Does vitreous haemorrhage and calcification lead to increased risk of enucleation in advanced retinoblastoma?

PURPOSE

To explore whether varying degrees of vitreous haemorrhage (VH) and calcification act as risk factors for enucleation in patients with advanced retinoblastoma (RB).

METHODS

Advanced RB was defined by the international classification of RB (Philadelphia version). Basic information for retinoblastoma patients diagnosed as groups D and E in our hospital between January 2017 and June 2022 was reviewed by logistics regression models. Additionally, a correlation analysis was performed, excluding variables with a VIF (variance inflation factor) >10 from the multivariate analysis.

RESULTS

A total of 223 eyes diagnosed with RB were included in assessing VH and calcification; of these, 101 (45.3%) eyes experienced VH, and 182 (76.2%) eyes were found to have calcification within the tumour through computed tomography (CT) or B-scan ultrasonography. Ninety-two eyes (41.3%) were enucleated, of which 67 (72.8%) had VH and 68 (73.9%) calcification, both of which were significantly relevant to enucleation (p < 0.001*). Other clinical risk factors, such as corneal edema, anterior chamber haemorrhage, high intraocular pressure during treatment and iris neovascularization, correlated significantly with enucleation (p < 0.001*). Multivariate analysis included IIRC (intraocular international retinoblastoma classification), VH, calcification and high intraocular pressure during treatment as independent risk factors for enucleation.

CONCLUSIONS

Despite identifying different potential risk factors for RB, there remains significant controversy concerning which patients require enucleation, and the degree of VH varies. Such eyes need to be evaluated carefully, and management with appropriate adjuvant therapy may improve the outcome of these patients.

Quantitative Analysis of Multimodal MRI Markers and Clinical Risk Factors for Cerebral Small Vessel Disease Based on Deep Learning

Background

Cerebral small vessel disease lacks specific clinical manifestations, and extraction of valuable features from multimodal images is expected to improve its diagnostic accuracy. In this study, we used deep learning techniques to segment cerebral small vessel disease imaging markers in multimodal magnetic resonance images and analyze them with clinical risk factors.

Methods and results

We recruited 211 lacunar stroke patients and 83 control patients. The patients' cerebral small vessel disease markers were automatically segmented using a V-shaped bottleneck network, and the number and volume were calculated after manual correction. The segmentation results of the V-shaped bottleneck network for white matter hyperintensity and recent small subcortical infarction were in high agreement with the ground truth (DSC>0.90). In small lesion segmentation, cerebral microbleed (average recall=0.778; average precision=0.758) and perivascular spaces (average recall=0.953; average precision=0.923) were superior to lacunar infarct (average recall=0.339; average precision=0.432) in recall and precision. Binary logistic regression analysis showed that age, systolic blood pressure, and total cerebral small vessel disease load score were independent risk factors for lacunar stroke (P<0.05). Ordered logistic regression analysis showed age was positively correlated with cerebral small vessel disease load score and total cholesterol was negatively correlated with cerebral small vessel disease score (P<0.05).

Conclusion

Lacunar stroke patients exhibited higher cerebral small vessel disease imaging markers, and age, systolic blood pressure, and total cerebral small vessel disease score were independent risk factors for lacunar stroke patients. V-shaped bottleneck network segmentation network based on multimodal deep learning can segment and quantify various cerebral small vessel disease lesions to some extent.

Developing and evaluating a predictive model for neonatal hyperbilirubinemia based on UGT1A1 gene polymorphism and clinical risk factors

Background

Neonatal hyperbilirubinemia (NHB) is one of the most common diseases in the neonatal period. Without timely diagnosis and treatment, it can lead to long-term complications. In severe cases, it may even result in fatality. The UGT1A1 gene and clinical risk factors play important roles in the development and progression of NHB.

Methods

In this study, we conducted a cohort study and analyzed 3258 newborns from the Jilin Women And Children Health Hospital in northern China, including 372 children with hyperbilirubinemia. We established a predictive model using a logistic regression model based on clinical risk factors and the polymorphism of the G211A locus in the UGT1A1 gene of newborns. Furthermore, the performance of the prediction model was evaluated using the ROC curve.

Results

The logistic regression model indicates that the following factors are associated with an increased risk of NHB: the time when stool turns yellow [P ≤ 0.001, OR 1.266 (95% CI: 1.125-1.425)]; neonatal cephalohematoma [P ≤ 0.001, OR 33.642 (95% CI: 21.823-51.861)]; hemolytic disease of newborn [P ≤ 0.001, OR 33.849 (95% CI: 18.589-61.636)]; neonatal weight loss [P ≤ 0.001, OR 11.275 (95% CI: 7.842-16.209)]; neonatal premature rupture of membranes (PROM) history [P = 0.021, OR 1.422 (95% CI: 1.056-1.917)]; genetic polymorphism at the UGT1A1 gene G211A locus. Gestational age is a protective factor [P ≤ 0.001, OR 0.766 (95% CI: 0.686-0.855)]. Compared to natural labor, cesarean section is a protective factor [P = 0.011, OR 0.711 (95% CI: 0.546-0.926)], while assisted delivery is a risk factor [P = 0.022, OR 2.207 (95% CI: 1.121-4.346)]. The area under the curve (AUC) of this prediction model is 0.804 (95% CI: 0.777-0.831), indicating good discrimination ability and value for predicting the risk of NHB after birth.

Conclusion

We have developed and evaluated a predictive model that combines UGT1A1 gene polymorphism and clinical risk factors for the first time. By using this nomogram and taking into account the results of serum total bilirubin measurement or transcutaneous bilirubin measurement, early prediction of the risk of neonatal hyperbilirubinemia can be achieved.

A Prospective Study on the Progression, Recurrence, and Regression of Cervical Lesions: Assessing Various Screening Approaches

(1) Background: The prediction of cervical lesion evolution is a challenge for clinicians. This prospective study aimed to determine and compare the predictive accuracy of cytology, HPV genotyping, and p16/Ki67 dual staining alone or in combination with personal risk factors in the prediction of progression, regression, or persistence of cervical lesions in human papillomavirus (HPV)-infected patients; (2) Methods: This prospective study included HPV-positive patients with or without cervical lesions who underwent follow-up in a private clinic. We calculated the predictive performance of individual tests (cervical cytology, HPV genotyping, CINtecPlus results, and clinical risk factors) or their combination in the prediction of cervical lesion progression, regression, and persistence; (3) Results: The highest predictive performance for the progression of cervical lesions was achieved by a model comprising a Pap smear suggestive of high-grade squamous intraepithelial lesion (HSIL), the presence of 16/18 HPV strains, a positive p16/Ki67 dual staining result along with the presence of at least three clinical risk factors, which had a sensitivity (Se) of 74.42%, a specificity of 97.92%, an area under the receiver operating curve (AUC) of 0.961, and an accuracy of 90.65%. The prediction of cervical lesion regression or persistence was modest when using individual or combined tests; (4) Conclusions: Multiple testing or new biomarkers should be used to improve HPV-positive patient surveillance, especially for cervical lesion regression or persistence prediction.

