Value of D-dimer in predicting various clinical outcomes following community-acquired pneumonia: A network meta-analysis

Factors associated with Mycoplasma pneumoniae-induced Lobar pneumonia with mucus plugging and the optimal timing for bronchoalveolar lavage: a retrospective study

BACKGROUND

Lobar pneumonia with mucus plugging (LPMP) caused by Mycoplasma pneumoniae (MP) is a severe form of community-acquired pneumonia in children, often leading to prolonged disease courses and complications. Identifying clinical factors associated with delayed radiographic resolution and determining the optimal timing for bronchoalveolar lavage (BAL) intervention are crucial for improving clinical outcomes.

METHODS

We conducted a retrospective analysis of 151 children aged 2-14 years diagnosed with LPMP between November 2023 and July 2024. Patients were divided into two groups based on radiographic resolution at one month: common resolution (n = 83) and delayed resolution (n = 68). Clinical data, laboratory results, and timing of BAL intervention were compared between groups. Multivariate logistic regression identified independent risk factors of delayed resolution, and receiver operating characteristic (ROC) curves assessed predictive performance.

RESULTS

Children in the delayed resolution group had significantly longer fever durations before intervention (P < 0.001), higher C-reactive protein levels (P < 0.001), and elevated lactate dehydrogenase levels (P < 0.001) compared to the common resolution group. Multivariate analysis identified elevated D-dimer levels (P = 0.010), delayed BAL intervention (P < 0.001), and prolonged hospital stay (P = 0.044) as independent risk factors of delayed resolution. ROC analysis showed that BAL intervention within 6 days had excellent predictive accuracy. Early BAL intervention was associated with shorter hospital stays (P < 0.001), faster cough resolution (P < 0.001), lower incidence of atelectasis at one month (P = 0.024), and higher rates of lung consolidation absorption (P < 0.001).

CONCLUSION

Elevated D-dimer levels, delayed BAL intervention, and prolonged hospital stay are significant associated with delayed radiographic resolution in children with LPMP. Early BAL intervention within 6 days of admission improves clinical outcomes by accelerating recovery and reducing complications. These findings support prompt BAL as a key component in the management of pediatric LPMP.

Construction and validation of a risk prediction model for postoperative pulmonary infection in patients with brain tumor: a retrospective study

Objectives

This study aimed to investigate the influencing factors and construct a risk prediction model for postoperative pulmonary infection in patients with brain tumor.

Methods

This investigation encompassed a cohort of 636 individuals who were diagnosed with brain tumors and underwent surgical treatment between October 2019 and October 2023. According to the ratio of 7:3, the patients were randomly divided into training set and validation set. Univariate analysis and multivariate Logistic regression analysis were performed on the data in the training set. Finally, the independent risk factors of postoperative pulmonary infection in patients with brain tumor were screened out. R software was used to establish a nomogram model for predicting the risk of postoperative pulmonary infection. Receiver operating characteristic (ROC) curve, calibration curve and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration of the model. Decision curve analysis was used to evaluate the clinical benefit of the model.

Results

The prevalence of postoperative pulmonary infection in patients with brain tumors was 17.9%. The nomogram contained several independent risk factors: age ≥ 60 years, diabetes mellitus, GCS score < 13 points, postoperative bedtime, and postoperative D-Dimer. The prediction model yielded an area under the curve (AUC) of 0.814 (95% confidence interval CI [0.756-0.873]) in the training set, and an AUC of 0.752 (95% CI [0.653-0.850]) in the validation set. The P-values for the Hosmer-Lemeshow test in the training set are 0.629, while in the validation set, they are 0.128. Decision curve analysis demonstrated that the model's clinical effectiveness is satisfactory.

Conclusions

Age ≥ 60 years, diabetes mellitus, GCS score < 13 points, postoperative bedtime and postoperative D-Dimer are risk factors for postoperative pulmonary infection in patients with brain tumor. The developed prediction model demonstrates substantial predictive value and clinical applicability, serving as a valuable reference for medical professionals in recognizing postoperative pulmonary infections in patients with brain tumors and facilitating preventive nursing measures.

A recurrence model for non-puerperal mastitis patients based on machine learning

OBJECTIVE

Non-puerperal mastitis (NPM) is an inflammatory breast disease affecting women during non-lactation periods, and it is prone to relapse after being cured. Accurate prediction of its recurrence is crucial for personalized adjuvant therapy, and pathological examination is the primary basis for the classification, diagnosis, and confirmation of non-puerperal mastitis. Currently, there is a lack of recurrence models for non-puerperal mastitis. The aim of this research is to create and validate a recurrence model using machine learning for patients with non-puerperal mastitis.

