Comorbidity in Older Patients Hospitalized with Cancer in Northeast China based on Hospital Discharge Data

Analyzing Comorbidity Patterns in Patients With Thyroid Disease Using Large-Scale Electronic Medical Records: Network-Based Retrospective Observational Study

BACKGROUND

Thyroid disease (TD) is a prominent endocrine disorder that raises global health concerns; however, its comorbidity patterns remain unclear.

OBJECTIVE

This study aims to apply a network-based method to comprehensively analyze the comorbidity patterns of TD using large-scale real-world health data.

METHODS

In this retrospective observational study, we extracted the comorbidities of adult patients with TD from both private and public data sets. All comorbidities were identified using ICD-10 (International Classification of Diseases, 10th Revision) codes at the 3-digit level, and those with a prevalence greater than 2% were analyzed. Patients were categorized into several subgroups based on sex, age, and disease type. A phenotypic comorbidity network (PCN) was constructed, where comorbidities served as nodes and their significant correlations were represented as edges, encompassing all patients with TD and various subgroups. The associations and differences in comorbidities within the PCN of each subgroup were analyzed and compared. The PageRank algorithm was used to identify key comorbidities.

RESULTS

The final cohorts included 18,311 and 50,242 patients with TD in the private and public data sets, respectively. Patients with TD demonstrated complex comorbidity patterns, with coexistence relationships differing by sex, age, and type of TD. The number of comorbidities increased with age. The most prevalent TDs were nontoxic goiter, hypothyroidism, hyperthyroidism, and thyroid cancer, while hypertension, diabetes, and lipoprotein metabolism disorders had the highest prevalence and PageRank values among comorbidities. Males and patients with benign TD exhibited a greater number of comorbidities, increased disease diversity, and stronger comorbidity associations compared with females and patients with thyroid cancer.

CONCLUSIONS

Patients with TD exhibited complex comorbidity patterns, particularly with cardiocerebrovascular diseases and diabetes. The associations among comorbidities varied across different TD subgroups. This study aims to enhance the understanding of comorbidity patterns in patients with TD and improve the integrated management of these individuals.

Exploring the impact of breast cancer on colonization resistance of mouse microbiota using network node manipulation

Breast cancer, a global health concern affecting women, has been linked to alterations in the gut microbiota, impacting various aspects of human health. This study investigates the interplay between breast cancer and the gut microbiome, particularly focusing on colonization resistance-an essential feature of the microbiota's ability to prevent pathogenic overgrowth. Using a mouse model of breast cancer, we employ diversity analysis, co-occurrence network analysis, and robustness tests to elucidate the impact of breast cancer on microbiome dynamics. Our results reveal that breast cancer exposure affects the bacterial community's composition and structure, with temporal dynamics playing a role. Network analysis demonstrates that breast cancer disrupts microbial interactions and decreases network complexity, potentially compromising colonization resistance. Moreover, network robustness analysis shows the susceptibility of the microbiota to node removal, indicating potential vulnerability to pathogenic colonization. Additionally, predicted metabolic profiling of the microbiome highlights the significance of the enzyme EC 6.2.1.2 - Butyrate--CoA ligase, potentially increasing butyrate, and balancing the reduction of colonization resistance. The identification of Rubrobacter as a key contributor to this enzyme suggests its role in shaping the microbiota's response to breast cancer. This study uncovers the intricate relationship between breast cancer, the gut microbiome, and colonization resistance, providing insights into potential therapeutic strategies and diagnostic approaches for breast cancer patients.

The regional disparities in liver disease comorbidity among elderly Chinese based on a health ecological model: the China Health and Retirement Longitudinal Study

PURPOSE

This study aimed to investigate the risk factors for liver disease comorbidity among older adults in eastern, central, and western China, and explored binary, ternary and quaternary co-morbid co-causal patterns of liver disease within a health ecological model.

METHOD

Basic information from 9,763 older adults was analyzed using data from the China Health and Retirement Longitudinal Study (CHARLS). LASSO regression was employed to identify significant predictors in eastern, central, and western China. Patterns of liver disease comorbidity were studied using association rules, and spatial distribution was analyzed using a geographic information system. Furthermore, binary, ternary, and quaternary network diagrams were constructed to illustrate the relationships between liver disease comorbidity and co-causes.

