BACKGROUND: The timely allocation of appointments for new patients is a daily challenge in rheumatological practice, which can be supported by digital solutions. The question is to find the simplest and most effective possible method for prioritization when allocating appointments.
METHODS: Using a registration form for new patients, standardized symptoms and laboratory results were collated. After reviewing this information by a medical specialist the allocation of appointments was carried out in three categories: a) < 6 weeks, b) 6 weeks up to 3 months and c) > 3 months. The waiting time between the time of registration and the presentation appointment was calculated and compared between patients with and without a diagnosis of an inflammatory rheumatic disease (IRD). In addition a decision tree (DT), a method taken from the field of supervised learning within artificial intelligence (AI), was established and the resulting classification was compared with respect to the accuracy and calculated saving in waiting time.
RESULTS: In this study 800 appointments between 2020 and 2023 (including 555 women, 69.4%, median age 53 years, interquartile range, IQR 39-63 years) were analyzed. An IRD could be confirmed in 409 (51.1%) cases with a waiting time of 58 vs. 93 days for non-IRD cases (-38%, p < 0.01). An AI-based stratification resulted in an accuracy of 67% for IRD and a predicted saving of 19% waiting time. The accuracy increased up to 78% with a time saving for IRD cases of up to 31%, when all basic laboratory results were known. Simplified algorithms, e.g., stratification by the use of laboratory findings alone, resulted in a lower accuracy and time savings.
CONCLUSIONS: Manual allocation of appointments by a medical specialist is effective and significantly reduces the waiting times for patients with IRD. An automated categorization can lead to a reduction in waiting times for appointments when taking complete laboratory results and a lower sensitivity into consideration.
UNASSIGNED: HINTERGRUND: Die zeitnahe Terminvergabe für Neuvorstellungen ist eine tägliche Herausforderung in der rheumatologischen Praxis, die von digitalen Lösungen unterstützt werden kann. Es stellt sich die Frage nach einer möglichst einfachen und effektiven Methode der Terminpriorisierung.
METHODS: Mithilfe eines Anmeldeformulars für Neuvorstellungen wurden standardisiert Symptome und Laborbefunde erfasst. Die Terminvergabe erfolgte nach fachärztlicher Sichtung dieser Informationen in 3 Kategorien: (a) < 6 Wochen, (b) 6 Wochen bis 3 Monate und (c) > 3 Monate. Die Wartezeiten zwischen dem Zeitpunkt der Anmeldung und dem Vorstellungstermin wurden berechnet und verglichen zwischen Patienten mit und ohne Diagnose einer entzündlich-rheumatischen Erkrankung (ERE). Zusätzlich wurde ein Entscheidungsbaum, eine Methode aus dem Bereich des überwachten Lernens innerhalb der künstlichen Intelligenz (KI), erstellt und die resultierende Klassifikation bezüglich Trefferrate und berechneter Wartezeitersparnis verglichen.
UNASSIGNED: Insgesamt wurden 800 Fälle (darunter 555 Frauen [69,4 %], medianes Alter 53 Jahre [IQA 39–63]) zwischen 2020 und 2023 ausgewertet. Eine ERE konnte in 409 (51,1 %) Fällen bestätigt werden mit einer Wartezeit von 58 vs. 93 Tagen bei Non-ERE-Fällen (−38 %, p < 0,01). Eine KI-Stratifizierung ergab eine Trefferrate von 67 % bezüglich einer ERE und eine prognostizierte Einsparung von 19 % Wartezeit. Die Trefferrate stieg hierbei auf 78 % mit einer Zeitersparnis für ERE-Fälle um bis zu 31 %, wenn grundlegende Laborergebnisse bekannt waren. Andererseits ergaben vereinfachte Algorithmen z. B. durch eine reine Laborwert-basierte Stratifizierung eine niedrigere Trefferrate und Zeitersparnis.
UNASSIGNED: Die fachärztliche Terminzuweisung ist effektiv und verkürzt die Terminwartezeit für Patienten mit ERE signifikant. Eine automatisierte Kategorisierung kann unter Berücksichtigung vollständiger Laborwerte mit reduzierter Sensitivität zu einer Verkürzung der Terminwartezeit führen.

