High Predictive Value Research Articles

The Australian Traumatic Brain Injury Initiative: Systematic Review and Consensus Process to Determine the Predictive Value of Pre-existing Health Conditions for People with Moderate-Severe Traumatic Brain Injury.

The first aim of the Australian Traumatic Brain Injury Initiative (AUS-TBI) encompasses development of a set of measures that comprehensively predict outcomes for people with moderate-severe TBI across Australia. This process engaged diverse stakeholders and information sources across six areas: social, health, and clinical factors; biological markers; treatments; and longer-term outcomes. Here, we report the systematic review of pre-existing health conditions as predictors of outcome for people with moderate-severe TBI. Standardized searches were implemented across databases until March 31, 2022. English-language reports of studies evaluating association between pre-existing health conditions and clinical outcome in at least 10 patients with moderate-severe TBI were included. A predefined algorithm was used to assign a judgement of predictive value to each observed association. The list of identified pre-existing health conditions was then discussed with key stakeholders during a consensus meeting to determine the feasibility of incorporating them into standard care. The searches retrieved 22,217 records, of which 47 articles were included. The process led to identification of 88 unique health predictors (homologized to 21 predictor categories) of 55 outcomes (homologized to 19 outcome categories). Only pre-existing health conditions with high and moderate predictive values were discussed during the consensus meeting. Following the consensus meeting, 5 out of 11 were included (migraine, mental health conditions, ≥4 pre-existing health conditions, osteoporosis, and body mass index [BMI]) as common data elements in the AUS-TBI data dictionary. Upon further discussion, 3 additional pre-existing health conditions were included. These are pre-existing heart disease, frailty score, and previous incidence of TBI.

High positive predictive value 22q11.2 microdeletion screening by prenatal cell-free DNA testing that incorporates fetal fraction amplification.

22q11.2 deletion syndrome (DS) is a serious condition with a range of features. The small microdeletion causing 22q11.2DS makes it technically challenging to detect using standard prenatal cfDNA screening. Here, we assess 22q11.2 microdeletion clinical performance by a prenatal cfDNA screen that incorporates fetal fraction (FF) amplification. The study cohort consisted of patients who received Prequel (Myriad Genetics, Inc.), a prenatal cfDNA screening that incorporates FF amplification, and met additional eligibility criteria. Pregnancy outcomes were obtained via a routine process for continuous quality improvement. Samples with diagnostic testing results were used to calculate positive predictive value (PPV). 379,428 patients met study eligibility criteria, 76 of whom were screen-positive for a de novo 22q11.2 microdeletion. 22 (29.7%) had diagnostic testing results available, and all 22 cases were confirmed as true positives, for a PPV of 100% (95% CI 84.6%-100%). This performance was based on cases that ranged broadly across FF (5.9%-41.1%, mean 23.0%), body mass index (22.3-44.8, mean 29.9), and gestational age at testing (10.0w-34.6w, median 12.7w). Ultrasound findings in screen-positive pregnancies were consistent with those known to be associated with 22q11.2DS. 22q11.2 microdeletion screening that incorporates FF amplification demonstrated high PPV across both general and high-risk population cohorts.

Assessing the clinical diagnostic value of anti-Müllerian hormone in polycystic ovarian syndrome and its correlation with clinical and metabolism indicators

BackgroundThis study investigated the association between Anti-Müllerian Hormone (AMH) and relevant metabolic parameters and assessed its predictive value in the clinical diagnosis of polycystic ovarian syndrome (PCOS).MethodsA total of 421 women aged 20–37 years were allocated to the PCOS (n = 168) and control (n = 253) groups, and their metabolic and hormonal parameters were compared. Spearman correlation analysis was conducted to investigate associations, binary logistic regression was used to determine PCOS risk factors, and receiver operating characteristic (ROC) curves were generated to evaluate the predictive value of AMH in diagnosing PCOS.ResultsThe PCOS group demonstrated significantly higher blood lipid, luteinizing hormone (LH), and AMH levels than the control group. Glucose and lipid metabolism and hormonal disorders in the PCOS group were more significant than in the control group among individuals with and without obesity. LH, TSTO, and AMH were identified as independent risk factors for PCOS. AMH along with LH, and antral follicle count demonstrated a high predictive value for diagnosing PCOS.ConclusionAMH exhibited robust diagnostic use for identifying PCOS and could be considered a marker for screening PCOS to improve PCOS diagnostic accuracy. Attention should be paid to the effect of glucose and lipid metabolism on the hormonal and related parameters of PCOS populations.

Use of percutaneous mechanical circulatory support for right ventricular failure.

