Height loss in postmenopausal women predicts multiple fractures in 10-year follow-up: results from the RAC-OST-POL study.

INTRODUCTION: In daily practice the diagnostic process for osteoporosis in elderly patients should also include physical assessment. The aim of the study was to verify the hypothesis that height loss (HL) predicts fracture incidence. MATERIAL AND METHODS: The study was performed in an epidemiological sample of postmenopausal women recruited in the RAC-OST-POL study. At baseline, data were collected in 978 postmenopausal women at a mean age of 66.48±7.6 years, and at 10-year follow-up 640 patients remained, with a mean age of 75.04 ± 6.95 years. Current height and HL were established in regard to maximal life height. Data on fracture incidence were gathered throughout the period of observation. RESULTS: During the follow-up period 190 osteoporotic fractures were noted. Ninety-one women had one fracture, and in 38 women, multiple fractures occurred. In the fractured and unfractured subgroups, HL was 5.45 ± 3.28 and 4.8 ± 3.56 cm, respectively, and differed significantly (p < 0.05). HL in subjects without fracture did not differ from those with one fracture (HL 4.8 ± 3.56 vs. 4.8 ± 2.66 cm, respectively). For patients with more than one fracture HL was 7.03 ± 4.06 cm and was significantly higher than in subjects with one or without any fracture (p < 0.01). Based on receiver operating characteristic (ROC) analysis, HL of 6 cm was identified as the cut-off point for high risk of multiple fractures. CONCLUSION: HL of at least 6 cm is the predictor of multiple fractures in a prospective observation of a representative epidemiological female sample. Therefore, the measurement of HL should always be included in patients' assessments.

Height Loss Is an Independent Predictor of Fracture Incidence in Postmenopausal Women: The Results from the Gliwice Osteoporosis Study (GO Study).

BACKGROUND: The aim of a longitudinal, retrospective study was to establish variables predicting fracture incidence over a decade. METHODS: The study sample comprises a group of 457 postmenopausal women aged over 55 years, recruited from the database of an outpatient osteoporotic clinic. Several variables with potential influence on bone status, including the measurement of body height and hip bone densitometry, were collected. BMD at the femoral neck (FN BMD) was established using a Prodigy device (Lunar, GE, USA). Current body height was compared with the maximal historical body height in early adulthood, as reported by the patient. RESULTS: Three hundred and ninety-four women did not have fractures during the follow up, and 63 subjects presented fractures. Subjects with fracture had lower FN BMD with a T-score of -1.86 ± 1.04 compared to -1.44 ± 0.89 in those without fractures (p < 0.001). Mean height loss (HL) was 3.47 ± 2.11 cm in fractured subjects and 2.50 ± 2.47 cm in unfractured ones, and differed significantly, p < 0.01. Fracture incidence was significantly related to age, rheumatoid arthritis, falls, and previous fractures. In the multivariable analysis using logistic regression, FN BMD, baseline fracture, and HL were identified as the significant predictors of fractures of follow up. CONCLUSIONS: Osteoporotic fractures in postmenopausal women were predicted by FN BMD, prior fracture(s), and HL easily established during physical examination.

POL-RISK: an algorithm for 10-year fracture risk prediction in postmenopausal women from the RAC-OST-POL study.

