Tag: statistics

Sports Med. 2023 May 9. doi: 10.1007/s40279-023-01839-8. Online ahead of print.

ABSTRACT

BACKGROUND: Several studies have utilised isometric, eccentric and downhill walking pre-conditioning as a strategy for alleviating the signs and symptoms of exercise-induced muscle damage (EIMD) following a bout of damaging physical activity.

OBJECTIVES: This systematic review and meta-analysis examined the effects of pre-conditioning strategies on indices of muscle damage and physical performance measures following a second bout of strenuous physical activity.

DATA SOURCES: PubMed, CINAHL and Scopus.

ELIGIBILITY CRITERIA: Studies meeting the PICO (population, intervention/exposure, comparison, and outcome) criteria were included in this review: (1) general population or “untrained” participants with no contraindications affecting physical performance; (2) studies with a parallel design to examine the prevention and severity of muscle-damaging contractions; (3) outcome measures were compared using baseline and post-intervention measures; and (4) outcome measures included any markers of indirect muscle damage and muscular contractility measures.

PARTICIPANTS: Individuals with no resistance training experiences in the previous 6 or more months.

INTERVENTIONS: A single bout of pre-conditioning exercises consisting of eccentric or isometric contractions performed a minimum of 24 h prior to a bout of damaging physical activity were compared to control interventions that did not perform pre-conditioning prior to damaging physical activity.

STUDY APPRAISAL: Kmet appraisal system.

SYNTHESIS METHODS: Quantitative analysis was conducted using forest plots to examine standardised mean differences (SMD, i.e. effect size), test statistics for statistical significance (i.e. Z-values) and between-study heterogeneity by inspecting I².

RESULTS: Following abstract and full-text screening, 23 articles were included in this paper. Based on the meta-analysis, the pre-conditioning group exhibited lower levels of creatine kinase at 24 h (SMD = – 1.64; Z = 8.39; p = 0.00001), 48 h (SMD = – 2.65; Z = 7.78; p = 0.00001), 72 h (SMD = – 2.39; Z = 5.71; p = 0.00001) and 96 h post-exercise (SMD = – 3.52; Z = 7.39; p = 0.00001) than the control group. Delayed-onset muscle soreness was also lower for the pre-conditioning group at 24 h (SMD = – 1.89; Z = 6.17; p = 0.00001), 48 h (SMD = – 2.50; Z = 7.99; p = 0.00001), 72 h (SMD = – 2.73; Z = 7.86; p = 0.00001) and 96 h post-exercise (SMD = – 3.30; Z = 8.47; p = 0.00001). Maximal voluntary contraction force was maintained and returned to normal sooner in the pre-conditioning group than in the control group, 24 h (SMD = 1.46; Z = 5.49; p = 0.00001), 48 h (SMD = 1.59; Z = 6.04; p = 0.00001), 72 h (SMD = 2.02; Z = 6.09; p = 0.00001) and 96 h post-exercise (SMD = 2.16; Z = 5.69; p = 0.00001). Range of motion was better maintained by the pre-conditioning group compared with the control group at 24 h (SMD = 1.48; Z = 4.30; p = 0.00001), 48 h (SMD = 2.20; Z = 5.64; p = 0.00001), 72 h (SMD = 2.66; Z = 5.42; p = 0.00001) and 96 h post-exercise (SMD = 2.5; Z = 5.46; p = 0.00001). Based on qualitative analyses, pre-conditioning activities were more effective when performed at 2-4 days before the muscle-damaging protocol compared with immediately prior to the muscle-damaging protocol, or 1-3 weeks prior to the muscle-damaging protocol. Furthermore, pre-conditioning activities performed using eccentric contractions over isometric contractions, with higher volumes, greater intensity and more lengthened muscle contractions provided greater protection from EIMD.

LIMITATIONS: Several outcome measures showed high inter-study heterogeneity. The inability to account for differences in durations between pre-conditioning and the second bout of damaging physical activity was also limiting.

CONCLUSIONS: Pre-conditioning significantly reduced the severity of creatine kinase release, delayed-onset muscle soreness, loss of maximal voluntary contraction force and the range of motion decrease. Pre-conditioning may prevent severe EIMD and accelerate recovery of muscle force generation capacity.

