Intensive Care Med (2014) 40:667–673 DOI 10.1007/s00134-014-3248-1
Corinne Alberti Rym Boulkedid
Received: 3 December 2013 Accepted: 10 February 2014 Published online: 11 March 2014 Ó Springer-Verlag Berlin Heidelberg and ESICM 2014 Take-home message: When presenting data for scientific purposes, good tables are an integral part of the communication. Particular attention should be paid to avoiding redundancy with figures and text and the definition of all information, allowing tables to be understandable, informative and readable on their own. Electronic supplementary material The online version of this article (doi:10.1007/s00134-014-3248-1) contains supplementary material, which is available to authorized users.
STATISTICAL NOTE
Describing ICU data with tables
C. Alberti R. Boulkedid AP-HP, Hoˆpital Robert Debre´, Unite´ d’Epide´miologie Clinique, 48 Bd Se´rurier, 75019 Paris, France C. Alberti ()) R. Boulkedid Inserm, U 1123 and CIC 1426, Hoˆpital Robert Debre´, 48 Bd Se´rurier, 75019 Paris, France e-mail: [email protected]; [email protected] Tel.: ?33-1-40032346 Fax: ?33-1-40032485 C. Alberti Univ Paris Diderot, Sorbonne Paris Cite´, UMRS 1123, 75010 Paris, France
tables are an integral part of the manuscript. To help researchers communicate their results, we present practical guidance for reporting statistical results using tables. Results: Five key points are presented for reporting statistical results using tables: (1) early reflection and choice about the results to present, (2) presentation of tables and definition of rows and columns, (3) filling the cells, (4) title, caption, footnotes, and quality, (5) final checklist. Conclusion: This guidance is a practical tool to improve the reporting of statistical results using tables when presenting ICU data in future research.
Abstract Introduction: The purpose of a scientific paper is to communicate results and within the Keywords Data presentation paper this applies especially to the presentation of data. It is the universal Tables Practical guidance practice in medical journals to present Reporting Statistical results statistical results using tables. Good
Introduction The purpose of a scientific paper is to communicate results and within the paper this applies especially to the presentation of data [1–3]. Hurried readers often limit their reading to the study objective at the end of the introduction, the methods section to assess the internal and external validity of the study, and then the tables and figures for the results. The results section of a research paper describes to the reader the outcome and findings of the research by presenting data in a precise and logical manner. Data can be presented as text, in tables, or pictorially as graphs and charts. However, it
is the universal practice in medical journals to present statistical results using tables. Good tables are an integral part of the manuscript. Tables are usually the best way of showing structured numeric information. They help to minimize the number of data values in the text and also to eliminate the need to discuss less significant variables that are not essential to the comprehension of the study. Many guidelines have been published to improve the reporting of research, such as the Consolidated Standards of Reporting Trials (CONSORT) [4], STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) [5], Preferred Reporting Items for Systematic
668
reviews and Meta-Analyses (PRISMA) [6], and STAndards for Reporting of Diagnostic accuracy (STARD) [7]. These guidelines specify the data to be reported in the results section and also provide some guidance on the presentation of results without going into detail notably about building the tables. When presenting results with tables, there are several key points to keep in mind, such as: Are the presented results appropriate to be placed in tables? Are the correct parameters used to present results? Are the results presented with adequate precision and accuracy? Are measures of confidence provided for all estimates if necessary and applicable? Are the tables readable by themselves? Here, we present practical guidance for reporting statistical results using tables to help researchers communicate their results in five key points and toolboxes.
Five key points for presenting data in tables
statistics with its 95 % confidence interval. These essential tables may be complemented by the presentation of additional results often concerning secondary results/outcomes, adverse effects, unexpected findings, subgroups, or sensitivity analyses. However, it is not necessary to create a table if its entire contents could be stated in an informative and clear sentence or two. Moreover, additional tables containing backup data too extensive to publish in print may be appropriate for publication in the electronic version of the journal. The manner of presenting the data depends on the type of study (clinical trial, observational or experimental studies) and is detailed below. Toolbox 1: early reflection and choice about results to present How many tables and for which purposes: Describe baseline characteristics of the study sample Present primary analyses/primary outcomes If appropriate, present secondary analyses/secondary outcomes/ sensitivity analyses/adverse events
1. Early reflection and choice about results to present The basic principle in the process of writing an article is to articulate logically the text, tables, and figures without redundancy. Thus, the choice of tables must be determined early in the process, as it will determine the structure of the results section, the narrative that accompanies it, and the figures to include [8]. Tables should present data in a clear and attractive manner. They do not duplicate data presented in figures. The number of tables varies depending on study design, data analysis, statistical methods considered as well as the journal’s editorial policy, publishing guidelines, and reviewers’ comments. Tables may be simply informational or comparative. In general, a scientific paper presenting clinical or experimental studies has at least two tables: – The first table usually describes the baseline characteristics of the study sample (e.g., demographics, major clinical and lifestyle variables). – The second table presents results of the main analyses or primary outcomes. This is particularly true for clinical trials, where the first table gives information on the population of each arm, allowing verification of the balance of included subjects’ characteristics, and the second table provides information on the effect of the intervention along with its variability. In observational studies, the characteristics of the study participants are often presented in the first table with one column providing a global description and a varying number of additional columns depending on the number of classes of either a single exposure factor or an outcome. The second table might describe the results of bivariate and multivariate analyses, with estimations of association using the appropriate
