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Journal articles on the topic 'Early predictors'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Dubrovina, Dubrovina A. V., Mutsalkhanova Yu S. Mutsalkhanova, and Vasilyeva V. V. Vasilyeva. "Early predictors of preeclampsia." Akusherstvo i ginekologiia 10_2018 (October 31, 2018): 47–51. http://dx.doi.org/10.18565/aig.2018.10.47-51.

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2

Peat, Jennifer K., and Craig M. Mellis. "Early predictors of asthma." Current Opinion in Allergy and Clinical Immunology 2, no. 3 (June 2002): 167–73. http://dx.doi.org/10.1097/00130832-200206000-00003.

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3

Garvey, Arthur J., Ryan E. Bliss, and Kenneth D. Ward. "Predictors of early relapse." Pharmacology Biochemistry and Behavior 36, no. 2 (June 1990): 424. http://dx.doi.org/10.1016/0091-3057(90)90436-l.

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4

Kessel, Ellen M., Lea R. Dougherty, Samantha Hubacheck, Emma Chad-Friedman, Tom Olino, Gabrielle A. Carlson, and Daniel N. Klein. "Early Predictors of Adolescent Irritability." Child and Adolescent Psychiatric Clinics of North America 30, no. 3 (July 2021): 475–90. http://dx.doi.org/10.1016/j.chc.2021.04.002.

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5

Melnik, J. M., and A. A. Shlyahtina. "Early predictors of placental dysfunction." HEALTH OF WOMAN, no. 8(114) (October 30, 2016): 25–28. http://dx.doi.org/10.15574/hw.2016.114.25.

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The article presents the predictors of placental dysfunction on the early stage of pregnancy. The objective: the search for prognostic markers and criteria for the occurrence of placental insufficiency in the early stages of the gestational process to optimize the pregnancy and labor with improved perinatal outcomes. Patients and methods. To solve this goal in the period from 2013 to 2015 were conducted a comprehensive survey of 334 pregnant women, which depending on the peculiarities of pregnancy and childbirth were divided into groups. The control group consisted of 236 pregnant women with uncomplicated gestational period, no morphological signs of placental dysfunction. The study group included 98 patients with a complicated pregnancy who had revealed violations of the fetal-placental relations, which was confirmed by morphological examination of the placenta in the postpartum period. Results. It was found that pregnant women with placental insufficiency in the first trimester of pregnancy have higher levels of interleukin-1B (IL-1v) and interleukin-3 (IL-3) in comparison with physiological pregnancy, as well as there is a direct significant correlation between IL-1v and pulsative index (PI) in the spiral (r=0.84) and uterine artery (r=0.77), and the inverse correlation between the level of IL-3 and PI in the terminal branches of the umbilical artery (r=-0.69). Verified an inverse relationship between the concentration of endothelin-1, the level of vascular endothelial growth factor (r=-0.87) and placental growth factor (r=-0.73), and also a direct link between the content of endothelin-1 and PI in spiral arteries (r=0.89), uterine artery (r=0.83) and the terminal branches of the umbilical artery (r=0.79). Conclusion. Thus, it is proven that early predictors of placental dysfunction can be considered the concentration of endothelin-1, vascular endothelial growth factor, placental growth factor, interleukin-1, interleukin-3, and the indices of pulsative index. Key words: placental dysfunction, predictors, endothelin-1, vascular endothelial growth factor, placental growth factor, interleukin, pulsative index.

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6

Mazza, James J., Robert D. Abbott, Charles B. Fleming, Tracy W. Harachi, Rebecca C. Cortes, Jisuk Park, Kevin P. Haggerty, and Richard F. Catalano. "Early Predictors of Adolescent Depression." Journal of Early Adolescence 29, no. 5 (November 5, 2008): 664–92. http://dx.doi.org/10.1177/0272431608324193.

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7

Wöhrle, Jochen, Holger M. Nef, Christoph Naber, Stephan Achenbach, Thomas Riemer, Julinda Mehilli, Thomas Münzel, et al. "Predictors of early scaffold thrombosis." Coronary Artery Disease 29, no. 5 (August 2018): 389–96. http://dx.doi.org/10.1097/mca.0000000000000618.

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8

Loeber, Rolf. "EARLY PREDICTORS OF CONDUCT DISORDER." Journal of the American Academy of Child & Adolescent Psychiatry 34, no. 9 (September 1995): 1122. http://dx.doi.org/10.1097/00004583-199509000-00006.

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9

Mitchell, Darcy B., and Penny Hauser-Cram. "Early Predictors of Behavior Problems." Journal of Early Intervention 32, no. 1 (November 6, 2009): 3–16. http://dx.doi.org/10.1177/1053815109349113.