PMID:37160563 | DOI:10.1007/s40279-023-01839-8

Sports Med. 2023 May 9. doi: 10.1007/s40279-023-01849-6. Online ahead of print.

ABSTRACT

Clinical prediction models in sports medicine that utilize regression or machine learning techniques have become more widely published, used, and disseminated. However, these models are typically characterized by poor methodology and incomplete reporting, and an inadequate evaluation of performance, leading to unreliable predictions and weak clinical utility within their intended sport population. Before implementation in practice, models require a thorough evaluation. Strong replicable methods and transparency reporting allow practitioners and researchers to make independent judgments as to the model’s validity, performance, clinical usefulness, and confidence it will do no harm. However, this is not reflected in the sports medicine literature. As shown in a recent systematic review of models for predicting sports injury models, most were typically characterized by poor methodology, incomplete reporting, and inadequate performance evaluation. Because of constraints imposed by data from individual teams, the development of accurate, reliable, and useful models is highly reliant on external validation. However, a barrier to collaboration is a desire to maintain a competitive advantage; a team’s proprietary information is often perceived as high value, and so these ‘trade secrets’ are frequently guarded. These ‘trade secrets’ also apply to commercially available models, as developers are unwilling to share proprietary (and potentially profitable) development and validation information. In this Current Opinion, we: (1) argue that open science is essential for improving sport prediction models and (2) critically examine sport prediction models for open science practices.

PMID:37160562 | DOI:10.1007/s40279-023-01849-6

Updates Surg. 2023 May 9. doi: 10.1007/s13304-023-01521-8. Online ahead of print.

ABSTRACT

Association of advanced age, neoplastic disease and immunocompromission (IC) may lead to surgical emergencies. Few data exist about this topic. Present study reports the preliminary data from the WIRES-T trial about patients managed for colorectal neoplastic emergencies in immunocompromised patients. The required data were taken from a prospective observational international register. The study was approved by the Ethical Committee with approval n. 17575; ClinicalTrials.gov Identifier: NCT03643718. 839 patients were collected; 753 (80.7%) with mild-moderate IC and 86 (10.3%) with severe. Median age was 71.9 years and 73 years, respectively, in the two groups. The causes of mild-moderate IC were reported such malignancy (753-100%), diabetes (103-13.7%), malnutrition (26-3.5%) and uremia (1-0.1%), while severe IC causes were steroids treatment (14-16.3%); neutropenia (7-8.1%), malignancy on chemotherapy (71-82.6%). Preoperative risk classification were reported as follow: mild-moderate: ASA 1-14 (1.9%); ASA 2-202 (26.8%); ASA 3-341 (45.3%); ASA 4-84 (11.2%); ASA 5-7 (0.9%); severe group: ASA 1-1 patient (1.2%); ASA 2-16 patients (18.6%); ASA 3-41 patients (47.7%); ASA 4-19 patients (22.1%); ASA 5-3 patients (3.5%); lastly, ASA score was unavailable for 105 cases (13.9%) in mild-moderate group and in 6 cases (6.9%) in severe group. All the patients enrolled underwent urgent/emergency surgery Damage control approach with open abdomen was adopted in 18 patients. Mortality was 5.1% and 12.8%, respectively, in mild-moderate and severe groups. Long-term survival data: in mild-moderate disease-free survival (median, IQR) is 28 (10-91) and in severe IC, it is 21 (10-94). Overall survival (median, IQR) is 44 (18-99) and 26 (20-90) in mild-moderate and severe, respectively; the same is for post-progression survival (median, IQR) 29 (16-81) and 28, respectively. Univariate and multivariate analyses showed as the only factor influencing mortality in mild-moderate and severe IC is the ASA score. Colorectal neoplastic emergencies in immunocompromised patients are more frequent in elderly. Sigmoid and right colon are the most involved. Emergency surgery is at higher risk of complication and mortality; however, management in dedicated emergency surgery units is necessary to reduce disease burden and to optimize results by combining oncological and acute care principles. This approach may improve outcomes to obtain clinical advantages for patients like those observed in elective scenario. Lastly, damage control approach seems feasible and safe in selected patients.

PMID:37160552 | DOI:10.1007/s13304-023-01521-8

Int J Clin Pharm. 2023 May 9. doi: 10.1007/s11096-023-01563-3. Online ahead of print.

