A special type of ordinal scale comprising a number of intervals of known numeric ranges can be used when estimating severity of a plant disease. The interval ranges are most often based on the ...percent area with symptoms e.g. the Horsfall–Barratt (H–B) scale. Studies in plant pathology and plant breeding often use this type of ordinal scale. The disease severity is estimated by a rater as a value on the scale and has been used to determine a disease severity index (DSI) on a percentage basis, where DSI (%) = sum (class frequency × score of rating class)/(total number of plants) × (maximal disease index) × 100. However, very few studies have investigated the effects of different scales on accuracy of the DSI. Therefore, the objectives of this study were to investigate the process of calculating a DSI on a percentage basis from ordinal scale data, and to use simulation approaches to explore the effect of using different methods for calculation of the interval range and the nature of the ordinal scales used on the DSI estimates (%). We found that the DSI is particularly prone to overestimation when using the above formula if the midpoint values of the rating class are not considered. Moreover, the results of the simulation studies show that, if rater estimates are unbiased, compared with other methods tested in this study, the most accurate method for estimation of a DSI is to use the midpoint of the severity range for each class with an amended 10% ordinal scale (an ordinal scale based on a 10% linear scale emphasising severities ≤50% disease, with additional grades at low severities). As for biased conditions, the accuracy for calculating DSI estimates (%) will depend mainly on the degree and direction of the rater bias relative to the actual mean value.
The Geriatric Nutritional Risk Index (GNRI) is a useful predictor of prognosis in older patients and those receiving hemodialysis. However, the predictive value of the GNRI in renal transplant ...recipients (RTRs) is unclear. In this study we investigated the correlation between the GNRI and muscle function, as indicated by handgrip strength (HGS).
A cross-sectional study was performed on 42 RTRs (50% women), with a mean age of 49.0 ± 10.8 years. The GNRI was derived from patients' body weight and serum albumin level by using the following equation: GNRI = 14.89 × albumin (g/dL) + 41.7 × (body weight/ideal body weight). HGS was evaluated in dominant arms; HGS measurement was repeated 3 times, and the highest value was used. Multivariable stepwise regression analyses were performed to obtain adjusted correlates, and the significance levels for entry and remaining were set at 0.1.
The mean values of the GNRI and HGS were 105.0 ± 5.4 and 29.0 ± 9.4, respectively. The GNRI was positively correlated with HGS (r = 0.36, P = .02). Linear and stepwise multivariable adjustment analyses revealed that the homeostatic model assessment of insulin resistance (HOMA-IR) and GNRI were independent determinants of HGS (βHOMA-IR = 0.53 and βGNRI = 0.43, adjusted R2 = 0.45) after adjustment for age, sex, total muscle mass, and C-reactive protein level as covariates.
This study has shown that the GNRI is a favorable predictor of muscle function in RTRs.
•The Geriatric Nutritional Risk Index (GNRI) is a strong predictor of handgrip strength in renal transplantation recipients.•The GNRI can be used as an objective tool for assessment of nutritional status and muscle strength.•Physiologic and pathophysiologic changes show the relationship between nutritional status and sarcopenia.
Oral cancer: A multicenter study Dhanuthai, K; Rojanawatsirivej, S; Thosaporn, W ...
Medicina oral, patología oral y cirugía bucal,
01/2018, Letnik:
23, Številka:
1
Journal Article
Recenzirano
Odprti dostop
To determine the prevalence and clinicopathologic features of the oral cancer patients.
Biopsy records of the participating institutions were reviewed for oral cancer cases diagnosed from 2005 to ...2014. Demographic data and site of the lesions were collected. Sites of the lesion were subdivided into lip, tongue, floor of the mouth, gingiva, alveolar mucosa, palate, buccal/labial mucosa, maxilla and mandible. Oral cancer was subdivided into 7 categories: epithelial tumors, salivary gland tumors, hematologic tumors, bone tumors, mesenchymal tumors, odontogenic tumors, and others. Data were analyzed by descriptive statistics using SPSS software version 17.0.
Of the 474,851 accessioned cases, 6,151 cases (1.30%) were diagnosed in the category of oral cancer. The mean age of the patients was 58.37±15.77 years. A total of 4,238 cases (68.90%) were diagnosed in males, whereas 1911 cases (31.07%) were diagnosed in females. The male-to-female ratio was 2.22:1. The sites of predilection for oral cancer were tongue, labial/buccal mucosa, gingiva, palate, and alveolar mucosa, respectively. The three most common oral cancer in the descending order of frequency were squamous cell carcinoma, non-Hodgkin lymphoma and mucoepidermoid carcinoma.
Although the prevalence of oral cancer is not high compared to other entities, oral cancer pose significant mortality and morbidity in the patients, especially when discovered late in the course of the disease. This study highlights some anatomical locations where oral cancers are frequently encountered. As a result, clinicians should pay attention to not only teeth, but oral mucosa especially in the high prevalence area as well since early detection of precancerous lesions or cancers in the early stage increase the chance of patient being cured and greatly reduce the mortality and morbidity. This study also shows some differences between pediatric and elderly oral cancer patients as well as between Asian and non-Asian oral cancer patients.