INTRODUCTION: Fragility fractures are the major consequence of osteoporosis. Thus, fracture risk assessment is an essential part of the diagnostic process in osteoporosis. OBJECTIVES: The aim of the study was to develop an algorithm for fracture risk prediction. PATIENTS AND METHODS: Bone status was evaluated in a population­basedcohort of postmenopausal women at a mean (SD) age of 66.4 (7.8) years. Subsequently, all participants were contacted by phone once a year (for 10 consecutive years) to update their history of fractures. At the end of the 10­year follow­up, the number of the study participants was 640, of whom 129 had a history of 190 osteoporotic fractures recorded during the study period. Statistical analysis included multistep data preprocessing, feature selection, identification of fracture risk factors, and design of the final model. Logistic regression models were fitted and used for the evaluation of variables from determined feature sets, including global fit measures, as well as individual parameters, such as the Wald statistic and P value, odds ratio, and 95% CI. RESULTS: The 10­year risk for any fracture depended on the age of the patient, the number of recorded fractures after the age of 40 years, femoral neck bone mass, and the occurrence of falls during the previous year. The achieved equation was incorporated into an algorithm, available at the www.fracture­risk.pl webpage. CONCLUSION: A fracture prediction algorithm was developed in a longitudinal study to enable calculation of the 10­year fracture risk. Identification of patients at a high risk of fracture should be followed by implementation of appropriate treatment strategy to reduce the number of future fractures.

The Impact of Environmental and Genetic Factors on Bone Quality in Monozygotic and Dizygotic Twins.

The purpose of the research was to assess the genetic and environmental influences on bone properties. One hundred thirty-two pairs of twins (99/33 monozygotic/dizygotic) underwent anthropometric measurements and phalangeal quantitative ultrasound (DBM Sonic 1200, Igea, Italy) measuring the amplitude speed of sound (AD-SoS, m/s). The mean age was 16.78 ± 12.35 years for monozygotic twins and 14.30 ± 8 years for dizygotic. Interpair and intrapair correlations between twins were calculated. In the groups of monozygotic and dizygotic twins, Ad-SoS correlated significantly with age (r = 0.56−0.73, p < 0.05), weight (r = 0.73−0.78, p < 0.05), and height (r = 0.80−0.81, p < 0.05). The strongest intrapair correlation (r = 0.99−0.998) was noted in monozygotic females for Ad-SoS, weight, and height. There was a statistically significant correlation between the intrapair difference of Ad-SoS and age but only in the groups of monozygotic and dizygotic females (r = 0.281, r2 = 0.079, and p = 0.028; r = 0.544, r2 = 0.296, and p = 0.01, respectively). After age adjustment, it was estimated that 28.62% of Ad-SoS in women and 13.2% of Ad-SoS in men was explained by genetic influence, leading to the conclusion that Ad-SoS changed with age, weight, and height. The strongest correlation between pairs of twins was observed in monozygotic twins. The differences in bone values between female twins arose with age, which indicated the role of environmental factors.

Symptom-based early-stage differentiation between SARS-CoV-2 versus other respiratory tract infections-Upper Silesia pilot study.

In the DECODE project, data were collected from 3,114 surveys filled by symptomatic patients RT-qPCR tested for SARS-CoV-2 in a single university centre in March-September 2020. The population demonstrated balanced sex and age with 759 SARS-CoV-2( +) patients. The most discriminative symptoms in SARS-CoV-2( +) patients at early infection stage were loss of taste/smell (OR = 3.33, p < 0.0001), body temperature above 38℃ (OR = 1.67, p < 0.0001), muscle aches (OR = 1.30, p = 0.0242), headache (OR = 1.27, p = 0.0405), cough (OR = 1.26, p = 0.0477). Dyspnea was more often reported among SARS-CoV-2(-) (OR = 0.55, p < 0.0001). Cough and dyspnea were 3.5 times more frequent among SARS-CoV-2(-) (OR = 0.28, p < 0.0001). Co-occurrence of cough, muscle aches, headache, loss of taste/smell (OR = 4.72, p = 0.0015) appeared significant, although co-occurrence of two symptoms only, cough and loss of smell or taste, means OR = 2.49 (p < 0.0001). Temperature > 38℃ with cough was most frequent in men (20%), while loss of taste/smell with cough in women (17%). For younger people, taste/smell impairment is sufficient to characterise infection, whereas in older patients co-occurrence of fever and cough is necessary. The presented study objectifies the single symptoms and interactions significance in COVID-19 diagnoses and demonstrates diverse symptomatology in patient groups.