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10

Szigety, T. ünde. "Early predictors of workplace mobbing." Procedia - Social and Behavioral Sciences 33 (2012): 418–22. http://dx.doi.org/10.1016/j.sbspro.2012.01.155.

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11

Robinson, Richard. "MRI PREDICTORS OF EARLY MS." Neurology Today 9, no. 1 (January 2009): 1. http://dx.doi.org/10.1097/01.nt.0000345149.63209.ac.

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12

Smith, C. B., L. B. Adamson, and R. Bakeman. "Interactional predictors of early language." Infant Behavior and Development 9 (April 1986): 347. http://dx.doi.org/10.1016/s0163-6383(86)80353-8.

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13

Smith, Connie B., Lauren B. Adamson, and Roger Bakeman. "Interactional predictors of early language." First Language 8, no. 23 (June 1988): 143–56. http://dx.doi.org/10.1177/014272378800802304.

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14

SHERMAN, CHARLES B., TOR D. TOSTESON, IRA B. TAGER, FRANK E. SPEIZER, and SCOTT T. WEISS. "EARLY CHILDHOOD PREDICTORS OF ASTHMA." American Journal of Epidemiology 132, no. 1 (July 1990): 83–95. http://dx.doi.org/10.1093/oxfordjournals.aje.a115646.

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15

de Jong, P. F., and R. K. Olson. "Early predictors of letter knowledge." Journal of Experimental Child Psychology 88, no. 3 (July 2004): 254–73. http://dx.doi.org/10.1016/j.jecp.2004.03.007.

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16

Hudson, Jennifer L., Kou Murayama, Lotte Meteyard, Talia Morris, and Helen F. Dodd. "Early Childhood Predictors of Anxiety in Early Adolescence." Journal of Abnormal Child Psychology 47, no. 7 (December 19, 2018): 1121–33. http://dx.doi.org/10.1007/s10802-018-0495-6.

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17

Waterhouse, Elizabeth. "Predictors of Early Seizures after Stroke." Epilepsy Currents 2, no. 3 (May 2002): 75–76. http://dx.doi.org/10.1111/j.1535-7597.2002.t01-1-00028.x.

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Prevalence and Predictors of Early Seizure and Status Epilepticus after First Stroke Labovitz DL, Allen Hauser W, Sacco RL Neurology 2001;57:200–206 Background Early seizure (ES) has been reported in 2 to 6% of strokes and is a predictor of recurrent seizures. Acute stroke has been reported to cause 22% of all cases of status epilepticus (SE) in adults. The determinants of ES and SE after stroke, however, are not well understood. Methods An incidence study was conducted to identify all cases of first stroke in adult residents of northern Manhattan. Cases of ES and SE within 7 days of stroke were identified through medical record review. Statistical analyses were performed by using univariate and multivariate logistic regression models. Results The cohort consisted of 904 patients; ES occurred in 37 (4.1%). The frequency of ES by stroke subtype and location was deep infarct in two (0.6%) of 356, lobar infarct in 20 (5.9%) of 341, deep intracerebral hemorrhage (ICH) in four (4.0%) of 101, lobar ICH in seven (14.3%) of 49, and subarachnoid hemorrhage in four (8.0%) of 50. SE occurred in 10 (1.1%) patients, representing 27.0% of patients with ES. Diabetes, hypertension, current smoking, alcohol use, age, gender, and race/ethnicity were not significant determinants of ES. In a subgroup of patients who had a National Institutes of Health (NIH) stroke scale (NIHSS) score recorded, NIHSS score was not an independent predictor of ES in multivariate analysis. After accounting for stroke severity, ES was not a predictor of 30-day case fatality. Conclusions Lesion location and stroke subtype are strong determinants of ES risk, even after adjusting for stroke severity. ES does not predict 30-day mortality. SE occurs in more than one fourth of patients with ES.

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18

Guðbrandsdóttir, Ragna Kristín, and Oddur Ingimarsson. "Functional recovery after first episode psychosis rehabilitation in an early intervention psychosis center in Iceland." Læknablaðið 108, no. 06 (June 2, 2022): 288–97. http://dx.doi.org/10.17992/lbl.2022.06.695.