Utilization of right ventricular mechanical circulatory support (RV-MCS) devices has been limited by a lack of recognition of RV failure as well as a lack of availability and experience with RV-MCS. We report a single-center experience with the use of percutaneous RV-MCS and report predictors of adverse outcomes. This was a single-center retrospective cohort study. Data from consecutive patients who received RV-MCS for any indication between June 2015 and January 2022 were included. Data on baseline comorbidities, hemodynamics, and laboratory values were collected. The primary outcome was in-hospital mortality analyzed as a logistic outcome in a multivariable model. These variables were further ranked by their predictive value. Among 58 consecutive patients enrolled, the median age was 66 years, 31% were female and 53% were white. The majority of the patients (48%) were hospitalized for acute on chronic heart failure. The majority of the patients were SCAI SHOCK Stage D (67%) and 34 (64%) patients had MCS placed within 24 h of the onset of shock. Before placement of RV-MCS, median central venous pressure (CVP) and RV stroke work index were 20 mmHg and 8.9 g m/m2, respectively. Median serum lactate was 3.5 (1.6, 6.2) mmol/L. Impella RP was implanted in 50% and ProtekDuo in the remaining 50%. Left ventricular MCS was concomitantly used in 66% of patients. Twenty-eight patients (48.3%) died. In these patients, median serum lactate was significantly higher (4.1 [2.3, 13.0] vs. 2.2 [1.4, 4.0] mmol/L, p = 0.007) and a trend toward higher median CVP (24 [18, 31] vs. 19 [14, 24] mmHg, p = 0.052). In the multivariable logistic model, both serum lactate and CVP before RV-MCS placement were independent predictors of in-hospital mortality. Serum lactate had the highest predictive value. In our real-world cohort, 52% of patients treated with RV-MCS survived their index hospitalization. Serum lactate at presentation and CVP were the strongest predictors of in-hospital mortality.

Abnormal biochemical indicators of neonatal inherited metabolic disease in carriers

BackgroundTraditional biochemical screening for neonatal inherited metabolic diseases has high false-positive rates and low positive predictive values, which are not conducive to early diagnosis and increase parents’ anxiety. This study analysed the relationship between gene variant carriers and their biochemical indicators in traditional biochemical screening, aiming to find explanations for false positives in newborns.ResultsThis retrospective study included 962 newborns. Newborns underwent traditional biochemical screening at birth using blood staining and genomic sequencing of their stored blood staining using the NeoSeq Pro panel, which was able to detect 154 pathogenic genes and 86 diseases. A total of 632 newborns were carriers of gene variants. 56% of congenital hypothyroidism carriers had higher thyroid-stimulating hormone levels than normal newborns. Abnormal biochemical indices were detected in 71% of carriers of organic acid metabolic diseases, 69% of carriers of amino acid metabolic diseases, and 85% of carriers of fatty acid β oxidation disorders. In carriers associated with organic acid metabolic diseases, the propionylcarnitine (C3), C3/acetylcarnitine (C2), and methylmalonylcarnitine (C4DC) + 3-hydroxyisovalerylcarnitine (C5OH) levels were higher than those in non-carriers (C3: 4.12 vs. 1.66 µmol/L; C3/C2: 0.15 vs. 0.09; C4DC + C5OH: 0.22 vs. 0.19 µmol/L). In carriers associated with amino acid metabolic diseases, phenylalanine levels were higher than those in non-carriers (68.00 vs. 52.05 µmol/L). For carriers of fatty acid β oxidation disorders, butyrylcarnitine levels were higher than those in non-carriers (0.31 vs. 0.21 µmol/L), while the free carnitine levels were lower than those in non-carriers (14.65 vs. 21.87 µmol/L). There was a higher occurrence of carriers among newborns who received false-positive results for amino acid metabolic diseases compared to those who received negative results (15.52% vs. 6.71%). Similarly, there was a higher occurrence of carriers among newborns who received false-positive results for fatty acid β oxidation disorders compared to those who received negative results (28.30% vs. 7.29%).ConclusionsThis study showed that the carriers comprised a large number of newborns. Carriers had abnormal biochemical indicators compared with non-carriers, which could explain the false-positive rate for newborns using traditional newborn biochemical screening, especially in amino acid metabolic and fatty acid β oxidation disorders.

