Backgrounds/AimsRanson's score (RS) and Glasgow score (GS) have been utilized to stratify the severity of acute pancreatitis (AP). The aim of this study was to validate RS and GS for stratifying the severity of acute pancreatitis and audit our experience of managing AP.MethodsWe conducted a retrospective review of patients treated for AP from July 2009 to September 2016. Final severity was determined using the revised Atlanta classification. Mortality and complications were analyzed.ResultsFrom July 2009 to September 2016, a total of 675 patients with a diagnosis of AP were admitted at the hospital. Of them, 669 patients who had sufficient data were analyzed. Their average age±SD was 58.7±17.4 years (range, 21–98 years). There was a male preponderance (n=393, 53.8%). A total of 82 (12.3%) patients had eventual severe pancreatitis. RS demonstrated a sensitivity of 92.7% and a specificity of 52.8% with a positive predictive value (PPV) of 21.5% and a negative predictive value (NPV) of 98.1%. GS demonstrated a sensitivity of 76.8% and a specificity of 69.2% with a PPV of 25.8% and a NPV of 95.5%. For severity prediction, areas under the curve (AUCs) for RS and GS were 0.848 (95% CI: 0.819–0.875) and 0.784 (95% CI: 0.750–0.814), respectively (p=0.003). Twelve (1.6%) patients died in the hospital.ConclusionsRS has higher sensitivity, NPV and AUC for predicting severity of AP than GS.
BACKGROUND Acute pancreatitis (AP) is a common surgical condition, with severe AP (SAP) potentially lethal. Many prognostic indices, including; acute physiology and chronic health evaluation II score (APACHE II), bedside index of severity in acute pancreatitis (BISAP), Glasgow score, harmless acute pancreatitis score (HAPS), Ranson’s score, and sequential organ failure assessment (SOFA) evaluate AP severity and predict mortality. AIM To evaluate these indices' utility in predicting severity, intensive care unit (ICU) admission, and mortality. METHODS A retrospective analysis of 653 patients with AP from July 2009 to September 2016 was performed. The demographic, clinical profile, and patient outcomes were collected. SAP was defined as per the revised Atlanta classification. Values for APACHE II score, BISAP, HAPS, and SOFA within 24 h of admission were retrospectively obtained based on laboratory results and patient evaluation recorded on a secure hospital-based online electronic platform. Data with < 10% missing data was imputed via mean substitution. Other patient information such as demographics, disease etiology, and patient outcomes were also derived from electronic medical records. RESULTS The mean age was 58.7 ± 17.5 years, with 58.7% males. Gallstones ( n = 404, 61.9%), alcohol ( n = 38, 5.8%), and hypertriglyceridemia ( n = 19, 2.9%) were more common aetiologies. 81 (12.4%) patients developed SAP, 20 (3.1%) required ICU admission, and 12 (1.8%) deaths were attributed to SAP. Ranson’s score and APACHE-II demonstrated the highest sensitivity in predicting SAP (92.6%, 80.2% respectively), ICU admission (100%), and mortality (100%). While SOFA and BISAP demonstrated lowest sensitivity in predicting SAP (13.6%, 24.7% respectively), ICU admission (40.0%, 25.0% respectively) and mortality (50.0%, 25.5% respectively). However, SOFA demonstrated the highest specificity in predicting SAP (99.7%), ICU admission (99.2%), and mortality (98.9%). SOFA demonstrated the highest positive predictive value, positive likelihood ratio, diagnostic odds ratio, and overall accuracy in predicting SAP, ICU admission, and mortality. SOFA and Ranson’s score demonstrated the highest area under receiver-operator curves at 48 h in predicting SAP (0.966, 0.857 respectively), ICU admission (0.943, 0.946 respectively), and mortality (0.968, 0.917 respectively). CONCLUSION The SOFA and 48-h Ranson’s scores accurately predict severity, ICU admission, and mortality in AP, with more favorable statistics for the SOFA score.
Purpose This study identified factors predicting malignant upgrade for atypical ductal hyperplasia (ADH) diagnosed on core-needle biopsy (CNB) and developed a nomogram to facilitate evidence-based decision making. Methods This retrospective analysis included women diagnosed with ADH at the National Cancer Centre Singapore (NCCS) in 2010–2015. Cox proportional hazards regression was used to identify clinical, radiological, and histological factors associated with malignant upgrade. A nomogram was constructed using variables with the strongest associations in multivariate analysis. Multivariable logistic regression coefficients were used to estimate the predicted probability of upgrade for each factor combination. Results Between 2010 and 2015, 238,122 women underwent mammographic screening under the National Breast Cancer Screening Program. Among 29,564 women recalled, 5,971 CNBs were performed. Of these, 2,876 underwent CNBs at NCCS, with 88 patients (90 lesions) diagnosed with ADH and 26 lesions upgraded to breast malignancy on excision biopsy. In univariate analysis, factors associated with malignant upgrade were the presence of a mass on ultrasound ( p = 0.018) or mammography ( p = 0.026), microcalcifications ( p = 0.047), diffuse microcalcification distribution ( p = 0.034), mammographic parenchymal density ( p = 0.008). and ≥ 3 separate ADH foci found on biopsy ( p = 0.024). Mammographic parenchymal density (hazard ratio [HR], 0.04; 95% confidence interval [CI], 0.005–0.35; p = 0.014), presence of a mass on ultrasound (HR, 10.50; 95% CI, 9.21–25.2; p = 0.010), and number of ADH foci (HR, 1.877; 95% CI, 1.831–1.920; p = 0.002) remained significant in multivariate analysis and were included in the nomogram. Conclusion Our model provided good discrimination of breast cancer risk prediction (C-statistic of 0.81; 95% CI, 0.74–0.88) and selected for a subset of women at low risk (2.1%) of malignant upgrade, who may avoid surgical excision following a CNB diagnosis of ADH.
BackgroundPeritoneal surface malignancies (PSM) present insidiously and often pose diagnostic challenges. There is a paucity of literature quantifying the frequency and extent of therapeutic delays in PSM and its impact on oncological outcomes.MethodsA review of a prospectively maintained registry of PSM patients undergoing Cytoreductive Surgery and Hyperthermic Intra-peritoneal Chemotherapy (CRS-HIPEC) was conducted. Causes for treatment delays were identified. We evaluate the impact of delayed presentation and treatment delays on oncological outcomes using Cox proportional hazards models.Results319 patients underwent CRS-HIPEC over a 6-years duration. 58 patients were eventually included in this study. Mean duration between symptom onset and CRS-HIPEC was 186.0 ± 37.1 days (range 18-1494 days) and mean duration of between patient-reported symptom onset and initial presentation was 56.7 ± 16.8 days. Delayed presentation (> 60 days between symptom onset and presentation) was seen in 20.7% (n=12) of patients and 50.0% (n=29) experienced a significant treatment delay of > 90 days between 1st presentation and CRS-HIPEC. Common causes for treatment delays were healthcare provider-related i.e. delayed or inappropriate referrals (43.1%) and delayed presentation to care (31.0%). Delayed presentation was a significantly associated with poorer disease free survival (DFS) (HR 4.67, 95% CI 1.11-19.69, p=0.036).ConclusionDelayed presentation and treatment delays are common and may have an impact on oncological outcomes. There is an urgent need to improve patient education and streamline healthcare delivery processes in the management of PSM.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.