METHODS

We retrospectively collected laboratory data from 120 NPM patients, dividing them into a non-recurrence group (n = 59) and a recurrence group (n = 61). Through random allocation, these individuals were split into a training cohort and a testing cohort in a 90%:10% ratio for the purpose of building the model. Additionally, data from 25 NPM patients from another center were collected to serve as an external validation cohort for the model. Univariate analysis was used to examine differential indicators, and variable selection was conducted through LASSO regression. A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. The finally selected model was interpreted and evaluated using Receiver Operating Characteristic (ROC) curves, calibration curves, Decision curve analysis (DCA), and Shapley Additive Explanations (SHAP) plots.

RESULTS

The logistic regression model emerged as the optimal model for predicting recurrence of NPM with machine learning, primarily utilizing three variables: FIB, bacterial infection, and CD4+ T cell count. The model showed an AUC of 0.846 in the training cohort and 0.833 in the testing cohort. The calibration curve indicated excellent calibration of the model. DCA revealed that the model possessed favorable clinical utility. Furthermore, the model effectively achieved in the external validation group, with an AUC of 0.825.

CONCLUSION

The machine learning model developed in this study, serving as an effective tool for predicting NPM recurrence, aids doctors in making more individualized treatment decisions, thereby enhancing therapeutic efficacy and reducing the risk of recurrence.

Research progress of biomarkers in evaluating the severity and prognostic value of severe pneumonia in children

Pneumonia is a serious and common infectious disease in children. If not treated in time, it may develop into severe pneumonia. Severe pneumonia in children is mainly characterized by hypoxia and acidosis, often accompanied by various complications such as sepsis and multiple organ dysfunction. Severe pneumonia has a rapid onset and progression, and a high mortality rate. Biomarkers assist clinicians in the early diagnosis and treatment of patients by quickly and accurately identifying their conditions and prognostic risks. In this study, common clinical and novel biomarkers of severe pneumonia in children were reviewed, and the application value of biomarkers related to the severity and prognosis of severe pneumonia in children was evaluated to provide help for early identification and precise intervention by clinicians.

Comprehensive airway management of ventilator-associated pneumonia in ICU populations

OBJECTIVE

To evaluate the validity of comprehensive airway management intervention on ventilator-associated pneumonia (VAP) in ICU patients requiring mechanical ventilation.

METHODS

In this retrospective observational study, the clinical data from 120 patients undergoing mechanical ventilation in the ICU of Hebei Chest Hospital from May 2020 to July 2022 were surveyed. Finally, 50 cases of VAP were identified and placed into an observation (n=25) and a control group (n=25) according to the nursing model they received. The control group was treated with routine nursing intervention, and the observation group was given comprehensive airway management intervention based on the control group. After 3 weeks of intervention, the clinical symptom recovery time, treatment-related indexes, nursing quality and nursing satisfaction score, and blood gas indexes and vital signs of the patients in the two groups were examined. The multivariate Logistic regression analysis was performed to identify the risk factors related to the death of critically ill patients.

RESULTS

The observation group showed a significant reduction in the recovery time of heart failure, wheezing cough, and lung rales compared with that in the control group. The duration of mechanical ventilation, hospitalization, and antibiotic use in the observation group were appreciably shorter compared with those in the control group (all P<0.05). Additionally, nursing satisfaction and nursing quality scores were higher in the observation group compared to the control group (P<0.05). The contrast of blood gas indexes and vital signs between the two groups before ventilation and 1 hour after evacuation ventilation showed that a statistical significance existed in the interaction between groups (P<0.05). The risk factors related to the death of critically ill patients included D-dimer (OR=1.051, 95% CI: 1.006-1.08, P<0.05) and lactic acid (OR=0.894, 95% CI: 0.923-1.031, P<0.05).

CONCLUSION

Comprehensive airway management mode can reduce the occurrence of VAP in ICU patients requiring mechanical ventilation.

Clinical significance of elevated D-dimer in emergency department patients: a retrospective single-center analysis

INTRODUCTION

D-dimer is a marker of coagulation and fibrinolysis widely used in clinical practice for assessing thrombotic activity. While it is commonly ordered in the Emergency Department (ED) for suspected venous thromboembolism (VTE), elevated D-dimer levels can occur due to various other disorders. The aim of this study was to find out the causes of elevated D-dimer in patients presenting to a large ED in Saudi Arabia and evaluate the accuracy of D-dimer in diagnosing these conditions.

METHODS

Data was collected from an electronic hospital information system of patients who visited the ED from January 2016 to December 2022. Demographic information, comorbidities, D-dimer levels, and diagnoses were analyzed. Statistical analysis was performed using the SPSS software. The different diagnoses associated with D-dimer levels were analyzed by plotting the median D-dimer levels for each diagnosis category and their interquartile ranges (IQR). The receiver operating characteristic (ROC) curves were calculated and their area under the curve (AUC) values were demonstrated. The optimal cut-off points for specific diseases were determined based on the ROC analysis, along with their corresponding sensitivities and specificities.

