Lancet (London, England) · 2003
F J García-Miguel、P G Serrano-Aguilar、J López-Bastida
Although anaesthetic and surgical procedures should be individualised for every patient, in practice many preoperative protocols and routines are used generally. In this article, we aim to emphasise: why preoperative assessment is important; how it should be done, and by whom; what can be expected; and the importance of test selection based on patients' needs and on scientific evidence of effectiveness. We outline the roles of preoperative medical assessment in otherwise healthy patients. Clinical history, preoperative questionnaires, physical examination, routine tests, individual risk-assessment, and fasting policies are investigated by review of published work. Cost of routine preoperative assessment, the anaesthetist's legal responsibility, and patients'views in the preoperative process are also considered. A thorough clinical preoperative assessment of the patient is more important than routine preoperative tests, which should be requested only when justified by clinical indications. Moreover, this practice eliminates unnecessary cost without compromising the safety and quality of care. Education and training of medical doctors should be more scientifically guided, emphasising the relevance of effectiveness, and cost-effectiveness in clinical decision-making and complemented by audit.
Nature Medicine · 2025
Seong-Keun Yoo、C. Fitzgerald、B. A. Cho 等
Predicting whether a patient with cancer will benefit from immune checkpoint inhibitors (ICIs) without resorting to advanced genomic or immunologic assays is an important clinical need. To address this, we developed and evaluated SCORPIO, a machine learning system that utilizes routine blood tests (complete blood count and comprehensive metabolic profile) alongside clinical characteristics from 9,745 ICI-treated patients across 21 cancer types. SCORPIO was trained on data from 1,628 patients across 17 cancer types from Memorial Sloan Kettering Cancer Center. In two internal test sets comprising 2,511 patients across 19 cancer types, SCORPIO achieved median time-dependent area under the receiver operating characteristic curve (AUC(t)) values of 0.763 and 0.759 for predicting overall survival at 6, 12, 18, 24 and 30 months, outperforming tumor mutational burden (TMB), which showed median AUC(t) values of 0.503 and 0.543. Additionally, SCORPIO demonstrated superior predictive performance for predicting clinical benefit (tumor response or prolonged stability), with AUC values of 0.714 and 0.641, compared to TMB (AUC = 0.546 and 0.573). External validation was performed using 10 global phase 3 trials (4,447 patients across 6 cancer types) and a real-world cohort from the Mount Sinai Health System (1,159 patients across 18 cancer types). In these external cohorts, SCORPIO maintained robust performance in predicting ICI outcomes, surpassing programmed death-ligand 1 immunostaining. These findings underscore SCORPIO’s reliability and adaptability, highlighting its potential to predict patient outcomes with ICI therapy across diverse cancer types and healthcare settings. Using multiple datasets from real-world evidence and completed trials, a machine learning model using routine blood and clinical data is shown to be predictive of patient response to immune checkpoint inhibitor therapy, across cancer types and outperforming standard biomarkers.
Anesthesiology clinics · 2018
Angela F Edwards、Daniel J Forest
Obtaining routine preoperative laboratory tests increases health care costs and has been listed, by the Choosing Wisely Campaign, as one of the top 5 practices anesthesiologists should avoid. Routine testing without clinical indication is not cost-effective and could cause harm and unnecessary delays. Abnormal findings are more likely to be false positive and costly to pursue, introduce new risks, and increase anxiety for the patient. Preoperative testing need to be performed only following a targeted history and physical examination, factoring severity of surgery, and comorbidities such that the benefit of the test outweighs risk.
The journal of the Royal College of Physicians of Edinburgh · 2014
Y L Chee
The haemostatic system comprises four compartments: the vasculature, platelets, coagulation factors, and the fibrinolytic system. There is presently no laboratory or near-patient test capable of reproducing the complex regulated interaction between these four compartments. The prothrombin time (PT) and activated partial thromboplastin time (APTT) only test the coagulation protein compartment of the system and results have to be carefully interpreted in the context of the clinical presentation and assay limitations. This article will give a general overview of the limitations of PT and APTT and discuss specific issues that need to be considered when the tests are requested, in the context of anticoagulant monitoring, bleeding symptoms, and routine preoperative screening. Of these indications, routine preoperative screening is the most controversial and is generally not warranted in the absence of an abnormal bleeding history.
