Pao/BEL family is probably the least well studied. It is becoming apparent that numerous LTR retrotransposons and other mobile genetic elements have colonized the genome of the human blood fluke, Schistosoma mansoni.Of the major families of long terminal repeat (LTR) retrotransposons, the Sinbad, a new LTR retrotransposon, was identified in the genome of S. mansoni. Phylogenetic analysis indicated that Sinbad belongs to one of five discreet subfamilies of Pao/BEL like elements. BLAST searches of whole genomes and EST databases indicated that members of this clade occurred in species of the Insecta, Nematoda, Echinodermata and Chordata, as well as Platyhelminthes, but were absent from all plants, fungi and lower eukaryotes examined. Among the deuterostomes examined, only aquatic species harbored these types of elements. All four species of nematode examined were positive for Sinbad sequences, although among insect and vertebrate genomes, some were positive and some negative. The full length, consensus Sinbad retrotransposon was 6,287 bp long and was flanked at its 5'- and 3'-ends by identical LTRs of 386 bp. Sinbad displayed a triple Cys-His RNA binding motif characteristic of Gag of Pao/BEL-like elements, followed by the enzymatic domains of protease, reverse transcriptase (RT), RNAseH, and integrase, in that order. A phylogenetic tree of deduced RT sequences from 26 elements revealed that Sinbad was most closely related to an unnamed element from the zebrafish Danio rerio and to Saci-1, also from S. mansoni. It was also closely related to Pao from Bombyx mori and to Ninja of Drosophila simulans. Sinbad was only distantly related to the other schistosome LTR retrotransposons Boudicca, Gulliver, Saci-2, Saci-3, and Fugitive, which are gypsy-like. Southern hybridization and bioinformatics analyses indicated that there were about 50 copies of Sinbad in the S. mansoni genome. The presence of ESTs representing transcripts of Sinbad in numerous developmental stages of S. mansoni along with the identical 5'- and 3'-LTR sequences suggests that Sinbad is an active retrotransposon.A proviral form of Sinbad is a Pao/BEL type retrotransposon from the genome of S. mansoni. The Pao/BEL group appears to be comprised of at least five discrete subfamilies, which tend to cluster with host species phylogeny. Pao/BEL type elements appear to have colonized only the genomes of the Animalia. The distribution of these elements in the Ecdysozoa, Deuterostomia, and Lophotrochozoa is discontinuous, suggesting horizontal transmission and/or efficient elimination of Pao-like mobile genetic elements from some genomes. Schistosoma mansoni, the African blood fluke and etiological agent of intestinal schistosomiasis, is endemic in numerous countries in Africa, the Middle East, the Caribbean and northeastern South America. The life cycle of S. mansoni involves parasitism of both humans and aquatic snails of the genus Biomphalaria. Cercariae, the infectious larvae, emerge from the snails into lakes and fresh water streams, where they initiate human infection by direct penetration of the skin. Within the infected person, the worms develop into male and female adults within the portal system blood vessels and mesenteric veins of the intestines. Eggs released from the female parasite into the blood traverse the intestinal wall and are passed out with the feces. Among the tropical diseases, schistosomiasis ranks second only to malaria in terms of morbidity and mortality .Sinbad in BAC 33-N-3 are identical in sequence, and appeared to contain a putative promoter for initiation of transcription by RNA polymerase II. Along with conservation of most residues contributing to the active sites of the retrotransposon enzyme domains, these structural characteristics suggested that Sinbad is active or had been transpositionally active in the recent past. Several other features also indicated that Sinbad is transpositionally active. Numerous transcripts spanning enzymatic domains and LTRs of Sinbad, from at least six developmental stages of S. mansoni, have been sequenced /E = F. This formula was derived from two equations: (A/B) × C = D and D/E = F, where A was the number of copies of Sinbad in the BAC 33-N-3 lane, B was the density volume of the 33-N-3 lane in units of optical density per mm2, C was the density volume of the S. mansoni genomic DNA lanes in units of optical density per mm2, D was the total number of copies of Sinbad per genomic DNA lane, E is the number of haploid genomes in the gDNA lane, and F represented the copy number of Sinbad per haploid S. mansoni genome. The insert of 33-N-3 was estimated to be 145 kb in length and assumed to contain only a single copy of the retrotransposon.Genomic DNAs of cercariae of a Puerto Rican strain of y action , and UV-cum gDNA  μg/lane Sinbad retrotransposon also were obtained by a comparative bioinformatics approach >), and with the E value at 0.000001. The E value  reflects the probability of obtaining a match purely by chance. Scores at or below this stringent cutoff E value of 10-6 were counted as positive. This exceptionally stringent cutoff value was used to minimize the chance of counting other Pao-like elements in the total copy number of Sinbad. Since the formula for E is based not only on the bit scores of the local alignment of each pair of sequences, but also on the lengths of the subject and query , no addTy3, S53577; Tas: Z29712; Suzu, AF537216; Sinbad, AY506538 (an N was inserted at position 2761 to a resolve a frameshift and generate a single ORF) Saci-1, DAA04498; Roo, AAN87269; Ninja, T31674; Moose, AF060859; Max, CAD32253; Kamikaze, AB042120; HIV-1, P04585; Gypsy, GNFFG1; Gulliver, AF243513; Copia, OFFCP; BEL, AAB03640; Cer7, AAB63932, Cer8, CAB04994, Cer9, CAB1647, and Cer11, AAA82437, two uncharacterized Anopheles gambiae retrotransposons, XP_309281 and XM_308737, an uncharacterized Caenorhabditis briggsae retrotransposon, AC084491, and two uncharacterized Danio rerio retrotransposons, BX537152 and BX005079 )5079 see . Two addd et al. .Sinbad. The deduced amino acid sequence encoding the region from the Cys-His Box through to the protease domain (encoded by nucleotides 106 to 753 of Sinbad [Y506538]) was employed as the query to search each genome individually using tBLASTn. The genomes searched in this way were as follows: Homo sapiens, Mus musculus, Rattus norvegicus, Takifugu rubripes, Danio rerio, Bos taurus, Gallus gallus, Sus scrofa, Canis