OBJECTIVE: To evaluate the predictive power of the high-sensitivity C-reactive protein (hs-CRP) to albumin (Alb) ratio for cardiovascular events in patients receiving maintenance hemodialysis (MHD) for end-stage renal disease (ESRD).
METHODS: This retrospective study enrolled 202 ESRD patients undergoing MHD at Bobai County People\'s Hospital from November 2020 to November 2022, with follow-up extending to November 2023. Patients were divided into two groups based on the occurrence of cardiovascular events during follow-up: the occurrence group (n = 92) and the non-occurrence group (n = 110). Clinical data were compared between these groups. Independent risk factors for cardiovascular events post-MHD were identified using a multivariate logistic regression model. The hs-CRP/Alb ratio\'s predictive utility was assessed through receiver operating characteristic (ROC) curve analysis, establishing an optimal cutoff value. A decision tree prediction model was developed to further delineate the probability of cardiovascular events.
RESULTS: The occurrence group was older and had a longer duration of dialysis compared to the non-occurrence group (P < 0.05). They also showed a higher prevalence of diabetic and hypertensive nephropathy and a higher proportion of smokers (all P < 0.05). Notably lower levels of hemoglobin (HGB), triglycerides, total cholesterol, low-density lipoprotein, albumin (Alb), and calcium were detected (all P < 0.05), whereas β2-microglobulin (β2-mg), hs-CRP, phosphorus, and the hs-CRP/Alb ratio were markedly increased (all P < 0.05). Multivariate analysis revealed diabetic nephropathy or hypertensive nephropathy, a high hs-CRP/Alb ratio, and elevated phosphorus levels as risk factors for cardiovascular events, while high hemoglobin levels were protective (P < 0.05). The ROC analysis indicated the hs-CRP/Alb ratio (AUC = 0.884) outperformed other predictors with an optimal cutoff at 0.111. Patients with a hs-CRP/Alb ratio ≥ 0.111 were found to have a 29-fold increased risk of cardiovascular events (95% CI: 11.304-74.842).
CONCLUSIONS: The hs-CRP/Alb ratio is a significant predictive biomarker for cardiovascular events in ESRD patients undergoing MHD. An elevated hs-CRP/Alb ratio is associated with an increased risk of cardiovascular events, underscoring its utility in this patient population.

OBJECTIVE: To analyze the predictive value of lipoprotein-associated phospholipase A2 (Lp-PLA2), N-terminal prohormone of brain natriuretic peptide (NT-proBNP), and peripheral blood-related ratios at the initial diagnosis for heart failure (HF) after early-onset infarction in patients with acute myocardial infarction (AMI).
METHODS: This retrospective analysis included 151 patients first diagnosed with AMI at Xianyang Central Hospital from February 2020 to February 2023. Patients were classified into two groups: those who developed HF during hospitalization (HF group, n=45) and those who did not (non-HF group, NHF, n=106). Differences in Lp-PLA2, NT-proBNP, and peripheral blood ratios at initial diagnosis were compared between the groups. Binary logistic regression was used to identify independent risk factors for HF, and a nomogram model was developed based on these factors.
RESULTS: HR (P=0.032), C-reactive protein (CRP) (P<0.001), alanine aminotransferase (ALT) (P=0.015), coronary artery lesion score (CALDS) (P<0.001), D-dimer (D-D) (P=0.021), neutrophil-to-lymphocyte ratio (NLR) (P<0.001), Lp-PLA2 (P<0.001), and NT-proBNP (P<0.001) were significantly higher in the HF group than in the NHF group. Left ventricular end-systolic diameter (LVESD) (P<0.001) and left ventricular end-diastolic diameter (LVEDD) (P<0.001) were significantly lower in the HF group. Multifactorial logistic regression identified HR (P=0.034), CRP (P=0.028), CALDS (P=0.007), NLR (P=0.001), Lp-PLA2 (P=0.001), and NT-proBNP (P=0.002) as independent predictors of HF. The AUCs for NLR, Lp-PLA2, and NT-proBNP were 0.806, 0.849, and 0.780, respectively. The nomogram model achieved an AUC of 0.964, significantly outperforming individual indicators per Delong\'s test, highlighting its superior predictive efficacy.
CONCLUSIONS: HR, CRP, CALDS, NLR, Lp-PLA2, and NT-proBNP were identified as independent predictors of HR post-AMI myocardial infarction. The constructed nomogram model provides an effective tool for early clinical identification of high-risk patients, potentially improving prognosis and guiding therapeutic strategies.

