoing model adaptation.

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

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

Prognostic value of neutrophil to lymphocyte ratio and lymphocyte counts before durvalumab consolidation after radio-chemotherapy in locally advanced non-small cell lung cancer

BackgroundDurvalumab, an anti-PD-L1 immune checkpoint inhibitor, after radio-chemotherapy (RCT) has changed the management of locally advanced non-small cell lung cancer (LA NSCLC). A series of retrospective studies have investigated different cut-off of lymphocyte count (LyC) and neutrophil-to-lymphocyte ratio (NLR) to predict survival in LA NSCLC. None of these studies has validated their threshold in an independent group of patients. We wanted to assess the OS prognostic value of NLR and LyC in patients with LA NSCLC treated by RCT and durvalumab, with threshold determination and their validation in an external cohort.MethodsPatients were enrolled in four institutions between Oct. 2017 and Jan. 2022. Pre durvalumab LyC, neutrophils count (NC) and NLR were collected. To define NLR and LyC cut-off value predicting survival event, time dependent Receiver Operating Characteristics (ROC) curves was performed. Survival outcomes were estimated by the Kaplan-Meier method and differences were compared using univariate and multivariate Cox proportional hazard models.ResultsWe included 76 patients in the training set and 85 in the test set. The best cut off were 2,94 for NLR and 0,61 G/l for LyC to predict OS in the training set. For patients with NLR > 2,94, univariate analysis showed no significant deterioration in OS in either the training set (p = 0,066) or the test set (p = 0,12). Patients with LyC > 0,61 G/L, in univariate analysis, had longer OS in training set (p = 0,030) and in test set (p = 0,0062). This OS increase was not found in multivariate analysis (p = 0,057) in training set but was confirmed in test set (0,039).ConclusionLyC > 0,61 G/l is associated with longer OS for LA NSCLC patient’s treated with RCT and durvalumab in univariate analysis. In this context, a particular expectation for organs at risk sparing during RT to avoid lymphopenia seems important.Trial registrationRetrospectively registered.

Diagnostic utility of testosterone priming prior to dynamic tests to differentiate constitutional delay in puberty from isolated hypogonadotropic hypogonadism in boys

BackgroundDifferentiation between isolated hypogonadotropic hypogonadism (IHH) and constitutional delay in puberty (CDP) throughout adolescence can be challenging for doctors. This study examines the withdrawal effects of short-term, low-dose testosterone treatment (testosterone priming) on the ability of dynamic testing to distinguish between CDP and IHH based on activation of the hypothalamo-pituitary–testicular axis.MethodsA case–control study included 20 boys with delayed puberty (group A) and 20 patients with IHH (group B). Both groups underwent Triptorelin and human chorionic gonadotropin (hCG) stimulation tests before and 2 months after testosterone injections (100 mg) intramuscularly every 4 weekly for 3 months.ResultsThe triptorelin-stimulated 4-h LH with a cutoff of 2.4 IU/L and the hCG-stimulated testosterone with a cutoff of 1.160 ng/mL had sensitivities of 65% each, and specificities of 90% and 95%, respectively, to diagnose CDP. After testosterone withdrawal, the cut-off values for 4-h LH were 8.850 IU/L and 3.190 ng/mL for hCG-stimulated testosterone. Basal inhibin B > 88.25 pg/ml was found to be a differentiating factor in diagnosing CDP after testosterone withdrawal.Conclusionsfollowing the withdrawal of testosterone therapy, Inhibin B levels or 4-h stimulated LH are the most effective discriminant assays to distinguish CDP from IHH.