The predictive value of dynamic changes of neutrophil/lymphocyte ratio (NLR) combined with the model of end-stage liver disease (MELD) score in patients with acute-on-chronic hepatitis B liver failure

Objective: To determine the predictive value of dynamic changes of neutrophil/lymphocyte ratio (NLR) combined with the model of end-stage liver disease (MELD) score in patients with acute-on-chronic hepatitis B liver failure. Methods: Patients with acute-on-chronic hepatitis B liver failure who were hospitalized in the Department of Hepatology of Qilu Hospital of Shandong University from January 2010 to July 2023 were retrospectively enrolled. According to the clinical outcomes of patients within 30 days of admission, they were divided into the survival group and the death group. The dynamic changes in NLR and initial values on day 3, 5, 8, and 12 in two groups were analyzed for the diagnostic value of 30-day prognosis in patients with acute-on-chronic hepatitis B liver failure. Logistic regression analysis and machine learning XGBoost algorithm were used to evaluate the risk factors influencing the prognosis of patients at 30 days. Receiver operating characteristic(ROC) curve was used to evaluate the diagnostic value of NLR and initial value change combined with MELD score on day 12 of admission in patients with chronic acute hepatitis B liver failure. Results: A total of 243 patients were enrolled in the study, including 145 patients in the survival group [115 males, 30 females, aged 25-74 (47±11)] and 98 patients in the death group [80 males, 18 females, aged 22-80 (49±13) ]. The median initial NLR of survival group and death group were 3.5 (2.1, 5.3) and 4.9 (2.9, 8.3), respectively, and the difference was statistically significant (P=0.003). The variation of NLR from the initial value on day 3, 5, 8, and 12 in the survival group [1.6 (0, 4.3), 1.9 (-0.2, 4.1), 2.0 (-0.1, 4.3) and 2.9 (0.3, 7.0), respectively] were lower than that in the death group [3.2 (0.9, 7.5), 5.1 (1.8, 7.6), 5.8 (2.0, 10.6) and 9.6 (3.5, 16.4), respectively] (all P<0.001). Logistic regression multivariate analysis showed that the changes in NLR on the 12th day and initial value (OR=1.07,95%CI:1.01-1.14, P=0.014), the changes in NLR on the 3rd day and initial value (OR=2.71, 95%CI: 1.32-5.55, P=0.007), the initial value of NLR (OR=1.18,95%CI:1.01-1.37,P=0.035) and fibrinogen (OR=0.21,95%CI:0.05-0.96,P=0.044) were related factors for death within 30 days. Machine learning XGBoost algorithm showed that the weight of the change between the NLR on the 12th day and the initial value was the highest. The area under the ROC curve of the combined MELD score was 0.812 (95%CI: 0.728-0.895), the specificity was 67.78%, and the sensitivity was 82.35%. Conclusion: Dynamic change of NLR combined with MELD score has high predictive value for the short-term prognosis of patients with acute-on-chronic hepatitis B liver failure.

Validity of Prescription-Defined and Hospital-Diagnosed Hypertension Compared with Self-Reported Hypertension in Denmark.

Hypertension is an important risk factor in cardio-epidemiological research, but data quality remains a concern. We validated different registry-based definitions of hypertension. The cohort included all first-time responders of the Danish National Health Surveys (2010, 2013, or 2017). Prescription-defined hypertension was defined as ≥1 or ≥2 filled prescriptions of antihypertensive specific drugs in ≥1 or ≥2 different antihypertensive drug classes within 90, 180, or 365 days before survey response. Hospital-diagnosed hypertension was defined from hypertension diagnoses within five years before the survey response. Considering self-reported hypertension as the reference, we calculated the positive predictive value (PPV), the negative predictive value (NVP), the sensitivity, and the specificity of prescription-defined and hospital-diagnosed hypertension. Among 442,490 survey responders, 127,247 (29%) had self-reported hypertension. For prescription-defined hypertension with 365-day lookback, the PPV was highest for ≥2 prescriptions in ≥2 drug classes (94%) and lowest for ≥1 prescription in ≥1 drug class (85%). The NPV was highest for ≥1 prescription in ≥2 drug classes (94%) and lowest for ≥1 prescription in ≥2 drug classes (80%). The sensitivity was highest for ≥1 prescription in ≥1 drug class (79%) and lowest for ≥2 prescriptions in ≥2 drug classes (30%). The specificity was ≥94% for all algorithms. The PPV and specificity did not change noteworthy with length of lookback period, whereas the NPV and the sensitivity generally were higher for longer lookback. The algorithm ≥1 prescription in ≥2 drug classes with 365-day lookback was among the best balanced across all measures of validity (PPV=88%, NPV=94%, sensitivity=75%, specificity=96%). For hospital-diagnosed hypertension, the PPV was 90%, the NPV was 76%, the sensitivity was 22%, and the specificity was 99%. Compared with self-reported hypertension, the algorithms for prescription-defined and hospital-diagnosed hypertension had high predictive values and specificity, but low sensitivity.

Identification of risk factors of EGFR-TKIs primary resistance in lung adenocarcinoma patients and construction of a risk predictive model: a case-control study.