Diagnosing postoperative lymph node metastasis in thyroid cancer with multimodal radiomics and clinical features

Purpose

This study aims to evaluate the diagnostic value of texture analysis for lymph node metastasis after thyroid cancer surgery.

Methods

We retrospectively analyzed patients who underwent positron emission tomography/computed tomography (PET/CT) examination before 131I treatment at Shanghai Tenth People's Hospital between 2017 and 2020. Clinical follow-up results were used as the criterion for determining the presence of lymph node metastasis. The study included 119 patients, who were then randomly divided into training and test groups in a 7:3 ratio. Regions of interest were identified, and radiomics features were extracted using LIFEx 7.3.0. Mann-Whitney U test and LASSO regression were employed to screen radiomics parameters for modeling. Subsequently, a nomogram model was built by combining radscore and clinical features. SPSS 26.0 software was utilized for statistical analysis, and p < 0.05 was considered statistically significant.

Results

Follow-up confirmed 54 patients with thyroid cancer lymph node metastasis and 65 patients in the non-metastasis group. A total of 119 lymph nodes were delineated. For each lesion, 164 CT texture features and 164 PET texture features were extracted, and 107 significant parameters were identified, including 16 CT texture parameters and 91 PET texture parameters. After screening, 3 CT parameters, 4 PET parameters and 12 PET/CT parameters were selected to establish three radiomic models. The AUC values were as follows: AUC (CT) = 0.730, AUC (PET) = 0.759 and AUC (PET/CT) = 0.864. We then combined clinical features and radscore to construct a nomogram, resulting in a C-index of 0.915 in the training group. In the test group, the C-index was confirmed to be 0.868.

Conclusions

Radiomics may enhance the diagnostic efficiency of lymph node metastases after thyroid cancer surgery and could potentially assist clinicians in future diagnoses. The developed nomogram, which combines radiomics and clinical features, offers relatively high accuracy in helping clinicians assess the risk of metastasis in thyroid patients after surgery.

Hemorrhagic Transformation of Ischemic Strokes

Ischemic stroke, resulting from insufficient blood supply to the brain, is among the leading causes of death and disability worldwide. A potentially severe complication of the disease itself or its treatment aiming to restore optimal blood flow is hemorrhagic transformation (HT) increasing morbidity and mortality. Detailed summaries can be found in the literature on the pathophysiological background of hemorrhagic transformation, the potential clinical risk factors increasing its chance, and the different biomarkers expected to help in its prediction and clinical outcome. Clinicopathological studies also contribute to the improvement in our knowledge of hemorrhagic transformation. We summarized the clinical risk factors of the hemorrhagic transformation of ischemic strokes in terms of risk reduction and collected the most promising biomarkers in the field. Also, auxiliary treatment options in reperfusion therapies have been reviewed and collected. We highlighted that the optimal timing of revascularization treatment for carefully selected patients and the individualized management of underlying diseases and comorbidities are pivotal. Another important conclusion is that a more intense clinical follow-up including serial cranial CTs for selected patients can be recommended, as clinicopathological investigations have shown HT to be much more common than clinically suspected.

Multi-Clinical Factors Combined with an Artificial Intelligence Algorithm Diagnosis Model for HIV-Infected People with Bloodstream Infection

Purpose

Although highly active antiretroviral therapy (HA-ART) can effectively suppress the disease process in patients with acquired immunodeficiency syndrome (AIDS), opportunistic infections, mainly bloodstream infections (BSI), are still the main cause of death in people living with HIV. There is no effective diagnostic strategy for HIV-infected people with BSI. This study aimed to develop an AI diagnostic model with high sensitivity to improve the early detection of HIV-infected people with BSI.

Patients and Methods

This study retrospectively analyzed the 40 clinical factors of 498 HIV-infected people (171 with BSI positive and 327 with BSI negative) who admitted to Wenzhou Central Hospital from September 2014 to July 2021. This study used the hospital information management system to collect the clinical characteristics, laboratory and imaging examination results, and clinical diagnosis of the two groups. The diagnostic results of all patients were in line with the diagnostic criteria of the Chinese Guidelines for the Diagnosis and Treatment of AIDS (2021 Edition), and the BSI diagnosis was in line with the diagnostic criteria of sepsis and bacteremia in Practical Internal Medicine (13th Edition). On this basis, various risk prediction models were established by combining 8 artificial intelligence (AI) algorithms in the training set and validating the diagnosis performance in the testing set. The model with the best diagnostic performance was selected as the final diagnostic model.

Results

The clinical characteristics of HIV-infected people with BSI are atypical, and the pathogens in this area are mainly fungi. Ten risk factors were selected: low level of hemoglobin, CD4+T cell and platelets, high level of lactate dehydrogenase and blood urea nitrogen, splenomegaly, without ART treatment, strip shadow, nodular shadow, and shock. The combination of the ten risk factors, age, gender and the "svmRadial" model can identify the HIV-infected people with BSI from the HIV-infected people without BSI with an area under the curve of 0.916 and a sensitivity and specificity of 0.824 and 0.855, respectively.

Conclusion

The model showed excellent performance in diagnosing HIV-infected people with BSI. Internal and external validation showed that the diagnosis model had high clinical application value.

The long-term survival of esophageal cancer in elderly patients: A multi-center, retrospective study from China

BACKGROUND

Esophageal cancer (EC) often occurs in the elderly, and approximately 40% of patients are 70 years or older. To investigate the long-term survival of EC in elderly patients, to provide a theoretical direction for better management and predicting survival of EC based on the hospital-based multi-center study in China.