ABSTRACT

BACKGROUND: When prescriptions are being processed in pharmacies, ‘rework’ is a phenomenon where an activity occurs that requires the return to a prior procedural step in the process for correction. To date, little is known regarding rework prevalence in community pharmacies or how this might be minimised.

AIM: To evaluate the cause and frequency of prescription rework in community pharmacies.

METHOD: A list of reworks was designed for community pharmacists to self-record prescription rework instances and causes in their workplace across a two-week period. Community pharmacists in Ireland were recruited via convenience sampling and snowballing. Descriptive statistics were used to assess rework frequency according to the various causes, as well as the pharmacist and pharmacy characteristics.

RESULTS: Eight pharmacists participated, recording 325 reworks across 92.9% of the 65 study days (mean 5 reworks/day). The pharmacists’ mean ranged from 1.82 to 15 reworks/day. Pharmacists and pharmacy technicians alone or together were involved in 72.3% of reworks. The three most common rework categories were involving labelling errors (22.8%), prepared prescriptions which necessitated opening and repackaging (15.1%), and medication owings to patients (13.9%).

CONCLUSION: This study reveals that prescription rework occurs frequently in community pharmacies and has provided an indication of some of the main causes. These findings demonstrate areas where pharmacy staff can address rework and should aid the development of approaches to minimise rework in future – thus decreasing workload and facilitating more time for community pharmacy staff to focus on providing patient care.

PMID:37160551 | DOI:10.1007/s11096-023-01563-3

Phys Eng Sci Med. 2023 May 9. doi: 10.1007/s13246-023-01274-z. Online ahead of print.

ABSTRACT

Examining P-wave morphological changes in Electrocardiogram (ECG) is essential for characterizing atrial arrhythmias. However, standard 12-lead ECGsuffer from diagnostic redundancy due to low signal-to-noise ratio of P-waves. To address this issue, various optimal leads have been proposed for improved atrial activity recording, but the right selection among these leads is crucial for enhancing diagnostic efficacy. This study proposes an automated lead selection technique using the CatBoost machine learning (ML) model to improve the detection of P-wave changes among optimal bipolar leads under different heart rates. ECGs were obtained from healthy participants with a mean age of 25 ± 3.81 years (34% women), including 114 in sinus rhythm (SR) and 38 in sinus tachycardia (ST). The recordings were made using a newly designed atrial lead system (ALS), standard limb lead (SLL), modified limb lead (MLL), modified Lewis lead (LLM) and P-lead. P-wave features and Atrioventricular (AV) ratio were extracted for statistical analysis and ML classification. The optimum ML model was chosen to identify the best-performing optimal lead, which was selected based on the SLL metrics among different ML classifiers. CatBoost was found to outperform the other ML models in SLL-II with the highest accuracy and sensitivity of 0.82 and 0.90, respectively. The CatBoost model, amid other optimal leads, gave the best results for AL-I and AL-II (0.86 and 0.83 in accuracy and 0.91 and 0.93 in sensitivity). The developed CatBoost model selected AL-I and AL-II as the top two best-performing optimal leads for the enhanced acquisition of P-wave changes, which may be useful for diagnosing atrial arrhythmias.

PMID:37160538 | DOI:10.1007/s13246-023-01274-z

Environ Sci Pollut Res Int. 2023 May 9. doi: 10.1007/s11356-023-27387-2. Online ahead of print.

ABSTRACT

This study examined the modelling and optimisation of the electrocoagulation-flocculation (ECF) recovery of aquaculture effluent (AQE) using aluminium electrodes. The response surface methodology (RSM), artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) were used for the modelling, while the optimisation tools were the numerical RSM and genetic algorithm (GA). Furthermore, the kinetics of the ECF process was studied to provide insight into the mechanism governing the ECF of AQE. The experimental design was performed using the central composite design (CCD) of the RSM. The ANFIS modelling was accomplished via the Grid Partition (GP) of the data set, while the ANN used the multi-layer perceptron (MLP) based feed-forward system. Statistically, the prediction accuracy of the models followed the order: ANFIS (R²: 0.9990), ANN (R²: 0.9807), and RSM (R²: 0.9790). The process optimisation gave optimal turbidity (TD) removal efficiencies of 98.98, 97.81, and 96.01% for ANFIS-GA, ANN-GA, and RSM optimisation techniques, respectively. The ANFIS-GA gave the best optimization result at optimum conditions of pH 4, current intensity (3 A), electrolysis time (7.2 min), settling time (23 min), and temperature (43.8 °C). In the kinetics study, the experimental data was analysed using pseudo-first-order (0.8787), pseudo-second-order (0.9395), and Elovich (R²: 0.9979) kinetic models; the Elovich model gave the best correlation with the experimental data showing that the process is governed by electrostatic interaction mechanism. This study effectively demonstrated that ECF recovery of AQE can effectively be modelled using RSM, ANN, and ANFIS and be optimised using RSM, ANN-GA, and ANFIS-GA techniques, and the order of performance is ANFIS > ANN > RSM and ANFIS-GA > ANN-GA > RSM, respectively.

