Gęstość mineralna kości u dorosłych chorych na talasemię major: własne doświadczenia i krótki przegląd piśmiennictwa

Introduction: Metabolic bone disease represents a major cause of morbidity in patients with thalassaemia major. The aim of our study was to assess the prevalence and underlying contributory factors of osteopenia/osteoporosis in a randomly selected population of adult patients with thalassaemia major. Patients and methods: The study population was selected using the random sampling method from the patients’ database of our thalassaemia clinic. Only transfusion-dependent beta-thalassaemia patients aged over 17 and with no history of treatment with bisphosphonates were included. BMD of lumbar spine and right femoral neck were measured by means of the calibrated dual energy X-ray absorption method. Independent factors likely to be associated with low bone mass were determined and included in the analysis to ascertain possible associations. Results: Our study included 40 patients (19 female and 21 male; mean age: 23.0 ± 4.1). The mean Z score of the right femoral neck was –1.2 (95% CI: –0.9 to –1.5) and for lumbar spine was –2.1 (95% CI: –1.7 to –2.5). The prevalences of osteopenia and osteoporosis involving the right femoral neck were 37.5%, and 12.5%, respectively. The respective prevalence rates for lumbar spine were 47.5% and 37.5%. Our study showed patient’s weight, age, duration of the disease and history of hypogonadism or concurrent hypothyroidism are significant contributory factors or predictors of bone mineral loss. Conclusions: Regarding the high prevalence of osteopenia/osteoporosis in patients with thalassaemia major, all patients should be screened periodically for bone disease. The uncertainty and disagreements as to the possible role of different factors indicate the necessity for further studies in order to recognise the pathophysiologic fundamentals of this serious complication of thalassaemia major.Wstęp: Zaburzenia metabolizmu tkanki kostnej są główna przyczyną chorobowości u pacjentów z talasemią major. Celem niniejszego badania była ocena częstości osteopenii/osteoporozy i określenie czynników przyczyniających się do ich rozwoju w losowo wybranej grupie chorych na talasemię major. Pacjenci i metody: Uczestników badania wybrano losowo z bazy danych pacjentów poradni leczenia talasemii. Do analizy włączono jedynie chorych w wieku powyżej 17 lat z transfuzjozależną talasemią beta, nieleczonych wcześniej bisfosfonianami. Metodą absorpcjometrii podwójnej wiązki promieniowania rentgenowskiego zmierzono BMD odcinka lędźwiowego kręgosłupa i szyjki prawej kości biodrowej. Określono niezależne czynniki, które mogły wpływać na niską masę kostną i uwzględniono je w analizie, aby wykryć wszelkie możliwe związki. Wyniki: Do badania włączono 40 chorych (19 kobiet i 21 mężczyzn, średnia wieku 23,0 ± 4,1 roku). Średnie wartości Z score wynosiły –1,2 (95% CI: od –0,9 do –1,5) dla szyjki prawej kości biodrowej i –2,1 (95% CI: od –1,7 do –2,5) dla kręgosłupa lędźwiowego. Częstość osteopenii i osteoporozy, oceniana na podstawie gęstości mineralnej szyjki prawej kości udowej, wynosiła odpowiednio 37,5%, i 12,5%. W badaniu wykazano, że masa ciała, wiek, czas trwania choroby i hipogonadyzm w wywiadzie lub współistniejąca niedoczynność tarczycy są istotnymi czynnikami ryzyka lub predyktorami utraty minerału kostnego. Wnioski: W związku z częstym występowaniem osteopenii/osteoporozy u wszystkich chorych na talasemię major należy okresowo przeprowadzać badania w kierunku chorób kości. Wątpliwości i rozbieżne opinie na temat potencjalnej roli różnych czynników w rozwoju tych poważnych powikłań talasemii major wskazują na konieczność prowadzenia dalszych badań w celu poznania ich patofizjologii

Spinal Fluid Lactate Dehydrogenase Level Differentiates between Structural and Metabolic Etiologies of Altered Mental Status in Children