Lung cancer is one of the malignancies with the highest incidence and mortality rates. Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are recommended as the first-line treatment for patients with EGFR-mutated lung adenocarcinoma (LUAD). However, some patients with EGFR-sensitive mutations develop primary resistance to EGFR-TKIs. This study aims to analyze the clinical characteristics of LUAD patients with primary resistance to EGFR-TKIs, identify independent risk factors for primary resistance, and establish a risk predictive model to provide reference for clinical decision-making. We collected data from LUAD patients with EGFR-sensitive mutations (19del/21L858R) who were hospitalized in our institution between 2020 and 2022 and received first-generation EGFR-TKIs with follow-up exceeding 6 months. These patients were categorized into primary resistance and sensitive groups based on treatment outcomes. We compared general clinical data, laboratory tests, and tumor-related characteristics between the two groups, analyzed risk factors for primary resistance to EGFR-TKIs, and constructed a risk predictive model. The model's predictive value was comprehensively assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Serum neuron-specific enolase (NSE) concentration (P=0.03), serum pro-gastrin-releasing peptide (ProGRP) concentration (P=0.01), and Ki67 expression (P<0.001) were identified as independent risk factors for primary resistance to EGFR-TKIs in LUAD. The combined presence of these three risk factors had the highest predictive value [area under the curve (AUC) =0.975, P<0.001]. We constructed a predictive model for the risk of primary resistance to EGFR-TKIs in LUAD patients, incorporating these three parameters, and represented it through a visually interpretable nomogram. The calibration curve of the nomogram demonstrated its strong predictive ability. Further decision curve analysis indicated the model's clinical utility. Based on a single-center retrospective case-control study, we identified serum NSE concentration, ProGRP concentration, and Ki67 expression as independent risk factors for primary resistance to EGFR-TKIs in LUAD patients. We constructed and validated a risk predictive model based on these findings. This predictive model holds promise for clinical application, aiding in the development of personalized treatment strategies and providing a scientific basis for early identification of primary resistance patients.

Monopolar stereoelectroencephalography-guided radiofrequency thermocoagulation.

Stereoelectroencephalography (SEEG)-guided radiofrequency thermocoagulation (RFTC) has the advantage of producing a lesion in the epileptogenic zone (EZ) at the end of SEEG. The majority of published SEEG-guided RFTCs have been bipolar and usually performed between contiguous contacts of the same electrode. In the present study, the authors evaluate the safety, efficacy, and benefits of monopolar RFTC at the end of SEEG. This study included a series of 31 consecutive patients who had undergone RFTC at the end of SEEG for drug-resistant focal epilepsy in the period of January 2013-December 2019. Post-RFTC seizure control was assessed after 2 months and at the last follow-up visit. Twenty-one patients underwent resective epilepsy surgery after the SEEG-guided RFTC, and the postoperative seizure outcome among these patients was compared with the post-RFTC seizure outcome. Four hundred forty-six monopolar RFTCs were done in the 31 patients. Monopolar RFTCs were performed in all cortical areas, including the insular cortex in 11 patients (56 insular RFTCs). There were 31 noncontiguous lesions (7.0%) because of vascular constraints. The volume of one monopolar RFTC, as measured on T2-weighted MRI immediately after the procedure, was between 44 and 56 mm3 (mean 50 mm3). The 2-month post-RFTC seizure outcomes were as follows: seizure freedom in 13 patients (41.9%), ≥ 50% reduced seizure frequency in 11 (35.5%), and no significant change in 7 (22.6%). Seizure outcome at the last follow-up visit (mean 18 months, range 2-54 months) showed seizure freedom in 2 patients (6.5%) and ≥ 50% reduced seizure frequency in 20 patients (64.5%). Seizure freedom after monopolar RFTC was not significantly associated with the number or location of coagulated contacts. Seizure response after monopolar RFTC had a high positive predictive value (93.8%) but a low negative predictive value (40%) for seizure outcome after subsequent resective surgery. In this series, the only complication (3.2%) was a limited intraventricular hematoma following RFTC performed in the hippocampal head, with spontaneous resolution and no sequelae. The use of monopolar SEEG-guided RFTC provides more freedom in terms of choosing the SEEG contacts for thermocoagulation and a larger thermolesion volume. Monopolar thermocoagulation seems particularly beneficial in cases with an insular EZ, in which vascular constraints could be partially avoided by making noncontiguous lesions within the EZ.

Factors influencing the therapeutic failure of high-flow nasal cannula oxygen humidification in patients with interstitial pneumonia complicated by respiratory failure.

