Defining Seropositivity Thresholds for Use in Trachoma Elimination Studies.

IntroductionIn the peri-elimination setting, the positive predictive value of trachomatous inflammation–follicular (TF), the primary marker used to determine need for antibiotics for trachoma, is suboptimal. Here, three non-TF measures are used to compare two regions where TF prevalence exceeds the threshold for intervention, but where the Chlamydia trachomatis (Ct) prevalence is different. MethodsPopulation prevalence of trachoma was measured in Vanuatu (n = 3470) and Kiribati (n = 2922). Dried blood spots (DBS) and conjunctival photographs were collected from every survey participant, and conjunctival swabs were collected from those aged 1–9 years. Individuals were tested for blood anti-Pgp3 antibodies, Ct DNA at the conjunctiva and severity of conjunctival scarring. ResultsThe prevalence of TF in 1–9-year-olds was 16.5% in Vanuatu and 38.2% in Tarawa. 7% of people aged ≥1 year in Vanuatu had conjunctival scarring compared to 27% in Tarawa. The prevalence of ocular Ct infection in 1–9-year-olds was 1.5% in Vanuatu and 27.4% in Tarawa. The seroconversion rate amongst 1–9-year-old children in Vanuatu and Tarawa was 0.018 and 0.197 events per child per year, respectively. ConclusionsComparing Vanuatu to Tarawa demonstrates several markers that could be used to differentiate the trachoma status of populations in these (and other) locations.

Trachoma causes blindness as a result of repeated ocular infection with Chlamydia trachomatis (Ct). International efforts are focused on eliminating trachoma as a public health problem by 2020; the World Health Organisation’s (WHO) and the Global Alliance for the Elimination of Trachoma by 2020 (GET2020) (1) recommend the SAFE strategy (Surgery to treat trichiasis, Antibiotics to treat infection with Ct, Facial cleanliness and Environmental change to reduce transmission) (2). Current implementation guidelines for the A, F and E aspects of the strategy are based on the prevalence of trachomatous inflammation-follicular (TF) in children aged 1-9 years. Antibiotics are administered as azithromycin mass drug administration (MDA) to all residents of districts wherein the prevalence of TF in 1-9 year old children is greater than 10% (3). As we approach the global elimination of trachoma, the prevalence of TF in children will decline towards the elimination threshold of 5%, and with it, the positive predictive value of TF. This may result in inappropriate, continued administration of antibiotics, which is a mis-use of valuable financial and person resources, as well as raising concerns about antimicrobial stewardship. Once the prevalence of TF in children aged 1-9 years is below 5%, re-emergence must be monitored. The WHO recommends a ‘pre-validation’ survey to determine if re-emergence has occurred (4). The 2014 Technical Consultation on Trachoma Surveillance (4) recommended exploring the district-level prevalence of TF, the district-level prevalence of conjunctival infection with Ct and the district-level prevalence of antibodies against Ct, to determine an appropriate measure, or combination of measures, for deciding when to stop MDA. Numerous methods exist for detecting antibodies against Ct antigens (5–9). Specimens may be collected by venepuncture or from fingerprick, stored as whole blood, serum or dried blood spots on filter paper, and assayed using enzyme-linked immunosorbent assays (ELISA), lateral flow assays (LFA), or multiplex bead assay (MBA); of theses, MBA allows for the testing for antibodies against numerous antigens from endemic infections, but the required instrumentation and reagents are more cost-intensive. Historically, serology for Ct fell out of favour due to the high cross-reaction with antigens from C pneumoniae, however, with the advent of new proteomic tools and assays with greater reported sensitivity and specificity, serology has re-emerged as a potential tool for monitoring the prevalence of antibody-inducing chlamydial infection (4,10,11). Both ELISA and MBA assays present output as numerical data, which must be translated to a population seroprevalence value. Therefore, a method must be determined for dichotomising numerical data and setting a threshold between seropositive and seronegative samples. Receiver 5 Operating Characteristic (ROC) curves have previously been used, but these rely on appropriate reference standards. Alternate methods that rely solely on the data generated within a study, such as finite mixture modelling, may be more appropriate (12–15). Once seropositivity has been estimated, it is of interest to detect changes in the age-specific seroprevalence of a population. Catalytic models have previously been used to monitor changes in the prevalence of malaria (13,16–22) and this methodology can be applied to detect changes in transmission as a proxy for the force of infection (FOI) as well as to estimate seroconversion rates, and to a lesser extent, seroreversion rates (13,19). The simplicity of dichotomous seroprevalence estimates may provide lower resolution information than the quantitative antibody levels. Recent work uses quantitative antibody levels to measure changes in transmission (23). Ensemble machine learning can be used to produce characteristic agespecific antibody curves that may reveal changes in population mean antibody levels that would otherwise be masked because changes occurred above or below the seropositivity threshold. There remain several areas to be elucidated. While antigens used in modern serological studies are considered specific for Ct, there is yet no way to distinguish between antibodies due to ocular infection or genital infection, making serological studies in anyone over the age of sexual debut a challenge. There is no standard reference for antibody levels, making a comparison between different studies challenging. The two most commonly used assays produce different output data: ELISAs measures optical density- the amount of light absorbed by the specimen- while MBAs detect fluorescence in an assayed specimen. An internal standard would allow for comparison between the two assays. This PhD research addresses several key questions about the use of serology and Ct-specific antibodies for monitoring the prevalence of trachoma. As more countries progress to eliminating trachoma as a public health problem by 2020, efforts will need to be increased to monitor and evaluate elimination efforts and to prevent re-emergence of the disease. Serological techniques may be ideal for such activities.