BACKGROUND: Premature coronary artery disease (PCAD) is prevailing. We aimed to investigate the evaluation value of atherogenic index of plasma (AIP) and high-sensitivity C-reactive protein (hs-CRP) for the occurrence and severity of coronary artery lesion in PCAD patients.
METHODS: PCAD (PACD group)/non-PCAD (control group) patients were enrolled. The coronary artery lesion degree was evaluated using Gensini score (GS). PCAD patients were allocated into the low/medium/high GS groups, with general clinical baseline data analyzed. Plasma hs-CRP/AIP levels were compared in PCAD patients with different disease degree. Correlations between plasma hs-CRP/AIP with Gensini score, independent risk factors affecting the occurrence of PCAD, and the predictive value of hs-CRP/AIP/their combination for the occurrence and degree of PCAD were evaluated by Spearman correlation analysis/Logistic multivariate regression/receiver operating characteristic (ROC) curve. The differences in the area under the curve (AUC) were compared using MedCalc-Comparison of ROC curves.
RESULTS: Plasma hs-CRP/AIP levels in the PCAD group were increased. Plasma hs-CRP/AIP levels varied significantly among PCAD patients with different disease degree. Plasma hs-CRP/AIP levels were markedly positively correlated with the Gensini score. Smoking history/homocysteine/fasting blood-glucose/hs-CRP/AIP were all independent risk factors affecting PCAD occurrence. The AUC of hs-CRP and AIP combination predicting the occurrence of PCAD was 0.950 (90.80% sensitivity/93.33% specificity). hs-CRP/AIP combination assisted in predicting the disease degree in PCAD patients.
CONCLUSIONS: AIP and hs-CRP are independent risk factors for the occurrence of PCAD, and their combination has high predictive value for PCAD occurrence and disease degree, which are both positively correlated with coronary artery lesion degree.

BACKGROUND: Cell-free fetal DNA (cffDNA) screening is routinely performed in pregnancy. Abnormal fetal fraction has been associated with adverse pregnancy outcomes, including hypertensive disorders of pregnancy, which are associated with severe maternal and neonatal morbidity and mortality.
OBJECTIVE: This study examined whether abnormal fetal fraction, defined in this study as fetal fraction either <6 or >15 on the basis of restricted-cubic-spline-plot within our study population, was associated with HDP in a retrospective sample, as well as whether fetal fraction improves the prediction of hypertensive disorders of pregnancy (HDP). We hypothesized that abnormal fetal fraction would be associated with HDP and that adding fetal fraction to a model would significantly improve its strength to predict HDP.
METHODS: This was a retrospective cohort study of 729 patients delivering singleton, non-anomalous pregnancies with conclusive cffDNA screening. The primary outcome was HDP. Logistic regression models tested associations between fetal fraction and HDP. We evaluated the impact of including fetal fraction on the prediction of hypertensive disorders of pregnancy (HDP) by comparing the area under the receiver operating characteristic (ROC) curve (AUC) between predictive models with and without fetal fraction.
RESULTS: Among the study sample, there was an HDP rate of 11.5 %. Abnormal fetal fraction was defined as <6 % percentile and >15 %, HDP incidence was significantly higher in patients with fetal fraction <6 % compared to patients with fetal fraction in normal range (fetal fraction 6-15 %) (19.5 % vs 10.7 %, p = 0.006 on post hoc comparison). Model 1 had one predictor (fetal fraction) with an AUC of 0.59, Model 2 had three predictors (BMI, nulliparity, history of HDP) with an AUC of 0.71, and Model 3 had four predictors (BMI, nulliparity, history of HDP, and fetal fraction) with an AUC of 0.73. Models 2 and 3 were not significantly different (p = 0.18).
CONCLUSIONS: More patients who developed HDP had low fetal fraction and fewer patients who developed HDP had high fetal fraction compared to those patients who did not develop HDP. Based on results from multivariable regression models, we cannot conclude that fetal fraction improves HDP prediction. However, developing standardized values for abnormal fetal fraction may be clinically useful.

