Internal Validity Research Articles

Assessing causality in deprescribing studies: A focus on adverse drug events and adverse drug withdrawal events.

Generating real-world evidence about the effect of medication discontinuation or dose reduction on outcomes, such as reduction of adverse drug effects (ADE; intended benefit) and occurrence of adverse drug withdrawal events (ADWE; unintended harm), is crucial to informing deprescribing decisions. Determining the causal effects of deprescribing is difficult for many reasons, including lack of randomization in real-world study designs and other design and measurement issues that pose threats to internal validity. The inherent challenge is how to identify the effects, both intended benefits and unintended harms, of a new medication stoppage or reduction when implemented in patients with many potential clinical and social risks that may influence the likelihood of deprescribing as well as outcomes. We discuss methodological issues of estimating the effect of medication discontinuation or reduction on risk of ADEs and ADWEs considering: (1) sampling study populations of sufficient size with the potential to demonstrate clinically meaningful and quantifiable outcomes, (2) accurate and appropriately timed measurement of covariates, outcomes, and discontinuation, and (3) statistical approaches to managing confounding and other biases inherent in long-term medication use by individuals with multiple morbidities. Designing rigorous deprescribing studies that address internal validity threats will support evidence generation by improving the ability to assess benefits and harms when the exposure of interest is the absence of a medication. Iterative learnings about data quality, variable definition, variable measurement, and exposure-outcome associations will inform strategies to improve the causal inferences possible in real-world deprescribing studies.

A prediction model for electroconvulsive therapy effectiveness in patients with major depressive disorder from the Dutch ECT Consortium (DEC).

Reliable predictors for electroconvulsive therapy (ECT) effectiveness would allow a more precise and personalized approach for the treatment of major depressive disorder (MDD). Prediction models were created using a priori selected clinical variables based on previous meta-analyses. Multivariable linear regression analysis was used, applying backwards selection to determine predictor variables while allowing non-linear relations, to develop a prediction model for depression outcome post-ECT (and logistic regression for remission and response as secondary outcome measures). Internal validation and internal-external cross-validation were used to examine overfitting and generalizability of the model's predictive performance. In total, 1892 adult patients with MDD were included from 22 clinical and research cohorts of the twelve sites within the Dutch ECT Consortium. The final primary prediction model showed several factors that significantly predicted a lower depression score post-ECT: higher age, shorter duration of the current depressive episode, severe MDD with psychotic features, lower level of previous antidepressant resistance in the current episode, higher pre-ECT global cognitive functioning, absence of a comorbid personality disorder, and a lower level of failed psychotherapy in the current episode. The optimism-adjusted R² of the final model was 19%. This prediction model based on readily available clinical information can reduce uncertainty of ECT outcomes and hereby inform clinical decision-making, as prompt referral for ECT may be particularly beneficial for individuals with the above-mentioned characteristics. However, despite including a large number of pretreatment factors, a large proportion of the variance in depression outcome post-ECT remained unpredictable.

Nomogram Predictive Model for Vaginal Birth after One Prior Cesarean Section: A Retrospective Study

Background: Repeat cesareans pose significant maternal risks, whereas vaginal birth after cesarean (VBAC) offers better outcomes, with a complication rate of 2.4% compared with 3.6% for elective repeat cesareans and 14.1% for failed trial of labor after cesarean (TOLAC). TOLAC rates are low in China, and success rates vary between 60% and 80%. This study aims to develop a nomogram-based predictive model for VBAC in China and improve existing, less rigorous scoring models. Methods: This retrospective cohort study was conducted at Hangzhou Women's Hospital from February 2015 to March 2020, and included 159 parturient attempts at labor after one prior low transverse cesarean section. The participants were divided into two groups based on their mode of delivery for comparison: the VBAC and the TOLAC failure group. Univariate and multivariate logistic regression analyses were conducted to identify independent predictors for VBAC and develop a nomogram predictive model to estimate the success rate of TOLAC. The bootstrap method was used for internal validation of the models. Three different VBAC prediction models were evaluated by plotting receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Results: A total of 127 women had VBAC and 32 women failed TOLAC, with a success rate of 79.9%. Three independent factors affecting the VBAC were identified: gestational age at delivery, Bishop score and newborn birth weight. A predictive nomogram model for the VBAC was constructed that incorporates these three factors. The model showed a good fit (χ2 = 11.94, p = 0.154) with an overall prediction accuracy of 81.1%. The area under the ROC curve was 0.83 (95% CI (confidence interval), 0.76–0.90) (p < 0.001) and the optimal cut-off value was 83.4%. The bootstrap internal validation showed that our predictive model maintained high overall accuracy and specificity, but exhibited low sensitivity and a low Kappa coefficient. Compared to the Grobman model and Jiaming Rao et al. model, our developed prediction model possesses the strongest discriminatory ability and the highest net benefit, followed by the model by Jiaming Rao et al. All three models demonstrate a high degree of fit. Conclusions: Shorter gestational age at delivery, lower newborn birth weight and higher cervical Bishop score are favorable factors for VBAC. The predictive nomogram model for the VBAC after a single cesarean section, constructed with these three factors, has good predictive efficacy. The model is simple to calculate and has practical value in the clinical selection of suitable candidates for TOLAC after a single cesarean section.