RESULTS

Among the 9,763 elderly adults studied, 536 were found to have liver disease comorbidity, with binary or ternary comorbidity being the most prevalent. Provinces with a high prevalence of liver disease comorbidity were primarily concentrated in Inner Mongolia, Sichuan, and Henan. The most common comorbidity patterns identified were "liver-heart-metabolic", "liver-kidney", "liver-lung", and "liver-stomach-arthritic". In the eastern region, important combination patterns included "liver disease-metabolic disease", "liver disease-stomach disease", and "liver disease-arthritis", with the main influencing factors being sleep duration of less than 6 h, frequent drinking, female, and daily activity capability. In the central region, common combination patterns included "liver disease-heart disease", "liver disease-metabolic disease", and "liver disease-kidney disease", with the main influencing factors being an education level of primary school or below, marriage, having medical insurance, exercise, and no disabilities. In the western region, the main comorbidity patterns were "liver disease-chronic lung disease", "liver disease-stomach disease", "liver disease-heart disease", and "liver disease-arthritis", with the main influencing factors being general or poor health satisfaction, general or poor health condition, severe pain, and no disabilities.

CONCLUSION

The comorbidities associated with liver disease exhibit specific clustering patterns at both the overall and local levels. By analyzing the comorbidity patterns of liver diseases in different regions and establishing co-morbid co-causal patterns, this study offers a new perspective and scientific basis for the prevention and treatment of liver diseases.

Phenotypic Disease Network-Based Multimorbidity Analysis in Idiopathic Cardiomyopathy Patients with Hospital Discharge Records

BACKGROUND

Idiopathic cardiomyopathy (ICM) is a rare disease affecting numerous physiological and biomolecular systems with multimorbidity. However, due to the small sample size of uncommon diseases, the whole spectrum of chronic disease co-occurrence, especially in developing nations, has not yet been investigated. To grasp the multimorbidity pattern, we aimed to present a multidimensional model for ICM and differences among age groups.

METHODS

Hospital discharge records were collected from a rare disease centre of ICM inpatients (n = 1036) over 10 years (2012 to 2021) for this retrospective analysis. One-to-one matched controls were also included. First, by looking at the first three digits of the ICD-10 code, we concentrated on chronic illnesses with a prevalence of more than 1%. The ICM and control inpatients had a total of 71 and 69 chronic illnesses, respectively. Second, to evaluate the multimorbidity pattern in both groups, we built age-specific cosine-index-based multimorbidity networks. Third, the associated rule mining (ARM) assessed the comorbidities with heart failure for ICM, specifically.

RESULTS

The comorbidity burden of ICM was 78% larger than that of the controls. All ages were affected by the burden, although those over 50 years old had more intense interactions. Moreover, in terms of disease connectivity, central, hub, and authority diseases were concentrated in the metabolic, musculoskeletal and connective tissue, genitourinary, eye and adnexa, respiratory, and digestive systems. According to the age-specific connection, the impaired coagulation function was required for raising attention (e.g., autoimmune-attacked digestive and musculoskeletal system disorders) in young adult groups (ICM patients aged 20-49 years). For the middle-aged (50-60 years) and older (≥70 years) groups, malignant neoplasm and circulatory issues were the main confrontable problems. Finally, according to the result of ARM, the comorbidities and comorbidity patterns of heart failure include diabetes mellitus and metabolic disorder, sleeping disorder, renal failure, liver, and circulatory diseases.

CONCLUSIONS

The main cause of the comorbid load is aging. The ICM comorbidities were concentrated in the circulatory, metabolic, musculoskeletal and connective tissue, genitourinary, eye and adnexa, respiratory, and digestive systems. The network-based approach optimizes the integrated care of patients with ICM and advances our understanding of multimorbidity associated with the disease.

