OBJECTIVES

A growing body of evidence points to a positive association between periodontitis and
various systemic diseases, including cardiovascular diseases (CVD), hypertension, and rheumatoid arthritis. However,
there is limited data on the prevalence and odds of having systemic conditions among Filipino periodontal patients.
Thus, this study aimed to determine the association of periodontal disease with systemic conditions among Filipino
patients at a university dental clinic.

METHODS

The periodontal and medical charts of all patients who underwent periodontal consult at a university
dental clinic within two academic years were reviewed. Periodontal diagnoses which had originally been assigned
using the 1999 classification of periodontal diseases were reclassified based on the 2018 European Federation
of Periodontology-American Academy of Periodontology classification. Listed medical conditions in the patients’
charts were self-reported. The prevalence of various systemic conditions in 715 periodontitis cases was compared
to that of 834 control patients without periodontitis. Fisher’s exact test was performed to evaluate the difference
in the prevalence of comorbidities between groups, while adjusted odds ratios (AOR) were computed using logistic
regression analysis, accounting for age, sex, educational attainment, and smoking status.

RESULTS

The prevalence of having at least one systemic condition was significantly higher among periodontitis patients
(44.5%) compared to non-periodontitis patients (36.3%). Compared to controls, a significantly higher number of
periodontitis cases had two systemic comorbidities (P=0.001). The prevalence of hypertension (18.6% versus 5.04%),
CVD including hypertension (20.42% versus 6.95%), arthritis (9.37% versus 3.0%), and diabetes mellitus (5.73% versus
0.84%) were all significantly higher in patients with periodontitis compared to non-periodontitis controls.
The odds of having CVD (AOR=1.81), hypertension (AOR=2.14) and diabetes (AOR=3.05) were higher in periodontitis cases. Meanwhile, the prevalence of asthma (9.23% versus 5.31%), respiratory diseases including asthma (12.95% versus 8.25%), and allergies (18.82% versus 13.71%) were significantly higher in non- periodontitis patients compared to periodontitis cases.

CONCLUSION

Periodontitis patients were more likely to present with CVD, hypertension, and diabetes mellitus. On the other hand, no association was found between periodontitis and respiratory diseases, as well as between periodontitis and asthma.

Human ; Male ; Female ; Adolescent: 13-18 Yrs Old ; Young Adult: 19-24 Yrs Old ; Adult: 25-44 Yrs Old ; Middle Aged: 45-64 Yrs Old ; Aged: 65-79 Yrs Old ; Regression (psychology) ; Respiratory Tract Diseases ; Regression Analysis ; Periodontal Diseases ; Cardiovascular Diseases

OBJECTIVES

To determine if there is a difference in the prevalence of abnormal spirometry in female adult residents of OLBAC who have significant and nonsignificant exposure to biomass fuel smoke

METHODS

A convenience sample of 54 adult female residents of OLBAC in San Mateo, Rizal, will be recruited in this analytical cross-sectional study. After enrollment, they will undergo a single spirometry procedure to determine their lung function status. The primary data to be collected from the experimental groups are FEV1, FVC and FEV1/ FVC ratio. The data will undergo descriptive and inferential analysis, and the lung function variable will be analyzed with logistic regression to account for confounding variables.

EXPECTED RESULTS

The descriptive data analysis will determine the mean values of lung function parameters (FEV1 and FVC) where long exposures may lead to an abnormal FVC compared to short or no exposure. The results in the inferential analysis may indicate a negative association between length of biomass fuel exposure and percentage predicted FVC among the sample, suggesting that more prolonged exposure to biomass fuel increases the risk of impaired lung function.

CONCLUSION

 

Human ; Female ; Adult: 25-44 Yrs Old ; Young Adult: 19-24 Yrs Old ; Adult ; Biomass ; Cross-sectional Studies ; Female ; Logistic Models ; Regression (psychology) ; Smoke ; Volition ; World Health Organization ; Spirometry