Background: The accurate evaluation of patient prognosis, prediction of mortality rates, and anticipation of long-term illness sequelae continue to pose significant challenges for clinicians managing COVID-19. Objectives: This study sought to ascertain the association between serum electrolyte levels at hospitalization and mortality in patients infected with the Delta variant of COVID-19. Methods: This retrospective study included 316 hospitalized COVID-19 patients. Demographic data, clinical characteristics, and admission serum electrolyte and albumin levels were collected. Receiver Operating Characteristic (ROC) curve analysis was performed to assess the predictive value of individual biomarkers. Multivariate logistic regression was then used to identify independent predictors of mortality, adjusting for potential confounders including age. Results: The mean age of the study population was 59.53 ± 15.92 years, with deceased patients significantly older (68.86 ± 15.92 years) than discharged patients (56.80 ± 16.82 years). Initial comparisons showed significant differences in sodium (Na), potassium (K), and albumin levels between the two groups. The ROC curve analysis indicated moderate predictive power for Na [area under the curve (AUC) = 0.637] and K (AUC = 0.605), while calcium (Ca), magnesium (Mg), and albumin showed poor or no predictive value. However, multivariate logistic regression revealed that only advanced age (OR = 1.033, 95% CI: 1.001 - 1.066, P = 0.040) and longer hospital stay (OR = 1.130, 95% CI: 1.022 - 1.250, P = 0.017) were independently associated with increased mortality. Serum electrolyte and albumin levels did not remain significant predictors after adjustment for these factors. Conclusions: This study confirms advanced age and longer hospital stay as independent risk factors for mortality in COVID-19 patients. While initial analyses suggested an association between elevated serum Na and K levels at admission and higher mortality, these correlations did not remain statistically significant after adjusting for age and length of hospital stay in multivariate analysis. Further research in larger, diverse populations is recommended to explore these relationships.

Clinical utility of complete blood count indices in pediatric MOG antibody-associated disease.