Turkish Translation And Validation of The Expectations of Aesthetic Rhinoplasty Scale.

The aim of this study was to translated, validate, and culturally adapt the original English version of the Expectations of Aesthetic Rhinoplasty Scale (EARS) into Turkish for use in Turkish-speaking communities. Fifty-one patients who wanted to undergo primary rhinoplasty and were literate in Turkish were included in the study. The control group consisted of 81 healthy volunteers who did not require rhinoplasty. A Turkish version of the EARS (EARS-T) was created. The participants completed the EARS-T questionnaire twice, four weeks apart. The internal consistency of the scale (Cronbach's α), the test-retest reliability (intraclass correlation coefficient [ICC]), and differences between the patient and control groups (Pearson's chi-square test) were analyzed. A statistically significant difference was found between the age and gender of the patient and control groups (p = 0.001 and p = 0.001, respectively). Univariate analysis showed that this significant difference did not affect the study results (age: p = 0.2; gender: p = 0.12). In addition, a statistically significant difference was found between the scale scores of the control and rhinoplasty groups (all p < 0.05). The EARS-T had good internal consistency, with high Cronbach's α scores ranging between 0.74 and 0.87. Test-retest reliability was demonstrated by high ICC scores ranging from 0.71 to 0.87. Our study revealed that the EARS-T has good internal consistency, reliability, and validity. Therefore, it can be used to assess the expectations of aesthetic rhinoplasty patients in preoperative consultation practice and in clinical studies related to rhinoplasty.

Screening for posttraumatic stress disorder (PTSD) in Mozambique: Validation of the Primary Care Posttraumatic Stress Disorder Screen for Diagnostic and Statistical Manual fifth edition (PC-PTSD-5).

The confluence of conflict-, climate-, and public health-related emergencies in Mozambique increases the risk of posttraumatic stress disorder (PTSD). Few brief screening tools for PTSD have been validated in low- and middle-income countries. We aimed to validate the five-item Primary Care PTSD Screen for the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5), the PC-PTSD-5 in Mozambique. This study recruited 957 participants who completed the Mini-International Neuropsychiatric Interview-Plus (MINI-Plus) and PC-PTSD-5, a convenience sample from primary and tertiary care settings in Maputo, Mozambique. Participants were administered a diagnostic interview for psychiatric disorders and the PC-PTSD-5 screening tool. We evaluated the criterion validity of the PC-PTSD-5 concerning the MINI-Plus diagnosis of PTSD, the internal construct validity and reliability using confirmatory factor analysis and Kuder-Richardson 20 (KR-20), discriminant validity of the PC-PTSD-5 in comparison to other common mental disorder and suicide risk screening tools, and measurement invariance of selected cutoffs by age, sex, and comorbidity. Internal consistency of the PC-PTSD-5 was high (KR-20 = 0.837), and confirmatory factor analysis suggested that a single PTSD factor fits the data well. PC-PTSD-5 items were moderately correlated with other psychiatric symptoms. Criterion validity analyses revealed that a cutoff score of 3 provided high specificity (0.833) and moderate sensitivity (0.673). This cutoff score performed optimally across age and gender; however, a cutoff score of 2 was preferred if the participant had no psychiatric comorbidities. Screening with the PC-PTSD-5 may facilitate case detection and linkages to appropriate treatment for individuals affected by potentially traumatic events in Mozambique. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Performance of instrumental activities of daily living in patients with haemophilic arthropathy. A cross-sectional cohort study.