OBJECTIVE: To analyze the risk factors of acute spinal cord injury complicated with respiratory dysfunction, and to construct the clinical prediction model of acute spinal cord injury complicated with respiratory dysfunction. METHODS: Continuous 170 cases of acute spinal cord injury treated from April 2019 to October 2022 were retrospectively collected, and clinical data were uniformly collected. Patients were divided into respiratory dysfunction group 30 cases and non-respiratory dysfunction group 140 cases according to whether they had respiratory dysfunction during treatment. The predictive factors of acute spinal cord injury complicated with respiratory dysfunction were screened by Lasso analysis, and the risk factors of acute spinal cord injury complicated with respiratory dysfunction were screened by multivariate Logistic regression analysis. R(R4.2.1) software was used to establish a nomogram risk warning model for predicting acute spinal cord injury complicated with respiratory dysfunction, and Hosmer-Lemeshow test was used to evaluate the model fit. Finally, area under receiver operating characteristic(ROC) curve (AUC), calibration curve, and decision curve analysis(DCA) were used to evaluate the differentiation, calibration and clinical impact of the model. RESULTS: The incidence of respiratory dysfunction in 170 patients was 17.65%. Lasso regression analysis selected age, residence, marital status, smoking, hypertension, degree of paralysis, spinal cord injury plane, multiple injuries, spinal cord fracture and dislocation, and ASIA grade as the influencing factors. Multivariate Logistic regression analysis showed that age, smoking, degree of paralysis, level of spinal cord injury, spinal cord injury of fracture and dislocation, and ASIA grade were risk factors for acute spinal cord injury complicated with respiratory dysfunction. The prediction model of acute spinal cord injury complicated with respiratory dysfunction was established by Hosmer-Lemeshow test, χ²=5.830, P=0.67. The AUC value of the model was 0.912. DCA analysis showed that the net benefit value of nomogram prediction of acute spinal cord injury complicated with respiratory dysfunction was higher when threshold probability ranged from 1% to 100%. CONCLUSION This column chart can help identify the risk of acute spinal cord injury complicated with respiratory dysfunction in early clinical stage, facilitate early clinical decision-making and intervention, and has important guiding significance for optimizing clinical efficacy and improving prognosis of patients. It is expected to improve and verify this model with larger samples and multi-center in the future.
Humans ; Spinal Cord Injuries/complications* ; Nomograms ; Male ; Female ; Middle Aged ; Adult ; Retrospective Studies ; Risk Factors ; Aged ; Respiration Disorders/etiology* ; Adolescent ; Logistic Models

Objective To mine and analyze the routine blood test data of children with allergic rhinitis (AR), identify routine blood parameters related to childhood allergic rhinitis, establish an effective diagnostic model, and evaluate the performance of the model. Methods This study was a retrospective study of clinical cases. The experimental group comprised a total of 1110 children diagnosed with AR at the First Affiliated Hospital of Air Force Medical University during the period from December 12, 2020 to December 12, 2021, while the control group included 1109 children without a history of allergic rhinitis or other allergic diseases who underwent routine physical examinations during the same period. Information such as age, sex and routine blood test results was collected for all subjects. The levels of routine blood test indicators were compared between AR children and healthy children using comprehensive intelligent baseline analysis, with indicators of P≥0.05 excluded; variables were screened by Lasso regression. Binary Logistic regression was used to further evaluate the influence of multiple routine blood indexes on the results. Five kinds of machine model algorithms were used, namely extreme value gradient lift (XGBoost), logistic regression (LR), gradient lift decision tree (LGBMC), Random forest (RF) and adaptive lift algorithm (AdaBoost), to establish the diagnostic models. The receiver operating characteristic (ROC) curve was used to screen the optimal model. The best LightGBM algorithm was used to build an online patient risk assessment tool for clinical application. Results Statistically significant differences were observed between the AR group and the control group in the following routine blood test indicators: mean cellular hemoglobin concentration (MCHC), hemoglobin (HGB), absolute value of basophils (BASO), absolute value of eosinophils (EOS), large platelet ratio (P-LCR), mean platelet volume (MPV), platelet distribution width (PDW), platelet count (PLT), absolute values of leukocyte neutrophil (W-LCC), leukocyte monocyte (W-MCC), leukocyte lymphocyte (W-SCC), and age. Lasso regression identified these variables as important predictors, and binary Logistic regression further analyzed the significant influence of these variables on the results. The optimal machine learning algorithm LightGBM was used to establish a multi-index joint detection model. The model showed robust prediction performance in the training set, with AUC values of 0.8512 and 0.8103 in the internal validation set. Conclusion The identified routine blood parameters can be used as potential biomarkers for early diagnosis and risk assessment of AR, which can improve the accuracy and efficiency of diagnosis. The established model provides scientific basis for more accurate diagnostic tools and personalized prevention strategies. Future studies should prospectively validate these findings and explore their applicability in other related diseases.
Humans ; Male ; Female ; Rhinitis, Allergic/blood* ; Child ; Biomarkers/blood* ; Retrospective Studies ; Early Diagnosis ; Child, Preschool ; ROC Curve ; Logistic Models ; Hematologic Tests ; Algorithms ; Adolescent ; Machine Learning