Introduction: Preeclampsia (PE) is one of the leading obstetric diseases with significant morbidity and mortality in both mother and foetus. The etiology of preeclampsia is unknown. It may result from several reasons with imbalance between angiogenic regulatory factors in maternal circulation as one of the factor. High circulatory levels of Soluble Fms-like Tyrosine Kinase-1 (sFlt-1) are detectable several weeks before clinical presentation of preeclampsia. Aim: To determine association of serum levels of sFlt-1 with preeclampsia in second and third trimester of pregnancy. Materials and Methods: A prospective cohort study was conducted in the Department of Biochemistry in collaboration with the Department of Obstetrics and Gynaecology in a tertiary care hospital (Sri Guru Ram Das Institute of Medical Sciences and Research, Amritsar, Punjab, India), from November 2018 to March 2021. The study participants were divided into two groups i.e, normotensive (group 1) and preeclamptic (group 2). The enrollment of participants was done during second trimester. Serum sFlt-1 concentration was measured in second trimester (24-28 weeks) and in third trimester (beyond 28 weeks) using Enzyme Linked Immunoassay (ELISA) kits. Receiver Operating Characteristics (ROC) curve analysis was done for evaluation of Area Under Curve (AUC), sensitivity and specificity using software defined cut-off values. Results: Total 60 participants were there in each group with maternal mean age of 25.8±3.2 years in group 1 and 30.6±5.5 years in group 2 (p-value <0.001). sFlt-1 levels were significantly higher in preeclampsia group both in second and third trimesters when compared with normotensive group with median 313.07 versus 65.150 (p-value <0.001) and 337.875 versus 76.925 (p-value <0.001), respectively. The ROC curve analysis using 190.5 ng/mL as cut-off point in second trimester showed sensitivity 90%, specificity 85%, AUC was 0.832, 95% CI (0.745-0.918) and in third trimester at cut-off point 271.5 ng/mL showed sensitivity 90%, specificity 90%, AUC was 0.884, 95% CI (0.817-0.951). Conclusion: The soluble Fms-Like Tyrosine Kinase-1-1 (sFlt-1), may serve as biomarker for early diagnosis and can improve prediction of preeclampsia.

Objective:To investigate the role of the body roundness index（BRI） and a body shape index（ABSI） in the assessment of Obstructive Sleep Apnea-Hypopnea Syndrome（OSAHS）. Methods:A retrospective analysis was performed on the medical records of 256 adult patients with suspected OSAHS who underwent polysomnography（PSG） in the Department of Otorhinolaryngology, Peking University Third Hospital, from March 2024 to February 2025. The collected data included gender, age, Body Mass Index（BMI）, waist circumference（WC）, Apnea-Hypopnea Index（AHI）, and the lowest oxygen saturation（LSaO2）. Non-parametric correlation analysis, Receiver Operating Characteristic（ROC） curve analysis, and multiple logistic regression analysis were employed to explore the relationships between WC, BMI, BRI, ABSI, age and other indicators, as well as AHI and LSaO2. Results:Non-parametric correlation analysis showed that, among males, the indicators most strongly correlated with AHI, in descending order, were WC（r=0.476, P<0.001）, BMI（r=0.458, P<0.001）, and BRI（r=0.456, P<0.001）. Among females, the order was BRI（r=0.567, P<0.001）, WC（r=0.484, P<0.001）, BMI（r=0.449, P<0.001）, and age（r=0.352, P=0.004）. For the correlation with LSaO2, in males, the order was BMI（r=-0.445, P<0.001）, WC（r=-0.426, P<0.001）, and BRI（r=-0.415, P<0.001）; in females, it was BRI（r=-0.482, P<0.001）, BMI（r=-0.468, P<0.001）, and WC（r=-0.373, P<0.001）. ROC curve analysis indicated that the indicators of predictive performance for AHI>15/h from strongest to weakest（area under the curve, AUC） were WC（AUC=0.655, P<0.001）, BRI（AUC=0.646, P=0.001）, and BMI（AUC=0.646, P=0.001） in males; in females they were BRI（AUC=0.836, P<0.001）, WC（AUC=0.799, P<0.001）, and BMI（AUC=0.766, P=0.001）. Predictors of LSaO2<80% from strongest to weakest performance were BMI（AUC=0.701, P<0.001）, WC（AUC=0.689, P<0.001）, and BRI（AUC=0.689, P<0.001） in men; in females they were BRI（AUC=0.744, P=0.007）, BMI（AUC=0.724, P=0.013）, and WC（AUC=0.680, P=0.046）. Multifactor logistic regression analysis shows that in men WC（OR=1.049, 95%CI1.009-1.091） was an independent risk factor for AHI>15/h, and WC（OR=1.075, 95%CI1.038-1.114） was an independent risk factor for LSaO2<80%; in women BRI（OR=2.899, 95%CI 1.528-5.550） was an independent risk factor for AHI>15/h, and BMI（OR=1.276, 95%CI1.067-1.527） was an independent risk factor for LSaO2<80%. Conclusion:BRI is closely correlated with the severity of OSAHS in both adult male and female populations, with a more pronounced correlation in females. BRI may have advantages over other anthropometric measures in predicting the risk of OSAHS, playing a decisive role in predicting OSAHS in adult females, and may serve as a novel indicator for predicting the severity of OSAHS in adult women.