Averaged Oxygen Desaturation Improves the Prognostic Value of the Six-Minute Walk Test in Elderly Patients with Heart Failure

Background: Heart failure (HF) is a major cause of hospitalization, and exercise capacity is a key prognostic marker. The six-minute walk test (6MWT) is widely used to assess exercise capacity, but six-minute walk distance (6MWD) varies among individuals, especially the elderly.Aim: This study aimed to assess the hypothesis that ΔSpO₂-Ex, the average oxygen desaturation during the 6MWT, could enhance the prognostic value of 6MWD in elderly HF patients for cardiovascular risk prediction.Methods: In this single-center, prospective observational study, 55 patients aged ≥ 65 years with acute HF were evaluated before discharge. Patients were divided into small and large ΔSpO₂-Ex groups and short and long 6MWD groups based on cut-off values of 6.7% and 220 m, respectively, obtained from the Receiver Operating Characteristics curve analysis. Patients were followed for one year to assess major adverse cardiovascular events, including rehospitalization for heart failure or cardiovascular death.Results: The mean ΔSpO₂-Ex was 5.8 ± 4.3%, and the mean 6MWD was 237.5 ± 106.7 m. Patients with large ΔSpO₂-Ex had significantly higher event rates (HR 6.66, p < 0.001), while those with short 6MWD had HR of 2.40 (p = 0.03). Combining ΔSpO₂-Ex with 6MWD improved predictive accuracy (AUC 0.78) compared to either marker alone (AUC 0.72 for ΔSpO₂-Ex and 0.62 for 6MWD). Importantly, patients with both large ΔSpO₂-Ex and short 6MWD had the highest event rates, indicating the additive prognostic value of combining both markers.Conclusion: ΔSpO₂-Ex is a complementary marker to 6MWD, improving risk stratification in elderly HF patients.

Optimal Number of Replications for Obtaining Stable Dynamic Fit Index Cutoffs

Factor analysis is commonly used in behavioral sciences to measure latent constructs, and researchers routinely consider approximate fit indices to ensure adequate model fit and to provide important validity evidence. Due to a lack of generalizable fit index cutoffs, methodologists suggest simulation-based methods to create customized cutoffs that allow researchers to assess model fit more accurately. However, simulation-based methods are computationally intensive. An open question is: How many simulation replications are needed for these custom cutoffs to stabilize? This Monte Carlo simulation study focuses on one such simulation-based method—dynamic fit index (DFI) cutoffs—to determine the optimal number of replications for obtaining stable cutoffs. Results indicated that the DFI approach generates stable cutoffs with 500 replications (the currently recommended number), but the process can be more efficient with fewer replications, especially in simulations with categorical data. Using fewer replications significantly reduces the computational time for determining cutoff values with minimal impact on the results. For one-factor or three-factor models, results suggested that in most conditions 200 DFI replications were optimal for balancing fit index cutoff stability and computational efficiency.

Comparison of the ability between dual‐energy X‐ray absorptiometry and bioelectrical impedance analysis for diagnosing low skeletal muscle mass and sarcopenia in patients with chronic liver disease

AbstractBackground and AimSarcopenia and osteoporosis adversely impact the clinical outcomes of patients with chronic liver disease (CLD). The Japan Society of Hepatology (JSH) sarcopenia criteria utilize bioelectrical impedance analysis (BIA) for assessing muscle mass rather than dual‐energy X‐ray absorptiometry (DXA), which can simultaneously diagnose these comorbidities. We investigated the correlations and interchangeability between the appendicular skeletal muscle mass index (ASMI) values determined using BIA and DXA and evaluated the diagnostic ability of DXA for sarcopenia and osteosarcopenia in patients with CLD.MethodsThis cross‐sectional study included 173 patients with CLD. Sarcopenia was defined as low ASMIBIA according to the JSH and Asian Working Group for Sarcopenia (AWGS) criteria (ASMIBIA cutoff) or low ASMIDXA according to the AWGS criteria (ASMIDXA cutoff) and low handgrip strength. For women, a provisional cutoff value was set for ASMIDXA using the ASMIBIA cutoff (ASMIDXA‐altered cutoff).ResultsWe found that ASMIBIA and ASMIDXA were significantly correlated (r = 0.921; P < 0.001). The Bland–Altman plots demonstrated substantial agreement between ASMIBIA and ASMIDXA, with a mean difference of 0.0116 kg/m2. The prevalence rates of sarcopenia and osteosarcopenia diagnosed using the ASMIBIA cutoff were 26.0% and 17.3%, respectively. The kappa coefficients for the prevalence of sarcopenia and osteosarcopenia were 0.759 and 0.775 between ASMIBIA cutoff and ASMIDXA cutoff and 0.780 and 0.806 between ASMIBIA cutoff and ASMIDXA‐altered cutoff, respectively.ConclusionsThe utilization of DXA can facilitate the comprehensive assessment and management of musculoskeletal comorbidities in patients with CLD.

