Laboratory Indicators Research Articles

The predictive value of nomogram for adnexal cystic-solid masses based on O-RADS US, clinical and laboratory indicators

The predictive value of nomogram for adnexal cystic-solid masses based on O-RADS US, clinical and laboratory indicators

A novel prediction model for the prognosis of non-small cell lung cancer with clinical routine laboratory indicators: a machine learning approach

A novel prediction model for the prognosis of non-small cell lung cancer with clinical routine laboratory indicators: a machine learning approach

A delphi-based model for prognosis of femoral head collapse in osteonecrosis: a multi-factorial approach.

Osteonecrosis of the femoral head (ONFH) is a progressive and debilitating condition characterized by the death of bone tissue due to inadequate blood supply. Despite advances in diagnostic imaging and treatment strategies, predicting the risk of femoral head collapse remains a significant clinical challenge. This study seeks to address this gap by developing a robust prognostic model that integrates clinical, imaging, and laboratory data to improve early diagnosis and guide therapeutic decision-making. We conducted a qualitative systematic review and employed the Delphi method to select key prognostic factors from clinical data, imaging findings, and laboratory indicators. The study included ONFH patients treated from January 2014 to December 2021. We used univariate and multivariate Cox regression analyses to develop a nomogram for predicting the risk of femoral head collapse. The model's performance was evaluated using the concordance index (C-index), calibration plots, and decision curve analysis (DCA). The study included 297 patients (454 hips) with ONFH. Key prognostic factors identified included pain presence (p < 0.001, RR = 0.185, 95% CI: 0.11-0.31), JIC classification (C1: p < 0.001, RR = 0.096, 95% CI: 0.054-0.171; C2: p < 0.001, RR = 0.323, 95% CI: 0.215-0.487), necrotic area (3 < MNAI < 6: p < 0.001, RR = 0.107, 95% CI: 0.061-0.190; MNAI ≥ 6: p < 0.001, RR = 0.466, 95% CI: 0.314-0.692), weight-bearing reduction (p < 0.001, RR = 0.466, 95% CI: 0.323-0.672), preservation of the anterolateral pillar (p < 0.001, RR = 0.223, 95% CI: 0.223-0.473), and subchondral bone fracture on CT (p < 0.001, RR = 0.32, 95% CI: 0.217-0.472). The nomogram demonstrated a high C-index of 0.88, indicating excellent predictive accuracy. Calibration plots showed good agreement between predicted and observed outcomes, and DCA confirmed the model's clinical utility. The prognostic model developed in this study provides a reliable tool for predicting femoral head collapse in ONFH patients. It allows for early identification of high-risk patients, guiding personalized treatment strategies to improve patient outcomes and reduce the need for invasive surgical procedures.

Analysis of components and related risk factors of urinary stones: a retrospective study of 1055 patients in southern China.

We conducted a retrospective study of 1055 patients with urinary stones who attended our single center from September 2017 to June 2024. Clinical data and laboratory indicators of patients were evaluated and compared with stone components. The most common type in our study was calcium oxalate (CaOx) stones (76.6%), followed by infection stones (13.2%) and uric acid (UA) stones (7.8%). Among the 1055 specimens, 899 (85.2%) cases were mixed component stones, of which calcium oxalate monohydrate (COM) and calcium oxalate dihydrate (COD) mixture were the most frequent (34.8%). There were only 156 cases (14.8%) of pure-component stones, of which anhydrous UA was the most frequent (7.0%). There were 738 males and 317 females, with a male-to-female ratio of 2.33:1. Male dominance was evident in CaOx stones (79.0 vs. 71.0%, P = 0.005). Female dominance was noted in infection stones (21.1 vs. 9.8%, P < 0.001). The multivariate analysis showed that higher serum albumin level was a risk factor for CaOx stone formation (OR = 2.959; 95% CI 1.470-5.953, P = 0.002). Women were more likely to develop infection stones than men (OR = 1.796; 95% CI 1.150-2.803, P = 0.010). As the urine pH increased, the risk of infection stones formation increased (OR = 2.521; 95% CI 1.809-3.513, P < 0.001). Moreover, a history of hypertension (OR = 2.339; 95% CI 1.409-3.881, P = 0.001), low urine pH (OR = 0.242; 95% CI 0.147-0.399, P < 0.001), and low serum albumin level (OR = 0.351; 95% CI 0.125-0.988, P = 0.047) were risk factors for the formation of UA stones.