How to Cite This Article: Khosroshahi N, Alizadeh P, Khosravi M, Salamati P, Kamrani K. Spinal Fluid Lactate Dehydrogenase Level Differentiates between Structural and Metabolic Etiologies of Altered Mental Status in Children. Iran J Child Neurol. 2015 Winter;9(1):31-36.AbstractObjectiveAltered mental status is a common cause of intensive care unit admission inchildren. Differentiating structural causes of altered mental status from metabolic etiologies is of utmost importance in diagnostic approach and management of the patients. Among many biomarkers proposed to help stratifying patients with altered mental status, spinal fluid lactate dehydrogenase appears to be the most promising biomarker to predict cellular necrosis.Materials & MethodsIn this cross sectional study we measured spinal fluid level of lactatedehydrogenase in children 2 months to 12 years of age admitted to a single center intensive care unit over one year. Spinal fluid level of lactate dehydrogenase in 40 pediatric cases of febrile seizure was also determined as the control group.ResultsThe study group included 35 boys (58.3%) and 25 girls (41.7%). Their meanage was 2.7+/-3 years and their mean spinal fluid lactate dehydrogenase levelwas 613.8+/-190.4 units/liter. The control group included 24 boys (55.8%) and19 girls (44.2%). Their mean age was 1.3+/-1.2 years and their mean spinalfluid lactate dehydrogenase level was 18.9+/-7.5 units/liter. The mean spinalfluid lactate dehydrogenase level in children with abnormal head CT scan was246.3+/-351.5 units/liter compared to 164.5+/-705.7 in those with normal CTscan of the head (p=0.001).ConclusionSpinal fluid lactate dehydrogenase level is useful in differentiating structural andmetabolic causes of altered mental status in children. ReferencesFesk SK. Coma and confusional states: emergency diagnosis and management. Neurol Clin 1998; 16: 237- 56.Cucchiara BL, Kanser SE, Wolk DA, et al. 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Indian Journal of Medical Sciences 1999; 53 (1): 1-6.Pollak AN, Gupton CL. Emergency Care and Transportation of the Sick and Injured. Boston: Jones and Bartlett 2002: pp. 140. ISBN 0-7637-1666-9.Nayak BS, Bhat R. Cerebrospinal fluid lactate dehydrogenase and glutamine in meningitis. Indian J Physiol Pharmacol. 2005 Jan; 49(1):108-10.A Twijnstra, A P van Zanten, A A Hart, et al. al. Serial lumbar and ventricle cerebrospinal fluid lactate dehydrogenase activities in patients with leptomeningeal metastases from solid and haematological tumours. J Neurol Neurosurg Psychiatry 1987 50: 313-320.Nussinovitch M, Finkelstein Y, Politi K, Harel D, Klinger G, Razon Y, Nussinovitch U, Nussinovitch N. Cerebrospinal fluid lactate dehydrogenase isoenzymes in children with bacterial and aseptic meningitis. Translational Research 2009. 154 (4): 214-218.Feldman William E. Cerebrospinal Fluid Lactic Acid Dehydrogenase Activity. Levels in Untreated and Partially Antibiotic-Treated Meningitis. Am J Dis Child. 1975; 129(1): 77-80.Lutsar I, Haldre S, Topman M, Talvik T. Enzymatic changes in the cerebrospinal fluid in patients with infections ofthe central nervous system. Acta Paediatr 1994; 83(11):1146-1150.Kepa L, Oczko-Grzesik B, Błedowski D. Evaluation of cerebrospinal fluid and plasma lactate dehydrogenase activity in patients with purulent, bacterial meningoencephalitis. Przegl Epidemiol. 2006; 60(2):291-8.Ruzak-Skocir B, Trbojevic-Cepe M. Study of serum and cerebrospinal fluid enzymes in diagnosis and differential diagnosis of cerebrovascular diseases. Neurologija. 1990; 39(4):239-50.Nand N, Sharma M, Saini DS. Evaluation of lactic dehydrogenase in cases of meningitis. Indian J Med Sci. 1993; 47(4): 96-100.Neches William, Platt Martin. Cerebrospinal Fluid LDH in 287 Children, Including 53 Cases of Meningitis of Bacterial and non-Bacterial Etiology. Pediatrics 1968; 41:1097-1103.Engelke S; Bridgers S, Saldanha R, Trought W. Cerebrospinal Fluid Lactate Dehydrogenase in Neonatal Intracranial Hemorrhage. American Journal of the Medical Sciences 1986; 291 (6): 391-395.Parakh N, Gupta HL, Jain A. Evaluation of enzymes in serum and cerebrospinal fluid in cases of stroke. Neurology India 2002; 50 (4): 518-9.Lampl Y, Paniri Y, Eshel Y, Sarova-Pinhas I. Cerebrospinal fluid lactate dehydrogenase levels in early stroke and transient ischemic attacks. Stroke 1990; 21: 854-857.Hall Robert T., Kulkarni Prakash B., Sheehan Michael B., Rhodes Philip G. Cerebrospinal Fluid Lactate Dehydrogenase in Infants with Perinatal Asphyxia. Developmental Medicine & Child Neurology 1980. 22 (3): 300-307.Nussinovitch M, Volovitz B, Finkelstein Y, Amir J, Harel D. Lactic dehydrogenase isoenzymes in cerebrospinal fluid associated with hydrocephalus. Acta Paediatr 2001; 90: 972-974