2. Presentation of tables and definition of rows and columns Tables consist of an ordered arrangement of rows and columns. They are usually vertical but a landscape presentation may be better suited for wide tables when several groups are compared. Tables are read from left to right and from top to bottom. Each table is inserted on a new page after the reference list of the article. The dimensionality has to be determined. This refers to the number of variables used to stratify the quantity that is the focus of the table: – A table that lists characteristics of the entire sample (Table 1) or presents information with no comparison (e.g., model inputs, model results) is no-way: – A table that describes patient characteristics (e.g., age, sex, comorbities) in two or more comparative groups (e.g., intervention vs non intervention, dead vs alive, nosocomial infection vs no nosocomial infection) is one-way (Table 2): – A table that shows patient characteristics (e.g., age, comorbities) stratified by each category defining subgroups (e.g., sex) for each comparative group (e.g., intervention vs non intervention, dead vs alive, nosocomial infection vs no nosocomial infection) is twoway (Table 3): With greater dimensionality in a table, more details and nuances of the data may be captured, thereby reducing the possibility for biases and misinterpretation of data and increasing the quality of reporting [9]. However, the best balance between provided information and dimensionality must be found to avoid creating
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Table 1 No-way table Characteristics
Patients n = 100
Age (years), mean (SD) (minimum–maximum) Sex, n (%)
35 (12) (18–68) Number (%) of male and female among all patients 50 (50) 50 (50) Number (%) of admission category among all patients 45 (45) 25 (25) 30 (30)
Male Female Admission category, n (%) Medical Surgical scheduled Surgical emergency
Table 1 shows characteristics of the study sample. Characteristics are defined in rows according to all sample placed in one column. For normally distributed quantitative variables (e.g., age in this table), data are expressed as mean and standard deviation (SD). For qualitative variables (e.g., sex and admission category in this table), data are expressed as numbers and percentages n (%) for each category placed in rows. All percentages are calculated taking into account the number of patients indicated in the column header as denominator. Admission category and sex variables are composed of exclusive categories, thus the sums of percentage within the categories are exactly equal to 100 %
unreadable tables with unnecessary complexity. Rows and columns represent variables for which numbers are described in data cells. Usually rows present sample characteristics to be described (e.g., age, gender, comorbidities, outcomes in clinical studies) (see Tables 1, 2, 3). The columns present: 1. Primarily the comparative groups from left to right (Tables 2, 3): arms of a clinical trial, exposure
categories (e.g., mechanical ventilation or not, ICUacquired infection or not), outcome categories (e.g., dead or alive). Ideally, compared numbers should be adjacent to help the reader. 2. Often the results of statistical tests (Tables 2A, 3A–C in the Electronic Supplementary Material) [10–12]. 3. Sometimes the number of missing data. Rows and columns headers should be clearly and briefly labeled, adequately describing the data in each row and each column. If abbreviations are necessary, either because they are commonly understood [e.g., chronic obstructive pulmonary disease (COPD)] or require long labels, they should be clearly defined in the explanatory material beneath the table (Tables 2A–C, 3A, B in the Electronic Supplementary Material) [10, 11, 13]. For variables presenting measurements, units should be indicated (e.g., age in months or years for children, biological parameters in mg/L or g/dL). Row headings should be placed in a meaningful order from top to bottom and subheadings for categories indented within a variable [9]. The results from the total sample are presented above those of any subsamples. All repetitive information that applies to all entries in the body of the table and corresponds to a row or a column must appear at the head of the row or column (Tables 2A–C, 3A–C in the Electronic Supplementary Material) [10–13]. In this way, one avoids needless repetition of numbers or definitions that make the table less readable. Usually, these statements refer to the measurement units, the number of individuals involved (e.g., the number in each treatment group) and the operators (%, CI 95 %).
Table 2 One-way table Characteristics
Experimental group n = 100
Control group n = 100
Age (years), mean (SD) Sex, n (%) Male
35 (10)
38 (12)
34 (34) Number (%) of male in experimental group 66 (66) Number (%) of female in experimental group
42 (42) Number (%) of male in control group 58 (58) Number (%) of female in control group
45 (45) Number (%) of medical admissions in experimental group 25 (25) Number (%) of surgical scheduled admissions in experimental group 30 (30) Number (%) of surgical emergency admission in experimental group
40 (40) Number (%) of medical admissions in control group 27 (27) Number (%) of surgical scheduled in control group 33 (33) Number (%) of surgical emergency admission in control group
Female Admission category, n (%) Medical Surgical scheduled Surgical emergency
Table 2 shows characteristics of the study sample in each group arm (experimental and control). Characteristics are defined in rows according to the two arms placed in columns. For normally distributed quantitative variables (e.g., age in this table), data are expressed as mean and standard deviation (SD). For qualitative variables (e.g., sex and admission category in this table), data are
expressed as numbers and percentages, n (%) for each category placed in rows. All percentages are calculated taking into account the number of patients indicated in each column header as denominator. Note that for admission category, the sum of percentages within the column is exactly equal to 100 % denoting a unique mode of admission for each patient
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Table 3 Two-way table Characteristics
Age (years), median [Q1–Q3] Comorbidities, n (%)
Diabetes
Arterial hypertension
Treatment group n = 100
Control group n = 100
Male n = 34
Female n = 66
Male n = 42