Case report: Infection-associated HPS during pregnancy cured by HLH-94 protocol with induction therapy of ruxolitinib

Hemophagocytic syndrome (HPS) is a rapidly progressive and highly fatal disease, and is even more complex when it occurs during pregnancy. Currently, the HLH-94 protocol is commonly used for treatment for HPS, with ruxolitinib being mostly used for salvage therapy. Here, we report a pregnant woman who presented with fever, thrombocytopenia, splenomegaly, and subsequently developed into severe pneumonia and multiple organ dysfunction(MODS). The patient was diagnosed as HPS based on clinical manifestations, laboratory indexes, and hemophagocytosis observed in bone marrow aspirate smear. After receiving ruxolitinib as induction therapy combined with HLH-94 protocol, the patient significantly improved and eventually cured.

Predicting the prognosis of Wilms tumor by peripheral blood cells: a real-world study of more than 30years.

Despite established excellent treatment strategies for Wilms tumor (WT), effective prognostic evaluation methods were lacking. This study aims to examine prognostic factors for WT through real-world peripheral blood cell profiling. Basic data and pre-treatment laboratory indices from WT and non-WT children underwent Wilcoxon test analysis. Chi-square tests assessed the correlation between blood cells and the overall survival (OS) and event-free survival (EFS) of WT. Further the Log-rank test and multivariate Cox were used to identify independent prognostic factors for OS. Traditional accepted factors were included in multi-Cox and the nomogram was constructed to further validate the outcome. Blood cells significantly differed between WT and non-WT groups (P < 0.05). Univariate analysis revealed that NLR above 1.380, stage IV, M below 0.325 × 103/μL were linked with lower OS, and PLR below 94.632, LB above 3.570 × 103/μL, stage IV, M above 0.325 × 103/μL,age ≤ 3years were meaningful for higher EFS (P < 0.05). While in the multifactorial COX, only M (HR:0.220, HR95%CI: 0.080 ~ 0.620, P = 0.004 and HR: 0.437, HR95%CI: 0.202 ~ 0.947, P = 0.036, respectively) and stage IV (HR: 7.890, HR95%CI: 1.650 ~ 37.770, P = 0.010 and HR: 3.720, HR95%CI: 1.330 ~ 10.408, P = 0.012, respectively) were independent prognostic factors for OS and EFS. These two variables also were significant after including recognized risk factors, and were demonstrated the predictability via nomogram. OS and EFS were poorer in WT children with M below 0.325 × 103/μL, suggesting the potential as a prognostic predictor for WT.

Influence of intestinal permeability and endotoxinemia on the course of asthma in obese patients

