Vitamin C, vitamin B12, folate and the risk of osteoporotic fractures. A case-control study.

Water-soluble vitamins influence the development of an adequate structure of bone tissue, but there is scant information relating them with osteoporotic fractures. We analyze whether serum vitamin C, vitamin B12, and erythrocyte folate, or dietary intake of vitamin C and folate, are related with osteoporotic fractures in the elderly. A hospital-based case-control study was carried out at the Hospital of Jaén (167 cases, 167 controls), Spain. Cases were defined as patients aged 65 or more years with a low-energy fracture. Controls were people without fracture, matched for age and sex with cases. Diet was assessed by a semi-quantitative food frequency questionnaire. Serum vitamin C was measured using high-performance liquid chromatography (HPLC). Folic acid and vitamin B12 were measured using procedures of competitive or immunometric immunoassay. Multivariable analyses were also fitted to adjust for confounding using analysis of covariance (for the comparison of adjusted means) and conditional logistic regression (for estimating adjusted odds ratios). A statistically significant difference between cases and controls for vitamin C blood levels was found, being higher for controls (p = 0.01). Analysis of the association between serum vitamin C and fracture risk showed a linear trend (p = 0.03) with a significantly reduced risk for the upper quartile (OR = 0.31; 95% CI 0.11-0.87). The intake of vitamin C, folic acid, and B12 was not related to fracture risk, nor was there any association with erythrocyte folate or serum vitamin B12. In conclusion, serum vitamin C levels were lower in cases with osteoporotic fractures than in controls.

[Contributions of systematic review and meta-analysis to public health]. / Aportaciones de la revisión sistemática y del metaanálisis a la salud pública.

Meta-analysis has several precedents; even in Confucius (VI BC) one can find a sentence about the synthesis of knowledge. Meta-analysis is a consequence of the paradigm of induction. Within this paradigm of research, meta-analysis gives an analysis of the principle of consistency of a causal association (2nd principle of Hill). It has promoted the development of evaluation questionnaires and protocols for different designs, mainly clinical trials. It favoured the movement of evidence-based medicine, which is behind the creation of agencies for the evaluation of health technologies, and the recognition of public health professionals dedicated to research methods (mainly epidemiologists). The contributions of meta-analysis to public health are not distinguishable from others made to other specialties, although in the field of research methods it has contributed to the study of publication bias and to the search of determinants of heterogeneity, the lack of consistency among the individual studies.

Consideraciones prácticas acerca de la detección del sesgo de publicación / Practical considerations on detection of publication bias

En la presente revisión se intenta dar respuesta a 3 preguntas en el ámbito del metaanálisis: ¿es necesario valorar el sesgo de publicación?, ¿qué procedimientos sencillos se pueden aplicar? y ¿qué otros aspectos hay que tener en cuenta en su interpretación? La primera cuestión es fácil de responder. El sesgo de publicación es una amenaza potencial para la validez de las conclusiones de un metaanálisis y, por ello, las declaraciones MOOSE y QUOROM recomiendan que se valore. A pesar de ello, con frecuencia se omite (p. ej., en metaanálisis realizados por la colaboración Cochrane), quizá debido a que realizan una estrategia de búsqueda exhaustiva. Los procedimientos más utilizados para la valoración del sesgo de publicación son los gráficos en embudo o «árboles de navidad », el «trim and fill» («podar y completar», que permite estimar la repercusión del sesgo) y los métodos de regresión sobre gráficos, como el de Egger y la regresión lineal en el gráfico en embudo. Estos métodos tienen la ventaja de que se pueden estimar tan sólo con los datos publicados, pero con frecuencia la concordancia entre ellos es baja. Por esto se recomienda aplicar más de un procedimiento para su detección. En la interpretación de los resultados de un test de detección del sesgo de publicación debe tenerse en cuenta el número de estudios (son procedimientos que funcionan mal con menos de 10 estudios, y la mayoría de metaanálisis en la actualidad combinan un número inferior de estudios) y la presencia de heterogeneidad en el metaanálisis (AU)