The development of haemophilic arthropathy causes joint damage that leads to functional impairment that limits the performance of activities in patients with haemophilia. The aim was to identify the best predictive model for performing instrumental activities of daily living in adult patients with haemophilia arthropathy. Cross-sectional cohort study. 102 patients were recruited. The dependent variable was the performance of instrumental activities of daily living (Lawton and Brody scale). The dependence on the performance of activities of daily living was the dependent endpoint (Barthel scale). The secondary variables were joint damage (Hemophilia Joint Health Score), pain intensity, and clinical, anthropometric, and sociodemographic variables. The degree of dependence, joint damage, pain intensity, and marital status (Cp=5.60) were the variables that best explain the variability in the performance of instrumental activities of daily living (R2 adj=0.51). Loss of predictive capacity is acceptable with good mean internal (R2 mean=0.40) and external (R2-r2=0.09) validation. According to the predictive pattern obtained, patients with haemophilia, who were married, without joint pain or damage, and independent in their day-to-day lives, had a score of 7.91 points (95% CI: 7.42; 8.39) in the performance of instrumental activities of daily living. The predictive model for the functional capacity of instrumental activities of daily living in haemophilia patients encompasses factors such as level of autonomy, joint impairment, pain severity, and marital status. Notably, despite the presence of joint damage, individuals with haemophilia exhibit a significant level of independence in carrying out both basic daily tasks and instrumental activities of daily living. Id NCT04715100.

Preoperative mortality risk evaluation in abdominal surgical emergencies: development and internal validation of the NDAR score from a national multicenter audit in Senegal

IntroductionAbdominal surgical emergencies have a high mortality rate. Effective management primarily relies on the early identification of patients at high risk of postoperative complications. The objective of our study was to determine the prognostic factors associated with poor outcomes from abdominal surgical emergencies in Senegal and to establish a predictive score for mortality for preoperative risk evaluation (NDAR (New Death Assessment Risk) score).MethodologyThis was a retrospective national cross-sectional study conducted over one year in 14 regions of Senegal. Adult patients (aged > 15 years) who presented with a traumatic or non-traumatic abdominal surgical emergency were included. The studied variables included clinical and paraclinical data. The variable of interest was death within 30 days of the surgery. Logistic regression was used to identify the factors independently associated with mortality. Risk factors identified after logistic regression analysis were weighted using odds ratio (OR) values rounded to the nearest whole number. The predictive capacity of the score was evaluated by analyzing the ROC (Receiver Operating Characteristic) curve based on the area under the curve (AUC).ResultsA total of 1114 patient records were included, with a mortality rate of 4.4%. Diagnoses were observed in patients included appendicitis in 39.8% of cases (n = 444), followed by peritonitis in 22.3% (n = 249), intestinal obstruction in 18.5% (n = 205), strangulated hernias in 10.5% (n = 117), and abdominal trauma in 6.1%. Logistic regression, established the following scores: age > 40 years (score 2), ASA status grade 2 or higher (score 1), presence of a positive QSIRS score (score 2), diagnosis of peritonitis (score 2), diagnosis of intestinal obstruction (score 1), and the presence of intestinal necrosis (score 3). The score is positive if the total is strictly greater than 5, indicating a 17.7% risk of mortality. This score had a high predictive capacity with an AUC of 0.7397.ConclusionThis study enabled the establishment of a score that allows for the early identification of at-risk patients, even in constrained resource settings, facilitating appropriate perioperative management and timely surgical intervention to reduce the risk of complications. This approach, focused on early recognition of high-risk patients, is crucial for improving clinical outcomes in abdominal surgical emergencies.

73 Predictors of neurodevelopmental impairment in extreme preterm infants with unremarkable cranial ultrasound: A Canadian population-based cohort