Objective. To study the characteristics of asthma with a severe course in obese patients and to evaluate the relationship of the level of intestinal endotoxin (ET) and fecal zonulin with clinical, laboratory and instrumental indicators in such patients. Materials and methods. The study included 98 patients with asthma combined with obesity (group 1 – mild asthma (n = 47), group 2 – severe asthma (n = 51)) and 45 obese patients without asthma composed the comparison group. A complete standard examination and tests were conducted in all the patients. Intestinal ET, fecal zonulin, TNF-a, IFN-g, IL-4, 6, 10, 17, total IgE levels were assessed as well. The IBM SPSS Statistics 26.0 application software package was used for statistical calculations. The results were considered as statistically significant at the level of p 0,05. Results. In patients of both groups, the average age of onset was 43 years. The median duration of BA characteristics was higher in patients of group 2: 14 [10; 19] years (p = 0.013). In all groups, CRPhs values increased significantly and the highest ones were in patients with severe asthma (p 0.001). Significantly lower levels of FVC, FEV1, FEV1/FVC, IL-10 (p0.001) with uncontrolled course of asthma (p = 0.008) and rare control (p = 0.009) occurred in patients of group 2. Higher levels of TNF-a, IFN-g, IL-6,17, intestinal ET, fecal zonulin were revealed in patients of group 2 (p≤0.001). The level of fecal zonulin positively correlated with the level of intestinal ET in patients of group 2 (p0.001, rs=0.813). In patients of group 2 direct correlations of the fecal zonulin and intestinal ET with BMI, WC, HC, WC/HC, lack of BA control, CRPhs, TNF-a, IL-6,17, IFN-g, LDL were established and inverse correlations were with IL-10, HDL, FEV1, AST; a negative correlation of fecal zonulin levels with FVC was also revealed. Conclusions. The obtained results allow us to speak about the existence of a clinical complex “severe asthma – obesity – intestinal endotoxemia and increased intestinal permeability” which is characterized by the predominance of pro-inflammatory markers, increased levels of intestinal ET and fecal zonulin, reduced function of external breathing.

Stratification of Hand Bone Fractures in the Kyrgyz Republic

The study aimed to stratify hand bone fractures in the Kyrgyz Republic based on patient data, including age, gender, and other clinical characteristics. Data from patients treated in 2019 were analyzed, with assessments made using key medical parameters such as fracture type, age, gender, blood group, and other laboratory indicators. A retrospective analysis of 200 hand fracture cases was conducted, classified by various clinical and demographic criteria. Conclusions were drawn based on statistical analysis of the data. Results: Significant differences in fracture incidence were observed between males and females, as well as across different age groups. The highest incidence was found in the working-age population, indicating a need for enhanced preventive measures in this demographic.

Quality of life as a reflection of metabolic indicators in patients undergoing programmed hemodialysis

Metabolic disorders associated with chronic kidney disease (CKD) can lead to a decrease in the quality of life of patients on hemodialysis. The aim of this study is to analyze the correlation between quality of life (QOL) in patients receiving treatment with PHD and clinical and laboratory indicators. Material and methods. 251 patients with stage 5 CKD were included in the study. There were 108 men and 143 women. The mean age was 54.4 ± 9.9 years. All participants completed a specific quality of life questionnaire KDQOL-SF. Results. The interviewed patients reported more concern about symptoms such as weakness, dizziness, and muscle pain (U = 765, p &lt; 0.001), which was correlated with albumin levels (R = 0.5, p &lt; 0.01) and calcium-phosphorus product levels (R = –0.48, p &lt; 0.05). They also expressed concern about the inability to travel or follow a special diet (U = 553, p &lt; 0.005), which correlated with heart rate levels (R = –0.51, P &lt; 0.1) and serum potassium levels (R = –0.6, P &lt; 0.1). Additionally, the burden of CKD correlated with triglycerides (R = 0.36, p = 0,01).Work capacity is associated with age (R = –0.54; p &lt; 0.001), eKT/V (R = 0.47; p &lt; 0.01). Indicators of cognitive function correlate with blood pressure (BP) (R = –0.51, p &lt; 0,001) and pulse pressure (P = –0,55, p &lt; 0,01). Sexual functions are associated with BP (R = –0,64, p &lt; 0,05), calcium levels (R = 0,76, p &gt; 0.80), iron (0,42, p = 0,90), transferrin saturation coefficient (0.5, p = 0.91). Sleep quality correlates with calcium-phosphate production (0.3, p &gt; 0.15). The feeling of social support correlates with magnesium (0,3, P &gt; 0,8), calcium (0.2, P &gt; 0,1). Conclusions. Correlations between quality of life, blood pressure, albumin, and calcium phosphate metabolism, iron, were found.

