Elderly patients are a crucial population for medical treatment and referral.The establishment of standardized and efficient referral channels is essential for enhancing the referral process, improving treatment outcomes for the elderly, and optimizing the allocation of medical resources.Referral network analysis examines the integrity, structure, and dynamics of referrals to infer the characteristics of the network.This can offer insights for enhancing referral policies and elevating medical service standards.While existing research predominantly concentrates on referral networks within the general population, there is a noticeable gap in studies focusing on elderly patients.This review article assesses domestic and international research on networks formed between medical institutions or physicians through patient referrals, aiming to inform and enhance referral policies in our country.

Elderly patients are a crucial population for medical treatment and referral.The establishment of standardized and efficient referral channels is essential for enhancing the referral process, improving treatment outcomes for the elderly, and optimizing the allocation of medical resources.Referral network analysis examines the integrity, structure, and dynamics of referrals to infer the characteristics of the network.This can offer insights for enhancing referral policies and elevating medical service standards.While existing research predominantly concentrates on referral networks within the general population, there is a noticeable gap in studies focusing on elderly patients.This review article assesses domestic and international research on networks formed between medical institutions or physicians through patient referrals, aiming to inform and enhance referral policies in our country.

Objective:To investigate the clinicopathological characteristics of dedifferentiated endometrial carcinoma/undifferentiated endometrial carcinoma (DDEC/UDEC) with loss of expression of SMARCA4.Methods:A total of 10 cases with loss of expression of SMARCA4 were diagnosed at Fujian Cancer Hospital between January 2019 and December 2023. A retrospective analysis was conducted on the clinical characteristics, morphology, immunophenotype, molecular classification, and prognosis.Results:(1) Clinical characteristics: among 10 cases of DDEC/UDEC with loss of expression of SMARCA4, the patients′ age ranged from 48 to 65 years, with a median age of 56 years.Five cases were classified as International Federation of Gynecology and Obstetrics (FIGO) stages Ⅰ-Ⅱ, while the remaining five were categorized as stages Ⅲ-Ⅳ. (2) Pathological features: tumor cells exhibited poor cell adhesion, with common intravascular tumor emboli (8/10), occasional vacuolated nuclei (6/10), rhabdoid cells (4/10), and starry sky phenomenon formed by tissue cell phagocytosis apoptosis bodies or fragments (4/10). Six cases (6/10) showed loss of mismatch repair (MMR) protein expression, two cases (2/10) exhibited p53 mutant expression, and five cases (5/10) tested positive for programmed cell death ligand 1 (PD-L1). (3) Molecular subtyping: molecular subtyping revealed POLEmut in 1 case (1/10), mismatch repair deficient (MMR-d) in 5 cases (5/10), p53 abn in 1 case (1/10), and no specific molecular profile (NSMP) in 3 cases (3/10). (4) Prognosis: the follow-up period ranged from 7 to 42 months, with a median of 20 months. Five patients succumbed to the tumor, whereas the remaining five exhibited no recurrence during subsequent postoperative evaluations. The 2-year progression-free survival rates and overall survival rates were 58.3% and 52.5%, respectively.Conclusions:Loss of expression of SMARCA4 occurs in approximately 1/5 of DDEC/UDEC, which presents with an aggressive clinical course and a poor prognosis. About half of them show MMR protein loss expression and PD-L1 positive expression, suggesting that there might be benefit from treatment with immune checkpoint inhibitors.

