Development of a radiomics model to diagnose pheochromocytoma preoperatively: a multicenter study with prospective validation

Background Preoperative diagnosis of pheochromocytoma (PHEO) accurately impacts preoperative preparation and surgical outcome in PHEO patients. Highly reliable model to diagnose PHEO is lacking. We aimed to develop a magnetic resonance imaging (MRI)-based radiomic-clinical model to distinguish PHEO from adrenal lesions. Methods In total, 305 patients with 309 adrenal lesions were included and divided into different sets. The least absolute shrinkage and selection operator (LASSO) regression model was used for data dimension reduction, feature selection, and radiomics signature building. In addition, a nomogram incorporating the obtained radiomics signature and selected clinical predictors was developed by using multivariable logistic regression analysis. The performance of the radiomic-clinical model was assessed with respect to its discrimination, calibration, and clinical usefulness. Results Seven radiomics features were selected among the 1301 features obtained as they could differentiate PHEOs from other adrenal lesions in the training (area under the curve [AUC], 0.887), internal validation (AUC, 0.880), and external validation cohorts (AUC, 0.807). Predictors contained in the individualized prediction nomogram included the radiomics signature and symptom number (symptoms include headache, palpitation, and diaphoresis). The training set yielded an AUC of 0.893 for the nomogram, which was confirmed in the internal and external validation sets with AUCs of 0.906 and 0.844, respectively. Decision curve analyses indicated the nomogram was clinically useful. In addition, 25 patients with 25 lesions were recruited for prospective validation, which yielded an AUC of 0.917 for the nomogram. Conclusion We propose a radiomic-based nomogram incorporating clinically useful signatures as an easy-to-use, predictive and individualized tool for PHEO diagnosis.

Comparison of laminoplasty and posterior fusion surgery for cervical ossification of posterior longitudinal ligament

This prospective multicenter study, established by the Japanese Ministry of Health, Labour and Welfare and involving 27 institutions, aimed to compare postoperative outcomes between laminoplasty (LM) and posterior fusion (PF) for cervical ossification of the posterior longitudinal ligament (OPLL), in order to address the controversy surrounding the role of instrumented fusion in cases of posterior surgical decompression for OPLL. 478 patients were considered for participation in the study; from among them, 189 (137 and 52 patients with LM and PF, respectively) were included and evaluated using the Japanese Orthopaedic Association (JOA) scores, the JOA Cervical Myelopathy Evaluation Questionnaire (JOACMEQ), and radiographical measurements. Basic demographic and radiographical data were reviewed, and the propensity to choose a surgical procedure was calculated. Preoperatively, there were no significant differences among the participants in terms of patient backgrounds, radiographical measurements (K-line or cervical alignment on X-ray, OPLL occupation ratio on computed tomography, increased signal intensity change on magnetic resonance imaging), or clinical status (JOA score and JOACMEQ) after adjustments. The overall risk of perioperative complications was found to be lower with LM (odds ratio [OR] 0.40, p = 0.006), and the rate of C5 palsy occurrence was significantly lower with LM (OR 0.11, p = 0.0002) than with PF. The range of motion (20.91° ± 1.05° and 9.38° ± 1.24°, p < 0.0001) in patients who had PF was significantly smaller than in those who had LM. However, multivariable logistic regression analysis showed no significant difference among the participants in JOA score, JOA recovery rate, or JOACMEQ improvement at two years. In contrast, OPLL progression was greater in the LM group than in the PF group (OR 2.73, p = 0.0002). Both LM and PF for cervical myelopathy due to OPLL had resulted in comparable postoperative outcomes at 2 years after surgery.

Delays in the presentation and diagnosis of women with breast cancer in Yogyakarta, Indonesia: A retrospective observational study

Purpose To investigate factors associated with delays in presentation and diagnosis of women with confirmed breast cancer (BC). Methods A cross-sectional study nested in an ongoing prospective cohort study of breast cancer patients at Dr Sardjito Hospital, Yogyakarta, Indonesia, was employed. Participants (n = 150) from the main study were recruited, with secondary information on demographic, clinical, and tumor variables collected from the study database. A questionnaire was used to gather data on other socioeconomic variables, herbal consumption, number of healthcare visits, knowledge-attitude-practice of BC, and open-ended questions relating to initial presentation. Presentation delay (time between initial symptom and first consultation) was defined as ≥3 months. Diagnosis delay was defined as ≥1 month between presentation and diagnosis confirmation. Impact on disease stage and determinants of both delays were examined. A Kruskal-Wallis test was used to assess the length and distribution of delays by disease stage. A multivariable logistic regression analysis was conducted to explore the association between delays, cancer stage and factors. Results Sixty-five (43.3%) patients had a ≥3-month presentation delay and 97 (64.7%) had a diagnosis confirmation by ≥1 month. Both presentation and diagnosis delays increased the risk of being diagnosed with cancer stage III-IV (odds ratio/OR 2.21, 95% CI 0.97–5.01, p = 0.059 and OR 3.03, 95% CI 1.28–7.19, p = 0.012). Visit to providers ≤3 times was significantly attributed to a reduced diagnosis delay (OR 0.15, 95% CI 0.06–0.37, p <0.001), while having a family history of cancer was significantly associated with increased diagnosis delay (OR 2.28, 95% CI 1.03–5.04, p = 0.042). The most frequent reasons for delaying presentation were lack of awareness of the cause of symptoms (41.5%), low perceived severity (27.7%) and fear of surgery intervention (26.2%). Conclusions Almost half of BC patients in our setting had a delay in presentation and 64.7% experienced a delay in diagnosis. These delays increased the likelihood of presentation with a more advanced stage of disease. Future research is required in Indonesia to explore the feasibility of evidence-based approaches to reducing delays at both levels, including educational interventions to increase awareness of BC symptoms and reducing existing complex and convoluted referral pathways for patients suspected of having cancer.