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BACKGROUND: Because of the early onset and disabling symptoms of schizophrenia spectrum disorders many individuals with these disorders are unemployed from an early age and disability pension rates are high. The aim of this study was to assess functional recovery and identify vocational predictors among young first episode psychosis patients registered in an early intervention psychosis center in Iceland in 2010-2020. METHODS: The study is a retrospective cohort study based on the medical records of those who were discharged from Laugaras, the only early intervention psychosis program in Iceland after six months or longer rehabilitation in 2010-2020 (n=144). Univariate and multivariate logistic regression was used to identify vocational predictors. RESULTS: 75% of patients were unemployed at admission to the early intervention center but over half of the patients were employed or in school at discharge. Vocational rehabilitation was the strongest vocational predictor (OR 13.93, 95% CI 3.85-63.89). Other vocational predictors were those that reflect a disabling psychiatric disorder and social functioning before the onset of early intervention. 66% of patients had a history of cannabis use which had a negative impact on employment and education at discharge. CONCLUSIONS: In spite of intensive rehabilitation at an early intervention center, almost half of the patients were neither employed nor in school at discharge. The strongest vocational predictor was vocational rehabilitation which was also one of few vocational predictors that can be influenced by admission to an early intervention psychosis center. It therefore seems important to ensure that effective vocational rehabilitation is readily available at early intervention psychosis centers.

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19

Thomas, P. R. S., M. S. Quraishy, R. Bowyer, R. A. P. Scott, J. M. Bland, and J. A. Dormandy. "Leucocyte count: A Predictor of Early Femoropopliteal Graft Failure." Cardiovascular Surgery 1, no. 4 (August 1993): 369–72. http://dx.doi.org/10.1177/096721099300100410.

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The patency of 90 elective femoropopliteal reconstructions was asessed 6 months after surgery. The preoperative white cell count was found to be a highly significant predictor of early graft failure ( P < 0.0001) independent of other previously recognized predictors of occlusion such as smoking and run-off.

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20

Douma, Joeri A. J., Laurien M. Buffart, Ramy Sedhom, Mariette Labots, Willemien C. Menke-van der Houven van Oordt, Mikkjal Skardhamar, Anthony De Felice, et al. "Clinical Predictors of Early Trial Discontinuation for Patients Participating in Phase I Clinical Trials in Oncology." Cancers 13, no. 10 (May 11, 2021): 2304. http://dx.doi.org/10.3390/cancers13102304.

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Despite stringent eligibility criteria for trial participation, early discontinuation often occurs in phase I trials. To better identify patients unlikely to benefit from phase I trials, we investigated predictors for early trial discontinuation. Data from 415 patients with solid tumors who participated in 66 trials were pooled for the current analysis. Early trial discontinuation was defined as (i) trial discontinuation within 28 days after start of treatment or (ii) discontinuation before administration of the first dosage in eligible patients. Multilevel logistic regression analyses were conducted to identify predictors for early trial discontinuation. Eighty-two participants (20%) demonstrated early trial discontinuation. Baseline sodium level below the lower limit of normal (OR = 2.95, 95%CI = 1.27–6.84), elevated alkaline phosphatase level > 2.5 times the upper limit of normal (OR = 2.72, 95%CI = 1.49–4.99), performance score ≥ 1 (OR = 2.07, 95%CI = 1.03–4.19) and opioid use (OR = 1.82, 95%CI = 1.07–3.08) were independent predictors for early trial discontinuation. Almost 50% of the patients with hyponatremia and all four patients in whom all four predictors were present together discontinued the trial early. Hyponatremia, elevated alkaline phosphatase level, performance score ≥ 1 and opioid use were identified as significant predictors for early trial discontinuation. Hyponatremia was the strongest predictor and deserves consideration for inclusion in eligibility criteria for future trials.

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21

French, Jacqueline A. "Response to Early AED Therapy and Its Prognostic Implications." Epilepsy Currents 2, no. 3 (May 2002): 69–71. http://dx.doi.org/10.1111/j.1535-7597.2002.00025.x.

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Determining the prognosis of patients when they first present with epilepsy is a difficult task. Several clinical studies have shed light on this very important topic. Potential predictors of the refractory state, including seizure etiology, duration of epilepsy before treatment, and epilepsy type, have not been successful indicators of long-term outcome. One predictor of the refractory state appears to be early response to AED therapy. Inadequate seizure control after initial treatment is a poor prognostic sign. Recent research into genetic causes of the refractory state has included investigation of the multiple drug resistance gene, and polymorphisms at drug targets. More work is needed to determine the causes and predictors of drug resistance.

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22

Abbas, Riwa A., Labib Ghulmiyyah, Elie Hobeika, Ihab M. Usta, Fadi Mirza, and Anwar H. Nassar. "Preeclampsia: A Review of Early Predictors." Maternal-Fetal Medicine 3, no. 3 (February 5, 2021): 197–202. http://dx.doi.org/10.1097/fm9.0000000000000088.