UNASSIGNED: By evaluating the level of serum procalcitonin (PCT), thromboelastography (TEG) and platelet count (PLT) of patients with septic shock in intensive care unit (ICU), the predictive value of the combination of the three indicators on the short-term progression was discussed, which provided a new basis for early clinical diagnosis and disease evaluation.
UNASSIGNED: The clinical data of 130 patients with septic shock admitted to the IUC of our hospital from December 2021 to December 2023 were analyzed retrospectively. These subjects were divided into good prognosis group (n=78) and poor prognosis group (n=52) according to the 28 d deaths. The influencing factors were explored using the Multivariate logistic regression analysis. The value of single or combined PCT, PLT and TEG in predicting poor short-term prognosis was assessed using the receiver operating characteristic (ROC) curve.
UNASSIGNED: The patients in poor prognosis group had higher Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, serum PCT level, coagulation reaction time (R value) and coagulation formation time (K value), but lower PLT levels, final strength of coagulation (MA value) and coagulation formation rate (α angle) than those in good prognosis group (P<0.001). PCT, R value and K value were risk factors (P<0.001), while PLT, MA value and α angle were protective factors (P<0.001). The area under the curve (AUC) of PCT, PLT and TEG predicting poor short-term progression was 0.813, 0.658 and 0.752, respectively. The AUC of combined three indicators was 0.905, which had the highest predictive value.
UNASSIGNED: Serum levels of PCT, PLT and TEG had certain value in predicting poor short-term progression of septic shock patients, and their combined diagnostic value was higher. Therefore, regular monitoring of these three indicators could provide certain guiding significance for the prevention and treatment of poor short-term prognosis in patients with septic shock.

UNASSIGNED: The POSSUM scoring system, widely employed in assessing surgical risks, offers a simplified and objective approach for the prediction of complications and mortality in patient. Despite its effectiveness in various surgical fields, including orthopedics and cardiovascular surgery, yet its utilization in elderly patients undergoing colorectal cancer surgery is infrequent.
UNASSIGNED: To analyze the predictive value of POSSUM scoring system for postoperative complications and mortality in elderly with colorectal cancer.
UNASSIGNED: 306 elderly colorectal cancer patients were grouped according to the complications and death within 30 days after surgery. Among them, 108 cases in complication group, 198 cases in non-complication group, 16 cases in death group and 290 cases in survival group. POSSUM scores of all subjects were obtained and its predictive value for postoperative complications and mortality of elderly was conducted by ROC curve.
UNASSIGNED: No apparent difference were observed in complications and mortality among patients with different disease types, operation types and operation timing (P> 0.05). The R2 in complication group was higher than non-complication group (P< 0.05). The R1 in death group were higher than survival group (P< 0.05). The AUC of R2 for predicting postoperative complications was 0.955 with a sensitivity of 88.89% and a specificity of 94.44% and the AUC of R1 for evaluating postoperative mortality of elderly with colorectal cancer was 0.783 with a sensitivity of 56.25% and a specificity of 82.93%.
UNASSIGNED: POSSUM score system has a certain predictive value for postoperative complications and mortality in elderly with colorectal cancer. However, the predicted mortality rate is higher than actual mortality rate.