Reliability and utility of blood glucose levels in the periodontal pockets of patients with type 2 diabetes mellitus: a cross-sectional study

Background Several studies have measured gingival blood glucose (GBG) levels, but few have confirmed systematic bias using Bland–Altman analysis. This study compared the effectiveness of GBG levels with that of fingertip blood glucose (FTBG) levels using Bland–Altman and receiver operating characteristic (ROC) analyses. Methods A total of 15 healthy volunteers and 15 patients with type 2 diabetes were selected according to inclusion and exclusion criteria. Each group comprised eight male and seven female participants. The GBG and FTBG levels were measured using a self-monitoring blood glucose device after periodontal examination. Pearson’s product‒moment correlation and simple linear regression analyses were performed. In addition, Bland‒Altman analysis was also performed to assess the degree of agreement between the two methods. ROC analysis was conducted to determine the sensitivity, specificity, and cutoff values for patients with diabetes. The area under the ROC curve (AUC) was used to identify significant differences. Results The mean GBG and FTBG levels were 120 ± 44.8 mg/dL and 137 ± 45.1, respectively, for the whole sample. The mean GBG and FTBG levels were 145 ± 47.2 mg/dL and 163 ± 49.1, respectively, in the diabetes group. The mean GBG and FTBG levels in the nondiabetes group were 95.3 ± 25.2 and 111 ± 18.8, respectively. Patients with diabetes were more likely to have a probing pocket depth (PPD) of ≥4 mm at the sampled site. Pearson’s product‒moment correlation and simple linear regression analyses revealed a significant correlation between the GBG and FTBG measurements. Bland–Altman analysis revealed that GBG and FTBG measurements differed significantly among all participants; however, no significant differences were observed among the patients with diabetes (mean difference (MD) ± standard deviation (SD) = −18.1 ± 34.2, 95% confidence interval (CI) [−37.0 to 0.88]) or among the participants with a PPD of ≥4 mm (MD ± SD = −15.2 ± 30.4, 95% CI [−30.8 to 0.43]). The sensitivity, specificity, and cutoff values of the GBG measurements for detecting diabetes were 80%, 93%, and 123.5 mg/dL, respectively. The sensitivity, specificity, and cutoff values of the FTBG measurements for detecting diabetes were 73%, 87%, and 134.0 mg/dL, respectively. No significant differences were observed between the AUCs (0.078, 95% CI [−0.006 to 0.161]). Conclusions The GBG measurements aligned with the FTBG measurements in the patients with diabetes and among the participants with a PPD of ≥4 mm. Patients with diabetes were more likely to have a PPD of ≥4 mm at the sampled site, GBG levels can be used to screen for type 2 diabetes in dental clinics.

Keratoconus Detection in High-Astigmatism Pediatric Patients: Optimal Pentacam Indices and Cutoff Points.

To assess the accuracy of various Pentacam indices in distinguishing keratoconus (KC) in pediatric patients with high astigmatism and to establish appropriate cutoff values. This prospective multicenter cross-sectional study included 312 eyes from 167 patients aged 6 to 18 years (mean age, 13.1 ± 3.2 years) evaluated with Oculus Pentacam HR. Patients were categorized into 4 groups: KC, forme fruste keratoconus, astigmatism greater than 2 diopters (Cyl2D), and control. A subgroup of Cyl2D comprised patients with astigmatism greater than 4 diopters (Cyl4D). Twenty-three Pentacam indices were analyzed, and receiver operating characteristic curves determined optimal cutoff points, sensitivity, and specificity. The best indices for distinguishing KC from Cyl2D were high-order aberration root mean square of the anterior corneal surface (area under the receiver operating characteristic curve 0.987), Belin/Ambrosio enhanced ectasia total derivation (0.971), index of vertical asymmetry (0.971), average pachymetric progression index (0.962), maximum Ambrosio relational thickness (0.960), posterior elevation (0.952), and anterior elevation (0.948). The accuracy of these indices was highest in the control group and lowest in the Cyl4D group. Area under the receiver operating characteristic curve was significantly lower for fruste keratoconus than KC. Optimal cutoff values were higher for astigmatic patients than for those with no refractive error. Most indices effectively distinguished between KC and normal pediatric patients. For individuals with high astigmatism, we suggest focusing on specific indices such as high-order aberration root mean square, Belin/Ambrosio enhanced ectasia total derivation value, maximum Ambrosio relational thickness, average pachymetric progression index, and index of vertical asymmetry. Optimal cutoff points for these patients were higher than those for nonastigmatic children and differed from adult populations.