The aim of this study was to explore the factors influencing the treatment failure of high-flow nasal cannula (HFNC) therapy in patients with interstitial pneumonia (IP) complicated by respiratory failure. A total of 158 patients with IP and respiratory failure treated with HFNC in our hospital from January 2020 to August 2023 were selected as the study population. Based on treatment efficacy, they were categorized into the HFNC treatment failure group and the HFNC treatment success group. Clinical data were compared between the two groups. Multiple logistic regression analysis was employed to identify independent factors influencing treatment failure, and the predictive value of these factors for HFNC treatment failure was assessed using receiver operating characteristic (ROC) curve analysis. After 7 days of HFNC treatment, among the 158 patients with IP and respiratory failure, 25 (15.8%) declared treatment failure, while the remaining 133 (84.2%) showed treatment success. Patients in the HFNC treatment failure group had significantly higher age, duration of IP, pre-treatment respiratory rate, C-reactive protein (CRP), and controlling nutritional status (CONUT) scores compared to the HFNC treatment success group. The PaO2/FiO2 ratio, left ventricular ejection fraction, and Glasgow Coma Scale (GCS) were significantly lower in the HFNC treatment failure group (p<0.05). Multiple logistic regression analysis revealed that pre-treatment PaO2/FiO2 ratio, CRP, CONUT, and GCS scores were independent factors influencing HFNC treatment failure in patients with IP and respiratory failure (p<0.05). Lower PaO2/FiO2 ratio and GCS scores, and higher CRP and CONUT scores were associated with an increased risk of HFNC treatment failure. ROC curve analysis indicated that pre-treatment PaO2/FiO2 ratio, CRP, CONUT, and GCS scores in patients with IP and respiratory failure had a high predictive value for HFNC treatment failure (p<0.05). The HFNC failure rate in patients with IP and respiratory failure is 15.8%. Pre-treatment PaO2/FiO2 ratio, CRP, CONUT, and GCS scores are independent factors associated with HFNC treatment failure and warrant clinical attention.

Disulfidptosis-related lncRNA signature reveals immune microenvironment and novel molecular subtyping of stomach adenocarcinoma

The main challenge in treating stomach adenocarcinoma (STAD) is chemotherapy resistance, which is characterized by changes in the immune microenvironment. Disulfidptosis, a novel form of programmed cell death, is involved in STAD but its mechanism is not fully understood. Long non-coding RNAs (LncRNAs) may play a role in regulating disulfidptosis and influencing the immune microenvironment and chemotherapy resistance in STAD. This study aims to establish disulfidptosis-related lncRNA (DRL) features and explore their significance in the immune microenvironment and chemotherapy resistance in STAD patients. By analyzing RNA sequencing and clinical data from STAD patients and extracting disulfidptosis-related genes, we identified DRLs through co-expression, single-factor and multi-factor Cox regression, and Lasso regression analyses. We also investigated differences in the immune microenvironment, immune function, immune checkpoint gene expression, and chemotherapy resistance between different risk groups using various algorithms. A prognostic risk model consisting of 2 DRLs was constructed, with a strong predictive value for patient survival, outperforming other clinical-pathological factors in predicting 3-year and 5-year survival. Immune-related analysis revealed a strong positive correlation between T cell CD4+ cells and risk score across all algorithms, and higher expression of immune checkpoint genes in the high-risk group. In addition, high-risk patients showed better sensitivity to Erlotinib, Oxaliplatin, and Gefitinib. Furthermore, three novel molecular subtypes of STAD were identified based on the 2-DRLs features, with evaluation of the immune microenvironment and chemotherapy drug sensitivity for each subgroup, which holds significant implications for achieving precise treatment in STAD. Overall, our 2-DRLs prognostic model demonstrates high predictive value for patient survival in STAD, potentially providing new targets for individualized immune and chemical therapy.

Study on the construction of nomogram prediction model for prognostic assessment of heart failure patients based on serological markers and echocardiography.

We aimed to construct a nomogram prediction model for prognostic assessment of patients with heart failure (HF) based on serological markers and echocardiography. A total of 200 HF patients admitted to the Second Affiliated Hospital of Nanchang University from January 2018 to January 2020 were selected as the research objects. According to the New York Heart Association (NYHA) cardiac function classification, they were divided into 3 groups, including 65 cases of grade II, 97 cases of grade III, and 38 cases of grade IV. Three groups of echocardiographic parameters were compared [including left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDD), left ventricular end-systolic diameter (LVESD), left ventricular end-systolic volume (LVESV)], differences in serum markers brain natriuretic peptide (BNP), soluble growth-stimulating expression gene 2 (sST2) and the Modified Early Warning Score (MEWS). The patients were divided into two groups according to their clinical outcomes during the follow-up period, including 52 cases in the death group and 148 cases in the survival group. The clinical data of the two groups were compared, and multi-factor logistic regression analysis was performed to screen out the independent risk factors affecting the patient's death. A nomogram model of the patient's mortality risk was constructed based on the independent risk factors. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the discrimination and accuracy of the nomogram model. As the cardiac function class of elderly chronic heart failure (CHF) patients increases, LVEDD, LVESD, sST2, and MEWS increase and LVEF decreases (p<0.05). Multifactor analysis results showed that LVEF, LVEDD, sST2, and MEWS were independent factors affecting the clinical outcome of patients. The AUCs predicted using LVEF, LVEDD, sST2, and MEWS alone were 0.738, 0.775, 0.717, 0.831, and 0.768, respectively. There is a certain degree of discrimination, and the model has extremely high accuracy. MEWS, LVEDD, and sST2 increase as the NYHA cardiac function grade of HF patients increases and LVEF decreases, which can reflect the severity of the disease to a certain extent. Additionally, the nomogram model established based on this has a high predictive value for the long-term prognosis of patients and can formulate effective intervention measures for quantitative values.