Analysis of risk factors for autoimmune thyroid disease based on blood indicators and urinary iodine concentrations

ObjectiveThe aim of this study was to elucidate the relationships between thyroid hormones, lifestyle factors, biochemical markers, and autoimmune thyroid disease (AITD), thereby identifying the factors influencing the development of these diseases.MethodsThe study encompassed 517 patients with AITD and 549 patients with non-autoimmune thyroid disease. Demographic and clinical data were collected, and various laboratory indicators, including urinary iodine and thyroid hormones, were measured and compared between the groups. Lasso regression was employed to select the independent variables, while logistic regression analysis determined the factors associated with the development of AITD.ResultsThe prevalence of drinking alcohol history, median urinary iodine, and TSH concentrations proved significantly greater in the AITD group compared to the control group, while FT3 levels demonstrated lower values within the AITD group (p&amp;lt;0.05). Furthermore, there was a significant difference in the distribution of iodine nutrition status between the two groups (p&amp;lt;0.05). Both univariate and multivariate logistic regression analyses revealed significant associations among excessive iodine intake, drinking alcohol history, TSH, FT3, and the development of AITD.ConclusionsExcessive iodine intake and drinking alcohol history are implicated in an augmented risk of developing AITD. The prevention of AITD may necessitate the regular monitoring of TSH and FT3 concentrations.

PECULIARITIES OF FATAL CASES IN HIV-INFECTED PATIENTS WITH CENTRAL NERVOUS SYSTEM LESIONS IN TUBERCULOSIS INPATIENT SETTINGS FOR 2014-2023

Aim of the work is to study the peculiarities of fatal cases of CNS lesions in patients with tuberculosis against the background of HIV infection.Materials and methods. A retrospective analysis of 68 medical histories of tuberculosis patients with HIV infection who died in the CNE "Zaporizhia Regional Phthisiopulmonology Clinical Treatment and Diagnostic Center" for the years 2014-2023 was carried out. An analysis of the anamnesis, clinical and radiological data, laboratory indicators, final clinical and pathological diagnoses was carried out.Results. The mortality rate among HIV-infected people in TB hospitals has a steady downward trend. In 2014-2023, 1234 patients with HIV infection were treated at the CNE "Zaporizhia Regional Phthisiopulmonology Clinical Treatment and Diagnostic Center", 214 (17.3%) died. In 2014, 33 (24.6%) out of 134 HIV-positive patients died, and in 2023, 3 (6.8%) out of 44 HIV-positive patients died. Central nervous system (CNS) lesions among the dead were noted in 68 (31.8%) patients. The study of medical records found that among those who died with CNS lesions, men prevailed - 55 (80.9%), women - 13 (19.1%), young patients - 53 (77.9%), and 15 (22.1%) patients over 45 years of age. In the structure of central nervous system lesions in patients with active tuberculosis, tuberculous meningoencephalitis prevails in fatal cases - 35 (51.5%), a significant share of cryptococcal meningoencephalitis - 18 (26.5%) and progressive multifocal leukoencephalopathy - 9 (13.2%). The main reason that leads to fatal consequences is the late diagnosis of HIV infection - in 26 (38.2%) the number of CD4&lt;50 cl./μl, 36 (52.9%) patients did not receive antiretroviral therapy (ART), 18 (26 .5%) of patients had been taking ART for a year. Improvement of tuberculosis microbiological diagnosis due to the introduction of the Xpert MTB/RIF® (Ultra) test at all levels of the laboratory network, the introduction of a mandatory test for cryptococci, free CT, MRI examination for the diagnosis in HIV-infected patients, improvement of drug-resistant tuberculosis treatment regimens contributed to the reduction of mortality in case of HIV and tuberculosis combination, which was 24.6% in 2014, and 6.8% in 2023.Conclusions. Diagnosis and treatment of CNS diseases in patients with active tuberculosis against the background of HIV infection requires a comprehensive approach: early diagnosis of HIV infection, tuberculosis and lesions of the CNS, improvement of treatment.

Study on the clinical characteristics, treatment, and outcome influencing factors of severe pneumonia complicated with ARDS.