BackgroundPatients undergoing transurethral resection (TUR) of the prostate are at risk of TUR syndrome, generally defined as having cardiovascular and/or neurological manifestations, along with serum sodium concentrations less than or equal to 125 mmol/l. As these symptoms can also occur in patients with serum sodium greater than 125 mmol/l, this study aimed to investigate the relationship between serum sodium concentrations and neurological manifestations of TUR syndrome.MethodsData on patients who underwent TUR of the prostate under local anesthesia over an 8-year period were retrospectively reviewed. Based on their cardiovascular and neurological manifestations, patients were divided into two groups: a symptomatic and an asymptomatic group. Logistic regression analysis was used to detect the risk factors for being symptomatic. Receiver operator characteristic (ROC) curve analysis was used to determine the optimal cutoff value of estimated change in serum sodium level that could predict the development of clinical manifestation of TUR syndrome.ResultsOf the 229 patients, 60 showed symptoms. Serum sodium level correlated with neurological score (Spearman’s correlation coefficient > 0.5). Logistic regression detected that the risk factors for being symptomatic were serum sodium level variables, operation time longer than or equal 90 min, and presence of continuous drainage from the bladder. ROC curve analysis showed that a change in serum sodium level of 7.4 mmol/l was the optimal cutoff value, with a sensitivity of 0.72, a specificity of 0.87, and an area under the curve (AUC) of 0.87. ROC curve analysis also showed that a 7.0% change in serum sodium level was optimal for this parameter, with a sensitivity of 0.70, a specificity of 0.89, and an AUC of 0.87.ConclusionsChanges in serum sodium concentration of > 7 mmol/l and of > 7% could predict the development of cardiovascular and neurological manifestations, which were assumed to be symptoms of TUR syndrome.

Comparison of Computed Tomography, Magnetic Resonance Imaging, and Positron Emission Tomography and Computed Tomography for the Evaluation Bone Invasion in Upper and Lower Gingival Cancers

This study provides a newly updated perspective of information on severely screened 21 previous studies of the various measurement methods for improving physical fitness and providing determined cutoff values from our reserved elderly human database. We aimed to provide scientific evidence-based information regarding physical fitness standards for developing useful prognostics, promoting and maintaining health programs for sarcopenic elderly. 21 previous studies emphasizing criterion referenced standards and receiver operator characteristic (ROC) curve analyses for improving physical fitness were screened. For predicting the prevalence of sarcopenia, the t-test, logistic regression, linear regression, ROC curve analyses, and voluntary categorizations such as the twentieth or sixtieth percentile classification were used. Based on these scientific evidences, we determined cutoff values from our reserved DB and realized that 75 years for men and 70 years for women are the transitional period during which there are large declines in muscle and fat mass (p < 0.01), which reflects physical function tests (p < 0.01) in both genders. Using the six factors with ideal cutoff thresholds, an individual exercise program can be designed for alleviating symptoms of frailty caused by sarcopenia for the elderly.

In the past decade, scientific research in the area of Nephrology has focused on evaluating the clinical utility and performance of various biomarkers for diagnosis, risk stratification and prognosis. Before implementing a biomarker in everyday clinical practice for screening a specific disease context, specific statistic measures are necessary to evaluate the diagnostic accuracy and performance of this biomarker. Receiver Operating Characteristic (ROC) Curve analysis is an important statistical method used to estimate the discriminatory performance of a novel diagnostic test, identify the optimal cut-off value for a test that maximizes sensitivity and specificity, and evaluate the predictive value of a certain biomarker or risk, prediction score. Herein, through practical examples, we aim to present a simple methodological approach to explain in detail the principles and applications of ROC curve analysis in the field of nephrology pertaining diagnosis and prognosis.