Low frequency of disease flare in patients with rheumatic musculoskeletal diseases who received SARS-CoV-2 mRNA vaccine

Background Little is known about the safety of SARS-CoV-2 vaccination in patients with rheumatic musculoskeletal disease (RMD). We evaluated the occurrence of adverse events following immunization (AEFI) in RMD patients and heathy subjects who received anti-SARS-CoV-2 mRNA vaccine. Methods We performed a telephone interview collecting any adverse event (AE) following immunization (AEFI) that occurred in RMD patients and healthy controls after the two doses of mRNA vaccine including common local reactogenicity and systemic events (for example, fever, fatigue/malaise, joint and muscle pain). We also investigated the onset of new signs or symptoms of the RMD after the vaccination. Results We evaluated 126 patients with RMDs [105 females and 19 males, median age 51(IQR 17)] and 85 controls [62 females and 23 males, (median age 49 (20)]. Seventy patients (55.6%) were taking immunosuppressants, conventional synthetic (n=31, 43.3%) and/or biological [TNF inhibitors (n=49, 68.6%)], and 30 (23.8%) were taking hydroxychloroquine; treatment remained unchanged in 77% of patients. Eleven out of 126 patients and none of the 85 controls previously contracted COVID-19. The median follow-up from the completion of vaccination was 15 (3) weeks both in patients and controls. We reviewed 5 suspected cases confirming mild articular flares in 3 women (2.8) with inflammatory arthritis (2 psoriatic arthritis and 1 rheumatoid arthritis) while no disease reactivation was recorded in patients with connective tissue diseases; the incidence rate of RMD reactivation was 0.007 person/month. Multivariable logistic regression analysis showed similar frequencies of local and systemic AEFI in patients and controls with no effect of therapies or previous COVID-19. Local reaction—pain in the injection site—was the most frequently reported AEFI both in RMD and controls (71% and 75% of all the AEFI, respectively) after the first dose. Overall, up to 66% of patients experienced at least one AEFI at the second dose and up to 62% in the control group. Most of AEFI occurred within 2 days of vaccine administration. Two RMD patients developed pauci-symptomatic COVID-19 after the first dose of vaccine. Conclusion The low incidence rate of disease reactivation and the similar AEFI occurrence compared to controls should reassure on mRNA vaccine safety in RMD patients.

A Novel Nomogram for Predicting the Risk of Premature Delivery Based on the Thyroid Function in Pregnant Women

BackgroundMaternal thyroid dysfunction and autoantibodies were associated with preterm delivery. However, recommendations for cutoff values of thyroperoxidase antibody (TPOAb) positivity and thyroid-stimulating homone (TSH) associated with premature delivery are lacking.ObjectiveTo identify the pregnancy-specific cutoff values for TPOAb positivity and TSH associated with preterm delivery. To develop a nomogram for the risk prediction of premature delivery based on maternal thyroid function in singleton pregnant women without pre-pregnancy complications.MethodsThis study included data from the International Peace Maternity and Child Care Health Hospital (IPMCH) in Shanghai, China, between January 2013 and December 2016. Added data between September 2019 and November 2019 as the test cohort. Youden’s index calculated the pregnancy-specific cutoff values for TPOAb positivity and TSH concentration. Univariate and multivariable logistic regression analysis were used to screen the risk factors of premature delivery. The nomogram was developed according to the regression coefficient of relevant variables. Discrimination and calibration of the model were assessed using the C-index, Hosmer-Lemeshow test, calibration curve and decision curve analysis.Results45,467 pregnant women were divided into the training and validation cohorts according to the ratio of 7: 3. The testing cohort included 727 participants. The pregnancy-specific cutoff values associated with the risk of premature delivery during the first trimester were 5.14 IU/mL for TPOAb positivity and 1.33 mU/L for TSH concentration. Multivariable logistic regression analysis showed that maternal age, history of premature delivery, elevated TSH concentration and TPOAb positivity in the early pregnancy, preeclampsia and gestational diabetes mellitus were risk factors of premature delivery. The C-index was 0.62 of the nomogram. Hosmer-Lemeshow test showed that the Chi-square value was 2.64 (P = 0.955 &gt; 0.05). Decision curve analysis showed a positive net benefit. The calibration curves of three cohorts were shown to be in good agreement.ConclusionsWe identified the pregnancy-specific cutoff values for TPOAb positivity and TSH concentration associated with preterm delivery in singleton pregnant women without pre-pregnancy complications. We developed a nomogram to predict the occurrence of premature delivery based on thyroid function and other risk factors as a clinical decision-making tool.