To investigate the clinical characteristics, treatment methods, and factors influencing the prognosis of patients with severe pneumonia complicated by Acute Respiratory Distress Syndrome (ARDS), aiming to provide references for clinical decision-making and improve patient outcomes. A retrospective analysis was conducted on 118 patients with severe pneumonia complicated by ARDS treated at our hospital from June 2018 to December 2022. Based on treatment outcomes, patients were divided into a death group (n = 75) and a survival group (n = 43). General data and clinical laboratory indicators, including blood urea nitrogen, serum creatinine, C-reactive protein, procalcitonin, arterial partial pressure of oxygen, and arterial partial pressure of carbon dioxide, were collected and compared between the 2 groups to identify independent factors affecting prognosis. Among the 118 patients, the mortality rate was 63.56%. Patients in the death group had a significantly higher average age (57.15 ± 13.38 years) and a higher proportion of severe ARDS (66.67%) compared to the survival group (40.02 ± 11.41 years, 30.23%, P < .001). The death group had significantly lower white blood cell counts (8.10 ± 1.64 × 109/L), oxygenation index (19.82 ± 2.29), and duration of mechanical ventilation (7.79 ± 2.11 days) compared to the Survival group (8.92 ± 1.22 × 109/L, 13.42 ± 1.82, 12.23 ± 3.05 days, P < .05). Conversely, the death group had significantly higher levels of blood urea nitrogen (6.87 ± 1.80 mmol/L), C-reactive protein (130.55 ± 50.28 mg/L), procalcitonin (5.50 ± 2.11 ng/mL), arterial partial pressure of carbon dioxide (41.12 ± 5.56 mm Hg), and a higher proportion of viral infections (48.00%) compared to the survival group (5.90 ± 1.72 mmol/L, 101.77 ± 55.56 mg/L, 3.98 ± 1.15 ng/mL, 35.59 ± 6.22 mm Hg, 27.91%, P < .05). Logistic regression analysis revealed that age (odds ratios [OR] = 1.990, 95% confidence interval [CI]: 1.306-3.033, P < .001), oxygenation index (OR = 1.426, 95% CI: 1.123-1.649, P < .001), and duration of mechanical ventilation (OR = 0.694, 95% CI: 0.557-0.864, P < .001) were independent factors influencing patient prognosis. This indicates that an increase in age and a decrease in oxygenation index are associated with a significantly higher risk of mortality, while shorter mechanical ventilation duration is related to poorer prognosis. Advanced age, lower oxygenation index, and shorter duration of mechanical ventilation are unfavorable prognostic factors in patients with severe pneumonia complicated by ARDS. These findings aid clinicians in identifying high-risk patients, optimizing treatment plans, and improving patient prognosis.

Analysis of ultrasound and magnetic resonance imaging characteristics of kaposiform hemangioen dothelioma

ObjectiveThe present study aims to investigate the ultrasound and magnetic resonance imaging (MRI) characteristics of kaposiform hemangioen dothelioma (KHE).MethodsA retrospective analysis was conducted on the clinical data of children diagnosed with KHE through postoperative pathology. Patients were divided into two groups: the KHE group and the KHE with Kasabach-Merritt Phenomenon (KMP) group (KMP group). Laboratory indicators, ultrasound, and MRI data were collected and analyzed statistically to summarize the imaging characteristics of the disease.ResultsThe levels of platelets and fibrinogen in the KHE group were significantly higher than those in the KMP group, while D-dimer levels, prothrombin time, and activated partial thromboplastin time were lower (P < 0.05). Ultrasound characteristics comparison revealed that lesions extending to the fat layer (42.47% vs. 54.24%) and invading the muscle layer (38.36% vs. 69.49%) were less common in the KHE group compared to the KMP group, with the lesion diameter being smaller in the KHE group (P < 0.05). The Adler grading predominantly showed Grade II (45.21%) in the KHE group, whereas Grade III (93.22%) was more prevalent in the KMP group (P < 0.05). MRI analysis indicated that the incidence of lesions invading the muscle layer and the presence of flow voids were lower in the KHE group compared to the KMP group (P < 0.05).ConclusionKHE patients with KMP exhibit lesions that are more prone to extending into the fat layer and invading the muscle layer, with larger diameters and abundant blood flow. Additionally, the MRI images of the lesions may exhibit flow voids.