METHODS

The study was conducted in 18 hospitals including 6 provincial hospitals, 8 municipal hospitals, and 4 county hospitals. We extracted information from medical record homepage, records of admission and discharge, and pathological diagnosis reports from the medical record department of the elderly patients at 70-84 years old to obtain the 3-year and 5-year overall survival (OS), and main associated factors, and to analyze the current therapeutic effect of different treatment options for elderly patients.

RESULTS

The 3-year and 5-year OS rate of the 1013 elderly patients was 44.8% and 32.8%, respectively. Their median survival was 28.00 months. The median survival of patients with squamous cell carcinoma was longer than that of other pathological type (squamous vs. other types: 31.00 vs. 20.00 months, p = 0.018). The median survival of patients with surgery only or combined therapy was longer than that of radiotherapy, chemotherapy, and no therapy (surgery only vs. combined therapy vs. radiotherapy vs. chemotherapy vs. no therapy: 56.00 vs. 33.00 vs. 26.00 vs.18.00 vs. 16.00 months, p < 0.001). The 5-year OS rate of patients with highly differentiated cancer was higher than that of medium differentiated and poor differentiation/undifferentiated. In multivariate analysis, the older ages, pathological stage, were independent prognostic risk factors for poor EC survival. Treatment method was independent protective factors predictive of a good EC OS.

CONCLUSIONS

The survival rate of the elderly EC patients was still low in China. Age, therapy method, and pathological stage were mainly associated with the survival rate of EC in elderly patients.

Predicting mortality risk in dialysis: Assessment of risk factors using traditional and advanced modeling techniques within the Monitoring Dialysis Outcomes initiative

INTRODUCTION

Several factors affect the survival of End Stage Kidney Disease (ESKD) patients on dialysis. Machine learning (ML) models may help tackle multivariable and complex, often non-linear predictors of adverse clinical events in ESKD patients. In this study, we used advanced ML method as well as a traditional statistical method to develop and compare the risk factors for mortality prediction model in hemodialysis (HD) patients.

MATERIALS AND METHODS

We included data HD patients who had data across a baseline period of at least 1 year and 1 day in the internationally representative Monitoring Dialysis Outcomes (MONDO) Initiative dataset. Twenty-three input parameters considered in the model were chosen in an a priori manner. The prediction model used 1 year baseline data to predict death in the following 3 years. The dataset was randomly split into 80% training data and 20% testing data for model development. Two different modeling techniques were used to build the mortality prediction model.

FINDINGS

A total of 95,142 patients were included in the analysis sample. The area under the receiver operating curve (AUROC) of the model on the test data with XGBoost ML model was 0.84 on the training data and 0.80 on the test data. AUROC of the logistic regression model was 0.73 on training data and 0.75 on test data. Four out of the top five predictors were common to both modeling strategies.

DISCUSSION

In the internationally representative MONDO data for HD patients, we describe the development of a ML model and a traditional statistical model that was suitable for classification of a prevalent HD patient's 3-year risk of death. While both models had a reasonably high AUROC, the ML model was able to identify levels of hematocrit (HCT) as an important risk factor in mortality. If implemented in clinical practice, such proof-of-concept models could be used to provide pre-emptive care for HD patients.

Fracture risk and fracture prevalence in women from outpatient osteoporosis clinic and subjects from population-based sample: A comparison between GO Study and RAC-OST-POL cohorts

BACKGROUND

The method of recruiting the study subjects is an important element of the study design. It can have a strong influence on the results. Different recruitment schedules can give a different picture of the studied phenomenon.

OBJECTIVES

The aim of the study was to compare bone health in a group of female patients treated for osteoporosis with a population-based sample.

MATERIAL AND METHODS

A cohort of women from GO Study from 1 outpatient osteoporotic clinic (n = 1442, mean age 65.8 ±6.7 years) and population-based female sample of RAC-OST-POL Study (n = 963, mean age 65.8 ±7.5 years) were studied. Mean age did not differ between groups. Mean weight, height and body mass index (BMI) in subjects from GO Study and RAC-OST-POL Study were 69.5 ±13.1 kg, 157.8 ±6.1 cm and 27.9 ±5.1 kg/m2, and 74.2 ±13.7 kg, 156.0 ±6.0 cm and 30.5 ±5.4 kg/m2, respectively, and differed significantly (p < 0.0001 for each variable). Data on clinical risk factors for osteoporosis and fractures were collected. Bone densitometry at hip was performed using a Prodigy or Lunar DPX device (GE Healthcare, Waukesha, USA). Fracture risk was established using FRAX, Garvan and POL-RISK.

RESULTS

Mean values of T-score for femoral neck in subjects from GO Study and RAC-OST-POL Study were -1.67 ±0.91 and -1.27 ±0.91 and differed significantly (p < 0.0001). In GO Study and RAC-OST-POL Study, there were 518 (35.9%) and 280 (29.1%) subjects with fractures, respectively. The fracture frequency was significantly higher in the GO Study group (p < 0.001). Among clinical risk factors, only rheumatoid arthritis (p < 0.0001) secondary osteoporosis (p < 0.0001) and falls (p < 0.0001) were more frequent in RAC-OST-POL Study. Fracture risk established using FRAX, Garvan and POL-RISK calculators was significantly greater in patients enrolled in the GO Study than in subjects from the RAC-OST-POL population-based sample (p < 0.0001 for each variable).

CONCLUSIONS

Differences noted between female patients treated for osteoporosis and population-based sample, especially in regard to fracture risk, reveal a strong influence of recruitment criteria on study results in the field of bone health and osteoporosis.

A Predictive Clinical-Radiomics Nomogram for Differentiating Tuberculous Spondylitis from Pyogenic Spondylitis Using CT and Clinical Risk Factors

OBJECTIVE

The study aimed to develop and validate a nomogram model with clinical risk factors and radiomic features for differentiating tuberculous spondylitis (TS) from pyogenic spondylitis (PS).

METHODS

A total of 254 patients with TS (n = 141) or PS (n = 113) were randomly divided into training (n = 180) and validation (n = 74) groups. In addition, 43 patients (TS = 22 and PS = 21) were collected to construct a test cohort. t-test analysis, de-redundancy analysis, and minimum absolute shrinkage and selection operator (lasso) algorithm were utilized on the training set to obtain the optimal radiomics features from computed tomography (CT) for constructing the radiomics model and determine the radiomics score (Rad-score). Eight clinical risk predictors were identified to develop the clinical model. Combined with clinical risk predictors and Rad-scores, a nomogram model was constructed using multivariate logistic regression analysis.