Determining a National Trauma Prognostic Scale (TPS) to Predict Preventable Trauma Death in Iran: the Research Protocol

Methods: A 7-phases methodology will be applied to conduct this study as following; 1- Identification of trauma severity parameters and scales predicting mortality from literature, 2- Developing a data collection tool for research data collection), 3- Data collection in selected clinical settings, 4- Statistical modeling, 5- Model adaptation with three levels of trauma care settings including pre-hospitals, general hospitals and trauma specialty hospitals, 6- Scale-up and extrapolation, and 7- comparison with international models and selection of Iranian national model. Results: The content validity of the tool was confirmed with a total scale-level content validity (S-CVI) = 0.93. The reliability of the final instrument was calculated using the Pearson correlation coefficient and the Spearman correlation was evaluated above 0.7 for all cases. Up to date April 2020, From the hospital of the study, 210 patients participated in the study. The mean and standard age deviation of patients was 35.18 ± 18.44 and 165 (78.57 %) of these patients were male. The most important cause of trauma in patients was a motorcycle accident (27.62 %). Keywords: Trauma, Modeling, Injury severity assessment, Mortality predictor, Trauma scal

Determining a National Trauma Prognostic Scale (TPS) to Predict Preventable Trauma Death in Iran: the Research Protocol

Methods: A 7-phases methodology will be applied to conduct this study as following; 1- Identification of trauma severity parameters and scales predicting mortality from literature, 2- Developing a data collection tool for research data collection), 3- Data collection in selected clinical settings, 4- Statistical modeling, 5- Model adaptation with three levels of trauma care settings including pre-hospitals, general hospitals and trauma specialty hospitals, 6- Scale-up and extrapolation, and 7- comparison with international models and selection of Iranian national model. Results: The content validity of the tool was confirmed with a total scale-level content validity (S-CVI) = 0.93. The reliability of the final instrument was calculated using the Pearson correlation coefficient and the Spearman correlation was evaluated above 0.7 for all cases. Up to date April 2020, From the hospital of the study, 210 patients participated in the study. The mean and standard age deviation of patients was 35.18 ± 18.44 and 165 (78.57 %) of these patients were male. The most important cause of trauma in patients was a motorcycle accident (27.62 %). Keywords: Trauma, Modeling, Injury severity assessment, Mortality predictor, Trauma scal

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Lifelong learning; why do we need it?

AbstractOur world is changing around us in such a frantic pace that if we do not continue to grow and develop; we will soon be left behind. In the 21st century, we all need to be lifelong learners. We need to continually keep our skills sharp and up to date so that we have an edge in all we do. Of course, we all have a natural desire to learn for adapting to change, enriching and fulfilling our lives. This review article is an attempt to present the main advantages which follow lifelong learning

Is Ceftizoxime an Appropriate Surrogate for Amikacin in Neonatal Sepsis Treatment? A Randomized Clinical Trial

Neonatal sepsis, a life-threatening condition, presents with non-specific clinical manifestations and needs immediate empirical antimicrobial therapy. Choosing an appropriate antibiotic regimen covering the most probable pathogens is an important issue. In this study we compared the effectiveness of ceftizoxime and amikacin in the treatment of neonatal sepsis both in combination with ampicillin. In a randomized clinical trial, all term neonates with suspected sepsis referred to Bahrami hospital during March 2008 to March 2010 were evaluated. Patients were randomly recruited into two groups; one group receiving ampicillin and amikacin and the other ampicillin and ceftizoxime. Blood, urine and cerebrospinal fluid cultures, leukocyte count and C-reactive protein level were measured in all neonates. A total of 135 neonates were evaluated, 65 in amikacin group and 70 in ceftizoxime group. 60 neonates (85.7%) in ceftizoxime group and 54 neonates (83.1%) in amikacin group responded to the treatment (P= 0.673 and χ2 = 0.178). Only 24 (18%) blood samples had a report of positive blood culture. The most frequent pathogen was coagulase negative staphylococcus with the frequency of 58.32% of all positive blood samples. Ceftizoxime in combination with ampicillin is an appropriate antimicrobial regimen for surrogating the combination of ampicillin and amikacin to prevent bacterial resistance against them

