British journal of hospital medicine最新文献

Aims/Background Elderly patients are at increased risk of hypoxemia in the post-anesthesia care unit (PACU) after general anesthesia. The Integrated Pulmonary Index (IPI) may have predictive value in identifying these patients. This study aimed to investigate the predictive value of the IPI for PACU hypoxemia in elderly patients after general anesthesia. Methods A retrospective analysis was conducted on 276 patients who underwent general anesthesia surgeries at Zhongshan Hospital, Fudan University, between December 2021 and December 2024. Patients were divided into a PACU hypoxemia group (n = 96) and a non-PACU hypoxemia group (n = 180). Univariate and binary logistic regression analyses were used to determine influencing factors, and a receiver operating characteristic (ROC) curve analysis was conducted to evaluate the predictive value of IPI for PACU hypoxemia in elderly patients after general anesthesia. Results Binary logistic regression analysis revealed that IPI was an independent influencing factor of PACU hypoxemia in elderly patients (p < 0.05). ROC analysis showed that IPI had an area under the curve of 0.843 (95% confidence interval [CI]: 0.799-0.887, p = 0.002), with a standard error of 0.023, a Youden index of 0.58, sensitivity of 85.42%, specificity of 72.22%, and an optimal cut-off value of 7.5. The discharge rate of patients with IPI >7.5 was significantly higher than that of patients with IPI ≤7.5 (p < 0.05). Conclusion IPI demonstrates a certain predictive value of PACU hypoxemia in elderly patients after general anesthesia.

Interstitial lung disease (ILD), a common manifestation of systemic sclerosis (SSc), has the highest organ-specific morbidity and mortality, particularly in patients with diffuse cutaneous SSc (dcSSc). Recent advances in diagnostics-including artificial intelligence (AI)-enhanced high-resolution computed tomography (HRCT) and biomarkers such as Krebs van den Lungen (KL)-6-have enabled earlier detection and monitoring of disease progression. Therapeutically, the approval of antifibrotics like nintedanib (NINT) and immunomodulators such as tocilizumab (Toci) has significantly expanded treatment options. Updated international guidelines from the American College of Rheumatology (ACR), American College of Chest Physicians (CHEST), American Thoracic Society (ATS), and European league against Rheumatism (EULAR) now reflect this evolving landscape. This review aims to provide a comprehensive synthesis of screening, monitoring, and therapeutic strategies in systemic sclerosis-associated interstitial lung disease (SSc-ILD), emphasizing recent advances in AI-based imaging, serological biomarkers, and updated international treatment guidelines. We conclude by highlighting the shift toward combination and potentially triple therapy approaches, and we propose future research directions aimed at improving biomarker validation, mechanistic understanding, and personalized treatment strategies.

Rehabilitation is an essential aspect in the care of stroke patients, both in the acute and long-term setting to improve patient outcomes and enhance their independence. In this review, we aim to summarise the pertinent points of the updated guidelines surrounding stroke rehabilitation to aid the general clinician. Importantly, we highlight recommendations such as the increase of rehabilitation intensity to 3 hours per day to improve patient outcomes, as well as the support of telerehabilitation to enable patients to remain in the community and assist in addressing unequal resource distribution across geographical locations. We emphasise that stroke rehabilitation should be personalised and focused on the patient's individual needs and goals. Future research should further explore the potential integration of psychosocial rehabilitation and remote technologies.

Aims/Background Early diagnosis of neonatal sepsis is hindered by nonspecific clinical signs and suboptimal biomarkers. Therefore, this study aimed to evaluate the diagnostic accuracy of serum procalcitonin (PCT) and C-reactive protein (CRP), both individually and in combination, and assess the robustness and clinical utility of a combined predictive model. Methods This single-center retrospective cohort (2022-2025, Longyan First Hospital Affiliated to Fujian Medical University, China) included 293 neonates (161 with sepsis and 132 controls). Univariate logistic regression was applied to compare the clinical and laboratory parameters between the sepsis and control groups. Diagnostic accuracy was evaluated using receiver operating characteristic (ROC) curves, contingency tables, and the DeLong tests. A logistic regression-based combined prediction model was developed using a 7:3 stratified random split into training and validation sets. Model robustness was assessed via calibration plots, decision curve analysis (DCA), and visualized as a nomogram. Subgroup and culture-confirmed-only sensitivity analyses further assessed the consistency of the combined predictive model. Results Sepsis cases exhibited significantly higher PCT, CRP, and white blood cell (WBC), and lower hemoglobin (Hb) and platelet (PLT) (all p < 0.001). Univariate logistic regression confirmed PCT [odds ratio (OR) = 3.32, 95% confidence interval (CI): 2.23-4.93, p < 0.001] and CRP (OR = 1.03, 95% CI: 1.01-1.05, p = 0.003) as significant predictors of neonatal sepsis. The combined PCT-CRP model provided better diagnostic performance, achieving a significantly greater area under the curve (AUC) of 0.94 (95% CI 0.92-0.97) than either marker alone (0.88 for PCT, 0.87 for CRP) as shown by DeLong test (p < 0.001). Furthermore, the model maintained higher sensitivity (82.61%) while significantly improving specificity (93.18%) and overall diagnostic accuracy (87.36%). The nomogram, validated in both sets, exhibited good calibration and net clinical benefit in DCA. Subgroup analysis confirmed consistent predictive performance across gestational age, delivery mode, and sex, with CRP more pronounced in preterm infants. Sensitivity analyses using culture-confirmed sepsis validated model robustness (AUC = 0.94). Conclusion PCT and CRP are key diagnostic biomarkers for neonatal sepsis. Their integration as a combined predictive model significantly enhances diagnostic performance and clinical applicability, providing a practical framework for early sepsis identification and potential for clinical implementation.