Summary
We investigated the association between fasting plasma glucose variability (FPG-CV) and the risk of hip fracture in elderly diabetic patients. Our finding showed a temporal association ...between FPG-CV and hip fracture as patients categorized as FPG-CV greater than 25.4 % showed an increased risk in hip fractures.
Introduction
Hip fracture is a major health burden in the population and is associated with high rates of mortality and morbidity especially in elderly. It is evident that diabetes mellitus is a risk factor of osteoporosis which is a significant risk factor of hip fracture. However, epidemiological studies exploring the risks of hip fracture among type 2 diabetic patients are limited.
Methods
A retrospective study of 26,501 ethnic Chinese older persons enrolled in the National Diabetes Care Management program in Taiwan was conducted; related factors were analyzed with extended Cox proportional hazards regression models to competing risk data on hip fracture incidence.
Results
The results show a temporal association between FPG-CV and hip fracture as patients categorized as FPG-CV greater than 25.4 % showed an increased risk in hip fractures, confirming a linear relationship between the two. After multivariate adjustment, the risk of hip fracture increased among patients with FPG-CV of 25.4–42.3 % and >42.3 % compared with patients with FPG-CV of ≦ 14.3 % (hazard ratio, 1.35; 95 % confidence interval 1.14–1.60 and 1.27; 1.07–1.52, respectively). Significant linear trends among various FPG-CV were observed.
Conclusions
Thus, the present study demonstrated the importance of glucose stability for fracture prevention in older persons with type 2 diabetes. Future studies should be conducted to explore whether reduction in glucose oscillation in older adults with diabetes mellitus can reduce the risk of hip fracture.
Disease severity in plant pathology is often measured by the amount of a plant or plant part that exhibits disease symptoms. This is typically assessed using a numerical scale, which allows a ...standardized, convenient, and quick method of rating. These scales, known as quantitative ordinal scales (QOS), divide the percentage scale into a predetermined number of intervals. There are various ways to analyze these ordinal data, with traditional methods involving the use of midpoint conversion to represent the interval. However, this may not be precise enough, as it is only an estimate of the true value. In this case, the data may be considered interval-censored, meaning that we have some knowledge of the value but not an exact measurement. This type of uncertainty is known as censoring, and techniques that address censoring, such as survival analysis (SA), use all available information and account for this uncertainty. To investigate the pros and cons of using SA with QOS measurements, we conducted a simulation based on three pathosystems. The results showed that SA almost always outperformed midpoint conversion with data analyzed using a
test, particularly when data were not normally distributed. Midpoint conversion is currently a standard procedure. In certain cases, the midpoint approach required a 400% increase in sample size to achieve the same power as the SA method. However, as the mean severity increases, fewer additional samples are needed (approximately an additional 100%), regardless of the assessment method used. Based on these findings, we conclude that SA is a valuable method for enhancing the power of hypothesis testing when analyzing QOS severity data. Future research should investigate the wider use of survival analysis techniques in plant pathology and their potential applications in the discipline.
The effects of bias (over‐ and underestimates) in estimates of disease severity on hypothesis testing using different assessment methods was explored. Nearest percentage estimates (NPE), the ...Horsfall–Barratt (H‐B) scale, and two linear category scales (10% increments, with and without additional grades at low severity) were compared using simulation modelling to assess effects of bias. Type I and type II error rates were used to compare two treatment differences. The power of the H‐B scale and the 10% scale were least for correctly testing a hypothesis compared with the other methods, and the effects of rater bias on type II errors were greater over specific severity ranges. Apart from NPEs, the amended 10% category scale was most often superior to other methods at all severities tested for reducing the risk of type II errors. It should thus be a preferred method for raters who must use a category scale for disease assessments. Rater bias and assessment method had little effect on type I error rates. The power of the hypothesis test using unbiased estimates was most often greater compared with biased estimates, regardless of assessment method. An unanticipated observation was the greater impact of rater bias compared with assessment method on type II errors. Knowledge of the effects of rater bias and scale type on hypothesis testing can be used to improve accuracy and reliability of disease severity estimates, and can provide a logical framework for improving aids to estimate severity visually, including standard area diagrams and rater training software.
Studies in plant pathology, agronomy, and plant breeding requiring disease severity assessment often use quantitative ordinal scales (i.e., a special type of ordinal scale that uses defined numeric ...ranges); a frequently used example of such a scale is the Horsfall-Barratt scale. Parametric proportional odds models (POMs) may be used to analyze the ratings obtained from quantitative ordinal scales directly, without converting ratings to percent area affected using range midpoints of such scales (currently a standard procedure). Our aim was to evaluate the performance of the POM for comparing treatments using ordinal estimates of disease severity relative to two alternatives, the midpoint conversions (MCs) and nearest percent estimates (NPEs). A simulation method was implemented and the parameters of the simulation estimated using actual disease severity data from the field. The criterion for comparison of the three approaches was the power of the hypothesis test (the probability to reject the null hypothesis when it is false). Most often, NPEs had superior performance. The performance of the POM was never inferior to using the MC at severity <40%. Especially at low disease severity (≤10%), the POM was superior to using the MC method. Thus, for early onset of disease or for comparing treatments with severities <40%, the POM is preferable for analyzing disease severity data based on quantitative ordinal scales when comparing treatments and at severities >40% is equivalent to other methods.