PMID:37160520 | DOI:10.1007/s11356-023-27387-2

Lasers Med Sci. 2023 May 9;38(1):121. doi: 10.1007/s10103-023-03775-5.

ABSTRACT

The aim of this study was to evaluate the effects of photobiomodulation (PBM) on cell migration and alkaline phosphatase (ALP), type I collagen (Col-1), runt-related transcription factor 2 (RUNX-2), and Osterix (OSX) gene expression in a cementoblast culture (OCCM-30), in a microenvironment mimicking an injury on the cementoblast layer, such as it occurs during root resorption. For this, OCCM-30 cells were cultured in 6-well plates and the following parameters were assayed: (1) migration by scratch assay and ALP, Col-1, Runx2, and Osx by real-time PCR. PBM was performed in two protocols using a LED device emitting light at 660 nm (± 30 nm). OCCM-30 cementoblasts were grown and divided into four groups: (1) negative control; (2) positive control (scratch); (3) scratch + PBM with a total energy of 36 J and energy density 1.6 J/cm²; and (4) scratch + PBM with a total energy of 72 J and energy density of 3.2 J/cm². Data were statistically analyzed, with the level of significance set at 5%. Cementoblasts migrated from the edge of the scratch toward the center, and the wound closed after 24 h, with the PBM3.2J/cm² group showing the higher cell migration compared with the other groups at 2 h, 6 h, 8 h, and 13 h (p < 0.05). The control and PBM1.6J/cm² groups showed similar levels of cell migration, with no significant differences (p > 0.05). PBM3.2J/cm² group exhibited greater ALP, Col-1, OSX, and RUNX2 in comparison with the other experimental groups (p < 0.05). Similar levels of all genes evaluated were observed between the PBM1.6J/cm² group and the positive control group (p > 0.05). In conclusion, our findings support the effectiveness of photobiomodulation on cementoblast migration and gene expression, which may contribute to the formation of a new cementum layer.

PMID:37160506 | DOI:10.1007/s10103-023-03775-5

Cardiovasc Drugs Ther. 2023 May 9. doi: 10.1007/s10557-023-07450-3. Online ahead of print.

ABSTRACT

CONTEXT: A nomogram model affecting the activated clotting time (ACT) targeting rate during radiofrequency ablation of atrial fibrillation (RFCA) in China.

PURPOSE: The aim of this study is to develop and validate a nomogram model for predicting the activated clotting time targeting rate after the initial bolus heparin dosages during the radiofrequency catheter ablation of atrial fibrillation in China.

METHODS AND RESULTS: A retrospective observational study was conducted on the data of 465 patients with atrial fibrillation who underwent radiofrequency catheter ablation (RFCA) from October 2019 to June 2022. All patients were randomized into a training cohort (70%; n = 325) and a validation cohort (30%; n = 140). Independent risk factors were identified using univariate and multifactorial logistic regression analysis. The predictive nomogram model was established using R software. The nomogram was developed and evaluated based on differentiation, calibration, and clinical efficacy using concordance statistic (C-statistic), calibration plots, and decision curve analysis (DCA), respectively. The nomogram was established using three variables, including sex (OR 1.01, 95% CI 0.29-1.76, P = 0.007), heparin dose (OR 0.04; 95%CI 0.02-0.05, P < 0.001), and the baseline ACT (OR 0.03; 95%CI 0.02-0.04, P < 0.001). The C-statistic of the nomogram was 0.736 (95%CI 0.675-0.732) in the training cohort and 0.700 (95%CI 0.622-0.721) in the validation cohort. The calibration plots showed good agreement between the predictions and observations in the training and validation cohorts. The clinical decision curve also proves that the map is useful in clinical settings.