RESULTS

A total of 1781 features were extracted, and 12 optimal radiomic features were utilized to construct the radiomic model and determine the Rad-score. The combined clinical radiomics model revealed good discrimination performance in both the training cohort and the validation cohort (AUC = 0.891 and 0.830) and was superior to the clinical (AUC = 0.807 and 0.785) and radiomics (AUC = 0.796 and 0.811) models. The calibration curve and DCA also depicted that the nomogram had better clinical efficacy. The discriminative performance of the model is well validated in the test cohort (AUC=0.877).

CONCLUSION

The clinical radiomic nomogram could serve as a promising predictive tool for differentiating TS from PS, which could be helpful for clinical decision-making.

Clinical Risk Factors for Aortic Root Dilation in Patients with 22q11.2 Deletion Syndrome: A Longitudinal Single-Center Study

BACKGROUND

Aortic root dilation (ARD) has been described in 22q11.2DS, even without congenital heart disease (CHD). However, the clinical implications and longitudinal course are unclear. In this study, we evaluated aortic root (AR) dimensions in 22q112.DS adolescents/adults without major intracardiac CHDs, analyzed the progression over time and investigated correlations with extracardiac comorbidities.

METHODS

AR dimensions were evaluated in 74 patients, measuring the sinus of Valsalva (VS) and proximal ascending aorta (AA), using Z-score to define mild, moderate and severe degrees. Changes in AR dimensions during longitudinal echocardiographic follow-up were investigated. Phenotypic characteristics have been collected.

RESULTS

Twenty-four patients (32.4%) showed ARD in terms of VS Z-score (2.43; IQR 2.08-3.01), eight (33.3%) of a moderate/severe degree. Thirteen (54.2%) had concomitant AAD (Z-score 2.34; IQR 1.60-2.85). The risk of ARD was significantly directly related to skeletal/connective tissue disorders (OR 12.82, 95% CI 1.43-115.31; p = 0.023) and inversely related to BMI (OR 0.86, 95% CI 0.77-0.97; p = 0.011). A significant increase in AR diameter's absolute value (p = 0.001) over time has been detected.

CONCLUSION

Isolated ARD is common in 22q11.2DS. Although some clinical risk factors have been identified, pathogenetic mechanisms and risk of complications are undefined. Regular cardiac evaluations should be part of the 22q11.2DS follow-up, and also in non-CHDs patients, to improve long-term outcome.

Black and White Adults With CKD Hospitalized With Acute Kidney Injury: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study

RATIONALE & OBJECTIVE

Few studies have investigated racial disparities in acute kidney injury (AKI), in contrast to the extensive literature on racial differences in the risk of kidney failure. We sought to study potential differences in risk in the setting of chronic kidney disease (CKD).

STUDY DESIGN

Prospective cohort study.

SETTING & PARTICIPANTS

We studied 2,720 self-identified Black or White participants with CKD enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study from July 1, 2013, to December 31, 2017.

EXPOSURE

Self-reported race (Black vs White).

OUTCOME

Hospitalized AKI (≥50% increase from nadir to peak serum creatinine).

ANALYTICAL APPROACH

Cox regression models adjusting for demographics (age and sex), prehospitalization clinical risk factors (diabetes, blood pressure, cardiovascular disease, estimated glomerular filtration rate, proteinuria, receipt of angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers), and socioeconomic status (insurance status and education level). In a subset of participants with genotype data, we adjusted for apolipoprotein L1 gene (APOL1) high-risk status and sickle cell trait.

RESULTS

Black participants (n = 1,266) were younger but had a higher burden of prehospitalization clinical risk factors. The incidence rate of first AKI hospitalization among Black participants was 6.3 (95% CI, 5.5-7.2) per 100 person-years versus 5.3 (95% CI, 4.6-6.1) per 100 person-years among White participants. In an unadjusted Cox regression model, Black participants were at a modestly increased risk of incident AKI (HR, 1.22 [95% CI, 1.01-1.48]) compared with White participants. However, this risk was attenuated and no longer significant after adjusting for prehospitalization clinical risk factors (adjusted HR, 1.02 [95% CI, 0.83-1.25]). There were only 11 AKI hospitalizations among individuals with high-risk APOL1 risk status and 14 AKI hospitalizations among individuals with sickle cell trait.

LIMITATIONS

Participants were limited to research volunteers and potentially not fully representative of all CKD patients.

CONCLUSIONS

In this multicenter prospective cohort of CKD patients, racial disparities in AKI incidence were modest and were explained by differences in prehospitalization clinical risk factors.

Fracture risk assessment by the FRAX model

The introduction of the FRAX algorithms has facilitated the assessment of fracture risk on the basis of fracture probability. FRAX integrates the influence of several well-validated risk factors for fracture with or without the use of bone mineral density. Since age-specific rates of fracture and death differ across the world, FRAX models are calibrated with regard to the epidemiology of hip fracture (preferably from national sources) and mortality (usually United Nations sources). Models are currently available for 73 nations or territories covering more than 80% of the world population. FRAX has been incorporated into more than 80 guidelines worldwide, although the nature of this application has been heterogeneous. The limitations of FRAX have been extensively reviewed. Arithmetic procedures have been proposed in order to address some of these limitations, which can be applied to conventional FRAX estimates to accommodate knowledge of dose exposure to glucocorticoids, concurrent data on lumbar spine bone mineral density, information on trabecular bone score, hip axis length, falls history, type 2 diabetes, immigration status and recency of prior fracture.

Reaching 80 Years of Age: Clinical, Behavioral, and Psychosocial Related Risk Factors in a Large Cohort of Israeli Working Men

The objective of this study was to estimate the probability of long-term overall survival based on total number of risk factors (RF). We also sought to examine the role of midlife clinical, behavioral, and psychosocial predictors of longevity in a large cohort of Israeli men. This study was based on the Israeli Ischemic Heart Disease (IIHD) cohort that included over 10,000 men who were followed up for mortality over more than four decades. During the 43 years of follow-up, 4634 (46.1%) men survived to 80 years of age or older. We considered cigarette smoking, diabetes mellitus, high systolic blood pressure, hypercholesterolemia, low socioeconomic status, and serious family problems as RF at ages 40–65. Cox proportional hazards regression models, with age as the time scale, were constructed to estimate the hazard ratios (HRs) for failure to survive 80 years of age. Compared with men free of all the above RF, those with one identified RF (HR = 1.58, 95% CI: 1.42–1.75) and counterparts with two identified RF (HR = 2.18, 95% CI: 1.96–2.43) were at a significantly greater risk of death before 80. Additional RF further increased the risk of early mortality (HR = 3.62, 95% CI: 1.50–8.73 for men with 5 RF). The results suggest a role of physiological, behavioral, and psychological risk factors at midlife in predicting longevity.