Female n = 58
33 [18–45]
35 [19–47]
37 [19–48]
39 [20–49]
10 (29) Number (%) of male patients in treatment group with at least one comorbidity 3 (9) Number (%) of male patients in treatment group presenting diabetes 8 (24) Number (%) of male patients in treatment group presenting hypertension
21 (32) Number (%) of female patients in treatment group with at least one comorbidity 7 (11) Number (%) of female patients in treatment group presenting diabetes 14 (21) Number (%) of female patients in treatment group presenting hypertension
15 (36) Number (%) of male patients in control group with at least one comorbidity 7 (17) Number (%) of male patients in control group presenting diabetes 8 (19) Number (%) of male patients in control group presenting hypertension
19 (33) Number (%) of female patients in control group with at least one comorbidity 10 (17) Number (%) of female patients in control group presenting diabetes 19 (33) Number (%) of female patients in control group presenting hypertension
Table 3 shows characteristics of the study sample in each group arm (treatment and control) stratified by sex. Characteristics are defined in rows tabulated by sex category (secondary column header) for each group arm (primary column header) (treatment and control). For nonnormally distributed quantitative variables (e.g., age in this table), data are expressed as median and 1st–3rd quartiles [Q1–Q3]. For qualitative variables (e.g., sex and comorbidities in this table), data
are expressed as numbers and percentages, n (%) for each category placed in rows. All percentages are calculated taking into account the number of patients indicated in the secondary column header as denominator. Note that the sum of patients presenting specific comorbidities may exceed the total number of patients with at least one comorbidity such as indicated in the data cell of the primary row because some patients can present more than one comorbidity
Toolbox 2: presentation of tables and definition of rows and In descriptive analyses, measures of central tendency columns with measures of variability are usually presented on the
basis of the nature of the variable. Here are some general
Display each table on a single page rules of presentation: Define the dimensionality Show tables in portrait or landscape view Read table from top to bottom and left to right – For quantitative variables (measurements such as Present rows and columns in logical order. Put comparative groups biological variables): determine beforehand whether in adjacent columns the results should be expressed as means with standard Define brief and meaningful labels for row and column headers deviation (SD) or median with quartiles (first quartile, Indent categories within a variable in rows third quartile) depending on whether or not there is a Identify repetitive information that should be put in headers Indicate units of measurements normal distribution. Consider whether minimum and Define abbreviations beneath the table maximum values would be useful. Enter the mean/
median in the cell and standard deviation/quartiles in brackets within the same cell. Avoid the ±sign in front 3. Filling in cells a value after an observed mean without specifying if the value refers to the SD or standard error [14]. If Cells are filled in with numbers (e.g., means, medians, minimum–maximum values are needed, put them in standard deviation, count, percentages), measures of brackets within the same cell but below with a hard effect size (e.g., hazard ratio, odds ratio), or inferential return (Table 1). Be sure that the unit is indicated in the statistics (e.g., p value, Chi square, standard error of the row header. mean) depending on the purpose of the table. – For qualitative variables (categories such sex, comorbities, admission categories in ICU, events): state the absolute number of cases for each category and Numbers percentages in brackets without the % sign. For binary variables (e.g., male/female, yes/no), the number for a The appropriate numbers to be entered in the cells and the single category may be used as the other should be means of obtaining them are explained in the statistical complementary. When calculating percentages, the section of the paper. denominator should be clear. By convention, when
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subjects). The same applies to measures of variability the denominator is not reported, the size of the total as long as greater precision is not required for further sample of the column N is often constant down the calculations [1]. column and is referenced in the column header. Usually, percentages are given by column but for – For percentages, no decimal is required in small samples, reporting of one decimal place should be analytical purposes, it may be appropriate to calculate sufficient for samples of 100 to 1,000 with possibly them by row. In the latter case, it should be specified in greater precision for samples beyond 1,000. the explanatory material beneath the table. The result from the total sample should be presented above those – For p values, two decimal places (e.g., p = 0.56) are largely sufficient. If p values vary from 0.01 to 0.001, of any subsamples. For subsamples, indicate the size of report three decimal places. If p values are smaller, each subgroup. If there are missing data for some present as p \ 0.001 or with the scientific number as subjects, indicate the denominator either in the cell or p \ 10-3. the number of missing data in a specific column placed to the immediate right of the variable column, depending on the specificities of the reported data. – For ratios, indicate the direction of the calculation (e.g., Internal coherence sex ratio: male/female or female/male). This refers to consistency, redundancy, providing useful Effect sizes (a measure of the difference in outcome information, and avoiding extraneous information: between intervention groups) are often provided by odds ratios (OR), relative risks (RR), or hazard ratios (HR), – When presenting the distribution of mutually exclusive regression coefficients for association studies, or differcategories, check that the sum of percentages is equal ences between two quantities (e.g., means or proportions) to 100 % for overall categories within a variable. for clinical trials. Each of these should be accompanied by Occasionally due to rounding, the total may be slightly their 95 % confidence interval presented in brackets different from 100 %. If the total is different from within the same cell (Tables 3A–C in the Electronic 100 %, authors should indicate in a footnote the Supplementary Material) [10–12]. reasons for this result. This is usually due to the For inferential statistics, particularly p