Global trends and regional differences in the burden of cancer attributable to secondhand smoke in 204 countries and territories, 1990–2019

Background

To describe the status quo and trends in the global burden of all cancers caused by secondhand smoke during 1990–2019.

Methods

Data on cancer associated with secondhand smoke were extracted from the Global Heath Data Exchange. Cancer burden was measured by cancer-related deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs).

Results

In 2019, age-standardized rates of death, DALYs and YLLs among the cancer population globally caused by secondhand smoke were 1.60, 38.54 and 37.77, respectively. The proportions of these in the total cancer burden for all risk factors combined decreased slightly from 1990 to 2003 and then increased from 2004 to 2019. In 2019, >50% of the cancer burden was concentrated in men aged 55–75 years and women aged 50–70 years. Between 1990 and 2019, there was an increase in age-standardized rates of death, DALYs, YLDs and YLLs among those aged ≥70 years. The age-standardized YLDs rate attributable to secondhand smoke was higher among women; it decreased in men but increased in women, causing a wider gap between the sexes. A greater cancer burden was mainly seen in North America in 1990 and Europe in 2019. Reductions in the annual rate change of cancer burden were found mainly in North America and Oceania, while increases were found in Africa and Asia. In 2019, high–middle- and middle-SDI countries had higher age-standardized rates of deaths, DALYs, YLDs and YLLs than the global level. During 1990 and 2019, the largest decline in cancer burden was seen in high-SDI countries, while middle- or low-SDI countries experienced increases in all age-standardized rates.

Conclusions

Cancer burden attributable to secondhand smoke is concerning given the increasing health loss and differences in distribution of cancer burden worldwide. Further studies are needed to investigate the causes of disparities in cancer burden attributable to secondhand smoke and to improve understanding of the contribution of secondhand smoke to the burden of different types of cancer.

Charlson comorbidity index is not associated with neutrophil-lymphocytes ratio in unselected hospitalized cancer patients: A cross-sectional study

This study sought to evaluate the association between Charlson Comorbidity Index (CCI) and neutrophil lymphocyte ratio (NLR). Cross-sectional study evaluated 134 patients of both sexes diagnosed with several types of cancer. NLR was calculated by dividing the absolute value of neutrophils by lymphocytes count, and the CCI questionnaire was used to assess the risk of comorbidities and mortality. The sample was dichotomized in CCI < 5 or ≥5. Student's t-test and Chi-square test were calculated to analyze the differences. The association between CCI and NLR was investigated by logistic regression analysis, performed with model 1 (crude) and model 2 (adjusted). The patients in the CCI ≥ 5 group were older, with higher neutrophil levels and prevalence of solid tumor type. There was no difference between groups regarding type of treatment, body weight, body mass index, performance status, lymphocyte count and NLR. There was no association between CCI and NLR, in both crude model (OR: 1.04 [95% CI: 0.99-1.09], p = 0.09), as well as adjusted for sex, age, physical activity, alcohol consumption, smoking habit, type of treatment, and performance status (OR: 1.04 [95% CI:0.97-1.12], p = 0.19). In hospitalized unselected cancer patients, despite of small sample size and design of study, we showed the presence of comorbidities is not related to the NLR.

Comorbidity combinations in schizophrenia inpatients and their associations with service utilization: A medical record-based analysis using association rule mining

BACKGROUND

Comorbidities are common among patients with schizophrenia yet the prevalence of comorbidity combinations and their associations with inpatient service utilization and readmission have been scarcely explored.

METHODS

Data were extracted from discharge summaries of patients whose primary diagnosis was schizophrenia spectrum disorders (ICD-10: F20-F29). We identified 30 most frequent comorbidities in patients' secondary diagnoses and then used the association rule mining (ARM) method to derive comorbidity combinations associated with length of stay (LOS), daily expense and one-year readmission.