Practice Guidelines for the Diagnosis of COVID-19-Associated Pulmonary Aspergillosis in an Intensive Care Setting

Coronavirus disease-2019 (COVID-19)-associated pulmonary aspergillosis (CAPA) is a new disease characterized by secondary Aspergillus mold infection in patients with COVID-19. It primarily affects patients with COVID-19 in critical state with acute respiratory distress syndrome, requiring intensive care and mechanical ventilation. CAPA has a higher mortality rate than COVID-19, posing a serious threat to affected individuals. COVID-19 is a potential risk factor for CAPA and has already claimed a massive death toll worldwide since its outbreak in December 2019. Its second wave is currently progressing towards a peak, while the third wave of this devastating pandemic is expected to follow. Therefore, an early and accurate diagnosis of CAPA is of utmost importance for effective clinical management of this highly fatal disease. However, there are no uniform criteria for diagnosing CAPA in an intensive care setting. Therefore, based on a review of existing information and our own experience, we have proposed new criteria in the form of practice guidelines for diagnosing CAPA, focusing on the points relevant for intensivists and pulmonary and critical care physicians. The main highlights of these guidelines include the role of CAPA-appropriate test specimens, clinical risk factors, computed tomography of the thorax, and non-culture-based indirect and direct mycological evidence for diagnosing CAPA in the intensive care unit. These guidelines classify the diagnosis of CAPA into suspected, possible, and probable categories to facilitate clinical decision-making. We hope that these practice guidelines will adequately address the diagnostic challenges of CAPA, providing an easy-to-use and practical algorithm to clinicians for rapid diagnosis and clinical management of the disease.

Perianal Fistula-Associated Carcinoma in Crohn's Disease: A Multicentre Retrospective Case Control Study

BACKGROUND AND AIMS

Carcinoma associated with perianal fistula in Crohn's disease is a pending threat for patients. This study aimed to improve understanding and facilitate development of diagnostic and therapeutic strategies.

METHODS

A retrospective case-control study was conducted at four German hospitals. The analysis included 40 patients with proven malignancy associated with perianal Crohn's fistulas and 40 randomly selected controls with fistulizing perianal Crohn's disease. Differences between groups were analysed and multivariate calculations were performed to describe risk factors for oncological outcomes.

RESULTS

Histology revealed adenocarcinoma in 33/40 patients and squamous cell carcinoma in 7/40 patients. Compared to fistula patients without carcinoma, patients with malignancies associated with fistula had a diagnosis of Crohn's disease at younger age. Crohn's disease lasted longer in patients with malignancy [25.8 ± 9.0 vs 19.6 ± 10.4; p = 0.006]. Fistula-related findings differed significantly between the two groups. Signs of complicated and severe fistulation including complex anatomy and chronic activity occurred significantly more often in patients with malignancy associated with fistula. Significant multivariate hazard ratios for overall mortality and progression-free survival were shown for histological type of cancer, metastatic disease and R1 resection. Overall survival was 45.1 ± 28.6 months and the 5-year survival rate was 65%.

CONCLUSIONS

In patients with adenocarcinoma or squamous cell carcinoma associated with perianal fistula in Crohn's disease, fistula characteristics determine the risk of malignancy. Early diagnosis influences outcomes, while treatment of chronic fistula activity may be key to preventing malignancy. Expert multimodal therapy is paramount for successful treatment of perianal fistula-associated malignancies.

Association of Coronary Artery Disease and Metabolic Syndrome: Usefulness of Serum Metabolomics Approach

Introduction

Individuals with metabolic syndrome (MetS) are at increasing risk of coronary artery disease (CAD). We investigated the common metabolic perturbations of CAD and MetS via serum metabolomics to provide insight into potential associations.

Methods

Non-targeted serum metabolomics analyses were performed using ultra high-performance liquid chromatography coupled with Q Exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry (UHPLC-Q-Orbitrap HRMS) in samples from 492 participants (272 CAD vs. 121 healthy controls (HCs) as cohort 1, 55 MetS vs. 44 HCs as cohort 2). Cross-sectional data were obtained when the participants were recruited from the First Affiliated Hospital of Zhengzhou University. Multivariate statistics and Student's t test were applied to obtain the significant metabolites [with variable importance in the projection (VIP) values >1.0 and p values <0.05] for CAD and MetS. Logistic regression was performed to investigate the association of identified metabolites with clinical cardiac risk factors, and the association of significant metabolic perturbations between CAD and MetS was visualized by Cytoscape software 3.6.1. Finally, the receiver operating characteristic (ROC) analysis was evaluated for the risk prediction values of common changed metabolites.

Results

Thirty metabolites were identified for CAD, mainly including amino acids, lipid, fatty acids, pseudouridine, niacinamide; 26 metabolites were identified for MetS, mainly including amino acids, lipid, fatty acids, steroid hormone, and paraxanthine. The logistic regression results showed that all of the 30 metabolites for CAD, and 15 metabolites for MetS remained significant after adjustments of clinical risk factors. In the common metabolic signature association analysis between CAD and MetS, 11 serum metabolites were significant and common to CAD and MetS outcomes. Out of this, nine followed similar trends while two had differing directionalities. The nine common metabolites exhibiting same change trend improved risk prediction for CAD (86.4%) and MetS (90.9%) using the ROC analysis.

Conclusion

Serum metabolomics analysis might provide a new insight into the potential mechanisms underlying the common metabolic perturbations of CAD and MetS.