Leukocyte Count and Erythrocyte Sedimentation Rate as Diagnostic Factors in Febrile Convulsion

"nFebrile convulsion (FC) is the most common seizure disorder in childhood. white blood cell (WBC) and erythrocyte sedimentation rate (ESR) are commonly measured in FC. Trauma, vomiting and bleeding can also lead to WBC and ESR so the blood tests must carefully be interpreted by the clinician. In this cross sectional study 410 children(163 with FC), aged 6 months to 5 years, admitted to Bahrami Children hospital in the first 48 hours of their febrile disease, either with or without seizure, were evaluated over an 18 months period. Age, sex, temperature; history of vomiting, bleeding or trauma; WBC, ESR and hemoglobin were recorded in all children. There was a significant increase of WBC (P<0.001) in children with FC so we can deduct that leukocytosis encountered in children with FC can be due to convulsion in itself. There was no significant difference regarding ESR (P=0.113) between the two groups. In fact, elevated ESR is a result of underlying pathology. In stable patients who don't have any indication of lumbar puncture, there's no need to assess WBC and ESR as an indicator of underlying infection. If the patient is transferred to pediatric ward and still there's no reason to suspect a bacterial infection, there is no need for WBC test

Adverse Drug Reactions; As a Cause for Admissions to a Childrenerved 12.6

Objective: The aim of this study was to investigate the adverse drug reactions (ADR) in pediatrics and determine the predominant symptoms of adverse drug reactions in children. Material & Methods: This case series study was carried out at the Bahrami Pediatric Hospital, Tehran where the files of 25 admitted patients with the diagnosis of adverse drug reaction 1998 to 2005 were studied. Findings: The average age was 4.6 (±3.7) years and symptoms of adverse drug reactions were observed 12.6 (±14.3) days after initiation of the drug intake. Skin rash was seen in all patients more in form of maculopapular rash followed by urticaria. Arthralgia was the next common symptom observed in 44% of patients. The common abnormal laboratory data was high erythrocyte sedimentation rate which was seen in 40% of patients. The most common ingested drugs were phenothiazine and sulfasalazine (each of them seen in 28% of patients) followed by penicillin (16%), furazolidone (16%), cephalosporins (4%) and valproic acid (4%). In 28% of patients poly-pharmacy was responsible for ADR.Conclusion: Awareness of the problem, observation of poly-pharmacy and potential drug-drug interactions, and continuous re-evaluation of the ongoing individual pharmacotherapy is important, especially in children, to reduce ADRs

Predictive power of Pediatric Trauma Score (PTS) in predicting of child’s mortality : Predictive power of Pediatric Trauma Score (PTS)

Introduction: Trauma is a serious global health issue, and children are among the world's most vulnerable victims. Pediatric Trauma Score (PTS) is a rating for the prediction of death in pediatric with trauma .This study aimed to evaluate the predictive power of PTS in predicting death in children with trauma. Methods: This prospective study was part of a national study to develop a primary model for estimating mortality by adjusting the severity of injury in Iran. Which was performed on 92 pediatric trauma participants. To predict the predictive power of PTS, the Area under the Curve (AUC), 95 % confidence interval (95 % CI), sensitivity, specificity, coefficient of determination and, odds ratio were utilized. All tests were carried out with a significance level of 0.05. Results: The mean age of patients participating in this study was 11.86 ± 4.94 years and 68 (73.91%) of them were male. The most common injury type was head and face (53.26%) trauma and the most common cause of trauma was motorcycle accidents (27.17%), respectively. The AUC value for PTS score was 0.911 and its coefficient of determination (R2) was 38%. Conclusion: PTS is a good score for predicting trauma death in children in Iran. PTS can be used especially for triage of children with trauma in hospitals