Abstract Background Extreme preterm infants are at high-risk of brain injury and neurodevelopmental impairment (NDI). Previous studies reported significant NDI (sNDI) in preterm infants with no abnormalities on routine cranial ultrasound screening (CUS), traditionally perceived to have favorable outcomes. Recent data from population-based outlining clinical predictors of sNDI in those infants are lacking. Objectives (1) to describe the incidence, perinatal and neonatal characteristics of NDI and sNDI in a large population-based cohort of extreme preterm infants with unremarkable CUS; (2) to develop a prediction model of sNDI (any of: CP ≥ GMFCS stage 3, Bayley III &amp;lt; 70 in any domain, deafness requiring aids, or bilateral blindness) in those infants. Design/Methods A retrospective review of a national cohort of preterm infants born at &amp;lt;29 weeks’ gestation between April 2009 and December 2018. We included surviving infants with unremarkable routine CUS (no hemorrhage, periventricular leukomalacia or ventricular dilatation) who had neurodevelopmental assessment at 18-24 month corrected age at one of participating centres in the Canadian Neonatal Follow Up Network. We compared the baseline characteristics between infants with no NDI and those with any NDI and sNDI. The population sample was then randomly split into training and testing datasets in 70:30 ratio for prediction model’s development and validation, respectively. Multivariate logistic regression with GEE accounting for clustering within site was used, adjusted for variables with p-value&amp;lt;0.1 using backward selection procedure. The AUC and the diagnostic properties of the model developed using training dataset was then validated in the testing dataset. Results Out of 7463 eligible infants, 4327 (58%) were included. Of those, 2501 (59%) had no NDI and 1736 (41%) had NDI. sNDI accounted for 14% of the cohort and one third of those with NDI. Perinatal and neonatal characteristics of the three groups are shown in Table 1. On internal validation, maternal hypertension, maternal level of education, gestational age, male sex, ROP≥ stage 3 and systemic steroids were predictive of sNDI (Table 2). The prediction model had Sensitivity 0.91, NPV 0.90, and AUC 0.69 (95% CI 0.64-0.73). Conclusion In this national cohort, 2 out of 5 extreme preterm infants with unremarkable CUS had NDI and 1 in 7 had sNDI. The developed prediction model had high sensitivity and NPV, but poor discrimination. The findings of this study can help clinicians to identify at-risk infants who may benefit from early targeted interventions.

Automated quantification of cerebral microbleeds in susceptibility-weighted MRI: association with vascular risk factors, white matter hyperintensity burden, and cognitive function.

To train and validate a deep learning (DL)-based segmentation model for cerebral microbleeds (CMB) on susceptibility-weighted MRI; and to find associations between CMB, cognitive impairment, and vascular risk factors. Participants in this single-institution retrospective study underwent brain MRI to evaluate cognitive impairment between January-September 2023. For training the DL model, the nnU-Net framework was used without modifications. The DL model's performance was evaluated on independent internal and external validation datasets. Linear regression analysis was used to find associations between log-transformed CMB numbers, cognitive function (mini-mental status examination [MMSE]), white matter hyperintensity (WMH) burden, and clinical vascular risk factors (age, sex, hypertension, diabetes, lipid profiles, and body mass index). Training of the DL model (n = 287) resulted in a robust segmentation performance with an average dice score of 0.73 (95% CI, 0.67-0.79) in an internal validation set, (n = 67) and modest performance in an external validation set (dice score = 0.46, 95% CI, 0.33-0.59, n = 68). In a temporally independent clinical dataset (n = 448), older age, hypertension, and WMH burden were significantly associated with CMB numbers in all distributions (total, lobar, deep, and cerebellar; all P <.01). MMSE was significantly associated with hyperlipidemia (β = 1.88, 95% CI, 0.96-2.81, P <.001), WMH burden (β = -0.17 per 1% WMH burden, 95% CI, -0.27-0.08, P <.001), and total CMB number (β = -0.01 per 1 CMB, 95% CI, -0.02-0.001, P = .04) after adjusting for age and sex. The DL model showed a robust segmentation performance for CMB. In all distributions, CMB had significant positive associations with WMH burden. Increased WMH burden and CMB numbers were associated with decreased cognitive function. CMB = cerebral microbleed; DL = deep learning, DSC = dice similarity coefficient; MMSE = mini-mental status examination; SVD = small vessel disease; SWI = susceptibility-weighted image; WMH = white matter hyperintensity.

