In-season nutrition strategies and recovery modalities to enhance recovery for basketball players: a narrative review

Basketball players face multiple challenges to in-season recovery. The purpose of this article is to review the literature on recovery modalities and nutritional strategies for basketball players and practical applications that can be incorporated throughout the season at various levels of competition. Sleep, protein, carbohydrate, and fluids should be the foundational components emphasized throughout the season for home and away games to promote recovery. Travel, whether by air or bus, poses nutritional and sleep challenges, therefore teams should be strategic about packing snacks and fluid options while on the road. Practitioners should also plan for meals at hotels and during air travel for their players. Basketball players should aim for a minimum of 8 h of sleep per night and be encouraged to get extra sleep during congested schedules since back-to back games, high workloads, and travel may negatively influence night-time sleep. Regular sleep monitoring, education, and feedback may aid in optimizing sleep in basketball players. In addition, incorporating consistent training times may be beneficial to reduce bed and wake time variability. Hydrotherapy, compression garments, and massage may also provide an effective recovery modality to incorporate post-competition. Future research, however, is warranted to understand the influence these modalities have on enhancing recovery in basketball players. Overall, a strategic well-rounded approach, encompassing both nutrition and recovery modality strategies, should be carefully considered and implemented with teams to support basketball players’ recovery for training and competition throughout the season

First month prednisone dose predicts prednisone burden during the following 11 months: An observational study from the RELES cohort

Aim: To study the influence of prednisone dose during the first month after systemic lupus erythematosus (SLE) diagnosis (prednisone-1) on glucocorticoid burden during the subsequent 11 months (prednisone-2–12). Methods: 223 patients from the Registro Español de Lupus Eritematoso Sistémico inception cohort were studied. The cumulative dose of prednisone-1 and prednisone-2–12 were calculated and recoded into a four-level categorical variable: no prednisone, low dose (up to 7.5 mg/day), medium dose (up to 30 mg/day) and high dose (over 30 mg/day). The association between the cumulative prednisone-1 and prednisone-2–12 doses was tested. We analysed whether the four-level prednisone-1 categorical variable was an independent predictor of an average dose >7.5 mg/day of prednisone-2–12. Adjusting variables included age, immunosuppressives, antimalarials, methyl-prednisolone pulses, lupus nephritis and baseline SLE Disease Activity Index (SLEDAI). Results: Within the first month, 113 patients (51%) did not receive any prednisone, 24 patients (11%) received average low doses, 46 patients (21%) received medium doses and 40 patients (18%) received high doses. There was a strong association between prednisone-1 and prednisone-2–12 dose categories (p7.5 mg/day, while patients receiving low-dose prednisone-1 were not (adjusted OR 1.4, 95% CI 0. 0.38 to 5.2). If the analysis was restricted to the 158 patients with a baseline SLEDAI of =6, the model did not change. Conclusion: The dose of prednisone during the first month after the diagnosis of SLE is an independent predictor of prednisone burden during the following 11 months

Voxel-based statistical analysis of thalamic glucose metabolism in traumatic brain injury: relationship with consciousness and cognition