familiaris, Anopheles gambiae, Apis mellifera, Drosophila melanogaster, Drosophila pseudoobscura, Brugia malayi, Caenorhabditis elegans, Caenorhabditis briggsae, Strongylocentrotus purpuratus, Ciona intestinalis, Ciona savigny, Giardia lamblia, Plasmodium falciparum, Plasmodium yoelii, Plasmodium berghei, Cryptosporidium parvum, Eimeria tenella, Theileria annulata, Toxoplasma gondii, Dictyostelium discoideum, Entamoeba histolytica, Leishmania major, Trypanosoma brucei, Trypanosoma cruzi, Arabidopsis thaliana, Avena sativa, Glycine max, Hordeum vulgare, Oryza sativa, Triticum aestivum, Zea mays, Lycopersicon esculentum, Schizosaccharomyces pombe, Saccharomyces cerevisiae, Saccharomyces paradoxus, Saccharomyces mikatae, Saccharomyces bayanus, Saccharomyces castelli, Saccharomyces kluyveri, Saccharomyces kudriavzevii, Neurospora crassa, Magnaporthe grisea, Aspergillus nidulans, Aspergillus fumigatus, Aspergillus terreus, Candida albicans, Coccidioides posadasii, Gibberella zeae, Coprinopsis cinerea, Cryptococcus neoformans, Ustilago maydis and Encephalitozoan cuniculi. In addition, 275 eubacterial and 21 Archaean genomes were searched [see Sinbad-like elements.A panel of fully or partially sequenced entire genomes was searched by BLAST for elements exhibiting sequence similarity to ched see . GenomesSinbad LTR retrotransposon have been assigned accession numbers AY506537, AY506538, AY645721, AAT66412, and AY871176. Other sequences introduced here been assigned GenBank Third Party Annotation accession numbers; BK005570 (Danio rerio), BK005571 (D. rerio), BK005572 (Caenorhabditis briggsae), BK005573 (Anopheles gambiae), BK005574 (D. rerio).Sequences of the MGE, mobile genetic element; ORF, open reading frame; EST, expressed sequence tag; gDNA, genomic DNA; LTR, long terminal repeat; RT, reverse transcriptase; PR, protease; IN, Integrase; CHB, Cys-His box; BAC, bacterial artificial chromosome; MB, megabase pairsCSC carried out the sequence analyses, sequence alignments, phylogenetic studies, other bioinformatics analyses, and Southern hybridizations, participated in cloning, sequencing and design of the study, and, together with PJB, drafted the manuscript. VHM and MEM participated in cloning and sequencing. BHK contributed to the design of experiments and analyses. PJB participated in the design and coordination of the study, and drafting the manuscript. All authors read and approved the final version of the manuscript.Sinbad sequence". Nucleotide and deduced amino acid sequence of the entire Sinbad retrotransposon in BAC clone 33-N-3. Hallmark features of the retrotransposon are identified in colored highlights as described in the key at the bottom of the figure."Annotated Click here for file"RT domain sequences of new and consensus elements used in the phylogenetic analysis". Deduced amino acid sequences of the RT domains used in the phylogenetic analysis from newly characterized elements, uncharacterized elements found within genome survey sequences, and elements for which consensus sequences were used. Accession numbers for the source sequences of each element are listed, as well as references where applicable.Click here for fileSinbad like elements" Table of prokaryotic genomes indicated by whole genome analysis to be devoid of Sinbad like elements."Prokaryotic genomes negative for Click here for file


Family doctors should care for individuals in the context of their family. Family has a powerful influence on health and illness and family interventions have been shown to improve health outcomes for a variety of health problems. The aim of the study was to investigate the Estonian family doctors' (FD) attitudes to the patients' family-related issues in their work: to explore the degree of FDs involvement in family matters, their preparedness for management of family-related issues and their self-assessment of the ability to manage different family-related problems.A random sample (n = 236) of all FDs in Estonia was investigated using a postal questionnaire. Altogether 151 FDs responded to the questionnaire (response rate 64%), while five of them were excluded as they did not actually work as FDs.Of the respondents, 90% thought that in managing the health problems of patients FDs should communicate and cooperate with family members. Although most of the family doctors agreed that modifying of the health damaging risk factors  of their patients and families is their task, one third of them felt that dealing with these problems is ineffective, or perceived themselves as poorly prepared or having too little time for such activities. Of the respondents, 58% (n = 83) were of the opinion that they could modify also relationship problems.Estonian family doctors are favourably disposed to involvement in family-related problems, however, they need some additional training, especially in the field of relationship management. There are significant differences in the way how primary health care is organised in Europe . EstoniaIrrespective of the health system, general practitioners/family doctors should care for individuals in the context of their family . Family In Estonia, a decade has passed after the new speciality, family doctor, was introduced into the health care system. The aim of the present study was to investigate the attitude of FDs in Estonia to family-oriented general practice : FDs' awA 21-item questionnaire was designed for the study. The items were developed by researchers considering the aims of the study.First, the FDs were asked whether their patients have registered on the list by families or not and whether they regard it as appropriate that the family should be cared by one doctor, or whether they think that children should have a separate primary care physician. The FDs rated their opinion on the degree of involvement with various problems in the family: they should deal only with the treatment and counselling of a particular patient, or to cooperate also with family members, in addition to treatment of a particular patient, or they should deal also with emotional and relationship problems of the family members. The questions about FDs' awareness of various issues related to their patients' families such as familial diseases and diseases of family members, financial coping, relationships in the family, living conditions (overcrowding), drug addiction, alcohol abuse, smoking and leisure activities were inquired on a three-step scale : yes, in the case of each patient; yes, in