Objective To investigate the causal relationship between serum total bile acid (TBA) levels and gastric cancer (GC) using regression discontinuity design (RDD). Methods A total of 1244 GC patients and 1333 healthy controls were included in the study. Demographic characteristics, gallbladder disease history, tumor markers, and serum TBA levels were collected from both groups. Logistic regression was used to construct a risk prediction model to estimate the risk of GC. RDD was employed with serum TBA as the grouping variable and the individual risk of developing GC as the outcome variable. Results The predictive factors in the GC risk prediction model included age, sex, body mass index(BMI), serum TBA, carcinoembryoniv antigen(CEA), alpha fetoprotein(AFP), carbohydrate antigen 199(CA199), and CA125. Serum TBA was identified as an independent risk factor for GC (OR=1.054, 95% CI: 1.030 to 1.079). RDD analysis indicated that when serum TBA levels reached 8 μmol/L, the probability of developing GC increased sharply by 23.7%. The breakpoint remained statistically significant following validity and robustness assessments. Conclusion The study demonstrates a positive causal relationship between serum TBA levels and GC, when the serum TBA level reaches 8 μmol/L, the risk of an individual developing GC increases sharply.
Humans ; Stomach Neoplasms/etiology* ; Male ; Female ; Middle Aged ; Bile Acids and Salts/blood* ; Aged ; Adult ; Risk Factors ; Case-Control Studies ; Biomarkers, Tumor/blood* ; Logistic Models

PURPOSE: We carried out the study aiming to explore and analyze the risk factors, the distribution of pathogenic bacteria, and their antibiotic-resistance characteristics influencing the occurrence of surgical site infection (SSI), to provide valuable assistance for reducing the incidence of SSI after traumatic fracture surgery. METHODS: A retrospective case-control study enrolling 3978 participants from January 2015 to December 2019 receiving surgical treatment for traumatic fractures was conducted at Tangdu Hospital of Air Force Medical University. Baseline data, demographic characteristics, lifestyles, variables related to surgical treatment, and pathogen culture were harvested and analyzed. Univariate analyses and multivariate logistic regression analyses were used to reveal the independent risk factors of SSI. A bacterial distribution histogram and drug-sensitive heat map were drawn to describe the pathogenic characteristics. RESULTS: Included 3978 patients 138 of them developed SSI with an incidence rate of 3.47% postoperatively. By logistic regression analysis, we found that variables such as gender (males) (odds ratio (OR) = 2.012, 95% confidence interval (CI): 1.235 - 3.278, p = 0.005), diabetes mellitus (OR = 5.848, 95% CI: 3.513 - 9.736, p < 0.001), hypoproteinemia (OR = 3.400, 95% CI: 1.280 - 9.031, p = 0.014), underlying disease (OR = 5.398, 95% CI: 2.343 - 12.438, p < 0.001), hormonotherapy (OR = 11.718, 95% CI: 6.269 - 21.903, p < 0.001), open fracture (OR = 29.377, 95% CI: 9.944 - 86.784, p < 0.001), and intraoperative transfusion (OR = 2.664, 95% CI: 1.572 - 4.515, p < 0.001) were independent risk factors for SSI, while, aged over 59 years (OR = 0.132, 95% CI: 0.059 - 0.296, p < 0.001), prophylactic antibiotics use (OR = 0.082, 95% CI: 0.042 - 0.164, p < 0.001) and vacuum sealing drainage use (OR = 0.036, 95% CI: 0.010 - 0.129, p < 0.001) were protective factors. Pathogens results showed that 301 strains of 38 species of bacteria were harvested, among which 178 (59.1%) strains were Gram-positive bacteria, and 123 (40.9%) strains were Gram-negative bacteria. Staphylococcus aureus (108, 60.7%) and Enterobacter cloacae (38, 30.9%) accounted for the largest proportion. The susceptibility of Gram-positive bacteria to Vancomycin and Linezolid was almost 100%. The susceptibility of Gram-negative bacteria to Imipenem, Amikacin, and Meropenem exceeded 73%. CONCLUSION Orthopedic surgeons need to develop appropriate surgical plans based on the risk factors and protective factors associated with postoperative SSI to reduce its occurrence. Meanwhile, it is recommended to strengthen blood glucose control in the early stage of admission and for surgeons to be cautious and scientific when choosing antibiotic therapy in clinical practice.
Humans ; Surgical Wound Infection/epidemiology* ; Male ; Female ; Risk Factors ; Retrospective Studies ; Middle Aged ; Adult ; Case-Control Studies ; Fractures, Bone/surgery* ; Aged ; Drug Resistance, Bacterial ; Logistic Models ; Anti-Bacterial Agents/therapeutic use* ; Incidence ; Bacteria/drug effects*