Objective: To study the relationship between thalamic glucose metabolism and neurological outcome after severe traumatic brain injury (TBI). Methods: Forty-nine patients with severe and closed TBI and 10 healthy control subjects with 18F-FDG PET were studied. Patients were divided into three groups: MCS&VS group (n ¼ 17), patients in a vegetative or a minimally conscious state; In-PTA group (n ¼ 12), patients in a state of post-traumatic amnesia (PTA); and Out-PTA group (n ¼ 20), patients who had emerged from PTA. SPM5 software implemented in MATLAB 7 was used to determine the quantitative differences between patients and controls. FDG-PET images were spatially normalized and an automated thalamic ROI mask was generated. Group differences were analysed with two sample voxel-wise t-tests. Results: Thalamic hypometabolism was the most prominent in patients with low consciousness (MCS&VS group) and the thalamic hypometabolism in the In-PTA group was more prominent than that in the Out-PTA group. Healthy control subjects showed the greatest thalamic metabolism. These differences in metabolism were more pronounced in the internal regions of the thalamus. Conclusions: The results confirm the vulnerability of the thalamus to suffer the effect of the dynamic forces generated during a TBI. Patients with thalamic hypometabolism could represent a sub-set of subjects that are highly vulnerable to neurological disability after TBI.Lull Noguera, N.; Noé, E.; Lull Noguera, JJ.; Garcia Panach, J.; Chirivella, J.; Ferri, J.; López-Aznar, D.... (2010). Voxel-based statistical analysis of thalamic glucose metabolism in traumatic brain injury: relationship with consciousness and cognition. Brain Injury. 24(9):1098-1107. doi:10.3109/02699052.2010.494592S10981107249Gallagher, C. N., Hutchinson, P. J., & Pickard, J. D. (2007). Neuroimaging in trauma. Current Opinion in Neurology, 20(4), 403-409. doi:10.1097/wco.0b013e32821b987bWoischneck, D., Klein, S., Rei�berg, S., D�hring, W., Peters, B., & Firsching, R. (2001). Classification of Severe Head Injury Based on Magnetic Resonance Imaging. Acta Neurochirurgica, 143(3), 263-271. doi:10.1007/s007010170106Grados, M. A. (2001). Depth of lesion model in children and adolescents with moderate to severe traumatic brain injury: use of SPGR MRI to predict severity and outcome. Journal of Neurology, Neurosurgery & Psychiatry, 70(3), 350-358. doi:10.1136/jnnp.70.3.350Meythaler, J. M., Peduzzi, J. D., Eleftheriou, E., & Novack, T. A. (2001). Current concepts: Diffuse axonal injury–associated traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 82(10), 1461-1471. doi:10.1053/apmr.2001.25137Scheid, R., Walther, K., Guthke, T., Preul, C., & von Cramon, D. Y. (2006). Cognitive Sequelae of Diffuse Axonal Injury. Archives of Neurology, 63(3), 418. doi:10.1001/archneur.63.3.418Brandstack, N., Kurki, T., Tenovuo, O., & Isoniemi, H. (2006). MR imaging of head trauma: Visibility of contusions and other intraparenchymal injuries in early and late stage. Brain Injury, 20(4), 409-416. doi:10.1080/02699050500487951Xu, J., Rasmussen, I.-A., Lagopoulos, J., & Håberg, A. (2007). Diffuse Axonal Injury in Severe Traumatic Brain Injury Visualized Using High-Resolution Diffusion Tensor Imaging. Journal of Neurotrauma, 24(5), 753-765. doi:10.1089/neu.2006.0208Levine, B., Fujiwara, E., O’connor, C., Richard, N., Kovacevic, N., Mandic, M., … Black, S. E. (2006). In Vivo Characterization of Traumatic Brain Injury Neuropathology with Structural and Functional Neuroimaging. Journal of Neurotrauma, 23(10), 1396-1411. doi:10.1089/neu.2006.23.1396Metting, Z., Rödiger, L. A., De Keyser, J., & van der Naalt, J. (2007). Structural and functional neuroimaging in mild-to-moderate head injury. The Lancet Neurology, 6(8), 699-710. doi:10.1016/s1474-4422(07)70191-6Nakayama, N. (2006). Relationship between regional cerebral metabolism and consciousness disturbance in traumatic diffuse brain injury without large focal lesions: an FDG-PET study with statistical parametric mapping analysis. Journal of Neurology, Neurosurgery & Psychiatry, 77(7), 856-862. doi:10.1136/jnnp.2005.080523Nakayama, N. (2006). Evidence for white matter disruption in traumatic brain injury without macroscopic lesions. Journal of Neurology, Neurosurgery & Psychiatry, 77(7), 850-855. doi:10.1136/jnnp.2005.077875O’Leary, D. D. M., Schlaggar, B. L., & Tuttle, R. (1994). Specification of Neocortical Areas and Thalamocortical Connections. Annual Review of Neuroscience, 17(1), 419-439. doi:10.1146/annurev.ne.17.030194.002223Mitelman, S. A., Byne, W., Kemether, E. M., Newmark, R. E., Hazlett, E. A., Haznedar, M. M., & Buchsbaum, M. S. (2006). Metabolic thalamocortical correlations during a verbal learning task and their comparison with correlations among regional volumes. Brain Research, 1114(1), 125-137. doi:10.1016/j.brainres.2006.07.043Laureys, S., Faymonville, M., Luxen, A., Lamy, M., Franck, G., & Maquet, P. (2000). Restoration of thalamocortical connectivity after recovery from persistent vegetative state. The Lancet, 355(9217), 1790-1791. doi:10.1016/s0140-6736(00)02271-6Laureys, S., Goldman, S., Phillips, C., Van Bogaert, P., Aerts, J., Luxen, A., … Maquet, P. (1999). Impaired Effective Cortical Connectivity in Vegetative State: Preliminary Investigation Using PET. NeuroImage, 9(4), 377-382. doi:10.1006/nimg.1998.0414Laureys, S., Owen, A. M., & Schiff, N. D. (2004). Brain function in coma, vegetative state, and related disorders. The Lancet Neurology, 3(9), 537-546. doi:10.1016/s1474-4422(04)00852-xGuye, M., Bartolomei, F., & Ranjeva, J.