RESULTS

The study included data from 8252 patients. The top five most common comorbidities were extrapyramidal syndrome (EPS, 44.58%), constipation (31.63%), common cold (21.80%), hyperlipidemia (20.99%) and tachycardia (19.13%). Most comorbidity combinations identified by ARM were significantly associated with longer LOS (≥70 days), few were associated with higher daily expenses, and fewer with readmission. The 3-way combination of common cold, hyperlipidemia and fatty liver had the strongest association with longer LOS (adjusted OR (aOR): 3.38, 95% CI: 2.12-5.38). The combination of EPS and mild cognitive disorder was associated with higher daily expense (≥700 RMB) (aOR: 1.67, 95% CI: 1.20-2.31). The combination of constipation, tachycardia and fatty liver were associated with higher 1-year readmission (aOR: 2.05, 95% CI: 1.03-4.09).

CONCLUSION

EPS, constipation, and tachycardia were among the most commonly reported comorbidities in schizophrenia patients in Beijing, China. Specific groups of comorbidities may contribute to higher inpatient psychiatric service utilization and readmission. The mechanism behind the associations and potential interventions to optimize service use warrant further investigation.

Phenotypic Disease Network Analysis to Identify Comorbidity Patterns in Hospitalized Patients with Ischemic Heart Disease Using Large-Scale Administrative Data

Ischemic heart disease (IHD) exhibits elevated comorbidity. However, few studies have systematically analyzed the comorbid status of IHD patients with respect to the entire spectrum of chronic diseases. This study applied network analysis to provide a complete picture of physical and mental comorbidities in hospitalized patients with IHD using large-scale administrative data. Hospital discharge records from a provincial healthcare database of IHD inpatients (n = 1,035,338) and one-to-one matched controls were included in this retrospective analysis. We constructed the phenotypic disease networks in IHD and control patients and further assessed differences in comorbidity patterns. The community detection method was applied to cluster diagnoses within the comorbidity network. Age- and sex-specific patterns of IHD comorbidities were also analyzed. IHD inpatients showed 50% larger comorbid burden when compared to controls. The IHD comorbidity network consisted of 1941 significant associations between 71 chronic conditions. Notably, the more densely connected comorbidities in IHD patients were not within the highly prevalent ones but the rarely prevalent ones. Two highly interlinked communities were detected in the IHD comorbidity network, where one included hypertension with heart and multi-organ failures, and another included cerebrovascular diseases, cerebrovascular risk factors and anxiety. Males exhibited higher comorbid burden than females, and thus more complex comorbidity relationships were found in males. Sex-specific disease pairs were detected, e.g., 106 and 30 disease pairs separately dominated in males and females. Aging accounts for the majority of comorbid burden, and the complexity of the comorbidity network increased with age. The network-based approach improves our understanding of IHD-related comorbidities and enhances the integrated management of patients with IHD.

Comorbidity Patterns of Older Lung Cancer Patients in Northeast China: An Association Rules Analysis Based on Electronic Medical Records

Purposes: This study aims to identify the comorbidity patterns of older men with lung cancer in China. Methods: We analyzed the electronic medical records (EMRs) of lung cancer patients over age 65 in the Jilin Province of China. The data studied were obtained from 20 hospitals of Jilin Province in 2018. In total, 1510 patients were identified. We conducted a rank–frequency analysis and social network analysis to identify the predominant comorbidities and comorbidity networks. We applied the association rules to mine the comorbidity combination with the values of confidence and lift. A heatmap was utilized to visualize the rules. Results: Our analyses discovered that (1) there were 31 additional medical conditions in older patients with lung cancer. The most frequent comorbidities were pneumonia, cerebral infarction, and hypertension. (2) The network-based analysis revealed seven subnetworks. (3) The association rules analysis provided 41 interesting rules. The results revealed that hypertension, ischemic cardiomyopathy, and pneumonia are the most frequent comorbid combinations. Heart failure may not have a strong implicating role in these comorbidity patterns. Cerebral infarction was rarely combined with other diseases. In addition, glycoprotein metabolism disorder comorbid with hyponatremia or hypokalemia increased the risk of anemia by more than eight times in older lung cancer patients. Conclusions: This study provides evidence on the comorbidity patterns of older men with lung cancer in China. Understanding the comorbidity patterns of older patients with lung cancer can assist clinicians in their diagnoses and contribute to developing healthcare policies, as well as allocating resources.