71 Development and validation of the COCINL scale assessing family resilience in the NICU among parents of preterm infants

Abstract Background Given the negative impact of parental distress on preterm infants and their families, examining the role of family resilience in the neonatal intensive care unit (NICU) is a promising avenue for promoting parental mental health while remaining consistent with family-centered care. A tool to assess NICU family resilience is essential to guide care and research, yet none specifically adapted for the neonatal context exists to date according to a recent systematic review. Objectives Therefore, the aim of this study was to develop and validate a new scale, the COCINL scale, designed to measure family resilience in the context of neonatal care among French-speaking parents of preterm infants. Design/Methods This methodological design study was carried out in four successive phases: (I) compilation of an item pool (II) mixed-method evaluation of content validity (clarity, relevance, representativeness) involving 12 experts, (III) pre-testing and electronic administration of the COCINL scale, along with a measure of psychological distress (Kessler-6) and an open-ended self-report question on family resilience to parents of preterm infants (n=88) and (IV) psychometric testing of the COCINL scale (internal consistency, construct validity, exploratory sensitivity and specificity). Parents of preterm infants and experts were recruited by convenience sampling from two urban, level III NICUs. Results From a pool of 112 items, 55 items were favorably evaluated after content validation (S-CVI&amp;gt;0.95). Based on preliminary interitem correlations and internal consistency results, the COCINL scale was shortened to 42 items and divided in four subscales. High internal consistency is also shown in subscales (0.796 to 0.908) and total scale (0.937) Cronbach’s alphas. The COCINL scale displays adequate construct validity, as determined by the Pearson correlation obtained between scores of family resilience and psychological distress (r=-0.236, p=0.027). Strong in between correlations of the four subscales and with the COCINL total score (0.732 to 0.851), further indicated good construct validity. Exploratory sensitivity and specificity analysis revealed the COCINL scale compares to participants' self-reported perception of family resilience (AUC 0.754). Conclusion The COCINL scale has shown strong evidence of validity and internal consistency. Thus, the scale can be recommended for research use as a measure of family resilience in the neonatal context. Still, additional evidence of its validity and reliability should be compiled before clinical use is considered. The COCINL scale could potentially support the development, evaluation and implementation of nursing interventions consistent with the family-centered care approach being promoted in NICUs across Canada and worldwide.

Significance of Image Reconstruction Parameters for Future Lung Cancer Risk Prediction Using Low-Dose Chest Computed Tomography and the Open-Access Sybil Algorithm.

Sybil is a validated publicly available deep learning-based algorithm that can accurately predict lung cancer risk from a single low-dose computed tomography (LDCT) scan. We aimed to study the effect of image reconstruction parameters and CT scanner manufacturer on Sybil's performance. Using LDCTs of a subset of the National Lung Screening Trial participants, which we previously used for internal validation of the Sybil algorithm (test set), we ran the Sybil algorithm on LDCT series pairs matched on kilovoltage peak, milliampere-seconds, reconstruction interval, reconstruction diameter, and either reconstruction filter or axial slice thickness. We also evaluated the cumulative effect of these parameters by combining the best- and the worst-performing parameters. A subanalysis compared Sybil's performance by CT manufacturer. We considered any LDCT positive if future lung cancer was subsequently confirmed by biopsy or surgical resection. The areas under the curve (AUCs) for each series pair were compared using DeLong's test. There was no difference in Sybil's performance between 1049 pairs of standard versus bone reconstruction filter (AUC at 1 year 0.84 [95% confidence interval (CI): 0.70-0.99] vs 0.86 [95% CI: 0.75-0.98], P = 0.87) and 1961 pairs of standard versus lung reconstruction filter (AUC at 1 year 0.98 [95% CI: 0.97-0.99] vs 0.98 [95% CI: 0.96-0.99], P = 0.81). Similarly, there was no difference in 1288 pairs comparing 2-mm versus 5-mm axial slice thickness (AUC at 1 year 0.98 [95% CI: 0.94-1.00] vs 0.99 [95% CI: 0.97-0.99], P = 0.68). The best-case scenario combining a lung reconstruction filter with 2-mm slice thickness compared with the worst-case scenario combining a bone reconstruction filter with 2.5-mm slice thickness uncovered a significantly different performance at years 2-4 (P = 0.03). Subanalysis showed no significant difference in performance between Siemens and Toshiba scanners. Sybil's predictive performance for future lung cancer risk is robust across different reconstruction filters and axial slice thicknesses, demonstrating its versatility in various imaging settings. Combining favorable reconstruction parameters can significantly enhance predictive ability at years 2-4. The absence of significant differences between Siemens and Toshiba scanners further supports Sybil's versatility.

