ObjectiveTo investigate the incidence, severity and longitudinal trajectories of symptoms at various time points in the perioperative period of lung cancer patients, and to provide scientific basis for clinical staff to implement predictive nursing and dynamic management of symptom clusters. MethodsA prospective longitudinal investigation was conducted. The patients with lung cancer who underwent thoracoscopic lung surgery in four wards of the Department of Thoracic Surgery in our hospital were investigated by face-to-face and telephone follow-up before surgery, 1-2 days after surgery, on the day of discharge and 2 weeks after discharge. The investigation tool was the revised Chinese version of MD Anderson Symptom Inventory lung cancer specific module. Results A total of 192 patients with lung cancer were included in this study, including 59 males and 133 females, with an average age of (55.68±11.01) years. There were two symptom clusters (respiratory-gastrointestinal and emotional/psychological-disturbed sleep symptom clusters) before surgery, three symptom clusters (respiratory, gastrointestinal, and emotional/psychological-disturbed sleep symptom clusters) 1-2 days after surgery, three symptom clusters (pain-fatigue-emotional/psychological, respiratory, and gastrointestinal symptom clusters) on the day of discharge, and two symptom clusters (pain-fatigue-respiratory and respiratory symptom clusters) 2 weeks after discharge. The composition of symptoms was different in each time point during perioperative period. ConclusionThere are four symptom clusters in patients with lung cancer during perioperative period, which are pain-fatigue-disturbed sleep symptoms, gastrointestinal symptoms, respiratory symptoms and emotional/psychological symptoms. The symptom clusters of lung cancer patients at different time points are relatively stable, but the symptoms within the symptom clusters show dynamic changes. Medical staff should attach great importance to and continuously monitor the dynamic changes of perioperative symptom groups of lung cancer patients, do relevant education and nursing in advance, and timely adjust the management plan according to the symptom group evaluation results.
Objective To investigate the latent categories of symptom cluster characteristics in patients with knee osteoarthritis (KOA) after total knee arthroplasty (TKA), and compare the quality of life between these categories. Methods Patients undergoing TKA for KOA in the joint surgery departments of four tertiary-level A hospitals in Urumqi, Xinjiang between November 2023 and March 2024 were selected for the study using the convenience sampling method. Symptoms of postoperative pain, swelling, anxiety, depression, and sleep disorders were collected from patients for latent class analysis using Mplus 8.3 software, and their influencing factors and differences in quality of life between categories were analyzed using SPSS 26.0 software. Results A total of 380 copies of questionnaire were distributed and 362 valid ones were returned, with a validity rate of 95.3%. Of the 362 patients, 342 (94.5%) had symptom cluster. The 342 patients aged 47-85 years, with a mean age of (65.25±7.03) years; 83 (24.3%) were male and 259 (75.7%) were female. According to the postoperative symptom cluster, the patients could be categorized into 3 latent categories: high-symptomatic group (16.1%), low-symptomatic group (51.8%), and high swelling group (32.2%). Compared to the low-symptomatic group, the current being the first joint surgery was a risk factor for the high-symptomatic group [odds ratio (OR)=2.732, 95% confidence interval (CI) (1.216, 6.139), P=0.015], whereas body mass index between 24.0 and 27.9 kg/m2 was a protective factor for the high-symptomatic group [OR=0.362, 95%CI (0.156, 0.840), P=0.018]; body mass index <24.0 kg/m2 was an independent risk factor for the high swelling group [OR=2.769, 95%CI (1.321, 5.803), P=0.007]. Comparison of the quality of life of patients in the 3 latent categories revealed that the high-symptomatic group had the lowest quality of life scores (P<0.05). Conclusion Post-TKA symptom cluster in patients with KOA can be classified into 3 potential categories, and the quality of life performance is different among different categories, so precise symptom management strategies should be provided according to the symptom characteristics of the patients to improve their quality of life.