OBJECTIVE: This study aimed to predict the bronchopulmonary dysplasia (BPD) in preterm infants with a gestational age(GA) < 32 weeks utilizing clinical data, serum mediator complex subunit 1 (MED1), and serum peroxisome proliferator-activated receptor gamma coactivator-1alpha (PGC-1α).
METHODS: This prospective observational study enrolled 70 preterm infants with GA < 32 weeks. The infants were categorized into two groups: non-BPD group(N = 35) and BPD group(N = 35), including 25 cases with mild BPD and 10 patients with moderate/severe subgroups. We performed multifactorial regression analysis to investigate the postnatal risk factors for BPD. Furthermore, we compared serum levels of biomarkers, including MED1 and PGC-1α, among infants with and without BPD at postnatal days 1, 7, 14, 28, and PMA 36 weeks. A logistic regression model was constructed to predict BPD\'s likelihood using clinical risk factors and serum biomarkers.
RESULTS: Serum levels of MED1 on the first postnatal day, PGC-1α on the 1st, 7th, and 28th days, and PMA at 36 weeks were significantly lower in the BPD group than in the non-BPD group (P < 0.05). Furthermore, the predictive model for BPD was created by combing serum levels of MED1 and PGC-1α on postnatal day 1 along with clinical risk factors such as frequent apnea, mechanical ventilation time > 7 d, and time to reach total enteral nutrition. Our predictive model had a high predictive accuracy(C statistics of 0.989) .
CONCLUSIONS: MED1and PGC-1α could potentially serve as valuable biomarkers, combined with clinical factors, to aid clinicians in the early diagnosis of BPD.

Background: To investigate the predictive value of preoperative peripheral blood inflammatory markers for surgical site infection (SSI) in laparoscopic radical gastrectomy for gastric cancer. Methods: A retrospective analysis was conducted on patients undergoing laparoscopic radical gastrectomy for gastric cancer, categorized into SSI and non-SSI groups based on postoperative SSI occurrences. Patient demographics, surgical details, laboratory results, and SSI incidence data were extracted. Differences in indicators, including neutrophil-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and platelet-lymphocyte ratio (PLR), were assessed between the two groups. Multivariate logistic regression was utilized to determine the independent association of each indicator with SSI. Receiver operating characteristics (ROC) curve analysis was utilized to evaluate the predictive value of parameters. Results: Of 169 patients, 36 (21.30%) experienced SSI postoperatively. The SSI group exhibited higher preoperative NLR and SII (p < 0.05). After adjusting for variables, preoperative NLR (OR = 1.691, 95% CI: 1.211-2.417, p = 0.003) and SII (OR = 1.001, 95% CI: 1.000-1.002, p = 0.006) were identified as independent risk factors for SSI. Both NLR (AUC = 0.758, 95% CI: 0.666-0.850) and SII (AUC = 0.753, 95% CI: 0.660-0.850) demonstrated favorable diagnostic performance for predicting postoperative SSI. Conclusion: Preoperative NLR and SII significantly associate with postoperative SSI in laparoscopic radical gastrectomy for gastric cancer, making them valuable indicators for early prediction of SSI.

Aim: There is a lack of data about the association between admission serum albumin levels and long-term mortality in heart failure (HF) patients with cardiac resynchronization therapy defibrillators (CRT-D). We aim to investigate this connection in HF patients with CRT-D. Methods: The study population consisted of 477 HF patients with CRT-D. The cohort was divided into three groups according to albumin values, and the relationship between these groups and long-term mortality were evaluated. Results: Long-term all-cause mortality (HR: 3.32, 95% CI: 2.12-6.84), appropriate (HR: 4.44, 95% CI: 2.44-8.06) and inappropriate (HR: 2.95, 95% CI: 1.88-6.02) shocks were higher in the low albumin group. Conclusion: Low albumin levels are associated with the long-term mortality and appropriate shock treatment in HF patients with CRT-D.
[Box: see text].