RESULTS

A total of 19,258 patients with D-dimer results were included in the study. The mean age of the participants was 50 years with a standard deviation of ± 18. Of the patients, 66% were female and 21.2% were aged 65 or above. Additionally, 21% had diabetes mellitus, 20.4% were hypertensive, and 15.1% had been diagnosed with dyslipidemia. The median D-dimer levels varied across different diagnoses, with the highest level observed in aortic aneurysm 5.46 g/L. Pulmonary embolism (PE) and deep vein thrombosis (DVT) were found in 729 patients (3.8%) of our study population and their median D-dimer levels 3.07 g/L (IQR: 1.35-7.05 g/L) and 3.36 g/L (IQR: 1.06-8.38 g/L) respectively. On the other hand, 1767 patients (9.2%) were diagnosed with respiratory infections and 936 patients (4.9%) were diagnosed with shortness of breath (not specified) with median D-dimer levels of 0.76 g/L (IQR: 0.40-1.47 g/L) and 0.51 g/L (IQR: 0.29-1.06 g/L), respectively. D-dimer levels showed superior or excellent discrimination for PE (AUC = 0.844), leukemia (AUC = 0.848), and aortic aneurysm (AUC = 0.963). DVT and aortic dissection demonstrated acceptable discrimination, with AUC values of 0.795 and 0.737, respectively. D-dimer levels in respiratory infections and shortness of breath (not specified) exhibited poor to discriminatory performance.

CONCLUSION

This is the first paper to identify multiple causes of elevated D-dimer levels in Saudi Arabia population within the ED and it clearly highlights their accurate and diagnostic values. These findings draw attention to the importance of considering the specific clinical context and utilizing additional diagnostic tools when evaluating patients with elevated D-dimer levels.

Risk factors and predicting nomogram for the clinical deterioration of non-severe community-acquired pneumonia

BACKGROUND

Currently, there remains insufficient focus on non-severe community-acquired pneumonia (CAP) patients who are at risk of clinical deterioration, and there is also a dearth of research on the related risk factors. Early recognition of hospitalized patients at risk of clinical deterioration will be beneficial for their clinical management.

METHOD

A retrospective study was conducted in The First Affiliated Hospital of Wenzhou Medical University, China, spanning from January 1, 2018 to April 30, 2022, and involving a total of 1,632 non-severe CAP patients. Based on whether their condition worsened within 72 h of admission, patients were divided into a clinical deterioration group and a non-clinical deterioration group. Additionally, all patients were randomly assigned to a training set containing 75% of patients and a validation set containing 25% of patients. In the training set, risk factors for clinical deterioration in patients with non-severe CAP were identified by using LASSO regression analysis and multivariate logistic regression analysis. A nomogram was developed based on identified risk factors. The effectiveness of the nomogram in both the training and validation sets was assessed using Receiver Operating Characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

RESULTS

Age, body mass index (BMI), body temperature, cardiovascular comorbidity, respiratory rate, LDH level, lymphocyte count and D-dimer level were identified as risk factors associated with the clinical deterioration of non-severe CAP within 72 h of admission. The area under curve (AUC) value of the nomogram was 0.78 (95% CI: 0.74-0.82) in the training set and 0.75 (95% CI: 0.67-0.83) in the validation set. Furthermore, the calibration curves for both the training and validation sets indicated that the predicted probability of clinical deterioration aligned with the actual probability. Additionally, DCA revealed clinical utility for the nomogram at a specific threshold probability.

CONCLUSION

The study successfully identified the risk factors linked to the clinical deterioration of non-severe CAP and constructed a nomogram for predicting the probability of deterioration. The nomogram demonstrated favorable predictive performance and has the potential to aid in the early identification and management of non-severe CAP patients at elevated risk of deterioration.

COVID-19 Biomarkers at the Crossroad between Patient Stratification and Targeted Therapy: The Role of Validated and Proposed Parameters

Clinical knowledge about SARS-CoV-2 infection mechanisms and COVID-19 pathophysiology have enormously increased during the pandemic. Nevertheless, because of the great heterogeneity of disease manifestations, a precise patient stratification at admission is still difficult, thus rendering a rational allocation of limited medical resources as well as a tailored therapeutic approach challenging. To date, many hematologic biomarkers have been validated to support the early triage of SARS-CoV-2-positive patients and to monitor their disease progression. Among them, some indices have proven to be not only predictive parameters, but also direct or indirect pharmacological targets, thus allowing for a more tailored approach to single-patient symptoms, especially in those with severe progressive disease. While many blood test-derived parameters quickly entered routine clinical practice, other circulating biomarkers have been proposed by several researchers who have investigated their reliability in specific patient cohorts. Despite their usefulness in specific contexts as well as their potential interest as therapeutic targets, such experimental markers have not been implemented in routine clinical practice, mainly due to their higher costs and low availability in general hospital settings. This narrative review will present an overview of the most commonly adopted biomarkers in clinical practice and of the most promising ones emerging from specific population studies. Considering that each of the validated markers reflects a specific aspect of COVID-19 evolution, embedding new highly informative markers into routine clinical testing could help not only in early patient stratification, but also in guiding a timely and tailored method of therapeutic intervention.