Predictive value of anthropometric and biochemical indices in non-alcoholic fatty pancreas disease: a cross-sectional study

ObjectivesTriglyceride (TG), triglyceride-glucose index (TyG), body mass index (BMI), TyG-BMI and triglyceride to high-density lipoprotein ratio (TG/HDL) have been reported to be reliable predictors of non-alcoholic fatty liver disease. However,...

Incidence and Characteristics of Knee Ligament and Meniscal Injuries in Patients With Posterolateral Tibial Plateau Fractures.

Anterior cruciate ligament (ACL) tears are commonly seen with concomitant injuries to the posterolateral tibial plateau, while the occurrence of ACL injuries in posterolateral tibial plateau fractures (PTPFs) remains unclear. To (1) explore the incidence of knee ligament (anterior or posterior cruciate ligament, medial or lateral collateral ligament) and medial or lateral meniscus injuries in patients with PTPF and (2) find reliable PTPF-related parameters to predict the risk of knee ligament and meniscal injuries. Cross-sectional study; Level of evidence, 3. Patients diagnosed with PTPF who had computed tomography and magnetic resonance imaging (MRI) data were identified. Morphological parameters of the PTPF were measured on sagittal computed tomography images. Knee ligament and meniscal injuries were assessed using MRI. The association of ACL injuries with meniscal injuries was analyzed. Receiver operating characteristic (ROC) analysis was used to determine the value and cutoff point of the PTPF morphological parameters for diagnosing complete in-substance ACL tears. Overall, 113 patients with PTPF were included. ACL injuries were present in 94 (83.2%) patients, including 43 (38.1%) avulsion fractures and 28 (24.8%) complete in-substance tears. Patients with in-substance ACL tears had a higher incidence of lateral meniscus posterior horn tears compared with the other patients (PBonferroni < .001). ROC analysis revealed that both the fracture depression angle (cutoff point, 25.5°) and the posterior articular surface loss percentage (cutoff point, 37.5%) had a sensitivity >90% and a specificity >80% for the diagnosis of complete in-substance ACL tears. ACL injuries were seen in 83.2% of the study patients. Complete in-substance ACL tears were associated with an increased incidence of lateral meniscus posterior horn tears. Among PTPF parameters, fracture depression angle and posterior articular surface loss percentage showed a high predictive value for the presence of complete in-substance ACL tears, thereby reducing delays in diagnosis and treatment.

Validity of ICD-10-based algorithms to identify patients with influenza in inpatient and outpatient settings.

To evaluate the validity of ICD-10-CM code-based algorithms as proxies for influenza in inpatient and outpatient settings in the USA. Administrative claims data (2015-2018) from the largest commercial insurer in New Jersey (NJ), USA, were probabilistically linked to outpatient and inpatient electronic health record (EHR) data containing influenza test results from a large NJ health system. The primary claims-based algorithms defined influenza as presence of an ICD-10-CM code for influenza, stratified by setting (inpatient/outpatient) and code position for inpatient encounters. Test characteristics and 95% confidence intervals (CIs) were calculated using test-positive influenza as a reference standard. Test characteristics of alternative outpatient algorithms incorporating CPT/HCPCS testing codes and anti-influenza medication pharmacy claims were also calculated. There were 430 documented influenza test results within the study period (295 inpatient, 135 outpatient). The claims-based influenza definition had a sensitivity of 84.9% (95% CI 72.9%-92.1%), specificity of 96.3% (95% CI 93.1%-98.0%), and PPV of 83.3% (95% CI 71.3%-91.0%) in the inpatient setting, and a sensitivity of 76.7% (95% CI 59.1%-88.2%), specificity of 96.2% (95% CI 90.6%-98.5%), PPV of 85.2% (95% CI 67.5%-94.1%) in the outpatient setting. Primary inpatient discharge diagnoses had a sensitivity of 54.7% (95% CI 41.5%-67.3%), specificity of 99.6% (95% CI 97.7%-99.9%), and PPV of 96.7% (95% CI 83.3%-99.4%). CPT/HCPCS codes and anti-influenza medication claims were present for few outpatient encounters (sensitivity 3%-10%). In a large US healthcare system, inpatient ICD-10-CM codes for influenza, particularly primary inpatient diagnoses, had high predictive value for test-positive influenza. Outpatient ICD-10-CM codes were moderately predictive of test-positive influenza.