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23

Millichap, J. Gordon. "Early Predictors of HIE Adverse Outcome." Pediatric Neurology Briefs 14, no. 5 (May 1, 2000): 37. http://dx.doi.org/10.15844/pedneurbriefs-14-5-7.

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24

ShawkyElfarargy, Mohamed, Mohamed Adel Eltomey, and Neama Ali Soliman. "Early predictors of neonatal intraventricular hemorrhage." Electronic Physician 9, no. 8 (August 25, 2017): 4946–51. http://dx.doi.org/10.19082/4946.

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25

Roberts, Rosebud O., and Ronald C. Petersen. "Predictors of early-onset cognitive impairment." Brain 137, no. 5 (April 23, 2014): 1280–81. http://dx.doi.org/10.1093/brain/awu089.

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26

Stevanovic, Marko, Andrijana Cvetkovic, Ivana Stosovic-Kalezic, Zoran Bukumiric, Zoraida Milojkovic, Brankica Martinovic, Nikola Stevanovic, Dragoslav Lazic, Olivera Jovicic, and Mirjana Ivanovic. "Detection of early childhood caries predictors." Vojnosanitetski pregled, no. 00 (2019): 60. http://dx.doi.org/10.2298/vsp181121060s.

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27

Keeney, Benjamin J., Judith A. Turner, Deborah Fulton-Kehoe, Thomas M. Wickizer, Kwun Chuen Gary Chan, and Gary M. Franklin. "Early Predictors of Occupational Back Reinjury." Spine 38, no. 2 (January 2013): 178–87. http://dx.doi.org/10.1097/brs.0b013e318266187d.

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28

Urban, R. R., H. He, R. Alfonso, M. M. Hardesty, and B. A. Goff. "Ovarian cancer: Predictors of early death." Gynecologic Oncology 139, no. 1 (October 2015): 180. http://dx.doi.org/10.1016/j.ygyno.2015.07.025.

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29

BOSCHERT, SHERRY. "Two Predictors of Early Arthritis Identified." Internal Medicine News 42, no. 2 (January 2009): 11. http://dx.doi.org/10.1016/s1097-8690(09)70052-6.

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30

Micali, Nadia, Charlotte U. Rask, Else Marie Olsen, and Anne Mette Skovgaard. "Early Predictors of Childhood Restrictive Eating." Journal of Developmental & Behavioral Pediatrics 37, no. 4 (May 2016): 314–21. http://dx.doi.org/10.1097/dbp.0000000000000268.

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31

Leucht, S. "C.03.02 Early predictors–areviewofcurrent knowledge." European Neuropsychopharmacology 18 (August 2008): S590—S591. http://dx.doi.org/10.1016/s0924-977x(08)70906-4.

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32

Bryant, Richard A. "Early predictors of posttraumatic stress disorder." Biological Psychiatry 53, no. 9 (May 2003): 789–95. http://dx.doi.org/10.1016/s0006-3223(02)01895-4.

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33

Shaw, Daniel S., Luke W. Hyde, and Lauretta M. Brennan. "Early predictors of boys' antisocial trajectories." Development and Psychopathology 24, no. 3 (July 11, 2012): 871–88. http://dx.doi.org/10.1017/s0954579412000429.

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AbstractDespite the large number of studies tracing patterns of youth antisocial behavior (AB) during adolescence, few have prospective data on the developmental precursors of AB beginning during infancy. Using a cohort of 268 low-income boys first assessed at 18 months, the current study examined predictors of early- and late-starting trajectories of AB assessed during early childhood and early adolescence. Four trajectory groups were identified, including early- and late-starting groups, a low stable group, and a high decreasing group, characterized by multiple risk factors during early childhood and early adolescence. During early childhood, parenting and maternal depression discriminated two AB trajectory groups, an early-starting and a high decreasing group, who would go on to demonstrate a high preponderance of juvenile court involvement (60% to 79%) and elevated rates of clinical depression 13 to 15 years later. The results were discussed in reference to targeting malleable family risk factors during early childhood associated with patterns of AB and mental health disorders during adolescence.

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34

Ram, A., L. Kikinzon, F. Ladame, A. Braconnier, A. Weizman, and S. Tyano. "Early developmental predictors of adolescent psychopathology." European Psychiatry 13, S4 (1998): 208S. http://dx.doi.org/10.1016/s0924-9338(99)80275-2.

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35

Bryanton, Janet, Anita J. Gagnon, Marie Hatem, and Celeste Johnston. "Predictors of Early Parenting Self-efficacy." Nursing Research 57, no. 4 (July 2008): 252–59. http://dx.doi.org/10.1097/01.nnr.0000313490.56788.cd.