certain cases; no, it is not necessary. FDs' were asked to self-estimate their ability to manage problems in families such as substance abuse and relationship problems. Questions about the FDs' ability to manage problems in families were open-ended, for example: how do you assess your possibilities as a FD to influence relationship problems in the family? If you assess that you cannot influence them, please specify why? If you assess you can influence them, please specify how? Also, the FDs were asked to estimate whether their professional training for dealing with the problems of families is adequate or inadequate. Several questions were related to sociodemographic characteristics  and professional history . The questionnaire was piloted for clarity and relevance in a group of five FDs, and minor changes were introduced.rd doctor, in alphabetical order, from the list of doctors who had passed residency or retraining courses in family medicine by that time in Estonia (n = 715). A note of reminder and a new questionnaire was sent to the non-responders 4 weeks after the first mailing. Of the 236 mailed questionnaires, 151 were returned after two mailings (64%), five of them were excluded as the respondents did not actually work as FDs. Thus, altogether 146 questionnaires were included in the study, of these 124 were fully completed, while in 22 cases some of the answers (1 to 3 per questionnaire) were missing.In February 2002, the questionnaire was mailed to 236 FDs. a random sample of family doctors of Estonia. The random sample of FDs was formed by choosing the name of every 3The data were analysed using SPSS for the Windows version 10. The chi-square test was used to test the differences in the proportions, all p-values calculated were two-tailed, the p-values higher than 0.05 were considered non-significant (NS).All open questions were analysed as follows: all statements expressing motivation for or indicating problems with dealing with family issues were marked. Further, all similar expressions were grouped under one category. Proceeding from this, the key problems relevant to the study were identified .The mean age of the respondents was 46 (± 8) years, the mean length of the period during which they had worked in primary health care was 18 (± 9) years and the mean size of the list was 1800 (± 513) patients. Of the respondents 55% worked in urban areas, 40% in rural areas, and 5% worked in both areas. The majority of the doctors (92%) were female. The age and sex distribution of the respondents and non-respondents did not differ significantly.A total of 90 (62%) FDs were of the opinion that it was good to have the same FD for the whole family, 31 (21%) responded that it was preferable that every family member chooses a FD on the basis of personal preference and 25 (17%) thought that children should have a primary health care physician other than adults of the same family. Of the FDs, 119 (82%) responded that most patients were registered in their lists by families.Of the respondents 15 (10%) were of the opinion that FDs should deal only with the health problems of concrete patients without involvement of family members, 94 (65%) responded that, besides managing the health problems of patients, FDs should communicate and cooperate with family members, and 36 (25%) thought that apart from the previously mentioned issues, FDs should deal with the family members' emotional and relationship problems.Over 70% of Estonian FDs agreed that in the case of all patients, it is necessary to be aware of drug addiction in the family, diseases of family members, living conditions and alcohol abuse in the family, while the remainder believed that they should be aware of these issues on certain occasions. Of the respondents, over a third thought that the FD should always be aware of relationships in the family and 12% thought that the FD should always be aware of leisure activities of their patients. However, between 60 to 75% believed that FDs should be aware of these issues in certain occasions  of the respondents felt that their preparedness was adequate. Regarding the other issues, less than half of the respondents considered their training adequate  in families. One hundred (70%) of the respondents reported that this was within the scope of their ability, while the majority (n = 71) stated that the methods used were advice and counselling, but also referral to specialists, use of specific medications and suggestions regarding appropriate reading material. However, 16 FDs admitted that the efficacy of their work in this field was low.Nearly one-third of the respondents (30%) estimated that they were not able to reduce the use of harmful substances in their patients' families. The analysis of the open-ended questions identifed some key problems:• Low motivation of patients.• Socio-economic reasons for substance abuse.• Limited time for consultation.• Inadequate preparedness for management of these issues.One hundred and forty-three FDs responded to the question about their influence on relationship problems in their patients' families, 83 (58%) of them were of the opinion that they were able to modify these problems. In most cases, FDs used advice and counselling (n = 52), but they also cooperated with specialists as the psychotherapist, family therapist, psychiatrist or social worker. Of the family doctors 60 (42%) thought that they were not able to influence the patients' relationship problems. In the analysis of the open questions, the doctors identified several key problems:• Limited time.• Lack of special training.• Patients do not address FDs with their problem.• Patients themselves deny the existence of the problem.