Development and validation of a nomogram for circuit lifespan of regional citrate anticoagulation-continuous renal replacement therapy in intensive care patients with acute kidney injury.

Regional citrate anticoagulation-continuous renal replacement therapy (RCA-CRRT) has a wide range of applications in clinical practice, but unplanned downtime due to RCA-CRRT circuit coagulation is as high as 15.75%-66.70%. To build a nomogram model for predicting the lifespan circuits of RCA-CRRT. A prospective observational cohort study was conducted in Sichuan, China. The collected clinical data from 404 RCA-CRRT sessions involving 135 patients were utilized. The patients' basic information, laboratory indicators and RCA-CRRT parameters were used as independent variables, and the survival status and survival time of RCA-CRRT circuits were used as dependent variables. A Cox multivariate analysis was performed to build the nomogram model for predicting the lifespan of RCA-CRRT circuits. The model was validated internally and externally. The median lifespan of RCA-CRRT circuits was 28.0 (12.0-46.5) h, and the unplanned downtime rate was 23.76%. In the Cox multivariate analysis, venous pressure, haemoglobin, Sequential Organ Failure Assessment (SOFA), lactate, and blood transfusion were identified as statistically significant predictive factors for the lifespan of RCA-CRRT circuits (p < .05). Subsequently, a nomogram model for predicting the lifespan of RCA-CRRT circuits was developed. The AUC values for internal and external validation within the 12-72-h timeframe ranged from 0.648 to 0.816 and 0.613 to 0.956, respectively. Both the calibration curve and clinical decision curve demonstrated the model's good performance. The nomogram model developed in this study demonstrates its efficacy in accurately predicting the lifespan circuits of RCA-CRRT. Clinical nurses can use the prediction model to assess the lifespan of RCA-CRRT circuits, so as to formulate a personalized RCA-CRRT treatment plan for patients, thus reducing the unplanned downtime of RCA-CRRT.

Correlation between oxygenation function and laboratory indicators in COVID-19 patients based on non-enhanced chest CT images and construction of an artificial intelligence prediction model

ObjectiveBy extracting early chest CT radiomic features of COVID-19 patients, we explored their correlation with laboratory indicators and oxygenation index (PaO2/FiO2), thereby developed an Artificial Intelligence (AI) model based on radiomic features to predict the deterioration of oxygenation function in COVID-19 patients.MethodsThis retrospective study included 384 patients with COVID-19, whose baseline information, laboratory indicators, oxygenation-related parameters, and non-enhanced chest CT images were collected. Utilizing the PaO2/FiO2 stratification proposed by the Berlin criteria, patients were divided into 4 groups, and differences in laboratory indicators among these groups were compared. Radiomic features were extracted, and their correlations with laboratory indicators and the PaO2/FiO2 were analyzed, respectively. Finally, an AI model was developed using the PaO2/FiO2 threshold of less than 200 mmHg as the label, and the model’s performance was assessed using the area under the receiver operating characteristic curve (AUC), sensitivity and specificity. Group datas comparison was analyzed using SPSS software, and radiomic features were extracted using Python-based Pyradiomics.ResultsThere were no statistically significant differences in baseline characteristics among the groups. Radiomic features showed differences in all 4 groups, while the differences in laboratory indicators were inconsistent, with some PaO2/FiO2 groups showed differences and others not. Regardless of whether laboratory indicators demonstrated differences across different PaO2/FiO2 groups, they could all be captured by radiomic features. Consequently, we chose radiomic features as variables to establish an AI model based on chest CT radiomic features. On the training set, the model achieved an AUC of 0.8137 (95% CI [0.7631–0.8612]), accuracy of 0.7249, sensitivity of 0.6626 and specificity of 0.8208. On the validation set, the model achieved an AUC of 0.8273 (95% CI [0.7475–0.9005]), accuracy of 0.7739, sensitivity of 0.7429 and specificity of 0.8222.ConclusionThis study found that the early chest CT radiomic features of COVID-19 patients are strongly associated not only with early laboratory indicators but also with the lowest PaO2/FiO2. Consequently, we developed an AI model based on CT radiomic features to predict deterioration in oxygenation function, which can provide a reliable basis for further clinical management and treatment.