Evaluation of Fungitell (1,3)-β-D-glucan assay in tear samples for rapid diagnosis of fungal keratitis.

Fungal keratitis (FK) is a serious suppurative and ulcerative corneal infection leading to blindness and vision loss. Rapid diagnosis of FK can contribute to prompt clinical management with early recovery. The study aimed to standardize the detection of (1,3)-β-D-glucan (BDG) and establish the diagnostic cut-off concentration in tears of suspected FK patients along with non-infected controls. This prospective multicentric study was conducted between the period of August 2022 and April 2024. Samples were collected from three tertiary eye-care facilities across India. All suspected FK patients were enrolled in the study. Prior to tear collection, the eye and eyelid were gently cleansed using sterile normal saline (NS) and lint-free tissue paper. Subsequently, 50 µL of sterile NS was instilled into the eye, followed by tear sample collection after 60 s using sterile fine microtips. Tear samples were collected from the contralateral eyes of the FK patients, and those from healthy volunteers served as controls. The concentration of BDG in tears in varying dilutions was quantitatively measured using the Fungitell Assay Kit (Associates of Cape Cod, East Falmouth, Massachusetts). A total of 53 tear samples were analyzed at 1:10 and 1:20 dilutions. The receiver operating curve revealed an area under the curve (AUC) of 0.919 for the 1:10 dilution, with a cut-off value of 123 pg/mL, yielding a sensitivity of 100% and specificity of 84.85%. The corresponding Youden Index was 0.798. At the 1:20 dilution, the AUC was 0.898 with a cut-off of 84 pg/mL, achieving a sensitivity of 70% and specificity of 96.88% with a Youden Index of 0.670. Given the higher specificity at the 1:20 dilution, it was further validated in 145 tear samples. The validation cohort demonstrated a sensitivity of 95.56%, specificity of 83%, positive predictive value (PPV) of 71.67%, negative predictive value (NPV) of 97.65%, and diagnostic odds ratio of 112.4. Notably, a significantly higher BDG concentration (P < 0.0001) was observed in infected tear samples compared to controls (270.6 ± 128.5 vs 37.31 ± 31.32). Detection of BDG in tear samples is a new, non-invasive, and rapid technique showing excellent performance and can be effectively implemented for diagnosing FK in laboratories.

Prevalence of self-reported symptoms of diabetic autonomic dysfunction in the North Denmark Region: a population-based survey.

Diabetic autonomic neuropathy is a severe complication of diabetes, estimated to affect up to 44% in type 1 diabetes (T1D) and 73% in type 2 diabetes (T2D) based on clinical studies. Currently, the assessment of diabetic autonomic neuropathy is not implemented in Denmark's clinical guidelines, complicating the estimation of the true prevalence. Thus, this study investigated the prevalence of self-reported symptoms of autonomic dysfunction in people living with diabetes in the North Denmark Region using the Composite Autonomic Symptoms Score (COMPASS)-31 questionnaire. In 2022, all adults with T1D or T2D in the North Denmark Region (n = 29,155) were identified using The National Health Insurance Service Registry and invited to an online survey including the Danish version of COMPASS-31. The prevalence and associated 95% confidence intervals (CI) for symptomatic autonomic dysfunction were determined using a cut-off value of 16. In total, 7,377 completed COMPASS-31, of which 82.4% reported having T2D and 13.7% T1D. The prevalence of symptomatic autonomic dysfunction was 36.8% (95% CI: 34-40) after a median of 26 years with diabetes for T1D and 44.2% (95% CI: 43-45) after a median of 10 years for T2D. Pupillary and orthostatic intolerance were the most frequent moderate to severe symptoms, respectively (38.4% and 24.0% in T1D and 32.8% and 26.3% in T2D). Symptoms of autonomic dysfunction are very common in individuals with diabetes living in the North Denmark Region, emphasizing the unmet need for regular testing to increase awareness and allow for adequate management, ultimately reducing the morbidity of diabetes.