values, stapresentation of observation frequencies (e.g., comortistically analyzed results should be presented and bidities, symptoms at ICU entry: one patient can accompanied by the exact p value. The p value is a present multiple states) and not to a distribution (e.g., useful statistical measure of evidence against a null admission categories in ICU: each category is excluhypothesis. By convention, a p value greater than 5 % is sive) (Tables 2A, B in the Electronic Supplementary considered non-significant. p values should not be Material) [10, 13]. reported as to ‘non significant’ or ‘NS’ or as p \ 0.05 – Check for empty cells, which are possible for rows, but even for significant results. Indeed, imagine results that there should be no empty columns. include p values of 0.049 and 0.001. Both are lower than – Null data (such as frequency equal to zero in a category 0.05, but the strength of evidence against the null for qualitative variable, or a mean equal to zero for hypothesis is different. There is very little difference in quantitative variable) should be indicated with a zero to the strength of evidence when a p value is 0.05 vs. avoid confusion with missing data. 0.049, but the difference is significant when a p value is – Missing data should be indicated with non applicable 0.05 vs. 0.001. (NA) or missing data (MD). Avoid the use of hyphens or minus signs. – If necessary, give explanatory information in footnotes Arithmetic precision (see below). This describes the position from which a number is rounded. Today, statistical software allows very precise Toolbox 3: filling in cells calculations. However, the precision of the numbers presented should be reflective of the likely precision of Determine appropriate numbers for measures of central tendency and variability of distributions, effect sizes, inferential statistics the data. It is not necessary to report additional decimal places if they have little scientific relevance [1, 9]. One of Be sure that denominators are well indicated: give numbers of total sample in column header and number of subsamples; indicate the basic rules is that the reporting should remain conappropriate denominators if missing data either in the cell or in a sistent for a particular variable throughout the entire table: specific column Specify the appropriate arithmetic precision for quantities
– For measurements, central position quantities should Avoid redundancy, empty cells, rows, or columns not be given to more than one extra decimal place over Check total counts and percentages within categories of variables Indicate particularities in footnotes the raw data, especially in small samples (e.g., \100
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Toolbox 4: title, caption, footnotes, and quality
4. Title, caption, footnotes, and quality Tables must be accompanied by a title. The title should be specific, brief but informative, and should contain enough detail so that a reader can understand the content without consulting the accompanying text. It is generally placed above the table and should follow the author guidelines of the journal. Tables may be accompanied by a caption that provides complementary information and helps to make the table autonomous and clear. The caption informs readers that the table they are reading requires additional information to make complete sense. Footnotes are generally attached to specific cells (Table 2A in the Electronic Supplementary Material) [10], including column headings (Table 3B in the Electronic Supplementary Material) [11] or row headings (Table 3C in the Electronic Supplementary Material) [12]. The type of markers often depends on publishing guidelines. Intensive Care Medicine recommends indicating footnotes by superscript lowercase letter. The order of the footnotes is the order they are found in the table from left to right and top to bottom. Intrinsic quality refers to the manner in which the table is understandable on its own. Indeed, tables should ideally be informative and self-explanatory. The reader must be able to understand it without detailed reference to the text, as readers may well pick things up from the tables without reading the whole text. Visual quality is important and consists of the production of a perfect alignment of numbers with row and column labels. For clarity, horizontal lines are used to mark the top and the bottom of the table and to separate the column headings from the body. No vertical lines are necessary. Moreover, journals usually adapt the layout of tables to their own style during the copy editing process.
Title: Write an explicit and informative title for each table that stands above the table Caption: Use a caption to provide additional information that completes the title and presents explanatory material (e.g., abbreviation definitions, statistical tests used) Footnotes: Define footnotes if necessary to improve understanding Reference footnotes with usual Vancouver style markers List footnotes in the order they appear in the table from top to bottom and left to right Quality: Check intrinsic quality: the table should be understandable and self-explanatory without extensive reference to the text Check visual quality: numbers should be perfectly aligned with row and column labels; avoid unnecessary lines
Each table should be mentioned at least once in the appropriate place in the text. The internal coherency of numbers should be verified in the text, figures, and tables. The same terms should be used for important information in the text, figures, and tables (e.g., name of intervention group or events defining the outcomes). Toolbox 5: final checklist Place all tables after reference list Number tables sequentially in the order in which they appear in the text Be sure that each table is referenced in the text Check internal coherence of numbers/counts in the text, tables, and figures Use the same terms for important information in the text, tables, and figures
5. Final checklist Each table should appear on a separate page, and all tables should be placed after the reference list. The table should have a unique number that allows referencing in the text in chronological order starting with 1 (e.g., table 1, table 2...).
Acknowledgments The authors wish to thank Karen Berg Brigham (URC Eco Ile-de-France) for her very helpful review of the manuscript. Conflicts of interest On behalf of all authors, the corresponding author states that there is no conflict of interest.
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2. Kotz D, Cals JWL (2013) Effective writing and publishing scientific papers, part V: results. J Clin Epidemiol 66:945. doi:10.1016/j.jclinepi. 2013.04.003