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36

Waterhouse, Elizabeth. "Predictors of Early Seizures after Stroke." Epilepsy Currents 2, no. 3 (May 2002): 75–76. http://dx.doi.org/10.1046/j.1535-7597.2002.t01-1-00028.x.

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37

Kagan, Jerome, and Marcel Zentner. "Early Childhood Predictors of Adult Psychopathology." Harvard Review of Psychiatry 3, no. 6 (January 1996): 341–50. http://dx.doi.org/10.3109/10673229609017202.

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38

Michels, Karin B. "Early Life Predictors of Chronic Disease." Journal of Women's Health 12, no. 2 (February 2003): 157–61. http://dx.doi.org/10.1089/154099903321576556.

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39

Dooley, David, and JoAnn Prause. "Predictors of Early Alcohol Drinking Onset." Journal of Child & Adolescent Substance Abuse 16, no. 2 (March 6, 2007): 1–29. http://dx.doi.org/10.1300/j029v16n02_01.

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40

Shorey, Shefaly, Lau Ying, and Piyanee Yobas. "Parenting Outcomes and Predictors of Parenting Satisfaction in the Early Postpartum Period." Western Journal of Nursing Research 43, no. 1 (January 2020): 13–24. http://dx.doi.org/10.1177/0193945920914593.

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This study examined the relationships among parenting self-efficacy (PSE), social support, postnatal depression (PND), and predictors of parenting satisfaction in the early postpartum period using a cross-sectional exploratory quantitative design. The hypothetical model was tested among interrelated concepts of outcome variables among 250 parents (125 couples). The structural equation model revealed an adequate fit between the hypothesized model and the data. PSE and spousal support were found to be predictors of parenting satisfaction. PSE was also found to be a predictor of social support. PND was not found to be a predictor of parenting satisfaction. None of the obstetric and demographic factors predicted parenting satisfaction. This is the first study that tested interrelations among crucial parenting outcome variables among fathers and mothers in the early postpartum period. It is important to assess interrelated parenting outcomes among both parents so that support can be provided to ultimately influence parenting satisfaction.

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41

Stabile, Giuseppe, Saverio Iacopino, Roberto Verlato, Giuseppe Arena, Paolo Pieragnoli, Giulio Molon, Massimiliano Manfrin, et al. "Predictive role of early recurrence of atrial fibrillation after cryoballoon ablation." EP Europace 22, no. 12 (October 2, 2020): 1798–804. http://dx.doi.org/10.1093/europace/euaa239.

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Abstract Aims The aims of this study were to determine the rate and the predictors of early recurrences of atrial fibrillation (ERAF) after cryoballoon (CB) ablation and to evaluate whether ERAF correlate with the long-term outcome. Methods and results Three thousand, six hundred, and eighty-one consecutive patients (59.9 ± 10.5 years, female 26.5%, and 74.3% paroxysmal AF) were included in the analysis. Atrial fibrillation recurrence, lasting at least 30 s, was collected during and after the 3-month blanking period. Three-hundred and sixteen patients (8.6%) (Group A) had ERAF during the blanking period, and 3365 patients (Group B) had no ERAF. Persistent AF and number of tested anti-arrhythmic drugs ≥2 resulted as significant predictors of ERAF. After a mean follow-up of 16.8 ± 16.4 months, 923/3681 (25%) patients had at least one AF recurrence. The observed freedom from AF recurrence, at 24-month follow-up from procedure, was 25.7% and 64.8% in Groups A and B, respectively (P < 0.001). ERAF, persistent AF, and number of tested anti-arrhythmic drugs ≥2 resulted as significant predictors of AF. In a propensity score matching, the logistic model showed that ERAF 1 month after ablation are the best predictor of long-term AF recurrence (P = 0.042). Conclusion In patients undergoing CB ablation for AF, ERAF are rare and are a strong predictor of AF recurrence in the follow-up, above all when occur >30 days after the ablation.

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42

Jin, Xuebo, Nianxiang Yang, Xiaoyi Wang, Yuting Bai, Tingli Su, and Jianlei Kong. "Integrated Predictor Based on Decomposition Mechanism for PM2.5 Long-Term Prediction." Applied Sciences 9, no. 21 (October 25, 2019): 4533. http://dx.doi.org/10.3390/app9214533.