• These are the patients' private issues in which physicians could not intervene.versus 57% (n = 24) of those who reported that their preparedness for such issues was not adequate (p < 0.05); in the case of relationship problems, the respective percentages were 41% (n = 34) versus 9% (n = 5) (p < 0.0001). There were found no other significant determinants among the sociodemographic or work related factors.The FDs who were sure that they were able to modify the patients' harmful habits as well as family relationships were more likely to estimate their preparedness for the management of these issues as adequate. Among the doctors who reported that their preparedness for counselling for lifestyle issues was adequate, 76% (n = 76) believed that they were able to treat harmful habits, The present study addressed the family doctors' opinions about their involvement in the patients' family issues. This is the first study of this kind conducted in Estonia, a country where family doctors were introduced into the health care system ten years ago. There is yet no definite agreement as to what are the appropriate, ideal or minimal levels of family orientation that family doctors should have . SeveralOur study revealed that care of patients in the context of the family is an important issue for FDs and that Estonian family doctors have good possibilities to take care of the whole family. Although all patients have the right to choose an individual family doctor, the FDs who responded to the questionnaire were sure that family members mostly have one and the same family doctor. This is concordant with the results of a recent survey among patients according to which 74% of the respondents reported that they had one and the same family physician for the whole family . In EstoIn our study, altogether 90% of the family doctors thought that they should communicate and cooperate with family members in management of the health problems of patients. It is a good result considering that family medicine is a new and developing speciality in Estonia. At the same time, most family doctors are not yet ready to deal with the family members' emotional and relationship problems. Primary care is an important early intervention site of most serious relationship issues, domestic violence, etc . HoweverConcerning the family doctors' attitudes to the importance of awareness of their patients' family-related issues, the results indicated that the awareness of drug addiction, diseases of family members, living conditions of the family and alcohol problems in the family were considered the most essential. The awareness of the patients' relationship problems, economic problems and leisure activities was not so highly valued. A recent survey among patients in Estonia revealed that they were also more disposed to involve the family physician in such problems as harmful habits and diseases in the family, but they were less willing to share the relationship problems . This caThe low willingness to be aware of the patients' relationship problems is partly related to insufficient preparedness in this field, as the doctors who considered themselves to be adequately prepared to tackle relationship issues were also more often willing to do this. From another point of view, family issues, especially relationships and economic situation, are always delicate topics and require consideration of the patient's attitude to corresponding activities. It has been shown that patients vary considerably in their preferences for physician inquiries into such problems as social functioning, psychosocial issues and health risks. Also, it may reflect cultural differences: in the Nordic countries biomedical talk is more common, while in the southern regions psychosocial dialogue is prevalent .Although most of the family doctors agreed that modifying of the health damaging risk factors  of their patients was their task, they also felt that management of these problems was ineffective, or they perceived themselves as poorly prepared, or had lack of time for such activities. This shows that despite the fact that family doctors are becoming increasingly more aware of their role, there exists the actual need to improve their instruments for handling lifestyle related and psychosocial problems. In practice, both individual and family–centered working methods are needed, while the choice depends on the patient's problems and needs . ManagemThe results of the present study allow to conclude that Estonian family practitioners are favourably disposed to involvement in family-related problems, but they need additional training especially in the field of relationship management.The author(s) declare that they have no competing interests.All authors participated in the design of the study. MO and RK carried out the data collection, performed the data analyses and drafted the manuscript. All authors participated in the discussion of the drafts. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Timeliness is a key performance measure of public health surveillance systems. Timeliness can vary by disease, intended use of the data, and public health system level. Studies were reviewed to describe methods used to evaluate timeliness and the reporting timeliness of National Notifiable Diseases Surveillance System (NNDSS) data was evaluated to determine if this system could support timely notification and state response to multistate outbreaks.Published papers that quantitatively measured timeliness of infectious disease surveillance systems operating in the U.S. were reviewed. Median reporting timeliness lags were computed for selected nationally notifiable infectious diseases based on a state-assigned week number and various date types. The percentage of cases reported within the estimated incubation periods for each disease was also computed.Escherichia coli O157:H7 infection, meningococcal disease, salmonellosis, and shigellosis, less than 40% of cases were reported within one incubation period for each reported date type.Few studies have published quantitative measures of reporting timeliness; these studies do not evaluate timeliness in a standard manner. When timeliness of NNDSS data was evaluated, the median national reporting delay, based on date of disease onset, ranged from 12 days for meningococcal disease to 40 days for pertussis. Diseases with the longer incubation periods tended to have a higher percentage of cases reported within its incubation period. For acute hepatitis A virus infection, which had the longest incubation period of the diseases studied, more than 60% of cases were reported within one incubation period for each date type reported. For cryptosporidiosis, Published evaluations of infectious disease surveillance reporting timeliness are few in number and are not comparable. A more standardized approach for evaluating and describing surveillance system timeliness should be considered; a recommended methodology is presented. Our analysis of NNDSS reporting timeliness indicated that among the conditions evaluated (except for acute hepatitis A infection), the long reporting lag and the variability across states limits the usefulness of NNDSS data and aberration detection analysis of those data for identification