Clinical characteristics and outcomes of immunocompromised patients with severe community-acquired pneumonia: A single-center retrospective cohort study

Background

Immunocompromised patients with severe community-acquired pneumonia (SCAP) warrant special attention because they comprise a growing proportion of patients and tend to have poor clinical outcomes. The objective of this study was to compare the characteristics and outcomes of immunocompromised and immunocompetent patients with SCAP, and to investigate the risk factors for mortality in these patients.

Methods

We conducted retrospective observational cohort study of patients aged ≥18 years admitted to the intensive care unit (ICU) of an academic tertiary hospital with SCAP between January 2017 and December 2019 and compared the clinical characteristics and outcomes of immunocompromised and immunocompetent patients.

Results

Among the 393 patients, 119 (30.3%) were immunocompromised. Corticosteroid (51.2%) and immunosuppressive drug (23.5%) therapies were the most common causes. Compared to immunocompetent patients, immunocompromised patients had a higher frequency of polymicrobial infection (56.6 vs. 27.5%, P < 0.001), early mortality (within 7 days) (26.1 vs. 13.1%, P = 0.002), and ICU mortality (49.6 vs. 37.6%, P = 0.027). The pathogen distributions differed between immunocompromised and immunocompetent patients. Among immunocompromised patients, Pneumocystis jirovecii and cytomegalovirus were the most common pathogens. Immunocompromised status (OR: 2.043, 95% CI: 1.114-3.748, P = 0.021) was an independent risk factor for ICU mortality. Independent risk factors for ICU mortality in immunocompromised patients included age ≥ 65 years (odds ratio [OR]: 9.098, 95% confidence interval [CI]: 1.472-56.234, P = 0.018), SOFA score [OR: 1.338, 95% CI: 1.048-1.708, P = 0.019), lymphocyte count < 0.8 × 10⁹/L (OR: 6.640, 95% CI: 1.463-30.141, P = 0.014), D-dimer level (OR: 1.160, 95% CI: 1.013-1.329, P = 0.032), FiO₂ > 0.7 (OR: 10.228, 95% CI: 1.992-52.531, P = 0.005), and lactate level (OR: 4.849, 95% CI: 1.701-13.825, P = 0.003).

Conclusions

Immunocompromised patients with SCAP have distinct clinical characteristics and risk factors that should be considered in their clinical evaluation and management.

Meningitis patients with pneumonia: correlation between blood parameters and clinical features

Background: This research aimed to explore the possible relationship between the main experimental parameters and clinical status in meningitis patients with pneumonia infection. Methods: A retrospective analysis of the demographic characteristics, clinical features and laboratory parameters of meningitis patients was performed. Results: D-dimer, C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) exhibited good diagnostic ability for meningitis complicated with pneumonia. Additionally, we observed a positive correlation between D-dimer and CRP in cases of meningitis with pneumonia infection. D-dimer, ESR and Streptococcus pneumoniae (S. pneumoniae) were independently associated with meningitis patients with pneumonia infection. Conclusion: D-dimer, CRP, ESR and S. pneumoniae infection may effectively anticipate disease progression and adverse consequences in meningitis patients with pneumonia infection.

Awareness on D-dimer assay among dental students

D-dimer molecules are formed by the degradation of cross-linked fibrin during the process of fibrinolysis. The formation of D-dimer requires the activity of activated factor XIII (factor XIIIa), plasmin, and thrombin. To assess the awareness about D-dimer assay among dental students. A cross-sectional study was done among 100 dental practitioners through an online survey. The survey consisted of 10 semiclosed prevalidated and reliable questionnaires based on the knowledge, attitude, and practice of the dentists on D-dimer assay. Descriptive and inferential statistics were performed to report the responses of the participants. Most participants did not know what a D-dimer assay is (55%). Forty-six percent of participants responded that the D-dimer assay is used to rule out serious blood clots. Fifty-four percent of the participants responded that fibrin D-dimers are formed when fibrin strands are formed. The current study shows that the knowledge about D-dimer assay is more in CRRI than in participants of junior year of study. Thus, more rigorous educational programs should be initiated to further enrich the knowledge among dental students.