Optical Coherence Tomography Versus Optic Disc Photo Assessment in Glaucoma Screening.

Optical coherence tomography (OCT) and optic disc photography present valuable but distinct capabilities for glaucoma screening. This review article examines the strengths and limitations of OCT and optic disc photography in glaucoma screening. A comprehensive literature review was conducted, focusing on the accuracy, feasibility, cost-effectiveness, and technological advancements in OCT and optic disc photography for glaucoma screening. OCT is highly accurate and reproducible but faces limitations due to its cost and less portable nature, making widespread screening challenging. In contrast, optic disc photos are more accessible and cost-effective but are hindered by subjective interpretation and inconsistent grading reliability. A critical challenge in glaucoma screening is achieving a high PPV, particularly given the low prevalence of the disease, which can lead to a significant number of false positives. The advent of artificial intelligence (AI) and deep learning models shows potential in improving the diagnostic accuracy of optic disc photos by automating the detection of glaucomatous optic neuropathy and reducing subjectivity. However, the effectiveness of these AI models hinges on the quality of training data. Using subjective gradings as training data, will carry the limitations of human assessment into the AI system, leading to potential inaccuracies. Conversely, training AI models using objective data from OCT, such as retinal nerve fiber layer thickness, may offer a promising direction. Both OCT and optic disc photography present valuable but distinct capabilities for glaucoma screening. An approach integrating AI technology might be key in optimizing these methods for effective, large-scale screening programs.

High frequency of circulating non-classical monocytes is associated with stable remission in relapsing-remitting multiple sclerosis

‘No evidence of disease activity (NEDA)’, judged by clinical and radiological findings, is a therapeutic goal in patients with multiple sclerosis (MS). It is, however, unclear if distinct biological mechanisms contribute to the maintenance of NEDA. To clarify the immunological background of long-term disease stability defined by NEDA, circulating immune cell subsets in patients with relapsing-remitting MS (RRMS) were analyzed using flow cytometry. Patients showing long-term NEDA (n = 31) had significantly higher frequencies of non-classical monocytes (NCMs) (6.1% vs 1.4%) and activated regulatory T cells (Tregs; 2.1% vs 1.6%) than those with evidence of disease activity (n = 8). The NCM frequency and NCMs to classical monocytes ratio (NCM/CM) positively correlated with activated Treg frequency and duration of NEDA. Co-culture assays demonstrated that NCMs could increase the frequency of activated Tregs and the expression of PD-L1, contributing to development of Tregs, was particularly high in NCMs from patients with NEDA. Collectively, NCMs contribute to stable remission in patients with RRMS, possibly by increasing activated Treg frequency. In addition, the NCM frequency and NCM/CM ratio had high predictive values for disease stability (AUC = 0.97 and 0.94, respectively), suggesting these markers are potential predictors of a long-term NEDA status in RRMS.

The Ratio of Serum Urea Nitrogen to Albumin Is a Better Predictor of Overall Survival in Multiple Myeloma Patients than Urea Nitrogen Alone

Introduction: Multiple myeloma (MM) is a malignant proliferative disease of plasma cells. Abnormally cloned plasma cells secrete large amounts of monoclonal immunoglobulins in the bone marrow of MM patients. Serum urea nitrogen (sUN) is a byproduct of protein metabolism, and its effect on MM patients’ prognoses remains unknown. Therefore, we analyzed MM patients’ clinical data to explore the role of sUN and sUN/serum albumin (sUAR) in the baseline tumor load and MM prognosis of MM patients. Methods: We downloaded the clinical data of 762 MM patients from the MMRF database. After excluding those without baseline sUN, 452 patients were finally included in the study. Smoothed curve fitting, threshold analysis, Tamhane’s T2 test, multivariate-adjusted Cox regression analysis, Kaplan-Meier (K-M) curves, and receiver operating characteristic (ROC) analysis were applied in the study. Results: There were 452 newly diagnosed MM patients included in this study. In most patient groups, sUN and sUAR were positively linked with β2-microglobulin (β2-MG) and lactic dehydrogenase (LDH) according to smoothing curve fitting and threshold analysis. The higher the ISS stage, the greater the values of sUN and sUAR. Furthermore, smoothed curve fitting and threshold analysis showed that sUN was correlated with overall survival (OS), although sUAR had a stronger correlation with OS and could be applied to a broader group. The results of a multivariate-adjusted Cox regression analysis demonstrated that sUN and sUAR were independent prognostic factors for OS. The K-M curve confirmed the correlation between higher sUN and sUAR levels and worse OS. β2-MG and LDH are generally recognized prognostic factors of OS. ROC analysis revealed that sUN might boost β2-MG and LDH’s predictive value and sUAR had a higher predictive value. Conclusion: This retrospective study based on the MMRF database showed that high sUN and sUAR levels were positively associated with β2-MG, LDH, and ISS staging, and sUAR exhibited a stronger correlation with OS than sUN alone.