Sepsis is still one of the leading causes of mortality and morbidity in children worldwide. Consumptive coagulopathy and suppression of thrombopoiesis in the bone marrow resulting from immune dysregulation are pathological mechanisms that cause thrombocytopenia in sepsis. Platelet count (PLT) and indices, such as mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT) are markers of platelet activation and are strongly influenced by platelet morphology and proliferation kinetics. We aimed to study the use of platelet count and indices as predictors of mortality in children with sepsis. This is a cross-sectional study of 45 children diagnosed with sepsis on admission at Haji Adam Malik Hospital, Medan, North Sumatra, Indonesia, between October and November 2022. Blood samples were drawn upon admission, and platelet count and indices were then determined for all children. Subjects were followed up till discharge from hospital or death. Receiver Operating Characteristic (ROC) curve analysis of platelet parameters was done to determine the area under the curve (AUC), optimal cut-off value, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) in predicting mortality in children with sepsis. Using the cut-off values from ROC curve analysis, the odds ratio with 95% confidence interval was calculated using multiple logistic regression analyses. A P value less than 0.05 was considered statistically significant. MPV, PDW, and PDW/PLT were significantly higher in non-survivors than survivors (P=0.04, P=0.02, and P=0.04, respectively). ROC curve analysis showed that PDW had the largest AUC (0.708 [95% CI=0.549-0.866]) with a cut-off value of 14.1%, sensitivity of 63.6%, and specificity of 82.6%. PDW was also the only parameter that significantly affected the outcome of children with sepsis. PDW≥14.1% at admission increases the risk of mortality by 5.7 times. Admission PDW is a fast and specific tool to predict the outcome of children with sepsis.

BackgroundThe aim of this study was to analyze the risk factors of pressure injury (PI) in critically ill patients with cancer to build a risk prediction model for PI.Material/MethodsBetween January 2018 and December 2019, a total of 486 critically ill patients with cancer were enrolled in the study. Univariate analysis and binary logistic regression analysis were used to explore risk factors. Then, a risk prediction equation was constructed and a receiver operator characteristic (ROC) curve analysis model was used for prediction.ResultsOf the 486 critically ill patients with cancer, 15 patients developed PI. Risk factors found to have a significant impact on PI in critically ill patients with cancer included the APACHE II score (P<0.001), semi-reclining position (P=0.006), humid environment/moist skin (P<0.001), and edema (P<0.001). These 4 independent risk factors were used in the regression equation, and the risk prediction equation was constructed as Z=0.112×APACHE II score +2.549×semi-reclining position +2.757×moist skin +1.795×edema–9.086. From the ROC curve analysis, the area under the curve (AUC) was 0.938, sensitivity was 100.00%, specificity was 83.40%, and Youden index was 0.834.ConclusionsThe PI risk prediction model developed in this study has a high predictive value and provides a basis for PI prevention and treatment measures for critically ill patients with cancer.

AimTo develop an accurate lab score based on in-hospital patients’ potent clinical and biological parameters for predicting COVID-19 patient severity during hospital admission.MethodsTo conduct this retrospective analysis, a derivation cohort was constructed by including all the available biological and clinical parameters of 355 COVID positive patients (recovered = 285, deceased = 70), collected in November 2020-September 2021. For identifying potent biomarkers and clinical parameters to determine hospital admitted patient severity or mortality, the receiver operating characteristics (ROC) curve and Fischer’s test analysis was performed. Relative risk regression was estimated to develop laboratory scores for each clinical and routine biological parameter. Lab score was further validated by ROC curve analysis of the validation cohort which was built with 50 COVID positive hospital patients, admitted during October 2021-January 2022.ResultsSensitivity vs. 1-specificity ROC curve (>0.7 Area Under the Curve, 95% CI) and univariate analysis (p<0.0001) of the derivation cohort identified five routine biomarkers (neutrophil, lymphocytes, neutrophil: lymphocytes, WBC count, ferritin) and three clinical parameters (patient age, pre-existing comorbidities, admitted with pneumonia) for the novel lab score development. Depending on the relative risk (p values and 95% CI) these clinical parameters were scored and attributed to both the derivation cohort (n = 355) and the validation cohort (n = 50). ROC curve analysis estimated the Area Under the Curve (AUC) of the derivation and validation cohort which was 0.914 (0.883–0.945, 95% CI) and 0.873 (0.778–0.969, 95% CI) respectively.ConclusionThe development of proper lab scores, based on patients’ clinical parameters and routine biomarkers, would help physicians to predict patient risk at the time of their hospital admission and may improve hospital-admitted COVID-19 patients’ survivability.