of and timely response to multistate outbreaks. Further evaluation of the factors that contribute to NNDSS reporting timeliness is warranted. Public health surveillance is defined as the "ongoing systematic collection, analysis, and interpretation of data essential to the planning, implementation, and evaluation of public health practice, closely integrated with the timely dissemination of these data to those who need to know". ReasonsTimeliness is a key surveillance system metric and should be periodically evaluated ,4 becausBefore data can be used for public health action, health-related data must be collected by the public health system, analyzed, and disseminated to those responsible for taking action Figure . Within Each week, states and the U.S. territories report case information on persons suspected of having or diagnosed with a nationally notifiable infectious disease to the Nationally Notifiable Diseases Surveillance System (NNDSS), maintained by the Centers for Disease Control and Prevention (CDC) . A natioInfectious disease surveillance evaluation studies reporting timeliness measures that were published between January 1970 and March 2003 in biomedical and public health literature were reviewed. English-language papers were identified by using the Medline database . The search strategy used various combinations of the following key words "timeliness," "reporting delay," "time delay," "lag time," "disease surveillance," "disease outbreaks," "communicable diseases," and "infectious diseases." Reference lists of the studies identified through the Medline search and studies citing CDC's surveillance evaluation guidelines were also reviewed [Reports were included if they evaluated a public health surveillance system operating in the United States and provided a quantitative estimate of disease-specific timeliness . Studies without quantitative timeliness estimates or that reported a quantitative estimate for a group of infectious diseases (versus a disease-specific estimate) were excluded. In addition, studies describing the timeliness of syndromic surveillance systems were excluded.Information abstracted for the review included the disease(s) under surveillance, the geographic area and time period studied, the purpose of the surveillance evaluation, the surveillance time interval measured, the surveillance processes or actions  from the following list of hierarchical date types: onset date, diagnosis date, date of laboratory result, or date of first report to the community health system. National reporting delay was calculated as the difference in days between the midpoint of the MMWR week and the earliest known date reported in association with the case. This time interval reflects various state-specific surveillance intervals in the surveillance process that occur between the occurrence of a health event and the reporting of that health event to NNDSS, but at a minimum it includes Intervals 1–4 , 30 days for acute hepatitis A virus infection, 4 days for meningococcal disease, 20 days for pertussis, 1.5 days for salmonellosis, and 3 days for shigellosis [To assess whether analysis of NNDSS data could support the timely identification of multistate outbreaks at the national level, the percentage of NNDSS cases reports reported within one to two incubation periods for each of the diseases was determined. Incubation periods were used as a surrogate measure for period of communicability which is critical to consider when implementing effective, disease-specific prevention and control measures. For this analysis, estimated incubation periods were used for the seven nationally notifiable infectious diseases selected for this study: 7 days for cryptosporidiosis, 4 days for gellosis . These dMMWR years 1999, 2000, and 2001.Only finalized case-specific data reported from U.S. states and two autonomous reporting entities  that designated the reported condition as notifiable (reportable by law or regulation) and that met NNDSS publication criteria  were incNeisseria meningitidis and Haemophilus influenzae infections [Eight papers were identified that met the inclusion criteria for this study  response .Neisseria meningitidis infection surveillance system for 1989–1992 indicated that the lengthy reporting interval limited the usefulness of the system for supporting rapid response for control and prevention [The reporting timeliness of AIDS and bacterial meningitis  surveillance systems were more frequently assessed than those for other infectious diseases. The AIDS reporting timeliness studies indicate that local and national AIDS reporting timeliness meets the goals of the AIDS surveillance systems monitoring trends, targeting prevention programs, estimating needs for medical and social services, and allocating resources ,15,17. Tevention . In contevention . In addievention .The definition of reference dates used in the timeliness evaluations varied. The initial date associated with the case varied among date of disease onset, date of diagnosis, and date of positive culture result. The ending date for the timeliness studies evaluated was the date the case report was received by the public health system, whether at the local, state, or national level. This time period corresponds to the sum of Intervals 1 and 2 or Interval 2 alone for local or state timeliness studies  cryptosporidiosis case reports, 9,674 (78.4%) case reports of E. coli O157:H7 infection, 32,953 (80.3%) case reports of acute hepatitis A virus infection, 5,580 (78.7%) case reports of meningococcal disease, 19,904 (87.5%) case reports of pertussis, 84,746 (70.2%) case reports of salmonellosis, and 41,643 (68.6%) case reports of shigellosis were eligible for analysis. A total of 72,293 (26.4%) case reports were excluded for one or more of the following reasons: reported as a summary or aggregate record in which individual cases may have different event dates , unknown or missing date types , date type coded to MMWR report date , and calculated reporting lag had a value of zero (indicating the event date and midpoint of the MMWR week matched) or had a negative value .For Timeliness of reporting varied by disease and date type Table . For casFor the same date type, NNDSS diseases with longest incubation periods tended to have a higher percentage of cases reported within one or two incubation periods than NNDSS diseases with shorter incubation periods Table . For exaNeisseria meningitidis infection (median 21 days). In