Relief After COVID-19 Vaccination: A Doubtful or Evident Outcome?

Background: Since development of the first COVID-19 vaccine, the landscape of public confidence in these vaccines is uncertain. Building confidence is crucial for better preparedness of future pandemics. Following the mandatory COVID-19 vaccination policy in the country, the aim of this study was to examine whether the Saudi public feels relieved post-vaccination and to identify the factors predicting such relief.Methods: An online cross-sectional survey was conducted in July 2021 among COVID-19 vaccine recipients in Saudi Arabia. A multivariable logistic regression analysis was employed to examine and identify the variables associated with feeling relieved post-vaccination.Results: Most of the respondents (66%) stated feeling more relieved post-vaccination. Male gender [adjusted odds ratio (AOR): 1.380; 95% confidence interval (CI): 0.981–1.943], being a student (AOR: 3.902; 95% CI: 1.674–9.096), and received two doses of the vaccine (AOR: 2.278; 95% CI: 1.630–3.182) were associated with feeling more relieved after getting vaccinated. Respondents who were anxious about the vaccine before receiving it (AOR: 0.220; 95% CI: 0.160–0.302), and experienced a severe reaction after vaccination (AOR: 0.288; 95% CI: 0.165–0.504) had lower odds of feeling relieved post-vaccination. Respondents who relied on social media as the main source of vaccine-related information and those having no information about the vaccine were also less likely to feel relieved post-vaccination.Conclusions: Individuals' attitudes toward COVID-19 vaccines may not necessarily alter post-vaccination. Although mandatory vaccination policies can significantly contribute to achieving herd immunity, public confidence toward vaccines might be eroded, which could in turn impose significant challenges in future pandemics efforts.

Postpartum women’s views on human milk banking in a city in Southeast China: a cross-sectional survey

Background Donor human milk is the best alternative for preterm infants when their mother’s own milk is insufficient or unavailable. The development of human milk banks in China started late, and in most of these banks, the amount of donor human milk is insufficient for clinical demand. Moreover, many mothers are reluctant to use donor human milk due to safety concerns. It is important to understand the potential supply and demand of donor human milk before establishing a new human milk bank. This study aimed to understand women’s acceptance of human milk banking in Wenzhou, southeastern China. Methods A cross-sectional study was conducted in three community health centers in Wenzhou, southeast China, in December 2020. Data were collected from 305 postpartum women selected through convenience sampling. Sociodemographic, perinatal and breastfeeding characteristics, awareness and knowledge of human milk banking and willingness to donate human milk, and to accept donor human milk were assessed. Multivariable logistic regression analysis was used to explore independent predictors of willingness to donate human milk and to accept donor human milk. Results Only 17% (52/305) of our participants had heard of human milk banking prior to this survey. The prevalence of willingness to donate human milk and use donor human milk in our study was 73.4% (224/305) and 44.6% (136/305), respectively. Employment (adjusted odds ratio [AOR] 2.30; 95% confidence interval [CI] 1.17, 4.50) and human milk banking knowledge (AOR 1.23; 95% CI 1.12, 1.35) were independent predictors of willingness to donate human milk. Monthly household income in the previous year (AOR 2.18; 95% CI 1.17, 4.06), awareness of human milk banking (AOR 2.41; 95% CI 1.24, 4.67) and knowledge of human milk banking (AOR 1.22; 95% CI 1.11, 1.35) were significantly associated with willingness to accept donor human milk. Conclusions In our study, awareness of human milk banks among women in the first year postpartum was low. More mothers were willing to donate human milk than to use donor human milk to feed their children. In our study, knowledge of human milk banking was a predictor of both willingness to donate human milk and willingness to use donor human milk. Programs with detailed information on human milk banking are needed to help mothers improve their knowledge and increase acceptance of human milk banking.