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It is crucial to predict PM2.5 concentration for early warning regarding and the control of air pollution. However, accurate PM2.5 prediction has been challenging, especially in long-term prediction. PM2.5 monitoring data comprise a complex time series that contains multiple components with different characteristics; therefore, it is difficult to obtain an accurate prediction by a single model. In this study, an integrated predictor is proposed, in which the original data are decomposed into three components, that is, trend, period, and residual components, and then different sub-predictors including autoregressive integrated moving average (ARIMA) and two gated recurrent units are used to separately predict the different components. Finally, all the predictions from the sub-predictors are combined in fusion node to obtain the final prediction for the original data. The results of predicting the PM2.5 time series for Beijing, China showed that the proposed predictor can effectively improve prediction accuracy for long-term prediction.

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43

D’Amico, Anthony V., Richard Whittington, S. Bruce Malkowicz, Yue Hui Wu, Ming-Hui Chen, Mark Hurwitz, Philip W. Kantoff, et al. "Utilizing Predictions of Early Prostate-Specific Antigen Failure to Optimize Patient Selection for Adjuvant Systemic Therapy Trials." Journal of Clinical Oncology 18, no. 18 (September 18, 2000): 3240–46. http://dx.doi.org/10.1200/jco.2000.18.18.3240.

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PURPOSE: Prostate-specific antigen (PSA) failure within 2 years after radical prostatectomy (RP) has been shown to be a clinically significant predictor of distant failure. This study was performed to estimate 2-year PSA failure rates on the basis of readily available clinical and pathologic factors to identify patients for whom effective adjuvant systemic therapy is needed. PATIENTS AND METHODS: A Cox regression multivariable analysis was used to determine whether the percentage of positive prostate biopsies, PSA level, and the pathologic findings at RP in 1,728 men provided clinically relevant information about PSA outcome after RP. A bootstrapping technique with 2,000 replications was used to provide 95% confidence intervals for the predicted 2-year PSA failure rates, which were determined on the basis of the independent clinical and pathologic predictors of PSA outcome. RESULTS: The independent predictors of time to PSA failure included a percentage of positive prostate biopsies of greater than 34% (P ≤ .009), PSA level greater than 10 ng/mL (P ≤ .01), seminal vesicle invasion (P = .02), prostatectomy Gleason score of 8 to 10 (P = .04), and positive surgical margins (P = .0001). Predictions of 2-year PSA failure rates and bootstrap estimates of the 95% confidence intervals were arranged in a tabular format, stratified by independent clinical and pathologic predictors of PSA outcome. CONCLUSION: Patients who are most likely to benefit from effective adjuvant systemic therapy after RP can be identified using readily available clinical and pathologic data.

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44

SPARKS, RICHARD L., JON PATTON, LEONORE GANSCHOW, and NANCY HUMBACH. "Long-term relationships among early first language skills, second language aptitude, second language affect, and later second language proficiency." Applied Psycholinguistics 30, no. 4 (October 2009): 725–55. http://dx.doi.org/10.1017/s0142716409990099.

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ABSTRACTFifty-four students were followed over 10 years beginning in first grade to determine best predictors of oral and written second language (L2) proficiency. Predictor variables included measures of first language (L1) skill administered in first through fifth grades, L1 academic aptitude, L2 aptitude (Modern Language Aptitude Test), and L2 affect (motivation, anxiety). All participants completed 2 years of L2 study in high school. Findings revealed strong correlations between early L1 skills and later L2 proficiency, but the Modern Language Aptitude Test was the best predictor of overall L2 proficiency and most L2 proficiency subtests. However, L1 word decoding was the best predictor of L2 word decoding skills. Early L1 skills, L2 motivation, or L2 anxiety added a small amount of variance to the prediction models. Findings suggested that language-related variables are the most robust predictors of L2 proficiency. Results are discussed in the context of long-term cross linguistic transfer of early L1 skills to later L2 aptitude and L2 proficiency.

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45

Kjønås, Didrik, Gry Dahle, Henrik Schirmer, Siri Malm, Jo Eidet, Lars Aaberge, Terje Steigen, Svend Aakhus, Rolf Busund, and Assami Rösner. "Predictors of early mortality after transcatheter aortic valve implantation." Open Heart 6, no. 1 (April 2019): e000936. http://dx.doi.org/10.1136/openhrt-2018-000936.