addition, the median reporting delay between disease onset and the date of report to CDC was shorter in this study than in a previous study (which used 1987 notifiable disease data) by 10 days for hepatitis A, 5 days for salmonellosis, and 8 days for shigellosis [The 1999–2001 NNDSS meningococcal disease median reporting interval between date of disease onset and date of report to CDC in this study was 8 days shorter than a previous study reported  using 19gellosis .Few published studies evaluating surveillance systems presented timeliness measures. When timeliness was evaluated, standard methods were not used. Information collected by public health surveillance systems should support the quantitative assessment of timeliness by various steps in the pubic health surveillance process. Public health programs should periodically assess timeliness of specific steps in the surveillance system process to ensure that the objectives of the surveillance system are being met. A more structured approach to describing timeliness studies should be considered.Published papers describing local or state surveillance system reporting timeliness generally do not explicitly describe the surveillance system processes contributing to the timeliness measure, such as processing and analyzing the data or implementing a public health action before data are reported from a state to CDC. To facilitate future comparisons of reporting timeliness across jurisdictions, studies should include an explicit description of the public health surveillance reporting process and the surveillance process interval being measured. Additionally, surveillance information systems must support the collection of appropriate reference dates to allow the assessment of the timeliness of specific surveillance processes.A more structured approach to describing timeliness studies could include a description of the following characteristics: 1) the level of the public health system being assessed , 2) the purpose of the surveillance evaluation, 3) goals of the surveillance system, 4) the surveillance interval being measured and a description of the reference dates that define the upper and lower boundaries of the surveillance interval, 5) the surveillance steps (processes or activities) that contribute to the surveillance interval being measured, 6) whether the measured timeliness met the needs of the surveillance step being evaluated, and 7) whether the timeliness met the goals of the surveillance system. No single timeliness measure will achieve the purpose of all evaluations or meet all the goals of the surveillance system. In addition, if the goal of the surveillance evaluation is to identify ways to improve timeliness, the analysis should identify factors associated with delayed reporting, such as the role of specific case ascertainment sources.E. coli O157:H7, meningococcal disease, salmonellosis, and shigellosis). Until reporting timeliness is enhanced, the application of aberration detection analytic methods to NNDSS data to aid in the identification of changes in disease reporting that may indicate a multistate outbreak in time to alert states for the purposes of disease control and prevention may be of limited use. Future work to improve reporting timeliness will need to address the substantial variation across states. As states enhance their reporting mechanisms with the use of automated electronic laboratory reporting systems [The 1999–2001 national notifiable diseases data were timely enough to support the following surveillance objectives: monitoring trends over time, informing allocation of public health resources, monitoring the effectiveness of disease control, identifying high risk populations, and testing hypotheses. If NNDSS data are to be used to support timely identification of and response to multistate outbreaks at the national level, the timeliness of reporting needs to be enhanced for all diseases, but especially for diseases with the shortest incubation periods  cases were excluded from our analysis because the information contained in the database would not permit calculation of timeliness and this exclusion may have resulted in our study results either falsely overestimating or underestimating the magnitude of NNDSS reporting lags.Our study findings are subject to several limitations. The variables available for assessing NNDSS reporting timeliness are based on the MMWR week numbers. Other factors that might have contributed to reporting delay in our study included: the patient's recognition of symptoms; the patient's acquisition of medical care; the use of confirmatory laboratory testing; reporting by the health care provider or the laboratory to the local, county, or state public health authority; the volume of cases identified in the state; case follow-up investigations to verify the case report or to collect additional case information; periods of decreased surveillance system activity due to variable staffing levels; computer system down-time for maintenance, upgrades, or new application development; and data processing routines, such as data validation or error checking. Following a structured approach to evaluation of timeliness by specifying the surveillance objectives and the process(es) being measured may allow better definition of the factors that contribute to reporting delay. It was beyond the scope of this study to assess how these factors contribute to NNDSS reporting timeliness.The reporting timeliness variations across states may result from different reporting protocols in the states  or from variations in how states assign In addition to reporting timeliness, other surveillance system attributes are important to assess . Completeness of notifiable infectious diseases reporting in the United States varies from 9% to 99% . Six of To improve public health surveillance infrastructure and performance in the United States, CDC and local and state health agencies are integrating a number of public health surveillance systems monitoring infectious diseases in the United States, including the NNDSS, into the National Electronic Disease Surveillance System (NEDSS) ,20. NEDSTo facilitate comparisons of surveillance system timeliness studies across jurisdictions or health conditions, a more standardized approach to describing timeliness studies is warranted. Public health surveillance systems should ensure that timeliness can be measured for specific surveillance system processes and in the context