3. Kotz D, Cals JWL (2013) Effective writing and publishing scientific papers, part VII: tables and figures. J Clin Epidemiol 66:1197. doi: 10.1016/j.jclinepi.2013.04.016
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8. Gelman A, Pasarica C, Dodhia R (2002) 12. SAFE Study Investigators, Finfer S, 4. Schulz KF, Altman DG, Moher D, McEvoy S, Bellomo R, McArthur C Let’s practice what we preach: turning CONSORT Group (2010) CONSORT et al (2011) Impact of albumin tables into graphs. Am Stat 56:121–130 2010 Statement: updated guidelines for compared to saline on organ function 9. Schriger DL, Sinha R, Schroter S, Liu reporting parallel group randomised and mortality of patients with severe PY, Altman DG (2006) From trials. BMC Med 8:18. doi: sepsis. Intensive Care Med 37:86–96. submission to publication: a 10.1186/1741-7015-8-18 doi:10.1007/s00134-010-2039-6 retrospective review of the tables and 5. Von Elm E, Altman DG, Egger M, 13. Ducros L, Logeart D, Vicaut E, Henry figures in a cohort of randomized Pocock SJ, Gøtzsche PC et al (2007) P, Plaisance P et al (2011) CPAP for controlled trials submitted to the British The strengthening the reporting of acute cardiogenic pulmonary oedema Medical Journal. Ann Emerg Med observational studies in epidemiology from out-of-hospital to cardiac 48:750–756, 756.e1–e21. doi: (STROBE) statement: guidelines for intensive care unit: a randomised 10.1016/j.annemergmed.2006.06.017 reporting observational studies. PLoS multicentre study. Intensive Care Med 10. Lauzier F, Arnold DM, Rabbat C, Med 4:e296. doi: 37:1501–1509. doi: Heels-Ansdell D, Zarychanski R et al 10.1371/journal.pmed.0040296 10.1007/s00134-011-2311-4 (2013) Risk factors and impact of major 6. Moher D, Liberati A, Tetzlaff J, Altman 14. Altman DG, Bland JM (2005) Standard bleeding in critically ill patients DG, PRISMA Group (2009) Preferred deviations and standard errors. BMJ receiving heparin thromboprophylaxis. reporting items for systematic reviews 331:903. doi: Intensive Care Med 39:2135–2143. doi: and meta-analyses: the PRISMA 10.1136/bmj.331.7521.903 10.1007/s00134-013-3044-3 statement. J Clin Epidemiol 11. Zahar JR, Garrouste-Orgeas M, Vesin 62:1006–1012. doi: A, Schwebel C, Bonadona A et al 10.1016/j.jclinepi.2009.06.005 (2013) Impact of contact isolation for 7. Bossuyt PM, Reitsma JB, Bruns DE, multidrug-resistant organisms on the Gatsonis CA, Glasziou PP et al (2003) occurrence of medical errors and The STARD statement for reporting adverse events. Intensive Care Med studies of diagnostic accuracy: 39:2153–2160. doi:10.1007/s00134explanation and elaboration. Clin Chem 013-3071-0 49:7–18
Corinne Alberti Rym Boulkedid
Received: 3 December 2013 Accepted: 10 February 2014 Published online: 11 March 2014 Ó Springer-Verlag Berlin Heidelberg and ESICM 2014 Take-home message: When presenting data for scientific purposes, good tables are an integral part of the communication. Particular attention should be paid to avoiding redundancy with figures and text and the definition of all information, allowing tables to be understandable, informative and readable on their own. Electronic supplementary material The online version of this article (doi:10.1007/s00134-014-3248-1) contains supplementary material, which is available to authorized users.
STATISTICAL NOTE
Describing ICU data with tables
C. Alberti R. Boulkedid AP-HP, Hoˆpital Robert Debre´, Unite´ d’Epide´miologie Clinique, 48 Bd Se´rurier, 75019 Paris, France C. Alberti ()) R. Boulkedid Inserm, U 1123 and CIC 1426, Hoˆpital Robert Debre´, 48 Bd Se´rurier, 75019 Paris, France e-mail: [email protected]; [email protected] Tel.: ?33-1-40032346 Fax: ?33-1-40032485 C. Alberti Univ Paris Diderot, Sorbonne Paris Cite´, UMRS 1123, 75010 Paris, France
tables are an integral part of the manuscript. To help researchers communicate their results, we present practical guidance for reporting statistical results using tables. Results: Five key points are presented for reporting statistical results using tables: (1) early reflection and choice about the results to present, (2) presentation of tables and definition of rows and columns, (3) filling the cells, (4) title, caption, footnotes, and quality, (5) final checklist. Conclusion: This guidance is a practical tool to improve the reporting of statistical results using tables when presenting ICU data in future research.
Abstract Introduction: The purpose of a scientific paper is to communicate results and within the Keywords Data presentation paper this applies especially to the presentation of data. It is the universal Tables Practical guidance practice in medical journals to present Reporting Statistical results statistical results using tables. Good
Introduction The purpose of a scientific paper is to communicate results and within the paper this applies especially to the presentation of data [1–3]. Hurried readers often limit their reading to the study objective at the end of the introduction, the methods section to assess the internal and external validity of the study, and then the tables and figures for the results. The results section of a research paper describes to the reader the outcome and findings of the research by presenting data in a precise and logical manner. Data can be presented as text, in tables, or pictorially as graphs and charts. However, it
is the universal practice in medical journals to present statistical results using tables. Good tables are an integral part of the manuscript. Tables are usually the best way of showing structured numeric information. They help to minimize the number of data values in the text and also to eliminate the need to discuss less significant variables that are not essential to the comprehension of the study. Many guidelines have been published to improve the reporting of research, such as the Consolidated Standards of Reporting Trials (CONSORT) [4], STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) [5], Preferred Reporting Items for Systematic
668
reviews and Meta-Analyses (PRISMA) [6], and STAndards for Reporting of Diagnostic accuracy (STARD) [7]. These guidelines specify the data to be reported in the results section and also provide some guidance on the presentation of results without going into detail notably about building the tables. When presenting results with tables, there are several key points to keep in mind, such as: Are the presented results appropriate to be placed in tables? Are the correct parameters used to present results? Are the results presented with adequate precision and accuracy? Are measures of confidence provided for all estimates if necessary and applicable? Are the tables readable by themselves? Here, we present practical guidance for reporting statistical results using tables to help researchers communicate their results in five key points and toolboxes.