Objective:To investigate the risk factors that were associated with the death of elderly patients who were admitted to the intensive care unit (ICU) after elective abdominal surgery, and to find reliable and sensitive predictive indicators for early interventions and reducing the mortality.Methods:A retrospective case-control study was conducted. The clinical data of elderly (age≥65 years old) patients after elective abdominal surgery admitted to the ICU of the Affiliated Hospital of Guizhou Medical University from January 1st 2016 to December 31st 2020 were collected, including the patient's gender, age, body mass index (BMI), medical history, American Society of Anesthesiologists (ASA) grades, surgical classification, intraoperative blood loss, duration of operation, interval time between end of operation and admission to the ICU, acute physiology and chronic health evaluationⅡ(APACHEⅡ) score and the worst laboratory examination results within 24 hours of ICU admission, the first blood gas analysis in ICU, the duration of invasive mechanical ventilation, and the length of ICU stay. Postoperative abdominal infection was evaluated by the pathogenic culture of peritoneal drainage fluid and clinical symptoms and signs. The patients were divided into death group and survival group based on clinical outcomes, and clinical data were compared between the two groups. Binary multivariate Logistic regression analysis was used to screen the risk factors of death, and the receiver operator characteristic curve (ROC curve) was plotted to analyze the predictive values of these risk factors.Results:A total of 226 elderly patients with elective abdominal surgery were admitted to the ICU of our hospital during the past 5 years, of whom, two patients who did not undergo laboratory examinations within 24 hours of admission to the ICU were excluded. Finally, 224 patients met the criteria, with 158 survivors and 66 deaths. Univariate analysis showed that: compared with survival group, APACHEⅡscore, blood lactate acid (Lac) and the proportion of postoperative abdominal infection were higher in death group [APACHEⅡ score: 27.5 (25.0, 31.3) vs. 23.0 (18.0, 27.0), Lac (mmol/L): 2.9 (1.8, 6.6) vs. 1.8 (1.1, 2.8), the proportion of postoperative abdominal infection: 65.2% (43/66) vs. 35.4% (56/158), all P < 0.01], prothrombin time (PT), activated partial thromboplastin time (APTT) and interval time between end of surgery and admission to ICU were longer [PT (s): 17.20 (14.50, 18.63) vs. 14.65 (13.90, 16.23), APTT (s): 45.15 (38.68, 55.15) vs. 39.45 (36.40, 45.70), interval time between end of surgery and admission to ICU (hours): 39.2 (0.7, 128.9) vs. 0.7 (0.3, 2.0), all P <0.01], postoperative hemoglobin (Hb), platelet count (PLT), prealbumin (PA), mean arterial pressure (MAP) and oxygenation index (PaO 2/FiO 2) were lower in death group [Hb (g/L): 95.79±23.64 vs. 105.58±19.82, PLT (×10 9/L): 138.5 (101.0, 177.5) vs. 160.5 (118.5, 232.3), PA (g/L): 80.88±43.63 vs. 116.54±50.80, MAP (mmHg, 1 mmHg = 0.133 kPa): 76.8±19.1 vs. 91.6±19.8, PaO 2/FiO 2 (mmHg): 180.0 (123.5, 242.5) vs. 223.5 (174.8, 310.0), all P < 0.05]. Binary multivariate Logistic regression analysis showed that APACHEⅡscore [odds ratio ( OR) = 1.187, 95% confidence interval (95% CI) =1.008-1.294, P < 0.001], interval time between end of operation and admission to ICU ( OR = 1.005, 95% CI = 1.001-1.009, P = 0.016) and postoperative abdominal infection ( OR = 2.630, 95% CI = 1.148-6.024, P = 0.022) were independent risk factors for prognosis in these patients. MAP ( OR = 0.978, 95% CI = 0.957-0.999, P = 0.041) and PaO 2/FiO 2 ( OR = 0.994, 95% CI = 0.990-0.998, P = 0.003) were protective factors for the patients' prognosis. Lac, Hb, PLT, PA, PT and APTT had no predictive value for the prognosis of elderly patients admitted to ICU after elective abdominal surgery [ OR value and 95% CI were 1.075 (0.945-1.223), 1.011 (0.99-1.032), 1.000 (0.995-1.005), 0.998 (0.989-1.007), 1.051 (0.927-1.192) and 1.003 (0.991-1.016), respectively, all P > 0.05. ROC curve analysis showed that APACHEⅡscore, interval time between end of operation and admission to the ICU and the postoperative abdominal infection had certain predictive values for the prognosis of elderly patients, the area under ROC curve (AUC) were 0.755, 0.732 and 0.649 respectively, all P < 0.001; When the cut-off of APACHEⅡscore and interval time between end of operation and admission to the ICU were 24.5 scores and 2.15 hours, the sensitivity were 78.8% and 66.7%, respectively, and the specificity were 62.0% and 76.6%, respectively. The combined predictive value of the three variables was the highest, which AUC was 0.846, the joint prediction probability was 0.27, the sensitivity was 83.3%, and the specificity was 75.3%. Conclusion:APACHEⅡscore, interval time between end of surgery and admission to ICU, and postoperative abdominal infection may be independent risk factors for the death of elderly patients who were admitted to the ICU after elective abdominal surgery, there would be far greater predictive values when the three variables were combined.