Journal of Cancer · 2021
Xiao-Ying Zhou、Han Chen、Wei-Feng Zhang 等
Aims: The present study was to evaluate the diagnostic value of routine blood test as potential inflammatory markers in early esophageal cancer (EEC) patients. Methods: A matched case-control study was conducted by recruiting 314 patients who were pathologically diagnosed with EEC and then underwent Endoscopic Submucosal Dissection (ESD) from July 2015 to July 2019 in First Affiliated Hospital of Nanjing Medical University. Each EEC patient was matched against one healthy control on the criteria of gender, and age (±2 years). Additionally, a total of 40 subjects (20 cases and 20 controls) were also included in the validation set. Statistical analysis of selected hematological parameters was performed between the two groups. The correlation between preoperative blood indexes and clinicopathological characteristics after ESD in EEC patients were further assessed. Results: Mono-factor analysis showed that the index of monocyte (p<0.001), MCV (p=0.018), MCH (p=0.01), MPV (p=0.022), PT (p=0.003), PT-INR (p=0.003), PDW (p<0.001) and MLR (p<0.001) were statistically significant in EEC patients when compared with those in healthy controls. Multivariate logistic regression analysis further identified that PDW and MLR was independently associated with the risk of early esophageal cancer (both p<0.001). The higher level of NLR (P=0.007) and MLR (P=0.015) were statistically significant with submucosal invasion in EEC patients and the level of MLR were significantly associated with larger tumor size (P=0.030). The results of the validation group were in consistence with the primary group. Conclusions: Hematological parameters of MLR and PDW can be used as an adjuvant tool for the diagnosis of EEC. Moreover, the value of MLR can reflect the invasion depth index.
Cancer management and research · 2021
Li-Wen Li、Xiao-Min Bu、Bin Wu 等
[This corrects the article DOI: 10.2147/CMAR.S268990.].
Journal of cardiac surgery · 2022
Pradeep Narayan、Gianni D Angelini
暂无摘要
BMC Cancer · 2023
Liping Luo、Yu-Bo Tan、Shixuan Zhao 等
Background Numerous studies have demonstrated that the high-order features (HOFs) of blood test data can be used to predict the prognosis of patients with different types of cancer. Although the majority of blood HOFs can be divided into inflammatory or nutritional markers, there are still numerous that have not been classified correctly, with the same feature being named differently. It is an urgent need to reclassify the blood HOFs and comprehensively assess their potential for cancer prognosis. Methods Initially, a review of existing literature was conducted to identify the high-order features (HOFs) and classify them based on their calculation method. Subsequently, a cohort of patients diagnosed with non-small cell lung cancer (NSCLC) was established, and their clinical information prior to treatment was collected, including low-order features (LOFs) obtained from routine blood tests. The HOFs were then computed and their associations with clinical features were examined. Using the LOF and HOF data sets, a deep learning algorithm called DeepSurv was utilized to predict the prognostic risk values. The effectiveness of each data set’s prediction was evaluated using the decision curve analysis (DCA). Finally, a prognostic model in the form of a nomogram was developed, and its accuracy was assessed using the calibration curve. Results From 1210 documents, over 160 blood HOFs were obtained, arranged into 110, and divided into three distinct categories: 76 proportional features, 6 composition features, and 28 scoring features. Correlation analysis did not reveal a strong association between blood features and clinical features; however, the risk value predicted by the DeepSurv LOF- and HOF-models is significantly linked to the stage. Results from DCA showed that the HOF model was superior to the LOF model in terms of prediction, and that the risk value predicted by the blood data model could be employed as a complementary factor to enhance the prognosis of patients. A nomograph was created with a C-index value of 0.74, which is capable of providing a reasonably accurate prediction of 1-year and 3-year overall survival for patients. Conclusions This research initially explored the categorization and nomenclature of blood HOF, and proved its potential in lung cancer prognosis.
International journal of surgery (London, England) · 2019
S B Navarrete、W B Rothstein、M J Scott
暂无摘要
Cancer Management and Research · 2020
Li-Wen Li、Xiao-Min Bu、Bin Wu 等
Background High-grade glioma (HGG) and solitary brain metastasis (sBM) patients show similar symptoms in clinical practice, and accurately differential diagnosis directly affects the management and prognosis of patients. The aim of this study was to distinguish two entities by preoperative serum β2-microglobulin (β2-m) and routine blood test-associated inflammatory indexes including, white blood cell (WBC), neutrophils, lymphocytes, monocytes, and platelets count, red cell distribution width (RDW), platelet distribution width (PDW), neutrophil/lymphocyte ratio (NLR) and monocyte/lymphocyte ratio (MLR). Patients and Methods A retrospective analysis was performed in the Cancer Hospital of the University of Chinese Academy of Sciences from January 2015 to December 2019, including 127 patients of newly pathologically diagnosed with HGG and 174 patients with sBM. Clinical information including age, gender, pathological diagnosis, preoperative serum β2-m and routine blood tests were collected, and NLR and MLR were calculated. The diagnostic significance of these markers for HGG and sBM was assessed by receiver operating characteristic (ROC) curves. Results The patients with sBM had significantly higher values of preoperative age, β2-m, NLR and MLR as well as lower lymphocytes count than patients with HGG. Besides, the area under the curve (AUC) in differentiating HGG from sBM was 0.625 (95%CI: 0.561–0.689) for age, 0.655 (0.594–0.717) for β2-m, 0.634 (0.571–0.698) for NLR and 0.622 (0.559–0.686) for MLR, and the combination of Age+β2-m+NLR+MLR showed the best diagnostic performance with AUC of 0.731 (0.675–0.788) and 0.048*Age+0.001*β2-m+0.201*NLR+0.594*MLR>5.813 could indicate sBM rather than HGG. Conclusion The Age+β2-m+NLR+MLR combination was revealed as an inexpensive and noninvasive biomarker for differentiating between HGG and sBM before surgery.
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