The Combination of High Levels of Adiponectin and Insulin Resistance Are Affected by Aging in Non-Obese Old Peoples

BackgroundAdipokine dysregulation is a key feature of insulin resistance and a metabolic syndrome associated with obesity. Low adiponectin levels are associated with higher risks of cardiovascular diseases (CVD). However, high adiponectin levels have also been associated with increased all-cause and cardiovascular mortality in the elderly. This adiponectin paradox has yet to be clarified, which has hindered our understanding of the biological role of adiponectin. Adipokine dysregulation and insulin resistance are also associated with energy-deprivation conditions, such as frailty in old age. The objective of this study was to investigate the association between plasma adiponectin and insulin resistance using the homeostasis model assessment for insulin resistance (HOMA-IR) classified by age. In particular, we sought to determine the factors of the subjects associated with both high adiponectin levels and HOMA-IR (H-adiponectin/H-HOMA) and high adiponectin levels and low HOMA-IR (H-adiponectin/L-HOMA).MethodsThe eligible subjects in this cross-sectional study were 33,216 individuals who had undergone health checkups at the Physical Checkup Center of Sumitomo Hospital between April 2008 and December 2018. After excluding 26,371 individuals who were under 60 years old, 529 who had been taking medications for diabetes mellitus, and 690 with missing data, the present study included 5,673 (3,467 males, 2,206 females) subjects with no missing data. The relationship between serum adiponectin levels and HOMA-IR was assessed using logistic regression models adjusted by clinically relevant factors.ResultsIn the multivariable logistic regression analysis, age and low BMI were shown to positively correlate with the characteristics of H-adiponectin/H-HOMA. In females, systolic blood pressure was also shown to be an associated factor.ConclusionIn conclusion, this study showed that aging or a low BMI may contribute to high adiponectin levels and insulin resistance.

Radiomics nomogram for the preoperative prediction of lymph node metastasis in pancreatic ductal adenocarcinoma

Purpose To develop and validate a radiomics nomogram for the preoperative prediction of lymph node (LN) metastasis in pancreatic ductal adenocarcinoma (PDAC). Materials and methods In this retrospective study, 225 patients with surgically resected, pathologically confirmed PDAC underwent multislice computed tomography (MSCT) between January 2014 and January 2017. Radiomics features were extracted from arterial CT scans. The least absolute shrinkage and selection operator method was used to select the features. Multivariable logistic regression analysis was used to develop the predictive model, and a radiomics nomogram was built and internally validated in 45 consecutive patients with PDAC between February 2017 and December 2017. The performance of the nomogram was assessed in the training and validation cohort. Finally, the clinical usefulness of the nomogram was estimated using decision curve analysis (DCA). Results The radiomics signature, which consisted of 13 selected features of the arterial phase, was significantly associated with LN status (p < 0.05) in both the training and validation cohorts. The multivariable logistic regression model included the radiomics signature and CT-reported LN status. The individualized prediction nomogram showed good discrimination in the training cohort [area under the curve (AUC), 0.75; 95% confidence interval (CI), 0.68–0.82] and in the validation cohort (AUC, 0.81; 95% CI, 0.69–0.94) and good calibration. DCA demonstrated that the radiomics nomogram was clinically useful. Conclusions The presented radiomics nomogram that incorporates the radiomics signature and CT-reported LN status is a noninvasive, preoperative prediction tool with favorable predictive accuracy for LN metastasis in patients with PDAC.

The Construction and Development of a Clinical Prediction Model to Assess Lymph Node Metastases in Osteosarcoma

Background: This study aimed to construct a clinical prediction model for osteosarcoma patients to evaluate the influence factors for the occurrence of lymph node metastasis (LNM).Methods: In our retrospective study, a total of 1,256 patients diagnosed with chondrosarcoma were enrolled from the SEER (Surveillance, Epidemiology, and End Results) database (training cohort, n = 1,144) and multicenter dataset (validation cohort, n = 112). Both the univariate and multivariable logistic regression analysis were performed to identify the potential risk factors of LNM in osteosarcoma patients. According to the results of multivariable logistic regression analysis, A nomogram were established and the predictive ability was assessed by calibration plots, receiver operating characteristics (ROCs) curve, and decision curve analysis (DCA). Moreover, Kaplan-Meier plot of overall survival (OS) was plot and a web calculator visualized the nomogram.Results: Five independent risk factors [chemotherapy, surgery, lung metastases, lymphatic metastases (M-stage) and tumor size (T-stage)] were identified by multivariable logistic regression analysis. What's more, calibration plots displayed great power both in training and validation group. DCA presented great clinical utility. ROCs curve provided the predictive ability in the training cohort (AUC = 0.805) and the validation cohort (AUC = 0.808). Moreover, patients in LNN group had significantly better survival than that in LNP group both in training and validation group.Conclusion: In this study, we constructed and developed a nomogram with risk factors, which performed well in predicting risk factors of LNM in osteosarcoma patients. It may give a guide for surgeons and oncologists to optimize individual treatment and make a better clinical decision.