Hypernatremia, defined as an elevated serum sodium concentration, is a critical electrolyte imbalance with significant neurological and systemic effects. Effective management hinges on understanding the condition's underlying aetiology, such as dehydration, excessive sodium intake, or impaired renal water handling. The approach to treatment varies by onset and severity: acute hypernatremia (<48 hours) necessitates rapid but controlled correction to prevent complications like vascular rupture or cerebral bleeding, while chronic hypernatremia (≥48 hours) requires gradual intervention to mitigate the risk of cerebral edema. Treatment focuses on restoring water balance through intravenous fluids (typically hypotonic solutions) while monitoring serum sodium levels to prevent overcorrection. Identifying and addressing associated conditions, such as diabetes insipidus (DI) or volume depletion, is crucial. Advances in the understanding of pathophysiology have informed clinical guidelines, emphasizing personalized care based on patient-specific factors, such as age, comorbidities, and the underlying cause of hypernatremia. Despite improvements in treatment protocols, challenges remain in managing hypernatremia in critically ill patients, where both rapid and excessively slow corrections are associated with increased mortality. Further research is needed to refine management strategies, develop predictive biomarkers for better risk assessment, and optimize outcomes in diverse patient populations. This review highlights the importance of a multidisciplinary approach in diagnosing, treating, and preventing complications of hypernatremia, ensuring safer and more effective care delivery.

Aims/Background Breast signet ring cell carcinoma (SRCC) represents an uncommon tumour that has not been extensively studied. This investigation sought to assess the clinical characteristics and prognosis of breast SRCC and compare them with those of invasive ductal carcinoma (IDC). Methods We obtained clinicopathological data from the Surveillance, Epidemiology, and End Results (SEER) database, including 222 patients with breast SRCC and 492,559 patients with IDC. Clinical features, treatments, and survival outcomes were compared between the two groups. Propensity score matching (PSM) methodology was used to balance baseline characteristics when evaluating overall survival (OS) and cancer-specific survival (CSS). Sensitivity analyses employing E-values quantified the potential impact of unmeasured confounding, and multiple imputation by chained equations (MICE) was used to address missing data for molecular subtype and histological grade. Additionally, predictive models in the form of nomograms were developed to estimate OS and CSS for patients with breast SRCC. Results Compared with IDC, breast SRCC was significantly associated with older age and more advanced tumour, node, metastasis (TNM) stage (p < 0.05 for all). Kaplan-Meier analyses revealed that breast SRCC patients exhibited markedly poorer survival outcomes (OS and CSS, p < 0.05) compared to IDC patients before PSM. For breast SRCC, the median OS was 67.0 months and the median CSS was 90.0 months. The OS rates at 3, 5, and 8 years stood at 60.9%, 51.5%, and 39.6%, respectively, while the corresponding CSS rates were 67.7%, 59.7%, and 48.6%. Following PSM analysis, survival outcomes between breast SRCC and IDC patients became comparable (p > 0.05). Multivariable assessment identified age, histological grade, T stage, and surgical intervention as independent OS predictors (p < 0.05 for all) in breast SRCC, while histological grade, T stage, and surgical approach were independent CSS factors (p < 0.05 for all). The nomograms were subsequently validated using the concordance index (C-index), receiver operating characteristic (ROC), calibration curves, and decision curve analysis (DCA), demonstrating robust prognostic capability. Sensitivity analysis revealed E-values of 1.35 (OS) and 1.49 (CSS), which exceeded typical confounder effects. Multiple imputation demonstrated consistent results (OS: hazard ratio [HR] = 1.20, 95% confidence interval [CI] 0.94-1.54; CSS: HR = 1.30, 95% CI 0.86-1.97), supporting the robustness of the findings. Conclusion Breast SRCC is associated with poorer outcomes primarily due to more advanced stage at presentation rather than histological type alone. Nomograms were developed to estimate OS and CSS for patients with breast SRCC.