CONCLUSION: The nomogram model has good discrimination and accuracy, which can screen attainment groups intuitively and individually, and has a certain predictive value for the probability of ACT reaching the target after the adequate dosage of initial heparin in Chinese patients with atrial fibrillation.

PMID:37160503 | DOI:10.1007/s10557-023-07450-3

Graefes Arch Clin Exp Ophthalmol. 2023 May 9. doi: 10.1007/s00417-023-06085-2. Online ahead of print.

ABSTRACT

PURPOSE: Anti-retinal autoantibodies are assumed to be associated with age-related macular degeneration (AMD). To our knowledge, this is the first evaluation of autoantibodies in human sera of participants with different stages of AMD in a large population-based, observational cohort study in Germany.

METHODS: The Gutenberg Health Study (GHS) is a population-based, observational cohort study in Germany, including 15,010 participants aged between 35 and 74. Amongst others, non-mydriatic fundus photography (Visucam PRO NM™, Carl Zeiss Meditec AG, Jena, Germany) was performed. Fundus images of the first 5000 participants were graded based on the Rotterdam Eye Study classification. Sera of participants with AMD (n=541) and sera of age-matched participants without AMD (n=490) were analyzed by antigen-microarrays. Besides descriptive statistics, autoantibody-levels were compared by Mann-Whitney-U test and the associations of level of autoantibodies with AMD were calculated by logistic regression analysis. Likewise, possible associations of the autoantibodies and both clinical and laboratory parameters on AMD subjects were analyzed.

RESULTS: Autoantibodies against transferrin (p<0.001) were significantly downregulated in participants with early AMD and soft, distinct drusen (≥63 μm) or pigmentary abnormalities only compared to Controls. Mitogen-activated protein kinase 3 (p=0.041), glutathione peroxidase 4 (p=0.048), clusterin (p=0.045), lysozyme (p=0.19), protein kinase C substrate 80K-H (p=0.02), heat shock 70 kDa protein 1A (p=0.04) and insulin (p=0.018) show a trend between Control and participants with early AMD and soft, distinct drusen (≥63 μm) or pigmentary abnormalities only.

CONCLUSIONS: This study contributes to a growing knowledge of autoantibodies in association with different AMD stages compared to controls in the context of a large population-based study in Germany. Especially autoantibodies against inflammatory proteins were downregulated in participants with early AMD and soft, distinct drusen (≥63 μm) or pigmentary abnormalities only.

PMID:37160502 | DOI:10.1007/s00417-023-06085-2

Sleep Breath. 2023 May 9. doi: 10.1007/s11325-023-02841-0. Online ahead of print.

ABSTRACT

OBJECTIVE: To explore the correlation between sleep duration and type II diabetes in adults.

METHOD: Computer databases searches were carried out through October 1, 2022, including PubMed, Cochrane Library, Embase, and Web of Science. Relevant literature was collected, and the Newcastle-Ottawa Scale (NOS) and extracted data were used to exclude studies and evaluate quality on the basis of inclusion and exclusion criteria. Meta-analysis was conducted using RevMan 5.4.1 software with random/fixed effects models.

RESULTS: A total of 5 studies with 74,226 subjects (31,611 in the male study group, 42,615 in the female study group) were included. The meta-analysis revealed that women with long sleep duration (LSD) have a higher risk for developing type II diabetes than men, OR = 0.70; 95% CI 0.59-0.84, Z = 4.00 and P < 0.001. Men with short sleep duration (SSD) tended to have a higher risk in developing type II diabetes than women though the difference between men and women did not reach statistical significance, OR = 1.09, 95% CI 0.73-1.62, Z = 0.42 and P = 0.68. Further subgroup analysis by regional populations suggested that men in Europe and America with SSD had a higher risk of type II diabetes OR = 1.52, 95% CI 1.04-2.21, Z = 2.18 and P = 0.03.

CONCLUSION: Women with LSD may have a higher risk for type II diabetes, and men in Europe and America with SSD may have a higher risk for type II diabetes than men of other regions.

PMID:37160494 | DOI:10.1007/s11325-023-02841-0