Five key points for presenting data in tables
statistics with its 95 % confidence interval. These essential tables may be complemented by the presentation of additional results often concerning secondary results/outcomes, adverse effects, unexpected findings, subgroups, or sensitivity analyses. However, it is not necessary to create a table if its entire contents could be stated in an informative and clear sentence or two. Moreover, additional tables containing backup data too extensive to publish in print may be appropriate for publication in the electronic version of the journal. The manner of presenting the data depends on the type of study (clinical trial, observational or experimental studies) and is detailed below. Toolbox 1: early reflection and choice about results to present How many tables and for which purposes: Describe baseline characteristics of the study sample Present primary analyses/primary outcomes If appropriate, present secondary analyses/secondary outcomes/ sensitivity analyses/adverse events
1. Early reflection and choice about results to present The basic principle in the process of writing an article is to articulate logically the text, tables, and figures without redundancy. Thus, the choice of tables must be determined early in the process, as it will determine the structure of the results section, the narrative that accompanies it, and the figures to include [8]. Tables should present data in a clear and attractive manner. They do not duplicate data presented in figures. The number of tables varies depending on study design, data analysis, statistical methods considered as well as the journal’s editorial policy, publishing guidelines, and reviewers’ comments. Tables may be simply informational or comparative. In general, a scientific paper presenting clinical or experimental studies has at least two tables: – The first table usually describes the baseline characteristics of the study sample (e.g., demographics, major clinical and lifestyle variables). – The second table presents results of the main analyses or primary outcomes. This is particularly true for clinical trials, where the first table gives information on the population of each arm, allowing verification of the balance of included subjects’ characteristics, and the second table provides information on the effect of the intervention along with its variability. In observational studies, the characteristics of the study participants are often presented in the first table with one column providing a global description and a varying number of additional columns depending on the number of classes of either a single exposure factor or an outcome. The second table might describe the results of bivariate and multivariate analyses, with estimations of association using the appropriate
2. Presentation of tables and definition of rows and columns Tables consist of an ordered arrangement of rows and columns. They are usually vertical but a landscape presentation may be better suited for wide tables when several groups are compared. Tables are read from left to right and from top to bottom. Each table is inserted on a new page after the reference list of the article. The dimensionality has to be determined. This refers to the number of variables used to stratify the quantity that is the focus of the table: – A table that lists characteristics of the entire sample (Table 1) or presents information with no comparison (e.g., model inputs, model results) is no-way: – A table that describes patient characteristics (e.g., age, sex, comorbities) in two or more comparative groups (e.g., intervention vs non intervention, dead vs alive, nosocomial infection vs no nosocomial infection) is one-way (Table 2): – A table that shows patient characteristics (e.g., age, comorbities) stratified by each category defining subgroups (e.g., sex) for each comparative group (e.g., intervention vs non intervention, dead vs alive, nosocomial infection vs no nosocomial infection) is twoway (Table 3): With greater dimensionality in a table, more details and nuances of the data may be captured, thereby reducing the possibility for biases and misinterpretation of data and increasing the quality of reporting [9]. However, the best balance between provided information and dimensionality must be found to avoid creating
669
Table 1 No-way table Characteristics
Patients n = 100
Age (years), mean (SD) (minimum–maximum) Sex, n (%)
35 (12) (18–68) Number (%) of male and female among all patients 50 (50) 50 (50) Number (%) of admission category among all patients 45 (45) 25 (25) 30 (30)
Male Female Admission category, n (%) Medical Surgical scheduled Surgical emergency
Table 1 shows characteristics of the study sample. Characteristics are defined in rows according to all sample placed in one column. For normally distributed quantitative variables (e.g., age in this table), data are expressed as mean and standard deviation (SD). For qualitative variables (e.g., sex and admission category in this table), data are expressed as numbers and percentages n (%) for each category placed in rows. All percentages are calculated taking into account the number of patients indicated in the column header as denominator. Admission category and sex variables are composed of exclusive categories, thus the sums of percentage within the categories are exactly equal to 100 %
unreadable tables with unnecessary complexity. Rows and columns represent variables for which numbers are described in data cells. Usually rows present sample characteristics to be described (e.g., age, gender, comorbidities, outcomes in clinical studies) (see Tables 1, 2, 3). The columns present: 1. Primarily the comparative groups from left to right (Tables 2, 3): arms of a clinical trial, exposure
categories (e.g., mechanical ventilation or not, ICUacquired infection or not), outcome categories (e.g., dead or alive). Ideally, compared numbers should be adjacent to help the reader. 2. Often the results of statistical tests (Tables 2A, 3A–C in the Electronic Supplementary Material) [10–12]. 3. Sometimes the number of missing data. Rows and columns headers should be clearly and briefly labeled, adequately describing the data in each row and each column. If abbreviations are necessary, either because they are commonly understood [e.g., chronic obstructive pulmonary disease (COPD)] or require long labels, they should be clearly defined in the explanatory material beneath the table (Tables 2A–C, 3A, B in the Electronic Supplementary Material) [10, 11, 13]. For variables presenting measurements, units should be indicated (e.g., age in months or years for children, biological parameters in mg/L or g/dL). Row headings should be placed in a meaningful order from top to bottom and subheadings for categories indented within a variable [9]. The results from the total sample are presented above those of any subsamples. All repetitive information that applies to all entries in the body of the table and corresponds to a row or a column must appear at the head of the row or column (Tables 2A–C, 3A–C in the Electronic Supplementary Material) [10–13]. In this way, one avoids needless repetition of numbers or definitions that make the table less readable. Usually, these statements refer to the measurement units, the number of individuals involved (e.g., the number in each treatment group) and the operators (%, CI 95 %).