A transformer-based deep learning model for identifying the occurrence of acute hematogenous osteomyelitis and predicting blood culture results

BackgroundAcute hematogenous osteomyelitis is the most common form of osteomyelitis in children. In recent years, the incidence of osteomyelitis has been steadily increasing. For pediatric patients, clearly describing their symptoms can be quite challenging, which often necessitates the use of complex diagnostic methods, such as radiology. For those who have been diagnosed, the ability to culture the pathogenic bacteria significantly affects their treatment plan.MethodA total of 634 patients under the age of 18 were included, and the correlation between laboratory indicators and osteomyelitis, as well as several diagnoses often confused with osteomyelitis, was analyzed. Based on this, a Transformer-based deep learning model was developed to identify osteomyelitis patients. Subsequently, the correlation between laboratory indicators and the length of hospital stay for osteomyelitis patients was examined. Finally, the correlation between the successful cultivation of pathogenic bacteria and laboratory indicators in osteomyelitis patients was analyzed, and a deep learning model was established for prediction.ResultThe laboratory indicators of patients are correlated with the presence of acute hematogenous osteomyelitis, and the deep learning model developed based on this correlation can effectively identify patients with acute hematogenous osteomyelitis. The laboratory indicators of patients with acute hematogenous osteomyelitis can partially reflect their length of hospital stay. Although most laboratory indicators lack a direct correlation with the ability to culture pathogenic bacteria in patients with acute hematogenous osteomyelitis, our model can still predict whether the bacteria can be successfully cultured.ConclusionLaboratory indicators, as easily accessible medical information, can identify osteomyelitis in pediatric patients. They can also predict whether pathogenic bacteria can be successfully cultured, regardless of whether the patient has received antibiotics beforehand. This not only simplifies the diagnostic process for pediatricians but also provides a basis for deciding whether to use empirical antibiotic therapy or discontinue treatment for blood cultures.

Incidence and Risk Factors of Infection After Fracture Fixation: A Multicenter Cohort Study.

Infection after fracture fixation (IAFF) is a severe complication. There are few multicenter studies targeting IAFF. This paper identifies independent risk factors associated with IAFF by analyzing multicenter clinical data. Appropriate interventions should be implemented to reduce the risk of IAFF. This is a multicenter retrospective cohort study. This study screened medical records of patients who underwent internal fixation for fractures at participating medical institutions from January 1, 2011, to December 31, 2020. Data extraction included demographic characteristics, disease features, surgical variables, and laboratory indicators. Logistic regression analysis was employed to identify the relationship between relevant risk factors and IAFF. Research data were sourced from the hospital's electronic medical record system and self-constructed databases. In our study, 202 patients who underwent internal fixation for fractures experienced postoperative infections, which corresponds to an overall incidence rate of approximately 1.7%. The predominant pathogen identified in these infections was Staphylococcus aureus. A multifactorial analysis indicated that several factors were independently associated with the occurrence of IAFF. These factors included BMI ranges of 24.0-27.9 and 28.0-31.9, smoking, a high ASA score, high-energy trauma, diabetes, open fracture, seasonal timing of the surgery (summer), bone grafting, drainage duration, surgical duration ≥ 180 min, and A/G ratio < 1.2. We strongly recommend that orthopedic surgeons perform comprehensive preoperative assessments on fracture patients to identify factors that may increase the risk of infection. Through the implementation of targeted interventions and beneficial modifications to these modifiable risk factors, it is possible to lower the incidence of IAFF. Additionally, proactive screening, risk stratification, and thorough patient education should be prioritized for patients with high risk but nonmodifiable factors.