Determining Maximal Outcome Improvement Thresholds for Patient-Reported Outcome Measures After Primary ACL Reconstruction: A Mid-Term Follow-up Study Using the Anchor Method.

The clinical interpretation of patient-reported outcome measures (PROMs) after anterior cruciate ligament (ACL) reconstruction (ACLR) can be challenging. This study aimed to establish the clinical relevance of PROMs by determining maximal outcome improvement (MOI) thresholds at mid-term follow-up after primary ACLR. A total of 343 patients who underwent primary single-bundle ACLR using hamstring tendon autograft at our institute were included. Patients were queried with a 2-option anchor question regarding satisfaction with their current knee symptom state. The MOI of a PROM was calculated for each patient as the percentage of improvement normalized by the maximal possible improvement. The MOI threshold for each PROM was determined as the optimal cutoff value for predicting patient satisfaction based on receiver operating characteristic curve analysis. Multivariable logistic regression analyses were performed to identify predictors of achieving these thresholds. Subgroup analyses that stratified the time from injury to surgery within the cohort were performed, and MOI thresholds were recalculated within each of these subgroups. The PROMs evaluated in this study were the modified Lysholm Knee Score and the International Knee Documentation Committee Subjective Knee Evaluation Form (IKDC) score. The calculated MOI threshold was 35.1% for the Lysholm score and 46.7% for the IKDC score. A longer time from injury to surgery reduced the odds of achieving the MOI threshold for the Lysholm score (odds ratio [OR] per time bracket = 0.7114, p < 0.0001) and IKDC score (OR = 0.8038, p = 0.0003). Male sex was associated with higher odds of achieving the MOI threshold for the IKDC score (OR = 1.9645, p = 0.0143). For patients with chronicity of ≤6 months, the MOI threshold was 35.1% for the Lysholm score and 57.9% for the IKDC score, and for patients with chronicity of >6 months, the thresholds were 24.5% and 27.1%, respectively. The calculated MOI thresholds for the Lysholm and IKDC scores at mid-term follow-up after primary ACLR were 35.1% and 46.7%, respectively. Greater chronicity of the ACL injury was associated with lower odds of achieving the MOI thresholds for the PROMs at mid-term follow-up. Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

A sex-dependent algorithm including kappa free light chain for multiple sclerosis diagnosis.

Multiple sclerosis (MS) diagnosis includes the presence of restricted oligoclonal bands (OCB) in cerebrospinal fluid (CSF), but it has several limitations, as it is an observer-dependent time-consuming technique and offers a dichotomous result. Thus kappa free light chains (KFLC) have emerged as a quantitative alternative. However, the cut-off values for KFLC have not been well established yet and it is not clear if differences between sexes exist. We aim to evaluate these and to compare the diagnostic accuracy of KFLC concentrations and their related indexes versus OCB. For that purpose, paired CSF and serum samples were collected and immediately processed for albumin, total protein, immunoglobulins and OCB, then frozen at -20°C. KFLC was measured in a BN II (Siemens Healthineers, Germany). KFLC-derived indexes were calculated. Diagnostic accuracy was evaluated by the area under the curve (AUC), Youden's index and odds ratio. From the 193 patients included, 56 were classified as MS according to the 2017 McDonald criteria. K-index, Q KFLC and Reiber's diagram showed good accuracy in MS diagnosis when studied distinguishing between sexes, similar to OCB. Cut-offs for K-index and Q KFLC change substantially between sex having the highest AUC similar than OCB. A sex-dependent algorithm combining the use of K-index, Q KFLC and OCB yields the highest diagnostic accuracy. In conclusion, CSF KFLC measurement is a rapid, quantitative and easy-to-standardize tool that used through the proposed sex-dependent algorithm may reduce the number of manual OCB tests performed.