-P. (2008). Imaging structural and functional connectivity: towards a unified definition of human brain organization? Current Opinion in Neurology, 24(4), 393-403. doi:10.1097/wco.0b013e3283065cfbPrice, C. J., & Friston, K. J. (2002). Functional Imaging Studies of Neuropsychological Patients: Applications and Limitations. Neurocase, 8(5), 345-354. doi:10.1076/neur.8.4.345.16186Kim, J., Avants, B., Patel, S., Whyte, J., Coslett, B. H., Pluta, J., … Gee, J. C. (2008). Structural consequences of diffuse traumatic brain injury: A large deformation tensor-based morphometry study. NeuroImage, 39(3), 1014-1026. doi:10.1016/j.neuroimage.2007.10.005Maxwell, W. L., MacKinnon, M. A., Smith, D. H., McIntosh, T. K., & Graham, D. I. (2006). Thalamic Nuclei After Human Blunt Head Injury. Journal of Neuropathology & Experimental Neurology, 65(5), 478-488. doi:10.1097/01.jnen.0000229241.28619.75SIDAROS, A., SKIMMINGE, A., LIPTROT, M., SIDAROS, K., ENGBERG, A., HERNING, M., … ROSTRUP, E. (2009). Long-term global and regional brain volume changes following severe traumatic brain injury: A longitudinal study with clinical correlates. NeuroImage, 44(1), 1-8. doi:10.1016/j.neuroimage.2008.08.030Ashburner, J., & Friston, K. J. (2000). Voxel-Based Morphometry—The Methods. NeuroImage, 11(6), 805-821. doi:10.1006/nimg.2000.0582Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N. A., Friston, K. J., & Frackowiak, R. S. J. (2001). A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains. NeuroImage, 14(1), 21-36. doi:10.1006/nimg.2001.0786Giacino, J. T., Ashwal, S., Childs, N., Cranford, R., Jennett, B., Katz, D. I., … Zasler, N. D. (2002). The minimally conscious state: Definition and diagnostic criteria. Neurology, 58(3), 349-353. doi:10.1212/wnl.58.3.349Gispert, J. ., Pascau, J., Reig, S., Martínez-Lázaro, R., Molina, V., García-Barreno, P., & Desco, M. (2003). Influence of the normalization template on the outcome of statistical parametric mapping of PET scans. NeuroImage, 19(3), 601-612. doi:10.1016/s1053-8119(03)00072-7Ashburner, J., & Friston, K. J. (1999). Nonlinear spatial normalization using basis functions. Human Brain Mapping, 7(4), 254-266. doi:10.1002/(sici)1097-0193(1999)7:43.0.co;2-gTzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., … Joliot, M. (2002). Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain. NeuroImage, 15(1), 273-289. doi:10.1006/nimg.2001.0978Genovese, C. R., Lazar, N. A., & Nichols, T. (2002). Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate. NeuroImage, 15(4), 870-878. doi:10.1006/nimg.2001.1037LAUREYS, S., LEMAIRE, C., MAQUET, P., PHILLIPS, C., & FRANCK, G. (1999). Cerebral metabolism during vegetative state and after recovery to consciousness. Journal of Neurology, Neurosurgery & Psychiatry, 67(1), 121-122. doi:10.1136/jnnp.67.1.121Tommasino, C., Grana, C., Lucignani, G., Torri, G., & Fazio, F. (1995). Regional Cerebral Metabolism of Glucose in Comatose and Vegetative State Patients. Journal of Neurosurgical Anesthesiology, 7(2), 109-116. doi:10.1097/00008506-199504000-00006ANDERSON, C. V., WOOD, D.-M. G., BIGLER, E. D., & BLATTER, D. D. (1996). Lesion Volume, Injury Severity, and Thalamic Integrity following Head Injury. Journal of Neurotrauma, 13(2), 59-65. doi:10.1089/neu.1996.13.59Ge, Y., Patel, M. B., Chen, Q., Grossman, E. J., Zhang, K., Miles, L., … Grossman, R. I. (2009). Assessment of thalamic perfusion in patients with mild traumatic brain injury by true FISP arterial spin labelling MR imaging at 3T. Brain Injury, 23(7-8), 666-674. doi:10.1080/02699050903014899Uzan, M. (2003). Thalamic proton magnetic resonance spectroscopy in vegetative state induced by traumatic brain injury. Journal of Neurology, Neurosurgery & Psychiatry, 74(1), 33-38. doi:10.1136/jnnp.74.1.33OMMAYA, A. K., & GENNARELLI, T. A. (1974). CEREBRAL CONCUSSION AND TRAUMATIC UNCONSCIOUSNESS. Brain, 97(1), 633-654. doi:10.1093/brain/97.1.633Giacino, J., & Whyte, J. (2005). The Vegetative and Minimally Conscious States. Journal of Head Trauma Rehabilitation, 20(1), 30-50. doi:10.1097/00001199-200501000-00005Zeman, A. (2001). Consciousness. Brain, 124(7), 1263-1289. doi:10.1093/brain/124.7.1263Kinney, H. C., Korein, J., Panigrahy, A., Dikkes, P., & Goode, R. (1994). Neuropathological Findings in the Brain of Karen Ann Quinlan -- The Role of the Thalamus in the Persistent Vegetative State. New England Journal of Medicine, 330(21), 1469-1475. doi:10.1056/nejm199405263302101Saeeduddin Ahmed, Rex Bierley, Java. (2000). Post-traumatic amnesia after closed head injury: a review of the literature and some suggestions for further research. Brain Injury, 14(9), 765-780. doi:10.1080/026990500421886Wilson, J. T., Hadley, D. M., Wiedmann, K. D., & Teasdale, G. M. (1995). Neuropsychological consequences of two patterns of brain damage shown by MRI in survivors of severe head injury. Journal of Neurology, Neurosurgery & Psychiatry, 59(3), 328-331. doi:10.1136/jnnp.59.3.328Wilson, J. T., Teasdale, G. M., Hadley, D. M., Wiedmann, K. D., & Lang, D. (1994). Post-traumatic amnesia: still a valuable yardstick. Journal of Neurology, Neurosurgery & Psychiatry, 57(2), 198-201. doi:10.1136/jnnp.57.2.198Fearing, M. A., Bigler, E. D., Wilde, E. A., Johnson, J. L., Hunter, J. V., Xiaoqi Li, … Levin, H. S. (2008). Morphometric MRI Findings in the Thalamus and Brainstem in Children After Moderate to Severe Traumatic Brain Injury. Journal of Child Neurology, 23(7), 729-737. doi:10.1177/0883073808314159Little, D. M., Kraus, M. F., Joseph, J., Geary, E. K., Susmaras, T., Zhou, X. J., … Gorelick, P. B. (2010). Thalamic integrity underlies executive dysfunction in traumatic brain injury. Neurology, 74(7), 558-564. doi:10.1212/wnl.0b013e3181cff5d