The present review aims to answer 3 questions: does publication bias need to be assessed in meta-analyses?; what procedures, not requiring complex statistical approaches, can be applied to detect it?; and should other factors be taken into account when interpreting the procedures? The first question is easy to answer. Publication bias is a potential threat to the validity of the conclusions of meta-analyses. Therefore, both the MOOSE and QUOROM statements include publication bias in their guidelines; nevertheless, many meta-analyses do not use these statements (e.g., meta-analyses conducted by the Cochrane Collaboration), perhaps because they use a comprehensive search strategy. There are many methods to assess publication bias. The most frequently used are funnel plots or «Christmas trees», «trim and fill» (which allow the effects of bias to be estimated), and methods based upon regression on plots, such as Egger's method and funnel plot regression. An advantage of these methods is that they can only be applied using published data. However, agreement between these methods in detecting bias is often poor. Therefore, application of more than one method to detect publication bias is recommended. To correctly interpret the results, the number of pooled studies should be more than 10 and the existence of heterogeneity in the pooled estimate must be taken into account (AU)

Aportaciones de la revisión sistemática y del metaanálisis a la salud pública / Contributions of systematic review and meta-analysis to public health

El metaanálisis tiene precedentes, incluso en Confucio (siglo VIAC) se puede apreciar una frase relativa a la síntesis del conocimiento.El metaanálisis es fruto del paradigma inductista de investigaciónque nos gobierna. Dentro de él nos ofrece un análisis del principio deconsistencia para una asociación causal (2º principio de Hill). Hamotivado el desarrollo de cuestionarios y protocolos de evaluaciónde diferentes tipos de diseños, principalmente de ensayos clínicos.Todo esto fue uno de los detonantes de lo que se ha dado en llamarmedicina basada en la «evidencia» (mejor «pruebas» en castellano).Ha impulsado la creación de agencias de evaluación de tecnologíassanitarias y favorecido el reconocimiento de los profesionales desalud pública más conocedores del método de investigación. Suscontribuciones a la salud pública no se pueden separar de las realizadasen otras especialidades, pero en el campo de la metodología deinvestigación ha contribuido de manera decisiva al estudio del sesgode publicación y la búsqueda de variables que influyen en la heterogeneidad,la existencia de discrepancia entre los estudios individuales

Meta-analysis has several precedents; even in Confucius (VIBC) one can found a sentence about the synthesis of knowledge.Meta-analysis is a consequence of the paradigm of induction.Within this paradigm of research, meta-analysis gives an analysisof the principle of consistency of a causal association (2nd principleof Hill). It has promoted the development of evaluation questionnairesand protocols for different designs, mainly clinical trials. Itfavoured the movement of evidence-based medicine, which isbehind the creation of agencies for the evaluation of health technologies,and the recognition of public health professionals dedicatedto research methods (mainly epidemiologists). The contributions ofmeta-analysis to public health are not distinguishable from othersmade to other specialties, although in the field of research methodsit has contributed to the study of publication bias and to the searchof determinants of heterogeneity, the lack of consistency among theindividual studies

[Practical considerations on detection of publication bias]. / Consideraciones prácticas acerca de la detección del sesgo de publicación.

The present review aims to answer 3 questions: does publication bias need to be assessed in meta-analyses?; what procedures, not requiring complex statistical approaches, can be applied to detect it?; and should other factors be taken into account when interpreting the procedures? The first question is easy to answer. Publication bias is a potential threat to the validity of the conclusions of meta-analyses. Therefore, both the MOOSE and QUOROM statements include publication bias in their guidelines; nevertheless, many meta-analyses do not use these statements (e.g., meta-analyses conducted by the Cochrane Collaboration), perhaps because they use a comprehensive search strategy. There are many methods to assess publication bias. The most frequently used are funnel plots or <>, <> (which allow the effects of bias to be estimated), and methods based upon regression on plots, such as Egger's method and funnel plot regression. An advantage of these methods is that they can only be applied using published data. However, agreement between these methods in detecting bias is often poor. Therefore, application of more than one method to detect publication bias is recommended. To correctly interpret the results, the number of pooled studies should be more than 10 and the existence of heterogeneity in the pooled estimate must be taken into account.