Multidimensional Clinical Surveillance of Pseudomonas aeruginosa Reveals Complex Relationships between Isolate Source, Morphology, and Antimicrobial Resistance

Antimicrobial susceptibility in Pseudomonas aeruginosa is dependent on a complex combination of host and pathogen-specific factors. Through the profiling of 971 clinical P. aeruginosa isolates from 590 patients and collection of paired patient metadata, we show that antimicrobial resistance is associated with not only patient-centric factors (e.g., cystic fibrosis and antipseudomonal prescription history) but also microbe-specific phenotypes (e.g., mucoid colony morphology). Additionally, isolates from different sources (e.g., respiratory tract, urinary tract) displayed rates of antimicrobial resistance that were correlated with source-specific antimicrobial prescription strategies. Furthermore, isolates from the same patient often displayed a high degree of heterogeneity, highlighting a key challenge facing personalized treatment of infectious diseases. Our findings support novel relationships between isolate and patient-level data sets, providing a potential guide for future antimicrobial treatment strategies. IMPORTANCE P. aeruginosa is a leading cause of nosocomial infection and infection in patients with cystic fibrosis. While P. aeruginosa infection and treatment can be complicated by a variety of antimicrobial resistance and virulence mechanisms, pathogen virulence is rarely recorded in a clinical setting. In this study, we discovered novel relationships between antimicrobial resistance, virulence-linked morphologies, and isolate source in a large and variable collection of clinical P. aeruginosa isolates. Our work motivates the clinical surveillance of virulence-linked P. aeruginosa morphologies as well as the tracking of source-specific antimicrobial prescription and resistance patterns.

A Nomogram Based on a Multiparametric Ultrasound Radiomics Model for Discrimination Between Malignant and Benign Prostate Lesions

Objectives

To evaluate the potential of a clinical-based model, a multiparametric ultrasound-based radiomics model, and a clinical-radiomics combined model for predicting prostate cancer (PCa).

Methods

A total of 112 patients with prostate lesions were included in this retrospective study. Among them, 58 patients had no prostate cancer detected by biopsy and 54 patients had prostate cancer. Clinical risk factors related to PCa (age, prostate volume, serum PSA, etc.) were collected in all patients. Prior to surgery, patients received transrectal ultrasound (TRUS), shear-wave elastography (SWE) and TRUS-guided prostate biopsy. We used the five-fold cross-validation method to verify the results of training and validation sets of different models. The images were manually delineated and registered. All modes of ultrasound radiomics were retrieved. Machine learning used the pathology of “12+X” biopsy as a reference to draw the benign and malignant regions of interest (ROI) through the application of LASSO regression. Three models were developed to predict the PCa: a clinical model, a multiparametric ultrasound-based radiomics model and a clinical-radiomics combined model. The diagnostic performance and clinical net benefit of each model were compared by receiver operating characteristic curve (ROC) analysis and decision curve.

Results

The multiparametric ultrasound radiomics reached area under the curve (AUC) of 0.85 for predicting PCa, meanwhile, AUC of B-mode radiomics and SWE radiomics were 0.74 and 0.80, respectively. Additionally, the clinical-radiomics combined model (AUC: 0.90) achieved greater predictive efficacy than the radiomics model (AUC: 0.85) and clinical model (AUC: 0.84). The decision curve analysis also showed that the combined model had higher net benefits in a wide range of high risk threshold than either the radiomics model or the clinical model.

Conclusions

Clinical-radiomics combined model can improve the accuracy of PCa predictions both in terms of diagnostic performance and clinical net benefit, compared with evaluating only clinical risk factors or radiomics score associated with PCa.

Contribution of Genetic Background and Data Collection on Adverse Events of Anti-human Immunodeficiency Virus (HIV) Drugs (D:A:D) Clinical Risk Score to Chronic Kidney Disease in Swiss HIV-infected Persons With Normal Baseline Estimated Glomerular Filtration Rate

BACKGROUND

In human immunodeficiency virus (HIV), the relative contribution of genetic background, clinical risk factors, and antiretrovirals to chronic kidney disease (CKD) is unknown.

METHODS

We applied a case-control design and performed genome-wide genotyping in white Swiss HIV Cohort participants with normal baseline estimated glomerular filtration rate (eGFR >90 mL/minute/1.73 m2). Univariable and multivariable CKD odds ratios (ORs) were calculated based on the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) score, which summarizes clinical CKD risk factors, and a polygenic risk score that summarizes genetic information from 86 613 single-nucleotide polymorphisms.

RESULTS

We included 743 cases with confirmed eGFR drop to <60 mL/minute/1.73 m2 (n = 144) or ≥25% eGFR drop to <90 mL/minute/1.73 m2 (n = 599), and 322 controls (eGFR drop <15%). Polygenic risk score and D:A:D score contributed to CKD. In multivariable analysis, CKD ORs were 2.13 (95% confidence interval [CI], 1.55-2.97) in participants in the fourth (most unfavorable) vs first (most favorable) genetic score quartile; 1.94 (95% CI, 1.37-2.65) in the fourth vs first D:A:D score quartile; and 2.98 (95% CI, 2.02-4.66), 1.70 (95% CI, 1.29-2.29), and 1.83 (95% CI, 1.45-2.40), per 5 years of exposure to atazanavir/ritonavir, lopinavir/ritonavir, and tenofovir disoproxil fumarate, respectively. Participants in the first genetic score quartile had no increased CKD risk, even if they were in the fourth D:A:D score quartile.

CONCLUSIONS

Genetic score increased CKD risk similar to clinical D:A:D score and potentially nephrotoxic antiretrovirals. Irrespective of D:A:D score, individuals with the most favorable genetic background may be protected against CKD.

Rapid Progression of Kidney Dysfunction in People Living With HIV: Use of Polygenic and Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) Risk Scores

BACKGROUND

In people with human immunodeficiency virus (PWH), it is unknown whether genetic background associates with rapid progression of kidney dysfunction (ie, estimated glomerular filtration rate [eGFR] decrease of >5mL/min/1.73m2 per year for ≥3 consecutive years).

METHODS

We obtained univariable and multivariable hazard ratios (HR) for rapid progression, based on the clinical D:A:D chronic kidney disease (CKD) risk score, antiretroviral exposures, and a polygenic risk score based on 14 769 genome-wide single nucleotide polymorphisms in white Swiss HIV Cohort Study participants.

RESULTS

We included 225 participants with rapid progression and 3378 rapid progression-free participants. In multivariable analysis, compared to participants with low D:A:D risk, participants with high risk had rapid progression (HR =  1.82 [95% CI, 1.28-2.60]). Compared to the first (favorable) polygenic risk score quartile, participants in the second, third, and fourth (unfavorable) quartiles had rapid progression (HR = 1.39 [95% CI, 0.94-2.06], 1.52 [95% CI, 1.04-2.24], and 2.04 [95% CI, 1.41-2.94], respectively). Recent exposure to tenofovir disoproxil fumarate was associated with rapid progression (HR = 1.36 [95% CI, 1.06-1.76]).