PURPOSE: Emergency resuscitative thoracotomy (ERT) is a final salvage procedure for critically injured trauma patients. Given its low success rate and ambiguous indications, its use in blunt trauma scenarios remains highly debated. Consequently, our study seeks to ascertain the overall survival rate of ERT in blunt trauma patients and determine which patients would benefit most from this procedure. METHODS: A retrospective case-control study was conducted for this research. Blunt trauma patients who underwent ERT between January 2020 and December 2023 in our trauma center were selected for analysis, with the endpoint outcome being in-hospital survival, divided into survival and non-survival groups. Inter-group comparisons were conducted using Chi-square and Fisher's exact tests, the Kruskal-Wallis test, Student's t-test, or the Mann-Whitney U test. Univariate and multivariate logistic regression analyses were conducted to assess potential predictors of survival. Then, the efficacy of the predictors was assessed through sensitivity and specificity analysis. RESULTS: A total of 33 patients were included in the study, with 4 survivors (12.12%). Multivariate logistic regression analysis indicated a significant association between cardiac tamponade and survival, with an adjusted odds ratio of 33.4 (95% CI: 1.31 - 850.00, p = 0.034). Additionally, an analysis of sensitivity and specificity, targeting cardiac tamponade as an indicator for survivor identification, showed a sensitivity rate of 75.0% and a specificity rate of 96.6%. CONCLUSION The survival rate among blunt trauma patients undergoing ERT exceeds traditional expectations, suggesting that select individuals with blunt trauma can significantly benefit from the procedure. Notably, those presenting with cardiac tamponade are identified as the subgroup most likely to derive substantial benefits from ERT.
Adult ; Female ; Humans ; Male ; Middle Aged ; Case-Control Studies ; China ; Logistic Models ; Resuscitation/mortality* ; Retrospective Studies ; Survival Rate ; Thoracotomy/methods* ; Trauma Centers/statistics & numerical data* ; Wounds, Nonpenetrating/surgery*

PURPOSE: Intrathoracic and intra-abdominal injuries in patients with rib fractures are often overlooked, leading to delayed and ineffective treatment. However, the relationship between rib fractures and organ damage has been rarely studied. The purpose of this study was to analyze the risk factors associated with intrathoracic and intra-abdominal injuries in patients with rib fractures. METHODS: This retrospective observational study included 1269 patients diagnosed with rib fractures from September 2020 to April 2023. Patient data were collected, including gender, age, body mass index, systolic blood pressure, heart rate, type of rib fracture, number of fractured ribs, location of the rib fracture, and the presence of thoracic and abdominal organ injuries. Patients without imaging examinations, the patient with rib fractures from iatrogenic causes or mental illnesses or rheumatic immune diseases was excluded. The primary outcomes were intra-thoracic and intra-abdominal injuries. Multivariate logistic regression analysis was conducted to identify the risk factors for these injuries in patients with rib fractures. RESULTS: The rib fracture characteristics in the occurrence group included bilateral fractures, higher number of fractures (≥3), and fractures located anteriorly, posteriorly, and laterally, as well as greater fracture displacement, compared to the non-occurrence group. The results of the multivariate logistic regression analysis indicated that age (p=0.016, odds ratio (OR)=0.95, 95% confidence interval (CI: 0.92-0.98), the number of rib fractures (≥3, p=0.001, OR=1.46, 95% CI: 1.13-1.89), rib type (bilateral rib fractures, p=0.043, OR=2.63, 95% CI: 2.16-3.12), and rib fracture location (lateral rib fractures, p=0.041, OR=2.85, 95% CI: 1.31-4.97; posterior rib fractures, p=0.022, OR=3.25, 95% CI: 1.46-6.92) were independent risk factors for thoracic and abdominal organ injuries in patients with traumatic rib fractures. CONCLUSIONS Patients with rib fractures resulting from blunt trauma, particularly those with lateral or posterior rib fractures, fractures involving more than 3 ribs, and bilateral rib fractures, are at an increased risk for significant intrathoracic and intra-abdominal injuries. These findings warrant attention and the implementation of appropriate preventive measures during treatment.
Humans ; Rib Fractures/complications* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Thoracic Injuries/epidemiology* ; Abdominal Injuries/epidemiology* ; Risk Factors ; Adult ; Aged ; Logistic Models ; Young Adult