Measurement properties of the Brazilian-Portuguese version of the PROMIS-29 questionnaire and the Impact Score in patients with chronic low back pain

BackgroundA task force from the US National Institute of Health aimed to establish parameters for surveys with patients with chronic low back pain (LBP) by recommending the use of the Patient-Reported Outcome Measurement Information System 29-item (PROMIS-29) questionnaire and the stratification according to the Impact Score. We aimed to assess the internal consistency, reliability, measurement error, construct validity and responsiveness of the Brazilian-Portuguese version of the PROMIS-29 questionnaire (version 2.1) and the Impact Score in patients with chronic LBP.MethodsA prospective cohort study was carried out with patients with chronic LBP who were receiving physiotherapy treatment in clinics in São Paulo and Vitória cities, Brazil. The sample included 102 patients with chronic LBP, aged between 18 and 80 years, and with the ability to read and write in the Brazilian-Portuguese language. Exclusion criteria were patients with serious spinal conditions, cognitive impairment, pregnant women, and patients who had undergone lumbar surgery within the past six months. The PROMIS-29 questionnaire, the 12-item Short-Form Health Survey and the Roland-Morris Disability Questionnaire were applied. The PROMIS-29 questionnaire was reapplied after 24 hours and 4 weeks.ResultsThe PROMIS-29 questionnaire showed Cronbach’s Alpha values between 0.81 (anxiety) and 0.91 (depression). The ICC2.1 ranged from 0.85 (95% CI: 0.77 to 0.89) to 0,97 (CI 95%: 0.95 to 0.98). The SEM values ranged between 0.85 (physical function) and 2.62 (ability to participate in social roles and activities). The Impact Score showed Cronbach’s Alpha, ICC2.1 and SEM values of 0.91, 0.97 (95% CI: 0.95 to 0.98) and 0.56, respectively. The PROMIS-29 questionnaire and the Impact Score showed sufficient construct validity. The PROMIS-29 questionnaire showed moderate responsiveness, while the Impact Score showed sufficient responsiveness.ConclusionsBoth the Brazilian-Portuguese version of the PROMIS-29 questionnaire and the Impact Score showed sufficient internal consistency, reliability, construct validity and responsiveness in Brazilian patients with chronic LBP. The results support the US National Institutes of Health’s recommendation to use the PROMIS-29 questionnaire and the Impact Score in patients with chronic LBP. We suggest that future studies evaluate the structural validity of the Brazilian-Portuguese version of the PROMIS-29 questionnaire.Clinical trial numberNot applicable.

Development and validation of a nomogram for sleep disorders among stroke patients

BackgroundPrecisely identifying high-risk sleep disorder patients and implementing suitable measures are important for decreasing the incidence of sleep disorders. In this study, a nomogram method was adopted to construct a tool to predict sleep disorders in stroke based on four factors: individual characteristics, treatment-related factors, psychological factors, and family-related factors. MethodsA total of 450 stroke patients were continuously diagnosed at the Affiliated Hospital of Nantong University, and the data on participants were randomly distributed into a training set (n = 315) and a validation set (n = 135). Within the training set, using LASSO regression and random forest methods, five optimal predictors of sleep disorders were identified. Five optimal predictors were used to develop a model. The calibration, discrimination, generalization, and clinical applicability of the model were evaluated using calibration curves, receiver operating characteristic (ROC) curves, internal validation, and decision curve analysis (DCA). ResultsWe found that the place of residence, average daily infusion time, the Hospital Anxiety and Depression Scale (HADS), the Type D Personality Scale-14 (DS14), and the Fatigue Severity Scale (FSS) were crucial factors associated with sleep disorders. The validation data showed an area under the curve (AUC) of 0.903 compared to 0.899 in the training set. There was an approach to the diagonal in the calibration curve of this model, and the results of DCA noted that it is clinically beneficial across a range of thresholds from 5 % to 99 %. ConclusionA model was developed to predict sleep disorders among stroke patients to help hospital staff evaluate the risk among patients and screen high-risk patients.