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ObjectivesTo investigate whether preoperative echocardiographic evaluation of ventricular function, especially right ventricular systolic and diastolic parameters including speckle-tracking analysis, could aid in the prediction of 30-day mortality after transcatheter aortic valve implantation (TAVI) in patients with aortic stenosis.MethodsThis is a prospective observational cohort study including 227 patients accepted for TAVI at the University Hospital of North Norway and Oslo University Hospital from February 2010 through June 2013. All patients underwent preoperative transthoracic echocardiography with retrospective speckle-tracking analysis. Primary endpoint was all-cause 30-day mortality.ResultsAll-cause 30-day mortality was 8.7 % (n = 19). Independent predictors of 30-day mortality were systolic pulmonary arterial pressure (SPAP) > 60 mm Hg (HR: 7.7, 95% CI: 1.90 to 31.3), heart failure (HR: 2.9, 95% CI: 1.1 to 7.78), transapical access (HR: 3.8, 95% CI: 1.3 to 11.2), peripheral artery disease (HR: 6.0, 95% CI: 2.0 to 18.0) and body mass index (HR: 0.73, 95% CI: 0.61 to 0.87). C-statistic for the model generated was 0.91 (95% CI: 0.85 to 0.98). Besides elevated SPAP, no other echocardiographic measurements were found to be an independent predictor of early mortality.ConclusionExcept for elevated systolic pulmonary artery pressure, our data suggests that clinical rather than echocardiographic parameters are useful predictors of 30-day mortality after TAVI.

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González-Blanch, C., B. Crespo-Facorro, M. Álvarez-Jiménez, J. M. Rodríguez-Sánchez, J. M. Pelayo-Terán, R. Pérez-Iglesias, and J. L. Vázquez-Barquero. "Pretreatment predictors of cognitive deficits in early psychosis." Psychological Medicine 38, no. 5 (October 9, 2007): 737–46. http://dx.doi.org/10.1017/s0033291707001705.

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BackgroundPredicting cognitive deficits in early psychosis may well be crucial to identify those individuals most in need of receiving intensive intervention. As yet, however, the identification of potential pretreatment predictors for cognitive performance has been hampered by inconsistent findings across studies. We aimed to examine the associations of functional and clinical pretreatment variables with cognitive functioning after a first psychotic episode.MethodOne hundred and thirty-one patients experiencing first-episode psychosis were assessed for psychopathology, pre-morbid functioning, duration of illness, age of onset, and family history of psychosis and neurocognitive functioning. Multiple regression analyses were conducted for six basic cognitive dimensions known to be affected in this population: verbal learning, verbal memory, verbal comprehensive abilities, executive functioning, motor dexterity and sustained attention.ResultsPre-morbid functioning was the main predictor for five out of the six basic cognitive domains. Pre-morbid social adjustment difficulties were associated with worse performance in executive functioning, motor dexterity and sustained attention. Academic functioning was associated with verbal comprehension, and verbal learning and memory. Gender, age of onset, duration of untreated psychosis, and family history of psychosis had no or limited value as predictors of neurocognitive outcome.ConclusionsPoor pre-morbid functioning was related to a worse performance in the six basic cognitive dimensions evaluated; however, this accounted for only a small amount of the explained variance. Cognitive impairment is a prominent feature in patients with early psychosis regardless of favorable prognostic features such as short duration of illness, female gender, later age of onset, and non-family history of psychosis.

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Wong, W. N., Antonio C. H. Sek, Rick F. L. Lau, K. M. Li, Joe K. S. Leung, M. L. Tse, Andy H. W. Ng, and Robert J. Stenstrom. "Early clinical predictors of severe acute respiratory syndrome in the emergency department." CJEM 6, no. 01 (January 2004): 12–21. http://dx.doi.org/10.1017/s148180350000885x.

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ABSTRACT Objectives: To assess the association of diagnostic predictors available in the emergency department (ED) with the outcome diagnosis of severe acute respiratory syndrome (SARS). Methods: This retrospective cohort study describes all patients from the Amoy Garden complex who presented to an ED SARS screening clinic during a 2-month outbreak. Clinical and diagnostic predictors were recorded, along with ED diagnoses. Final diagnoses were established independently based on diagnostic tests performed after the ED visit. Associations of key predictors with the final diagnosis of SARS were described. Results: Of 821 patients, 205 had confirmed SARS, 35 undetermined SARS and 581 non-SARS. Multivariable logistic regression showed that the strongest predictors of SARS were abnormal chest x-ray (odds ratio [OR] = 17.4), subjective fever (OR = 9.7), temperature >38°C (OR = 6.4), myalgias (OR = 5.5), chills and rigors (OR = 4.0) and contact exposure (OR = 2.6). In a subset of 176 patients who had a complete blood cell count performed, the strongest predictors were temperature ≥38ºC (OR = 15.5), lymphocyte count <1000 (OR = 9.3) and abnormal chest x-ray (OR = 5.7). Diarrhea was a powerful negative predictor (OR = 0.03) of SARS. Conclusions: Two components of the World Health Organization case definition — fever and contact exposure — are helpful for ED decision-making, but respiratory symptoms do not discriminate well between SARS and non-SARS. Emergency physicians should consider the presence of diarrhea, chest x-ray findings, the absolute lymphocyte count and the platelet count as significant modifiers of disease likelihood. Prospective validation of these findings in other clinical settings is desirable.