Patients with inflammatory bowel disease (IBD) often face the complex challenge of multiple coexisting symptoms, and systematic assessment and management of symptom clusters are key to improving prognosis. This article provides a systematic review and analysis of domestic and international literature on symptom clusters in patients with IBD, briefly introduces the clinical characteristics of these symptom clusters, and summarizes the types, applicability, reliability, validity, and current application status of related assessment tools. At present, assessment tools for symptom clusters in patients with IBD still require optimization in terms of standardization and individualization. In the future, more precise symptom cluster management systems should be developed to provide a basis for research and clinical management of symptom clusters in these patients, thereby enhancing the precision of symptom management.
Objective To explore the incidence and severity of diverse clinical symptoms in patients with severe acute pancreatitis (SAP), construct a symptom correlation network model, accurately identify core symptoms within the network, and classify symptom clusters. MethodsA convenience sampling method was adopted. A total of 211 patients with SAP admitted to the First Affiliated Hospital with Nanjing Medical University (Jiangsu Provincial People’s Hospital) from January 2024 to December 2025 were enrolled. The memorial symptom assessment scale was used for evaluation to investigate the composition of clinical symptoms in SAP patients. Exploratory factor analysis was performed to extract symptom clusters. R 4.4.2 software was applied to construct symptom clusters network. Centrality indicators including strength, betweenness and closeness were analyzed to identify core symptoms and core symptom clusters. ResultsA total of three symptom clusters were extracted in this study, including the gastrointestinal symptom cluster (abdominal pain, abdominal distension, dyspnea, dry mouth, nausea, vomiting, diarrhea, constipation, dizziness), the fatigue symptom cluster (lack of energy, difficulty concentrating, drowsiness), and the psychological symptom cluster (anxiety, sleep disturbance, irritability, sadness, distress). Among them, anxiety [95.7% (202/211)], difficulty concentrating [94.8% (200/211)], lack of energy [92.4% (195/211)], and abdominal pain [90.0% (190/211)] were identified as core symptoms. Symptoms with high strength values included anxiety (rs=2.2), difficulty concentrating (rs=1.2), and dyspnea (rs=1.0); symptoms with high closeness centrality values included drowsiness (rc=1.8), difficulty concentrating (rc=1.7), and anxiety (rc=1.1); symptoms with high betweenness centrality values included difficulty concentrating (rb=2.3), anxiety (rb=2.0), and drowsiness (rb=1.5). ConclusionsAnxiety, difficulty concentrating, lack of energy, and abdominal pain were identified as the core symptoms within the symptom clusters of SAP patients, with the fatigue symptom cluster being the core symptom cluster. It is recommended that medical staff pay close attention to the manifestations of core symptoms in SAP patients during treatment and formulate targeted symptom management plans.
Patients with lung cancer commonly experience multiple interrelated symptoms during chemotherapy, including fatigue, pain, and sleep disturbance, which together form a core symptom cluster and substantially impair daily functioning, treatment experience, and quality of life. At present, evidence regarding the non-pharmacological management of this core symptom cluster remains fragmented, and there is a lack of standardized, comprehensible, and practical guidance tools designed for patients and their caregivers. This guideline was developed using an evidence-based methodological framework. Stakeholders’ health-related needs and concerns were identified through qualitative interviews and on-site questionnaire surveys. In accordance with predefined inclusion and exclusion criteria, systematic searches were conducted across domestic and international guideline repositories, websites of relevant professional associations, and comprehensive databases. The included literature was subjected to quality appraisal, and recommendations were extracted, synthesized, and graded to produce a summary of the best available evidence. Based on the identified health concerns and the evidence summary, preliminary recommendations for the patient guideline were formulated. These recommendations were subsequently revised through two rounds of Delphi expert consultation, during which consensus was reached on the strength of each recommendation. The final guideline comprises four major domains: screening and assessment of the core symptom cluster, daily management, intervention strategies, and indications for referral. Its core content covers nine areas: symptom-cluster screening, assessment, lifestyle modification, dietary interventions, sleep environment optimization, exercise interventions, psychological interventions, Traditional Chinese Medicine interventions, and referral criteria. The development of this patient guideline followed a rigorous process and fully incorporated patients’ needs, which demonstrates good feasibility, appropriateness, and clinical relevance, and can provide a decision-making basis for the self-management of the core symptom cluster among patients with lung cancer undergoing chemotherapy.