Development and validation of machine learning models for young-onset colorectal cancer risk stratification

Incidence of young-onset colorectal cancer (YOCRC, younger than 50) has significantly increased worldwide. The performance of fecal immunochemical test in detecting YOCRC is unsatisfactory. Using routine clinical data, we aimed to develop machine learning (ML) models to identify individuals with high-risk YOCRC who require further colonoscopy. We retrospectively extracted data of 10,874 young individuals. Multiple supervised ML techniques were devised to distinguish individuals with and without CRC, classifiers were trained, internally validated and temporally validated. In internal validation cohort, Random Forest (RF) ML model demonstrated good performance with AUC of 0.859 and highest recall of 0.840. In temporal validation cohort, the RF ML model also exhibited good classification performance, achieving AUC of 0.888 and highest recall of 0.872. RF algorithm-based approach is effective and feasible in YOCRC risk stratification. This could be valuable in assessing the risk of YOCRC so that clinical management, including further colonoscopy, can be subsequently made. (Registration: This study was registered with ClinicalTrials.gov (NCT06342622) on March 15, 2024.).

Internal structure validation of a teacher autonomy scale through confirmatory factor analysis

Purpose: Teacher autonomy is defined as the freedom of teachers to organize the learning and teaching process at school. The teaching autonomy scale measures teacher autonomy (Pearson &amp; Hall, 1993). This study was conducted to identify whether the measuring instrument of teacher autonomy meets the validity and reliability requirements of a measuring instrument. Method: The number of respondents in this study was obtained using a proportional sampling technique involving 170 respondents. The teacher autonomy measuring instrument produced from this study consists of 17 items that measure two dimensions; curriculum autonomy and general teaching autonomy. The quantitative data analysis techniques used were content-based validity tests through CVR and readability tests, validity evidence based on internal structure through CFA, and reliability tests based on homogeneity (internal consistency) through CR and AVE. Result: Shows CVR value with a minimum value of 0.78; loading factor ≥ 0.4, except for item 7 and item 8, as well as fit model fit with RMSEA = 0,077; RMR = 0,030; GFI = 0,847; CFI = 0,858; TLI = 0,797; NFI = 0,805; and p-value &lt; 0.05. reliability test through CR value (0.944) &gt; 0.7 and AVE (0.544) &gt; 0.4. Conclusion: The adaptation of the teacher autonomy measurement tool for female junior high school teachers met good validity and reliability values.

Computational Study of Coumarin Compounds as Potential Inhibitors of Casein Kinase 2: DFT, 2D-QSAR, ADMET and Molecular Docking Investigations

Casein kinase 2 (CK2) is an ubiquitous, essential, and highly pleiotropic protein kinase whose abnormally high constitutive activity is suspected to underlie its pathogenic potential in neoplasia and other diseases. Recently, there has been a notable increase in interest in the use of casein kinase 2 (CK2) inhibitors to improve the treatment of a specific form of cancer while minimizing the risk of undesirable side effects. Recently, using different virtual screening approaches, we have identified several novel CK2 inhibitors. In particular, we have discovered that the coumarin moiety can be considered an attractive CK2 inhibitor scaffold. In the present work, quantitative structure-activity relationship (QSAR) analysis has been employed to envisage the inhibitory effects of 32 coumarin derivatives on the CK2 protein. The most efficient model is found by using multiple linear regression (MLR). Its capability is considered by the external and internal validation values found (R2 = 0.884, Q2cv = 0.822, R2pred = 0.821, and R2p = 0.811), which aligned well with Tropsha and Golbraikh’s approach. The highest docking score founded for the newly designed coumarins is −7.50 kcal mol-1, which indicates that candidates can bind to the CK2 receptor with greater affinity. Based on the results of the ADMET properties and drug similarity analyses, a DFT investigation was conducted to confirm the stability of the newly explored compounds. It appears that the most stable complexes are those of compound with the highest binding affinity with a lower risk of toxicité.

Factores de riesgo y protección para la ideación e intento de suicidio en adolescentes y jóvenes latinoamericanos: revisión sistemática

Suicidal behavior is constituted as a public health problem, and the literature is recognized extensively for enunciating risk and protection factors associated with the attempt of suicide. The evaluation of the methodological quality of the primary studies is required by systematic reviews, thus guiding decision-making regarding the design of interventions from the risk approach. The identification of the risk and protective factors associated with suicidal ideation and attempts in adolescents and young people in Latin America studies and the evaluation of the methodological quality of the included studies were the objectives of this systematic review. The databases CUIDEN, LILACS, Pubmed, Scielo, Science Direct, SCOPUS, EBSCO, and Medline were consulted, with the results being restricted to articles in the last 10 years.A total of 3,642 documents were obtained, from which 19 studies were included. Of the studies, 52.63% (n=10) were found to have a medium internal validity level, and 57.89% (n=11) were determined to have a medium global quality level. The most frequently reported family risk factors were family dysfunction and suicide background, with other factors including the presence of mental disorder, psychoactive substances consumption, physical violence, sexual violence, and the social factor.On the other hand, the study of protective factors was found to be limited, with family functionality and support being the most frequently reported evidence.