of the goals of surveillance. In addition, when timeliness is being measured, it is important to be explicit about how it is being measured. Our analysis of NNDSS reporting timeliness suggests that current acute hepatitis A infection reporting timeliness may be sufficient to support a timely public health response in the event of a multistate outbreak. However, for the other conditions evaluated, the long reporting lag and the variability across states limits the usefulness of NNDSS data and aberration detection analysis of those data for identification of and response to multistate outbreaks. The NNDSS timeliness data presented in this paper represents a baseline against which timeliness can be measured in the future. Further study is needed to identify the major sources of reporting delay and to assess how NNDSS reporting timeliness may be improved for the timely detection of cases and disease clusters.None declared.Both authors contributed equally to project conception and write-up of the manuscript. RAJ was responsible for data analysis. Both authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:Published reports quantitatively measuring timeliness of reporting infectious disease surveillance data. Table summarizes the findings of the review of published literature about quantitative measurements of infectious disease surveillance system timelinessClick here for file


Shigella spp. was reported to be the third commonest bacterial agent responsible for childhood diarrhoea. Currently, isolation of the bacterium and confirmation of the disease by microbiological and biochemical methods remain as the "gold standard". This study aimed to detect the prevalence of four Shigella virulence genes present concurrently, in randomly selected Malaysian strains via a rapid multiplex PCR (mPCR) assay.In Malaysia, set1A, set1B, ial and ipaH) in Shigella spp. One hundred and ten Malaysian strains (1997–2000) isolated from patients from various government hospitals were used. Reproducibility and sensitivity of the assay were also evaluated. Applicability of the mPCR in clinical settings was tested with spiked faeces following preincubation in brain heart infusion (BHI) broth.A mPCR assay was designed for the simultaneous detection of chromosomal- and plasmid-encoded virulence genes  of shigellae per reaction mixture in spiked faeces following preincubation.The The mPCR system is reproducible, sensitive and is able to identify pathogenic strains of shigellae irrespective of the locality of the virulence genes. It can be easily performed with a high throughput to give a presumptive identification of the causal pathogen. Shigella, namely S. flexneri, S. dysenteriae, S. sonnei and S. boydii have caused and continue to be responsible for mortality and/or morbidity in high risk populations such as children under five years of age, senior citizens, toddlers in day-care centres, patients in custodial institutions, homosexual men and, war- and famine-engulfed people. Yearly episodes of shigellosis globally have been estimated to be 164.7 million and of these, 163.2 million were in developing countries and the remaining in industrialized nations. The mortality rate was approximately 0.7% [Shigella spp. was the third most common bacteria isolated. S. flexneri and S. dysenteriae type 1 infections are usually characterized by frequent passage of small amounts of stool and mucus or blood. At times, watery stool followed by typical dysenteric stool maybe present with S. dysenteriae type 1 infection. S. sonnei and S. boydii infections are less severe with watery faeces but little mucus or blood.Members of the genus Shigellosis is usually a self-limiting infection, however when it subsides, the intestinal ulcers heal with scar tissue formation. Uncomplicated recovery is usual and the organisms rarely cause other types of infections. Adversely, in 3 to 50% of cases, depending on the virulence of the strain, the nutritional and immune status of the host, the initial infection maybe followed by neurological complications or kidney failure. Serious complications do occur at greatest frequencies in malnourished infants, toddlers, older adults and immunocompromised individuals .inv plasmid borne by the organism. They are often multifactorial and coordinately regulated, and the genes tend to be clustered in the genome. Previously reported PCR-based detection methods concentrated mainly on the ipaH gene alone [ipaH and ial genes in two separate PCR assays [ial is found on the large inv plasmid which is prone to loss or deletions, this gene-based detection may give false negative results. ipaH, on the other hand, is present on both the Shigella chromosome and on a large plasmid and hence, it is a more stable gene to detect. However, the sole presence of ipaH is not an absolute indicator of virulence as loss or deletion of the plasmid renders the bacterium noninvasive and therefore, avirulent. set1A and set1B are chromosomal genes encoding Shigella enterotoxin 1 (ShET1), which cause the watery phase of diarrhoea in shigellosis [ial and ipaH are responsible for directing epithelial cell penetration by the bacterium and for the modification of host response to infection, respectively [Virulence genes responsible for the pathogenesis of shigellosis may be located in the chromosome or on the ne alone ,6 or on R assays ,8. As iagellosis ,10. ial ectively -13.set1A, set1B, ial and ipaH) in Shigella spp. and to determine the prevalence of these virulence genes in a random selection of Malaysian Shigella strains.Here, we describe the application of a multiplex PCR (mPCR) design for simultaneous detection of four virulence genes (Shigella strains of S. flexneri (n = 84), S. sonnei (n = 15), S. dysenteriae (n = 10) and S. boydii (n = 1) were used in this study. These strains were isolated from patients with diarrhoea in Peninsular Malaysia from 1997–2000, and were provided by the Institute for Medical Research (IMR), Malaysia. Serotyping of the strains  was carried out by the Bacteriological Unit, IMR. All the strains were checked on Salmonella-Shigella (SS) agar before being transferred to Luria Bertani (LB) agar plate, incubated overnight at 37°C for subsequent screening of virulence-associated genes. All strains were stored at -20°C in LB broth containing 15% glycerol.A total of 110 2, 130 μM of each deoxynucleotide (dNTP), 0.5 μM of each primer, 1 U of Taq DNA polymerase  and 2 μl of DNA template. Amplifications were