The aim of this study was to compare platelet distribution width (PDW) and neutrophil to lymphocyte ratio (NLR) values in mild-to-moderate and severe knee osteoarthritis (OA). This was a retrospective study of patients with knee OA according to the Kellgren-Lawrence (KL) grading system. Of 465patients, 231 were excluded (62 due to not meeting the inclusion criteria and 169 due to the lack of simultaneous haemogram and radiographic evaluations). Demographic characteristics and PDW and NLR values were recorded. The patients were then divided into two groups: KL grade 1-3 (mild-to-moderate OA) and KL grade 4 (severe OA). In severe knee OA patients, blood PDW (13.44 ± 2.58, p= 0.01) and NLR values (2.16 ± 0.84, p= 0.04) were elevated as compared with those in mild-to-moderate knee OA patients. Blood PDW and NLR values of ⩾ 12.5 and ⩾ 2.1, respectively, were taken as cut-offs based on a receiver operating characteristics (ROC) curve analysis. In the ROC curve analysis, blood NLR ⩾ 2.1 had 60% sensitivity and 64.8% specificity, and PDW ⩾ 12.5 had 61% sensitivity and 58% specificity in predicting severe knee OA. In a univariate analysis, age (p< 0.001), PDW ⩾ 12.5 (p= 0.029) and blood NLR ⩾ 2.1 (p= 0.030) emerged as significant predictors of the severe knee OA. The results suggested that the blood PDW and NLR are novel inflammatory markers that can predict the radiographic severity of knee OA in clinical practice.

Introduction: Pre-eclampsia (PE), a pregnancy induced hypertensive disorder affects approximately 8-10% of all pregnancies in developing countries. A highly sensitive and specific marker for diagnosis of PE is the need of the hour as diagnostic criteria are still based on non-specific clinical symptoms, ultrasound, and laboratory findings. Imbalance in the placental release of various angiogenesis regulatory factors to the maternal circulation is one of the significant contributors to its clinical manifestations. Low levels of pro-angiogenic biomarker Placental Growth Factor (PLGF) are detectable several weeks before clinical presentation of PE. Aim: To determine the association of serum levels of PLGF with PE in second and third trimester of pregnancy. Materials and Methods: A prospective cohort study was performed in a tertiary care hospital from December 2018 to November 2021, on 130 patients by dividing study participants into two groups: Pre-eclamptic cases, Normotensive controls. At enrollment in second trimester (24-28 weeks) and during third trimester (beyond 28 weeks) serum PLGF concentration was measured by using the Enzyme-linked Immunosorbent Assay (ELISA) kit method. Data was statistically analysed. Student’s t-test was used for comparing differences between study groups. The chi-square test was used to compare qualitative categorical data. Evaluation of the Area Under the Curve (AUC), diagnostic accuracy, sensitivity and specificity was done by Receiver Operating Characteristics (ROC) curve analysis done using software defined cut-off values. Results: Total of 115 patients were analysed in the present study with 55 patients in group 1(mean age: 25.83±3.27 years) and 60 patients in group 2 (mean age: 30.52±5.63 years) When compared with normotensive group PLGF levels were significantly lower in pre-eclamptic group with median 16.27 ng/mL versus 12.20 ng/ mL (p &lt;0.001) in second and 14.05 ng/mL versus 10.50 ng/mL (p &lt;0.001) in third trimesters respectively. ROC curve analysis using cut-off point of 14.91 ng/mL showed sensitivity 80%, specificity 96.7%, AUC 0.896, 95%CI:(0.832-.959) in second trimester and in third trimester at cut-off point of 13 ng/mL sensitivity 73%, specificity 96.7%, AUC 0.882 95% CI:(0.816-.948) was found. Conclusion: PLGF may be used as a biomarker for early prediction, diagnosis, and management of PE. It might serve as ideal discriminating biochemical markers of PE. In the near future, the clinical utility of disease specific angiogenic biomarker in early detection of PE might improve health outcomes by preventing adverse maternal and neonatal outcomes and serious complications.