Bridging Synchronous and Asynchronous Learning through English Presentation Course

This study investigated students' perceptions of synchronous and asynchronous learning in the context of English presentation skills. A qualitative descriptive design was employed, and data were collected from ten students enrolled in an English presentation course using convenience sampling. A semi-structured interview guide was developed to gather information from the participants' perspectives, ensuring they understood the study and their role in it. Thematic analysis was utilized to analyze the collected data, ensuring reliability and logical sorting of themes. To enhance internal validity, the interview guide was reviewed by experienced researchers, and both interviewers practiced the procedure to ensure consistency. Additionally, the resulting themes from the analysis were discussed with a different group of researchers to minimize potential biases. The study revealed that regular practice in forming simple past tense sentences and memorizing common irregular verbs are recommended and crucial for improving language skills. Contextual considerations are essential for choosing the correct tense. Synchronous learning encourages quick thinking, while asynchronous activities allow students to learn at their own pace and reinforce vocabulary. Consistent practice is crucial, and supplementing synchronous learning with asynchronous activities can enhance language skills. Asynchronous learning offers a valuable platform for pronunciation practice and enables students to progress at their own pace. These findings have practical implications for language educators, providing guidance on how to structure their teaching methods to best support their students' language learning.

Development and validation of a chronic kidney disease progression model using patient-level simulations

Chronic disease progression models are available for several highly prevalent conditions. For chronic kidney disease (CKD), the scope of existing progression models is limited to the risk of kidney failure and major cardiovascular (CV) events. The aim of this project was to develop a comprehensive CKD progression model (CKD-PM) that simulates the risk of CKD progression and a broad range of complications in patients with CKD. A series of literature reviews informed the selection of risk factors and identified existing risk equations/algorithms for kidney replacement therapy (KRT), CV events, other CKD-related complications, and mortality. Risk equations and transition probabilities were primarily sourced from publications produced by large US and international CKD registries. A patient-level, state-transition model was developed with health states defined by the Kidney Disease Improving Global Outcomes categories. Model validation was performed by comparing predicted outcomes with observed outcomes in the source cohorts used in model development (internal validation) and other cohorts (external validation). The CKD-PM demonstrated satisfactory modeling properties. Accurate prediction of all-cause and CV mortality was achieved without calibration, while prediction of CV events through CKD-specific equations required implementation of a calibration factor to balance time-dependent versus baseline risk. Predicted annual changes in estimated glomerular filtration rate (eGFR) and urine albumin-creatinine ratio were acceptable in comparison to external values. A flexible eGFR threshold for KRT equations enabled accurate prediction of these events. This CKD-PM demonstrated reliable modeling properties. Both internal and external validation revealed robust outcomes.

Translation and internal content validation of the Swedish version of the Brachial Assessment Tool (BrAT).

To translate and culturally adapt the Brachial Assessment Tool (BrAT) into Swedish and evaluate the internal consistency, and internal content validity using Rasch analysis in patients with traumatic brachial plexus injuries (TBPI). The translation was made in accordance with international guidelines. TBPI patients were identified in clinical records. The BrAT-Swe was sent out to patients by post. Internal consistency was assessed using Cronbach alpha and content validity using Rasch analysis evaluating fit to the Rasch model, threshold response, local dependency, dimensionality, differential item functioning (DIF), and targeting. The translation of the BrAT was completed without major discrepancies. A total of 164 patients completed the BrAT-Swe. Internal consistency ranged from 0.90 to 0.98. Rasch analysis supported the content validity. All subscales demonstrated fit to the model with no local dependency, minimal disordered thresholds and no unidimensionality. Uniform DIF for item 6 by age, was identified. Minimal differences in hierarchical ordering were identified. This study presents a Swedish translation of the BrAT (BrAT-Swe) and has demonstrated that the translated BrAT-Swe is well adapted for Swedish circumstances. Analysis supports the internal content validity of the BrAT-Swe as a unidimensional targeted PROM designed to assess activity limitation after TBPI.