DISCUSSION

An individual polygenic risk score is associated with rapid progression in Swiss PWH, when analyzed in the context of clinical and antiretroviral risk factors.

Longitudinal Network Structure and Changes of Clinical Risk and Protective Factors in a Nationwide Sample of Forensic Psychiatric Patients

In this study, we investigated network configurations of 14 Clinical risk and protective factors in a sample of 317 male forensic psychiatric patients across two time points: at the time of admission to the forensic psychiatric centers (T1) and at the time of unconditional release (T2). In terms of network structure, the strongest risk edge was between "hostility-violation of terms" at T1, and between "hostility-impulsivity" at T2. "Problem insight-crime responsibility" was the strongest protective edge, and "impulsivity-coping skills" was the strongest between-cluster edge, at both time points, respectively. In terms of strength centrality, "cooperation with treatment" had the highest strength centrality at both measurement occasions. This study expands the risk assessment field toward a better understanding of dynamic relationships between individual clinical risk and protective factors and points to the highly central risk and protective factors, which would be the best for future treatment targets.

Risk factors for mortality and management of children with complicated severe acute malnutrition at a tertiary referral hospital in Malawi

BACKGROUND

Severe acute malnutrition (SAM) is a major cause of childhood mortality in resource-limited settings. The relationship between clinical factors and adherence to the 'WHO 10 Steps' and mortality in children with SAM is not fully understood.

METHODS

Data from an ongoing prospective observational cohort study assessing admission characteristics, management patterns and clinical outcome in children aged 6-36 months admitted to a tertiary hospital in Malawi from September 2018 to September 2019 were analysed. Data clerks independently collected data from patients' charts. Demographics, clinical and nutritional status, identification of SAM and adherence to the 'WHO 10 Steps' were summarised. Their relationship to in-hospital mortality was assessed using multivariable logistic regression.

RESULTS

Of the 6752 patients admitted, 9.7% had SAM. Mortality was significantly higher in those with SAM (10.1% vs 3.8%, p < 0.001). Compared with independent assessment anthropometrics, clinicians appropriately documented SAM on admission in 39.5%. The following factors were independently associated with mortality: kwashiorkor [adjusted odds ratio (aOR) 5.14, 95% confidence interval (CI) 1.27-20.78], shock (aOR 18.54, 95% CI 3.87-88.90), HIV-positive (aOR 5.32, 95% CI 1.76-16.09), SAM documented on admission (aOR 2.41, 95% CI 1.11-5.22), documentation of blood glucose within 24 hrs (aOR 3.97, 95% CI 1.90-8.33) and IV fluids given without documented shock (aOR 3.13, 95% CI 1.16-8.44).

CONCLUSION

HIV infection remains an important predictor of mortality in children with SAM. IV fluids should be avoided in those without shock. Early identification of SAM by the clinical team represents a focus of future quality improvement interventions at this facility.

Radiomics prediction model for the improved diagnosis of clinically significant prostate cancer on biparametric MRI

Background

To evaluate the potential of clinical-based model, a biparametric MRI-based radiomics model and a clinical-radiomics combined model for predicting clinically significant prostate cancer (PCa).

Methods

In total, 381 patients with clinically suspicious PCa were included in this retrospective study; of those, 199 patients did not have PCa upon biopsy, while 182 patients had PCa. All patients underwent 3.0-T MRI examinations with the same acquisition parameters, and clinical risk factors associated with PCa (age, prostate volume, serum PSA, etc.) were collected. We randomly stratified the training and test sets using a 6:4 ratio. The radiomic features included gradient-based histogram features, grey-level co-occurrence matrix (GLCM), run-length matrix (RLM), and grey-level size zone matrix (GLSZM). Three models were developed using multivariate logistic regression analysis to predict clinically significant PCa: a clinical model, a radiomics model and a clinical-radiomics combined model. The diagnostic performance and clinical net benefit of each model were compared via receiver operating characteristic (ROC) curve analysis and decision curves, respectively.

Results

Both the radiomics model (AUC: 0.98) and the clinical-radiomics combined model (AUC: 0.98) achieved greater predictive efficacy than the clinical model (AUC: 0.79). The decision curve analysis also showed that the radiomics model and combined model had higher net benefits than the clinical model.

Conclusions

Compared with the evaluation of clinical risk factors associated with PCa only, the radiomics-based machine learning model can improve the predictive accuracy for clinically significant PCa, in terms of both diagnostic performance and clinical net benefit.

DEVELOPMENT OF CLINICAL RISK ASSESSMENT TOOL FOR OSTEOPOROSIS (OSTEORISKAPP) USING A SYNDROMIC APPROACH

CONTEXT

DEXA is recommended for osteoporosis screening. However, the rate of screening with DEXA is very low. Therefore, methods that can be used more easily and cost effectively are needed.

OBJECTIVE

The objective of this study is to develop a clinical risk assessment tool of osteoporosis (OSTEORISKAPP) by using syndromic approach.

DESIGN

A methodological study was performed.

SUBJECTS AND METHODS

Three hundred and fifty-six participants who are above 50 years old are participants of study and take history and physical examination. Positive likelihood ratio (LR), pre and post test probability, is calculated. A logistic regression analysis and a ROC analysis are made with the model constructed by those criteria.

RESULTS

Eighteen different clinical risk indices are diagnosed. According to LR, 4 of these criteria are minimally effective, 11 of them are weakly effective and 3 of them are medium effective criteria According to results of logistic regression analysis, back pain, waist pain, and usage of cortisone for more than 3 months, vertebra tenderness in physical examination, having dorsal kyphosis and being obese are turned out to be statistically significant in 89.9% confidence interval. AUC is found to be 0.948 and diagnostic test is found to have perfect distinction ability.

CONCLUSION

Syndromic diagnostic criteria that will be used for osteoporosis screening of population and that is cost effective, no need to refer, practical, reliable and has tried to be developed.

Alternative Response Criteria and Clinical Risk Factors for Assessing Tumor Response in Patients With Metastatic Renal Cell Carcinoma Who Are Receiving Salvage Therapy

OBJECTIVE

The purpose of this study is to compare the prognostic value of various solid tumor response criteria as well as the additive value of clinical risk factors in patients with advanced renal cell carcinoma (RCC).