Effect of alirocumab on mortality after acute coronary syndromes. An analysis of the ODYSSEY OUTCOMES randomized clinical trial

Background: Previous trials of PCSK9 (proprotein convertase subtilisin-kexin type 9) inhibitors demonstrated reductions in major adverse cardiovascular events, but not death. We assessed the effects of alirocumab on death after index acute coronary syndrome. Methods: ODYSSEY OUTCOMES (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) was a double-blind, randomized comparison of alirocumab or placebo in 18 924 patients who had an ACS 1 to 12 months previously and elevated atherogenic lipoproteins despite intensive statin therapy. Alirocumab dose was blindly titrated to target achieved low-density lipoprotein cholesterol (LDL-C) between 25 and 50 mg/dL. We examined the effects of treatment on all-cause death and its components, cardiovascular and noncardiovascular death, with log-rank testing. Joint semiparametric models tested associations between nonfatal cardiovascular events and cardiovascular or noncardiovascular death. Results: Median follow-up was 2.8 years. Death occurred in 334 (3.5%) and 392 (4.1%) patients, respectively, in the alirocumab and placebo groups (hazard ratio [HR], 0.85; 95% CI, 0.73 to 0.98; P=0.03, nominal P value). This resulted from nonsignificantly fewer cardiovascular (240 [2.5%] vs 271 [2.9%]; HR, 0.88; 95% CI, 0.74 to 1.05; P=0.15) and noncardiovascular (94 [1.0%] vs 121 [1.3%]; HR, 0.77; 95% CI, 0.59 to 1.01; P=0.06) deaths with alirocumab. In a prespecified analysis of 8242 patients eligible for ≥3 years follow-up, alirocumab reduced death (HR, 0.78; 95% CI, 0.65 to 0.94; P=0.01). Patients with nonfatal cardiovascular events were at increased risk for cardiovascular and noncardiovascular deaths (P<0.0001 for the associations). Alirocumab reduced total nonfatal cardiovascular events (P<0.001) and thereby may have attenuated the number of cardiovascular and noncardiovascular deaths. A post hoc analysis found that, compared to patients with lower LDL-C, patients with baseline LDL-C ≥100 mg/dL (2.59 mmol/L) had a greater absolute risk of death and a larger mortality benefit from alirocumab (HR, 0.71; 95% CI, 0.56 to 0.90; Pinteraction=0.007). In the alirocumab group, all-cause death declined wit h achieved LDL-C at 4 months of treatment, to a level of approximately 30 mg/dL (adjusted P=0.017 for linear trend). Conclusions: Alirocumab added to intensive statin therapy has the potential to reduce death after acute coronary syndrome, particularly if treatment is maintained for ≥3 years, if baseline LDL-C is ≥100 mg/dL, or if achieved LDL-C is low. Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01663402