Characterisation of Paediatric Neuroblastic Tumours by Quantitative Structural and Diffusion-Weighted MRI

Purpose: To determine the diagnostic accuracy of quantitative diffusion-weighted (DW) MRI apparent diffusion coefficient (ADC) and tumour volumes to differentiate between malignant (neuroblastoma (NB)) and benign types of neuroblastic tumours (ganglioneuroma (GN) and ganglioneuroblastoma (GNB)) using different region-of-interest (ROI) sizes. Materials and Methods: This single-centre retrospective study included malignant and benign paediatric neuroblastic tumours that had undergone DW MRI at diagnosis. The outcome was diagnostic accuracy of the tumour volume from structural and ADC DW MRI, in comparison to histopathology (reference standard). Results: Data from 40 patients (NB, n = 24; GNB, n = 6; GN, n = 10), 18 (45%) females and 22 (55%) males, with a median age at diagnosis of 21 months (NB), 64 months (GNB), and 133 months (GN), respectively, ranging from 0 to 193 months, were evaluated. The area under the receiver operating characteristic (AUROC) curve for ADC for discriminating between neuroblastic tumours’ histopathology for a small ROI was 0.86 (95% CI: 0.75–0.98), and for a large ROI, 0.83 (95% CI: 0.71–0.96). An ADC cut-off value of 1.06 × 10−3 mm2/s was able to distinguish malignant from benign tumours with 83% (68–98%) sensitivity and 75% (95% CI: 54–98%) specificity. Tumour volume was not indicative of malignant vs. benign tumour diagnosis. Conclusions: In this study, both small and large ROIs used to derive ADC DW MRI metrics demonstrated high accuracy to differentiate malignant from benign neuroblastic tumours, with the ADC AUROC for the averaged multiple small ROIs being slightly greater than that of large ROIs, but with overlapping 95% CIs. This should be taken into consideration for standardisation of ROI-related data analysis by international initiatives.

Systemic Immune Inflammatory Index as Predictor of Blood Pressure Variability in Newly Diagnosed Hypertensive Adults Aged 18–75

Background: Accumulating evidence from clinical trials, large registries, and meta-analyses of population studies shows that increased Blood Pressure Variability (BPV) is predictive of Cardiovascular (CV) outcomes, independently of the average Blood Pressure (BP) values. One of the mechanisms explaining the relationship between BPV and target organ damage is the inflammatory response. The Systemic Immune Inflammation Index (SII), which relies on peripheral blood cell counts, including platelets, neutrophils, and lymphocytes, has emerged as a predictor of prognosis and outcomes in various diseases. The aim of this study was to investigate the association of the SII with Ambulatory Blood Pressure Variability (ABPV) in newly diagnosed hypertensive patients. Methods: This study was designed as a cross-sectional observational study. A total of 1606 consecutive newly diagnosed Hypertension (HT) patients were included in the study. The population was evaluated across 3 different categories according to HT grades (5 groups), eligibility for antihypertensive therapy (2 groups) and ABPV levels (2 groups). Results: Significant differences were observed between ABPV groups in terms of Neutrophil to Lymphocyte ratio, Platelet to Lymphocyte ratio, glucose, SII, high-sensitive CRP, HT grade, Inter-Ventricular Septum, Posterior Wall thickness, and Left Ventricular Mass (p &lt; 0.005). There was a significant relationship between SII and ABPV (r: 0.619, p &lt; 0.05). At the cutoff value of 580.49, SII had 77% sensitivity and 71% specificity for ABPV &gt; 14 (AUC: 0.788). Conclusions: SII may assist in developing an early treatment approach to minimize complications in patients with high ABPV who are at a higher risk of CV events.

Prognostic significance of novel muscle quality index utilization in hospitalized adults with cancer: A secondary analysis.