The importance of combined HPV and CINtec® PLUS genotyping testing for p16 in women with cervical squamous cell carcinoma.

Immunohistochemistry (IHC) for p16INK4A (p16) is a reliable surrogate test for the presence of a high-risk, potentially transformative human papillomavirus (HPV) infection in precursor and malignant lesions of the cervix. The purpose of this study was to evaluate changes in cervical cells caused by persistent HPV infection, by IHC (p16 protein) by comparison with HPV genotyping. The study included female patients aged between 26 and 57 years who presented to a public hospital, with complaints related to the genital area, namely vaginal bleeding and dyspareunia. After selecting the patients, samples were subjected to cytological testing and IHC for p16 and for the determination of HPV types. The relationship between HPV status and p16 status was statistically significant (p=0.0001), of the 41 patients, 53.7% were HPV positive, respectively 56.1% were p16 positive, the agreement relationship between the two indicators was very high (weighted kappa: 0.951). The clinical performance of CINtec® PLUS triage for p16 shows a high positive predictive value (PPV) and a high negative predictive value (NPV) of 95.7% and 100%, respectively, as regards HPV. The p16 marker (CINtec® PLUS) can be used as a prognostic biomarker and provides clinical usefulness through increased sensitivity (Se) and specificity (Sp) in the triage of women at risk of developing precancerous lesions, compared to cytology that is based on morphology, but has a rather low Se and high Sp, while HPV testing is very sensitive but slightly more specific.

Abstract 6186: Histopathology-derived molecular portrait of serous ovarian cancer

Abstract Background: The progression of ovarian cancer (OV) is often evaluated through clinical staging and molecular profiling of genomic alterations and subtypes, with the molecular profiling of tumors playing a crucial role in cancer management by informing therapeutic decisions. However, collecting molecular data is expensive, time-consuming, and can be sensitive to sample handling protocols. These factors prevent routine implementation at many care centers, thereby limiting benefit to patients. This work examines the viability of an image-centric method for inferring molecular endophenotypes and predicting overall survival in OV, leveraging commonly gathered histopathology scans. Methods: Embedding representations of digitized Hematoxylin and Eosin slides were produced using a self-supervised histology model. First, we assessed the ability of the embeddings to predict overall survival using Cox proportional hazards models by calculating the concordance index. Next, these embeddings served as input features to machine learning models trained to predict genomic patterns within tumors, including molecular subtypes, driver gene alterations, and mutational processes, leading to a more comprehensive analysis of the prognostic potential of our approach. Results: Histopathological embeddings were found to be more predictive of patient survival than traditional factors such as age, histological grade, and clinical stage. Embedding risk combined with clinicopathological risk had a higher predictive value than clinicopathological risk alone (0.578 vs 0.569, p = 0.025). Moreover, embedding risk alone was more predictive of survival (0.577 vs 0.569, p = 0.038). Risk scores derived from embeddings and all clinicopathological features were uncorrelated (R = 0.03), indicating that embeddings provide unique prognostic information. Motivated by these findings, we investigated the reasons behind the enhanced accuracy in survival prediction. We found that models trained on embeddings predicted previously defined molecular subtypes (TCGA, 2011), achieving area under the receiver operating characteristic curve (AUROC) scores as follows: Differentiated (0.86), Immunoreactive (0.85), Mesenchymal (0.9), and Proliferative (0.89). Similarly, our models identified crucial oncogenic events, including the loss of TP53 and CDKN2A, and instances of whole genome duplication (AUROCs of 0.85, 0.99 and 0.8). Conclusions: Taken together, this work showcases the potential utility of standard of care digitized histopathology scans for imputing genomic patterns and predicting overall survival in OV. Our results suggest that imputation could provide a fast and scalable solution for deploying patient screening biomarkers, thereby playing a pivotal role in shaping the future of precision medicine. Citation Format: Yajas Shah, Zachary R. McCaw, Anna Shcherbina, Christopher Probert. Histopathology-derived molecular portrait of serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6186.