Alcohol drinking as a predictor of intensive care and hospital mortality in general surgery: a prospective study.

AIMS: To analyse whether alcohol drinking increases admission to intensive care and in-hospital mortality in general surgery. DESIGN AND PARTICIPANTS: A prospective cohort study on a consecutive series of 1505 hospitalized patients in a Service of General Surgery of a tertiary hospital. MEASUREMENTS: Drinking pattern was defined by quantity, frequency and volume of drinking. Information on relevant confounders was obtained: smoking, body mass index, nutritional status (measured by serum albumin), cholesterol and its fractions, severity of the underlying disease and all therapeutic measures. Multivariate logistic regression was applied to assess the relationship between drinking and both admission to intensive care and in-hospital death. RESULTS: Twenty-nine (1.9%) patients died and 33 (2.1%) were admitted to the intensive care unit (ICU). Drinking was heavier in men, patients without antecedents of cancer, with lower preoperative risk assessment scores, number of co-morbidities and age and higher serum albumin levels. After adjusting for age, severity of underlying disease, smoking and serum albumin, male drinkers of 72+ g/day had an increased risk of being admitted to ICU, the effect being stronger for week-day drinking (odds ratio, OR = 8.48; 95% confidence interval, CI = 1.68-42.8). A significant association was also seen between week-day drinking (72+ g/day) and death in men (OR = 7.19, 95% CI = 1.43-36.1). Numbers for women were too small to evaluate. CONCLUSION: Heavy drinking increases admission to intensive care and in-hospital mortality in hospitalized male patients undergoing general surgery procedures.

A prospective study of tobacco smoking as a predictor of complications in general surgery.

OBJECTIVE: To analyze whether tobacco smoking is related to nosocomial infection, admission to the intensive care unit, in-hospital death, and length of stay. DESIGN: A prospective cohort study. SETTING: The Service of General Surgery of a tertiary-care hospital. PATIENTS: A consecutive series of patients admitted for more than 1 day (N = 2,989). RESULTS: Sixty-two (2.1%) patients died and 503 (16.8%) acquired a nosocomial infection, of which 378 (12.6%) were surgical site and 44 (1.5%) were lower respiratory tract. Smoking (mainly past smoking) was associated with a worse health status (eg, longer preoperative stay and higher American Society of Anesthesiologists score). A long history of smoking (> or = 51 pack-years) increased postoperative admission to the intensive care unit (adjusted odds ratio [OR] = 2.86; 95% confidence interval [CI95], 1.21 to 6.77) and in-hospital mortality (adjusted OR = 2.56; CI95, 1.10 to 5.97). There was no relationship between current smoking and surgical-site infection (adjusted OR = 0.99; CI95, 0.72 to 1.35), whereas a relationship was observed between past smoking and surgical-site infection (adjusted OR = 1.46; CI95, 1.02 to 2.09). Current smoking and, to a lesser degree, past smoking augmented the risk of lower respiratory tract infection (adjusted OR = 3.21; CI95, 1.21 to 8.51). Smokers did not undergo additional surgical procedures more frequently during hospitalization. In the multivariate analysis, length of stay was similar for smokers and nonsmokers. CONCLUSION: Smoking increases in-hospital mortality, admission to the intensive care unit, and lower respiratory tract infection, but not surgical-site infection. Deleterious effects of smoking are also observed in past smokers and they cannot be counteracted by hospital cessation programs.