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Erkinovna, Makhmudova Sevara, and Negmadjanov Baxodur Boltaevich. "PLGF/ SFLT-1 Concentrations As Early Predictors Preeclampsia In Pregnancy During Pandemic Covid-19." American Journal of Medical Sciences and Pharmaceutical Research 02, no. 08 (August 30, 2020): 146–51. http://dx.doi.org/10.37547/tajmspr/volume02issue08-22.

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Chand, Savin S., Kevin J. E. Walsh, and Johnny C. L. Chan. "A Bayesian Regression Approach to Seasonal Prediction of Tropical Cyclones Affecting the Fiji Region." Journal of Climate 23, no. 13 (July 1, 2010): 3425–45. http://dx.doi.org/10.1175/2010jcli3521.1.

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Abstract This study presents seasonal prediction schemes for tropical cyclones (TCs) affecting the Fiji, Samoa, and Tonga (FST) region. Two separate Bayesian regression models are developed: (i) for cyclones forming within the FST region (FORM) and (ii) for cyclones entering the FST region (ENT). Predictors examined include various El Niño–Southern Oscillation (ENSO) indices and large-scale environmental parameters. Only those predictors that showed significant correlations with FORM and ENT are retained. Significant preseason correlations are found as early as May–July (approximately three months in advance). Therefore, May–July predictors are used to make initial predictions, and updated predictions are issued later using October–December early-cyclone-season predictors. A number of predictor combinations are evaluated through a cross-validation technique. Results suggest that a model based on relative vorticity and the Niño-4 index is optimal to predict the annual number of TCs associated with FORM, as it has the smallest RMSE associated with its hindcasts (RMSE = 1.63). Similarly, the all-parameter-combined model, which includes the Niño-4 index and some large-scale environmental fields over the East China Sea, appears appropriate to predict the annual number of TCs associated with ENT (RMSE = 0.98). While the all-parameter-combined ENT model appears to have good skill over all years, the May–July prediction of the annual number of TCs associated with FORM has two limitations. First, it underestimates (overestimates) the formation for years where the onset of El Niño (La Niña) events is after the May–July preseason or where a previous La Niña (El Niño) event continued through May–July during its decay phase. Second, its performance in neutral conditions is quite variable. Overall, no significant skill can be achieved for neutral conditions even after an October–December update. This is contrary to the performance during El Niño or La Niña events, where model performance is improved substantially after an October–December early-cyclone-season update.

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Cholack, George, Joshua Garfein, Rachel Krallman, Delaney Feldeisen, Daniel Montgomery, Eva Kline-Rogers, Geoffrey D. Barnes, Kim Eagle, Melvyn Rubenfire, and Sherry Bumpus. "Predictors of Early (0-7 Days) and Late (8-30 Days) Readmission in a Cohort of Acute Coronary Syndrome Patients." International Journal of Medical Students 10, no. 1 (April 1, 2022): 38–48. http://dx.doi.org/10.5195/ijms.2022.1058.

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Background: Readmissions following acute coronary syndrome are unevenly distributed across the 30-day post-discharge period. There is limited data on predictors of all-cause readmission in early (0-7 day) and late (8-30 day) post-discharge periods for this population; the purpose of this retrospective cohort study was to identify predictors of early and late readmission. Methods: Patients at Michigan Medicine (Ann Arbor, Michigan, United States) with a principal discharge diagnosis of unstable angina, ST-segment elevation myocardial infarction, or non-ST segment elevation myocardial infarction between April 2008 and November 2017 were identified. Predictors of early and late readmission were analyzed with multivariable logistic regression models. Results: Of 1120 patients hospitalized following acute coronary syndrome, 198 (17.68%) were readmitted within 30 days while 70 (6.25%) were readmitted within 7 days of discharge. Of 30-day readmissions, early readmissions were more likely in females [OR 2.26, 95% confidence interval (CI) 1.23, 4.16], non-white individuals (p=0.05), or patients requiring intensive care unit admission during hospitalization (OR 2.20, 95% CI 1.14, 4.24). Relative to patients not readmitted within 7 days, patients who were female, had history of atrial fibrillation, principal discharge diagnosis of non-ST segment elevation myocardial infarction, or required intensive care unit admission were more likely readmitted early. History of congestive heart failure was a predictor of late readmission when compared to patients not readmitted in 30 days. Conclusion: Following acute coronary syndrome, predictors of readmission varied between early and late readmission groups. Readmission predictors provides healthcare providers with information useful in minimizing readmissions and concomitant financial penalties.

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