Table 2 One-way table Characteristics
Experimental group n = 100
Control group n = 100
Age (years), mean (SD) Sex, n (%) Male
35 (10)
38 (12)
34 (34) Number (%) of male in experimental group 66 (66) Number (%) of female in experimental group
42 (42) Number (%) of male in control group 58 (58) Number (%) of female in control group
45 (45) Number (%) of medical admissions in experimental group 25 (25) Number (%) of surgical scheduled admissions in experimental group 30 (30) Number (%) of surgical emergency admission in experimental group
40 (40) Number (%) of medical admissions in control group 27 (27) Number (%) of surgical scheduled in control group 33 (33) Number (%) of surgical emergency admission in control group
Female Admission category, n (%) Medical Surgical scheduled Surgical emergency
Table 2 shows characteristics of the study sample in each group arm (experimental and control). Characteristics are defined in rows according to the two arms placed in columns. For normally distributed quantitative variables (e.g., age in this table), data are expressed as mean and standard deviation (SD). For qualitative variables (e.g., sex and admission category in this table), data are
expressed as numbers and percentages, n (%) for each category placed in rows. All percentages are calculated taking into account the number of patients indicated in each column header as denominator. Note that for admission category, the sum of percentages within the column is exactly equal to 100 % denoting a unique mode of admission for each patient
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Table 3 Two-way table Characteristics
Age (years), median [Q1–Q3] Comorbidities, n (%)
Diabetes
Arterial hypertension
Treatment group n = 100
Control group n = 100
Male n = 34
Female n = 66
Male n = 42
Female n = 58
33 [18–45]
35 [19–47]
37 [19–48]
39 [20–49]
10 (29) Number (%) of male patients in treatment group with at least one comorbidity 3 (9) Number (%) of male patients in treatment group presenting diabetes 8 (24) Number (%) of male patients in treatment group presenting hypertension
21 (32) Number (%) of female patients in treatment group with at least one comorbidity 7 (11) Number (%) of female patients in treatment group presenting diabetes 14 (21) Number (%) of female patients in treatment group presenting hypertension
15 (36) Number (%) of male patients in control group with at least one comorbidity 7 (17) Number (%) of male patients in control group presenting diabetes 8 (19) Number (%) of male patients in control group presenting hypertension
19 (33) Number (%) of female patients in control group with at least one comorbidity 10 (17) Number (%) of female patients in control group presenting diabetes 19 (33) Number (%) of female patients in control group presenting hypertension
Table 3 shows characteristics of the study sample in each group arm (treatment and control) stratified by sex. Characteristics are defined in rows tabulated by sex category (secondary column header) for each group arm (primary column header) (treatment and control). For nonnormally distributed quantitative variables (e.g., age in this table), data are expressed as median and 1st–3rd quartiles [Q1–Q3]. For qualitative variables (e.g., sex and comorbidities in this table), data
are expressed as numbers and percentages, n (%) for each category placed in rows. All percentages are calculated taking into account the number of patients indicated in the secondary column header as denominator. Note that the sum of patients presenting specific comorbidities may exceed the total number of patients with at least one comorbidity such as indicated in the data cell of the primary row because some patients can present more than one comorbidity
Toolbox 2: presentation of tables and definition of rows and In descriptive analyses, measures of central tendency columns with measures of variability are usually presented on the
basis of the nature of the variable. Here are some general
Display each table on a single page rules of presentation: Define the dimensionality Show tables in portrait or landscape view Read table from top to bottom and left to right – For quantitative variables (measurements such as Present rows and columns in logical order. Put comparative groups biological variables): determine beforehand whether in adjacent columns the results should be expressed as means with standard Define brief and meaningful labels for row and column headers deviation (SD) or median with quartiles (first quartile, Indent categories within a variable in rows third quartile) depending on whether or not there is a Identify repetitive information that should be put in headers Indicate units of measurements normal distribution. Consider whether minimum and Define abbreviations beneath the table maximum values would be useful. Enter the mean/
median in the cell and standard deviation/quartiles in brackets within the same cell. Avoid the ±sign in front 3. Filling in cells a value after an observed mean without specifying if the value refers to the SD or standard error [14]. If Cells are filled in with numbers (e.g., means, medians, minimum–maximum values are needed, put them in standard deviation, count, percentages), measures of brackets within the same cell but below with a hard effect size (e.g., hazard ratio, odds ratio), or inferential return (Table 1). Be sure that the unit is indicated in the statistics (e.g., p value, Chi square, standard error of the row header. mean) depending on the purpose of the table. – For qualitative variables (categories such sex, comorbities, admission categories in ICU, events): state the absolute number of cases for each category and Numbers percentages in brackets without the % sign. For binary variables (e.g., male/female, yes/no), the number for a The appropriate numbers to be entered in the cells and the single category may be used as the other should be means of obtaining them are explained in the statistical complementary. When calculating percentages, the section of the paper. denominator should be clear. By convention, when
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subjects). The same applies to measures of variability the denominator is not reported, the size of the total as long as greater precision is not required for further sample of the column N is often constant down the calculations [1]. column and is referenced in the column header. Usually, percentages are given by column but for – For percentages, no decimal is required in small samples, reporting of one decimal place should be analytical purposes, it may be appropriate to calculate sufficient for samples of 100 to 1,000 with possibly them by row. In the latter case, it should be specified in greater precision for samples beyond 1,000. the explanatory material beneath the table. The result from the total sample should be presented above those – For p values, two decimal places (e.g., p = 0.56) are largely sufficient. If p values vary from 0.01 to 0.001, of any subsamples. For subsamples, indicate the size of report three decimal places. If p values are smaller, each subgroup. If there are missing data for some present as p \ 0.001 or with the scientific number as subjects, indicate the denominator either in the cell or p \ 10-3. the number of missing data in a specific column placed to the immediate right of the variable column, depending on the specificities of the reported data. – For ratios, indicate the direction of the calculation (e.g., Internal coherence sex ratio: male/female or female/male). This refers to consistency, redundancy, providing useful Effect sizes (a measure of the difference in