Research on gut microbiota characteristics of PBC patients at different ALBI grades based on machine learning

BackgroundThe Albumin-Bilirubin (ALBI) score and grade are widely used to stratify patients with primary biliary cholangitis (PBC) into different disease statuses and risk levels. Recent studies have increasingly highlighted the role of gut microbiota in autoimmune liver diseases. This study aimed to investigate the differences in gut microbiota among PBC patients with varying ALBI grades.MethodsClinical data and stool samples were collected from outpatient and inpatient PBC patients between 2019 and 2022. Gut microbiota profiles were obtained using 16S rDNA sequencing of stool samples. We analyzed alpha diversity, beta diversity, LEfSe analysis and pathway function prediction. Additionally, various machine learning methods—including random forest (RF), lasso, gradient boosting machine (GBM) and support vector machine (SVM)—were employed to identify key features and to build and validate predictive models using bootstrap techniques.ResultsClinical characteristics of ALBI grade 1 patients were comparatively better than those of ALBI grade 2 and 3 patients, including multiple laboratory indices. Gut microbiota analysis revealed that species richness and balance were higher in ALBI grade 1 patients. Both the comparison of the most abundant genera and the linear discriminant analysis (LDA) in LEfSe demonstrated that Lachnospira had a higher abundance and better discriminative ability in ALBI grade 1. Pathway function prediction indicated that sulfur metabolism was upregulated in higher ALBI grades. Furthermore, RF identified 10 specific genera, which were then used to build and validate models for discriminating PBC patients according to their ALBI grades. All three models, developed using different machine learning methods, demonstrated good discrimination ability (mean AUC 0.75–0.80).ConclusionThis study highlights significant differences in gut microbiota profiles among PBC patients with different ALBI grades. The increased abundance of Lachnospira and upregulation of sulfur metabolism pathways are notable in patients with lower ALBI grades. The machine learning models developed based on gut microbiota features offer promising tools for discriminating between PBC patients with varying disease severities, which could enhance the precision of treatment strategies.

Features of laboratory indicators in cancer patients with COVID‑19, staying in the intensive care unit

Features of laboratory indicators in cancer patients with COVID‑19, staying in the intensive care unit

Effectiveness of long-term bimekizumab treatment and predictive factors for responders in moderate-to-severe psoriasis: A 52-week real-world study.

Psoriasis is a chronic, inflammatory skin disease in which the interleukin (IL)-23/IL-17 axis plays a central role. Bimekizumab is a novel antibody that targets both IL-17A and IL-17F. This retrospective study aimed to assess the long-term effectiveness and safety of 52-week treatment with bimekizumab, and to identify predictive factors for short- (16 weeks) and long-term (52 weeks) responders (i.e., achievers of a Psoriasis Area and Severity Index (PASI) score of 100) to bimekizumab in Japanese patients with psoriasis. The study was conducted on 56 Japanese patients (aged ≥ 15 years) with moderate-to-severe psoriasis treated with bimekizumab from May 2022 to March 2024. The therapeutic effectiveness was evaluated by the transition of PASI scores during treatment. Baseline characteristics and clinical and laboratory indexes were compared between responders and poor responders. Treatment-emergent adverse events (TEAEs) were recorded to assess the safety of the treatment. At week 52, the achievement of PASI 100, static Physician's Global Assessment 0/1, and the Dermatology Life Quality Index 0/1 were 72.4%, 94.7%, and 93.3%, respectively. Short-term responders showed lower baseline values of neutrophil-to-lymphocyte ratio, monocyte-to-lymphocyte ratio (MLR), and systemic inflammatory response index compared to poor responders. Long-term responders showed younger age and lower MLR compared to poor responders. TEAEs were mild or moderate, without serious adverse events. Long-term treatment with bimekizumab is effective and safe for psoriasis patients. Lower MLR and younger age might predict long-term response to treatment with bimekizumab, aiding in personalized treatment strategies.