MATERIALS AND METHODS

Two sets of CT scans (pretreatment scans and scans obtained 1-3.5 months after treatment) were reviewed for 57 patients with metastatic RCC treated with pazopanib in the salvage setting. Tumor response on the posttherapy scan was evaluated using Response Evaluation Criteria in Solid Tumors (RECIST) and Choi, modified Choi (mChoi), MASS (Morphology, Attenuation, Size, and Structure), and 10% threshold criteria. In addition, combined Memorial Sloan-Kettering Cancer Center (MSKCC) risk factors plus imaging criteria were used to define response groups. Response evaluations using these criteria were correlated with overall survival (OS) and progression-free survival (PFS), with use of the log-rank test.

RESULTS

Patients classified as having progressive disease (PD) on the basis of RECIST, mChoi, and MASS criteria had a significantly worse OS than patients with stable disease (SD) and partial response (PR). With the addition of MSKCC risk factors, all groups with PD defined by combined criteria had significantly worse OS. For 37 patients with no or one MSKCC risk factor, response groups defined by Choi, mChoi, MASS, and 10% threshold criteria did not differ in PFS or OS. However, among 20 patients with two to three MSKCC risk factors, those classified as having PR had longer PFS than did those with SD and had longer OS than did those with PD.

CONCLUSION

For patients with advanced RCC for which prior therapies have failed, the prognostic value of various imaging-based tumor response criteria differs on the basis of the MSKCC clinical risk status.

Hyperhomocysteinemia is an independent predictor of long-term clinical outcomes in Chinese octogenarians with acute coronary syndrome

Objective

To evaluate the prognostic value of homocysteine (Hcy) in Chinese acute coronary syndrome (ACS) octogenarians.

Methods

The study cohort comprised 660 consecutive ACS octogenarians who underwent coronary angiography. We classified the patients into three groups according to Hcy tertiles. Kaplan–Meier method was performed for survival and major adverse cardiac events (MACE) rates. Multivariate Cox regression was performed to identify mortality predictors. Receiver operating characteristic curve analysis was performed to predict the cutoff value of Hcy for all-cause mortality.

Results

The follow-up period was 28 (inter-quartile range: 16–38) months. Diastolic blood pressure, ratios of male, renal failure and old myocardial infarction in high plasma level Hcy (H-Hcy) group were higher than those in low (L-Hcy) and middle (M-Hcy) plasma level of Hcy groups (P<0.05). The Hcy level was positively correlated with uric acid level (r=0.211, P=0.001) and Cystatin C (Cys C) level (r=0.212, P=0.001) and negatively correlated with estimated glomerular filtration rate (r=−0.148, P=0.018). For the long-term outcomes, the cumulative survival rate of H-Hcy group was significantly lower than that of L-Hcy and M-Hcy groups (P=0.006). All-cause mortality and MACE of H-Hcy group were higher than those of L-Hcy and M-Hcy group (P=0.0001, P=0.0008). Hcy is an independent predictor for long-term all-cause mortality (odds ratio =2.26, 95% CI=1.23–4.16, P=0.023) and MACE (odds ratio =1.91, 95% CI=1.03–3.51, P=0.039). Receiver operating characteristic curve analysis indicated the predictive cutoff value of Hcy for all-cause mortality was 17.67 μmol/L (0.667, 0.681).

Conclusion

In ACS octogenarians, hyperhomocysteinemia is an important predictor for long-term all-cause mortality and MACE.

FRAX and the assessment of fracture probability in men and women from the UK

A fracture risk assessment tool (FRAX) is developed based on the use of clinical risk factors with or without bone mineral density tests applied to the UK.

INTRODUCTION

The aim of this study was to apply an assessment tool for the prediction of fracture in men and women with the use of clinical risk factors (CRFs) for fracture with and without the use of femoral neck bone mineral density (BMD). The clinical risk factors, identified from previous meta-analyses, comprised body mass index (BMI, as a continuous variable), a prior history of fracture, a parental history of hip fracture, use of oral glucocorticoids, rheumatoid arthritis and other secondary causes of osteoporosis, current smoking, and alcohol intake 3 or more units daily.

METHODS

Four models were constructed to compute fracture probabilities based on the epidemiology of fracture in the UK. The models comprised the ten-year probability of hip fracture, with and without femoral neck BMD, and the ten-year probability of a major osteoporotic fracture, with and without BMD. For each model fracture and death hazards were computed as continuous functions.

RESULTS

Each clinical risk factor contributed to fracture probability. In the absence of BMD, hip fracture probability in women with a fixed BMI (25 kg/m(2)) ranged from 0.2% at the age of 50 years for women without CRF's to 22% at the age of 80 years with a parental history of hip fracture (approximately 100-fold range). In men, the probabilities were lower, as was the range (0.1 to 11% in the examples above). For a major osteoporotic fracture the probabilities ranged from 3.5% to 31% in women, and from 2.8% to 15% in men in the example above. The presence of one or more risk factors increased probabilities in an incremental manner. The differences in probabilities between men and women were comparable at any given T-score and age, except in the elderly where probabilities were higher in women than in men due to the higher mortality of the latter.

CONCLUSION

The models provide a framework which enhances the assessment of fracture risk in both men and women by the integration of clinical risk factors alone and/or in combination with BMD.

Clinical risk factors for venous thromboembolus in users of the combined oral contraceptive pill

AIMS

To estimate the risk of venous thromboembolism among women prescribed the oral contraceptive pill who have acute clinical conditions such as lower limb fractures, compared with women with idiopathic venous thromboembolism.

METHODS

A nested case-control analysis using the General Practice Research Database, January 1993 to December 1999 was carried out. The participants were women aged 15-39 years, prescribed third generation oral contraceptives (gestodene and desogestrel) or oral contraceptives containing levonorgestrel. The main outcome measures were odds ratios as a measure of the relative risk estimate for venous thromboembolism in women with clinical conditions that predispose to VTE.

RESULTS

The adjusted relative risk estimate for venous thromboembolism among patients with the acute clinical conditions, compared with those without such illness, and adjusted for oral contraceptive use, was 17 (95% CI 6.5, 46).

CONCLUSIONS

This paper documents the strong independent association between certain acute clinical conditions and venous thromboembolism in women prescribed oral contraceptives. Failure to accurately identify and exclude such patients from a study of the effect of oral contraceptives on the risk of venous thromboembolism would result in an underestimate of the risk of venous thromboembolism associated with oral contraceptives.