This study aimed to investigate and propose novel approaches to calculate muscle quality index (MQI) using muscle mass derived from single-frequency bioelectrical impedance analysis (SF-BIA) and calf circumference in both unadjusted and body mass index (BMI)-adjusted forms. In addition, we examined their prognostic significance in patients with cancer. A secondary analysis was conducted on a prospective cohort study of patients with cancer. Handgrip strength was measured. SF-BIA was conducted to estimate appendicular lean soft tissue (ALST, in kilograms). MQI was calculated using three approaches: (1) the ratio of handgrip strength to ALST (MQISF-BIA), (2) the ratio of handgrip strength to calf circumference (MQIcalf circumference), and (3) the ratio of handgrip strength to BMI-adjusted calf circumference (MQIadj. calf circumference). Maximally selected log-rank was calculated to estimate their cutoff values to predict survival. Two hundred eighty-four patients were included (51.1% men; median age, 61 years). Solid tumors were the most frequent (89.8%). All approaches to MQI (MQISF-BIA, MQIcalf circumference, and MQIadj. calf circumference) were independent predictors of 6-month mortality. The found cutoffs were (1) MQISF-BIA (<1.52 for men, <0.63 for women), (2) MQIcalf circumference (<0.74 for men, <0.24 for women), and (3) MQIadj. calf circumference (<0.75 for men, <0.25 for women). This study introduces MQISF-BIA, MQIcalf circumference, and MQIadj. calf circumference as future potential surrogate methods for computing MQI in clinical practice when other robust procedures are unavailable, pending further validation.

Hamstring-to-Quadriceps Strength Ratios in Women Team Sport Athletes: A Systematic Review

ABSTRACT Women experience a higher rate of anterior cruciate ligament (ACL) injuries than men. Muscle imbalance, in particular hamstring-to-quadriceps (H:Q) strength ratio, is considered a risk factor for ACL injury. The purpose of this systematic review was to identify isokinetic H:Q strength ratios in women team sport athletes and determine whether cutoff values, determined from research with predominantly males, of &gt;0.6 for conventional ratio (Hamstringconcentric:Quadricepsconcentric [CR]) and &gt;1.0 for functional ratio (Hamstringeccentric:Quadricepsconcentric [FR]) were met. The CR (0.6) was not met for team ([mean ± SD: 0.56 ± 0.08]), field (0.57 ± 0.08), and court (0.56 ± 0.08) sports. Handball presented the highest (0.58 ± 0.07), and softball presented the lowest CRs (0.47 ± 0.06). The FR (1.0) was not met for team (0.69 ± 0.14), field (0.85 ± 0.14), and court (0.65 ± 0.14) sports. Soccer presented the highest (0.85 ± 0.14) and handball the lowest (0.66 ± 0.13) FRs. When assessing hamstring and quadriceps strength balance, women team sport athletes did not meet CR or FR values, which may contribute to increased ACL injury risk. H:Q ratios below cutoff values may indicate compromised hamstring strength. It is recommended practitioners implement strength exercises aimed to improve H:Q ratios.

A comprehensive approach to defining the cutoff value of oligometastasis in head and neck squamous cell carcinoma.

Patients with limited distant metastatic disease, also known as oligometastasis, show better survival rates than polymetastatic patients, and may be amenable for curative-intent treatment. The definition of oligometastasis, however, is unknown, and no quantitative analyses on the cutoff value for oligometastasis have been performed before. This study aims to derive specific threshold values for the number of metastases and affected locations that defines oligometastatic disease in head and neck squamous cell carcinoma. A retrospective cohort study was conducted including all patients diagnosed with distant metastases between 2006 and 2021. For each patient, the number of distant metastases and affected locations was recorded on the basis of the available imaging at the time of diagnosis. Cox regression analyses and a machine-learning k-means algorithm were used to determine threshold values. A total of 384 patients untreated for their metastatic foci were analyzed. Most patients (n=207; 53.9%) had metastasis to one anatomic location, followed by metastases in two anatomic locations (n=62; 16.1%). The majority of patients had ≥9 metastatic foci (n=174; 45.3%), followed by one focus (n=74; 19.3%) and two foci (n=32; 8.3%). Cox regression and machine-learning k-means models showed that although the number of metastases did not predict survival, the number of affected locations did significantly (p<.001), by identifying a threshold of two locations. Contrary to the prevalent dogma, the definition of oligometastasis should not be defined by the number of metastases but rather by the number of affected locations, with a maximum number of affected locations set at two.