outcome information, and avoiding extraneous information: between intervention groups) are often provided by odds ratios (OR), relative risks (RR), or hazard ratios (HR), – When presenting the distribution of mutually exclusive regression coefficients for association studies, or differcategories, check that the sum of percentages is equal ences between two quantities (e.g., means or proportions) to 100 % for overall categories within a variable. for clinical trials. Each of these should be accompanied by Occasionally due to rounding, the total may be slightly their 95 % confidence interval presented in brackets different from 100 %. If the total is different from within the same cell (Tables 3A–C in the Electronic 100 %, authors should indicate in a footnote the Supplementary Material) [10–12]. reasons for this result. This is usually due to the For inferential statistics, particularly p values, stapresentation of observation frequencies (e.g., comortistically analyzed results should be presented and bidities, symptoms at ICU entry: one patient can accompanied by the exact p value. The p value is a present multiple states) and not to a distribution (e.g., useful statistical measure of evidence against a null admission categories in ICU: each category is excluhypothesis. By convention, a p value greater than 5 % is sive) (Tables 2A, B in the Electronic Supplementary considered non-significant. p values should not be Material) [10, 13]. reported as to ‘non significant’ or ‘NS’ or as p \ 0.05 – Check for empty cells, which are possible for rows, but even for significant results. Indeed, imagine results that there should be no empty columns. include p values of 0.049 and 0.001. Both are lower than – Null data (such as frequency equal to zero in a category 0.05, but the strength of evidence against the null for qualitative variable, or a mean equal to zero for hypothesis is different. There is very little difference in quantitative variable) should be indicated with a zero to the strength of evidence when a p value is 0.05 vs. avoid confusion with missing data. 0.049, but the difference is significant when a p value is – Missing data should be indicated with non applicable 0.05 vs. 0.001. (NA) or missing data (MD). Avoid the use of hyphens or minus signs. – If necessary, give explanatory information in footnotes Arithmetic precision (see below). This describes the position from which a number is rounded. Today, statistical software allows very precise Toolbox 3: filling in cells calculations. However, the precision of the numbers presented should be reflective of the likely precision of Determine appropriate numbers for measures of central tendency and variability of distributions, effect sizes, inferential statistics the data. It is not necessary to report additional decimal places if they have little scientific relevance [1, 9]. One of Be sure that denominators are well indicated: give numbers of total sample in column header and number of subsamples; indicate the basic rules is that the reporting should remain conappropriate denominators if missing data either in the cell or in a sistent for a particular variable throughout the entire table: specific column Specify the appropriate arithmetic precision for quantities
– For measurements, central position quantities should Avoid redundancy, empty cells, rows, or columns not be given to more than one extra decimal place over Check total counts and percentages within categories of variables Indicate particularities in footnotes the raw data, especially in small samples (e.g., \100
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Toolbox 4: title, caption, footnotes, and quality
4. Title, caption, footnotes, and quality Tables must be accompanied by a title. The title should be specific, brief but informative, and should contain enough detail so that a reader can understand the content without consulting the accompanying text. It is generally placed above the table and should follow the author guidelines of the journal. Tables may be accompanied by a caption that provides complementary information and helps to make the table autonomous and clear. The caption informs readers that the table they are reading requires additional information to make complete sense. Footnotes are generally attached to specific cells (Table 2A in the Electronic Supplementary Material) [10], including column headings (Table 3B in the Electronic Supplementary Material) [11] or row headings (Table 3C in the Electronic Supplementary Material) [12]. The type of markers often depends on publishing guidelines. Intensive Care Medicine recommends indicating footnotes by superscript lowercase letter. The order of the footnotes is the order they are found in the table from left to right and top to bottom. Intrinsic quality refers to the manner in which the table is understandable on its own. Indeed, tables should ideally be informative and self-explanatory. The reader must be able to understand it without detailed reference to the text, as readers may well pick things up from the tables without reading the whole text. Visual quality is important and consists of the production of a perfect alignment of numbers with row and column labels. For clarity, horizontal lines are used to mark the top and the bottom of the table and to separate the column headings from the body. No vertical lines are necessary. Moreover, journals usually adapt the layout of tables to their own style during the copy editing process.
Title: Write an explicit and informative title for each table that stands above the table Caption: Use a caption to provide additional information that completes the title and presents explanatory material (e.g., abbreviation definitions, statistical tests used) Footnotes: Define footnotes if necessary to improve understanding Reference footnotes with usual Vancouver style markers List footnotes in the order they appear in the table from top to bottom and left to right Quality: Check intrinsic quality: the table should be understandable and self-explanatory without extensive reference to the text Check visual quality: numbers should be perfectly aligned with row and column labels; avoid unnecessary lines
Each table should be mentioned at least once in the appropriate place in the text. The internal coherency of numbers should be verified in the text, figures, and tables. The same terms should be used for important information in the text, figures, and tables (e.g., name of intervention group or events defining the outcomes). Toolbox 5: final checklist Place all tables after reference list Number tables sequentially in the order in which they appear in the text Be sure that each table is referenced in the text Check internal coherence of numbers/counts in the text, tables, and figures Use the same terms for important information in the text, tables, and figures
5. Final checklist Each table should appear on a separate page, and all tables should be placed after the reference list. The table should have a unique number that allows referencing in the text in chronological order starting with 1 (e.g., table 1, table 2...).
Acknowledgments The authors wish to thank Karen Berg Brigham (URC Eco Ile-de-France) for her very helpful review of the manuscript. Conflicts of interest On behalf of all authors, the corresponding author states that there is no conflict of interest.
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3. Kotz D, Cals JWL (2013) Effective writing and publishing scientific papers, part VII: tables and figures. J Clin Epidemiol 66:1197. doi: 10.1016/j.jclinepi.2013.04.016
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