PURPOSE: To analyze risk factors for severe trauma and establish a nomogram for early risk prediction, to improve the early identification of severe trauma. METHODS: This study was conducted on the patients treated in 81 trauma treatment institutions in Gansu province from 2020 to 2022. Patients were grouped by year, with 5364 patients from 2020 to 2021 as the training set and 1094 newly admitted patients in 2020 as the external validation set. Based on the injury severity score (ISS), patients in the training set were classified into 2 subgroups of the severe trauma group (n = 478, ISS scores ≥25) and the non-severe trauma group (n = 4886, ISS scores <25). Univariate and binary logistic regression analyses were employed to identify independent risk factors for severe trauma. Subsequently, a predictive model was developed using the R software environment. Furthermore, the model was subjected to internal and external validation via the Hosmer-Lemeshow test and receiver operating characteristic curve analysis. RESULTS: In total, 6458 trauma patients were included in this study. Initially, this study identified several independent risk factors for severe trauma, including multiple traumatic injuries (polytrauma), external hemorrhage, elevated shock index, elevated respiratory rate, decreased peripheral oxygen saturation, and decreased Glasgow coma scale score (all p < 0.05). For internal validation, the area under the receiver operating characteristic curve was 0.914, with the sensitivity and specificity of 88.4% and 87.6%, respectively; while for external validation, the area under the receiver operating characteristic curve was 0.936, with the sensitivity and specificity of 84.6% and 93.7%, respectively. In addition, a good model fitting was observed through the Hosmer-Lemeshow test and calibration curve analysis (p > 0.05). CONCLUSION This study establishes a nomogram for early risk prediction of severe trauma, which is suitable for primary healthcare institutions in underdeveloped western China. It facilitates early triage and quantitative assessment of trauma severity by clinicians prior to clinical interventions.
Humans ; Nomograms ; Male ; Female ; Wounds and Injuries/diagnosis* ; Risk Factors ; Middle Aged ; Adult ; Injury Severity Score ; Risk Assessment ; ROC Curve ; Aged ; Logistic Models ; China ; Glasgow Coma Scale

OBJECTIVES: To investigate the clinical sub-phenotype (SP) of pediatric acute kidney injury (AKI) and their association with clinical outcomes. METHODS: General status and initial values of laboratory markers within 24 hours after admission to the pediatric intensive care unit (PICU) were recorded for children with AKI in the derivation cohort (n=650) and the validation cohort (n=177). In the derivation cohort, a least absolute shrinkage and selection operator (LASSO) regression analysis was used to identify death-related indicators, and a two-step cluster analysis was employed to obtain the clinical SP of AKI. A logistic regression analysis was used to develop a parsimonious classifier model with simplified metrics, and the area under the curve (AUC) was used to assess the value of this model. This model was then applied to the validation cohort and the combined derivation and validation cohort. The association between SPs and clinical outcomes was analyzed with all children with AKI as subjects. RESULTS: In the derivation cohort, two clinical SPs of AKI (SP1 and SP2) were identified by the two-step cluster analysis using the 20 variables screened by LASSO regression, namely SP_d1 group (n=536) and SP_d2 group (n=114). The simplified classifier model containing eight variables (P<0.05) had an AUC of 0.965 in identifying the two clinical SPs of AKI (P<0.001). The validation cohort was clustered into SP_v1 group (n=156) and SP_v2 group (n=21), and the combined derivation and validation cohort was clustered into SP1 group (n=694) and SP2 group (n=133). After adjustment for confounding factors, compared with the SP1 group, the SP2 group had significantly higher incidence rates of multiple organ dysfunction syndrome and death during the PICU stay (P<0.001), and SP2 was significantly associated with the risk of death within 28 days after admission to the PICU (P<0.001). CONCLUSIONS This study establishes a parsimonious classifier model and identifies two clinical SPs of AKI with different clinical features and outcomes.The SP2 group has more severe disease and worse clinical prognosis.
Humans ; Acute Kidney Injury/diagnosis* ; Prognosis ; Male ; Female ; Child ; Child, Preschool ; Phenotype ; Infant ; Logistic Models ; Adolescent