Summary
Cosmetic surgical procedures, including hair transplantation and face‐lift surgery, are becoming increasingly popular. However, there is very little information regarding the associated ...development of dermatological conditions following these procedures. Lichen planopilaris (LPP) is an uncommon inflammatory hair disorder of unknown aetiology that results in permanent alopecia and replacement of hair follicles with scar‐like fibrous tissue. Frontal fibrosing alopecia (FFA), a variant of LPP, involves the frontal hairline and shares similar histological findings with those of LPP. We report 10 patients who developed LPP/FFA following cosmetic scalp surgery. Seven patients developed LPP following hair transplantation, and three patients developed FFA following face‐lift surgery. In all cases there was no previous history of LPP or FFA. There is currently a lack of evidence to link the procedures of hair transplantation and cosmetic face‐lift surgery to LPP and FFA, respectively. This is the first case series to describe this connection and to postulate the possible pathological processes underlying the clinical observation. Explanations include Koebner phenomenon induced by surgical trauma, an autoimmune process targeting an (as yet, unknown) hair follicle antigen liberated during surgery or perhaps a postsurgery proinflammatory milieu inducing hair follicle immune privilege collapse and follicular damage in susceptible individuals.
This study aimed to investigate the metabolic risk factors of high hepatitis B viral load.
Large-scale, community-based cross-sectional study.
A total of 3587 hepatitis B virus (HBV)-infected ...participants without liver cirrhosis at study entry were investigated. High HBV viral load was defined as a serum level 10(4) copies per ml for hepatitis B e antigen (HBeAg) seronegatives or 10(8) copies per ml for HBeAg seropositives.
Among HBeAg seropositives (n=545), high HBV viral load was reversely associated with extreme obesity (odds ratio (OR), 0.30; 95% confidence interval (CI), 0.13-0.68; P=0.004) or central obesity (OR, 0.53; 95% CI, 0.34-0.82; P=0.004) after adjustment for gender, hypertriglyceridemia, hyperuricemia and history of hypertension. High HBV viral load remained significantly inversely associated with extreme obesity (OR, 0.17; 95% CI, 0.05-0.63; P=0.008) and central obesity (OR, 0.44; 95% CI, 0.25-0.78; P=0.005) in male HBeAg-seropositive participants in stratification analyses by gender. Among HBeAg seronegatives (n=3042), however, high HBV viral load was inversely associated with hypertriglyceridemia (OR, 0.74; 95% CI, 0.61-0.89, P=0.002) after adjustment for age, gender, high serum alanine aminotransferase level, and extreme obesity or central obesity. High HBV viral load was still inversely associated with hypertriglyceridemia in both female (OR, 0.70; 95% CI, 0.50-0.97; P=0.041) and male (OR, 0.75; 95% CI, 0.60-0.94; P=0.011) HBeAg-seronegative participants.
Extreme obesity and central obesity were associated with a low prevalence of high HBV viral load in HBeAg seropositives, especially in men; while hypertriglyceridemia was associated with a low prevalence of high viral load in HBeAg seronegatives in both women and men.
Ensuring careful selection of heart transplant recipients with pretransplant malignancies (PTM) has been suggested in several retrospective studies. However, cancer survival rates continue to ...increase and we still lack outcomes data on PTM patients who have undergone heart transplantation (HT) within the Asian region. Herein we report pretransplant characteristics and outcomes among PTM patients with HT.
A total of 354 patients underwent HT from January 2004 to January 2016. Eight of these patients had a history malignancy that was being treated before transplantation. Posttransplant outcomes and clinical characteristics were collected and possible prognostic factors analyzed.
The median age of the patients with a preexisting malignancy was 60 years. The PTM group included 5 males and 3 females, with a median duration of follow-up of 43 months. In this group there were 2 patients with lymphoma after chemotherapy, 1 with colon cancer postoperatively, and 1 was on chemotherapy. In the other 4 patients, nasopharyngeal cancer, thyroid cancer, breast cancer, and endometrial cancer were identified, and each had undergone treatment. Only 1 premalignancy patient, with nasopharyngeal cancer, had disease recurrence. The 5-year overall survival of these patients was 50.0 ± 17.7%, but 5-year survival for those without PTM was 68.7 ± 2.0%.
PTM was 2.3% in our cohort. PTM is associated with an increased risk of all-cause mortality. Thus, our findings suggest careful consideration when selecting PTM patients for HT.
•Current outcomes are discussed for patients with preexisting malignancies after heart transplantation in Asia.•Preexisting malignancies are associated with increased risk of all-cause mortality, but may be unrelated to malignancy directly. Careful posttransplantation follow-up is necessary.•Findings from similar studies on patients receiving heart transplantation with preexisting malignancies are discussed.
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