carried out using a Robocycler Gradient 40 Temperature Cycler . The cycling conditions were an initial denaturation at 95°C for 5 min, template denaturation at 95°C for 50 s, annealing at 55°C for 1.5 min, and extension at 72°C for 2 min for a total of 30 cycles, with a final extension at 72°C for 7 min.Boiled suspension of bacterial cells was used as DNA template. Previously described primers, obtained from Integrated DNA Techs, USA, for detection of the four virulence genes were applied to the template ,14,15 (T2 (2 to 4 μM), Taq DNA polymerase (0.6 to 4 U) and dNTPs (100–150 μM) and buffer strength (1.4X to 2.4X) were tested. The simultaneous gene amplifications were performed in a reaction volume of 25 μl consisting of 1.8X PCR buffer B , 4 mM MgCl2, 130 μM of each dNTP, 0.3 μM of each ShET1B primer, Shig1 and Shig2 primers, 0.5 μM of each ShET1A and ial primers, 1 U of Taq DNA polymerase  and 2 μl of DNA template. All the reaction mixtures were overlaid with 20 μl of sterile mineral oil. Amplifications were similarly carried out as above.Based on the results of individual priming, an mPCR was designed. Various parameters such as concentrations of primers (0.5–0.8 μM), MgClS. flexneri 2a) was chosen as a positive control for PCR assays. A negative control using sterile distilled water as template was included in every PCR assay. The DNA fragments were separated in 2% agarose gel.After initial screening, strain TH13/00 , S. Paratyphi C, S. Typhimurium, S. Enteritidis, S. Typhi (ATCC 7251), Listeria monocytogenes, Pseudomonas aeruginosa, Klebsiella pneumoniae, Citrobacter freundii, Escherichia coli O157:H7 and E. coli O78:H11.The specificity of the mPCR assay was tested with 12 other non-S. flexneri 2a was harvested and serially diluted 10-fold with BHI. Then, 250 μl of each dilution of cell culture was mixed with 250 μl of the broth-faecal suspension and 500 μl of BHI in a new eppendorf tube. The tubes were vortexed and preincubated at 37°C for 4 h without shaking. Simultaneously, 100 μl of each diluted culture was plated on LB agar  to determine the number of viable bacteria in each dilution. After preincubation, mPCR assay was performed on the boiled lysates of each diluted culture. A pure culture of S. flexneri 2a (TH13/00) and an unspiked faecal sample served as positive and negative controls.. The test was repeated with a spiked faecal sample of another healthy individual, and the average detection limit was reported.This was based on a modification of that described by Chiu and Ou . ApproxiSS agar plates and incubated overnight at 37°C. mPCR assay was performed on the boiled lysate of the broth-faecal suspension after preincubation. A pure culture of strain TH13/00 and a Shigella-spiked faecal sample served as a positive control, whilst a PCR reaction mixture without bacterial DNA template and an unspiked faecal sample from a healthy individual acted as a negative control.0.2 g of each faecal sample from 10 patients suffering from diarrhoea in a local tertiary University Hospital was suspended in 1 ml of BHI and diluted 10-fold. A volume of 250 μl of broth-faecal suspension was inoculated into 5 ml of BHI and preincubated at 37°C for 4 h without shaking. Concurrently, 100 μl of the suspension was plated onto MacConkey and 2 (3 mM), dNTP (400 μM each) and primers (1 μM each) were used as recommended, unspecific bands were present together with intense primer-dimers. In order to reduce the background noise and primer-dimers, concentrations of 0.5 μM of each primer and 200 μM of each dNTP were used. Further optimizations of MgCl2 concentrations (2 to 4 μM) and dNTP  gave intense amplicons with a clean background in each monoplex amplification  and set1B (ShET1B) were reduced to 0.3 μM each and the primers for both set1A (ShET1A) and ial  genes were maintained at 0.5 μM each. Following optimization of the concentrations of Taq DNA polymerase (0.6 to 4U/25 μL), buffer strength (1.4 X to 2.4 X), dNTPs (140 to 220 μM) and annealing temperatures (49 to 59°C) (at a constant MgCl2 concentration of 4 mM), a more uniform amplification of all the genes with no background noise was obtained  is to increase the amount of primers of the gene at same time with a decrease of the amount of primers for all the loci that can be amplified, especially those with strong amplifications. Hence, the concentrations of primers for both Shigella spp. tested showed the presence of ipaH  belonged to S. flexneri 2a serotype. Among the predominant strains of Shigella flexneri in Malaysia, ial was found in serotypes 4a, 6, 3a, 2a, 1a and 3c. All the four genes were present only in S. flexneri 2a and 3a.All the 110 strains of aH Table . Conversset1A, set1B, ial and ipaH genes assayed in the mPCR was 100%. None of the non-Shigella strains tested gave any amplification (data not shown).Reproducibility for the detection ofS. flexneri 2a. All the four virulence-associated genes were detected until 10-3 dilutions (data not shown). This was equivalent to 2.45 × 105 lysate or a minimum of 490 cfu of shigellae per 25 -μLmPCR reaction.The mPCR assay was tested on 10-fold dilutions of an overnight culture of 4 colony-forming units (cfu) shigellae ml-1 or approximately 100 cfu per reaction mixture . When the faecal suspension was diluted and preincubated in BHI for 4 h, the mPCR assay was successful in detecting the presence of the four virulence genes at an average concentration of 5.0 × 10ure Fig.  lane 8.Shigella virulence genes on faecal samples was tested on ten diarrhoeal patients. No mPCR product was detected although both the positive controls had amplifications. By conventional culture method, there was no growth of Shigella on the LB, MacConkey and SS agar plates.A preliminary study on the efficacy of the mPCR assay in the direct detection of the aforementioned Shigella by monoplex PCRs [Shigella detection, on the other hand, are scarce. Although the optimization of mPCR is more tedious and difficult to achieve than monoplexes, the ease of screening a large number of specimens, once the system is optimized, far outweighs the initial problems. The present mPCR system encompasses the presence of virulence genes found in the Shigella chromosome and on the large inv plasmid. Hence, it can determine if the pathogenesis of a particular strain is attributable to its chromosome or the plasmid, or if the strain is still invasive or otherwise, in a single reaction.Numerous studies had been performed to detect virulence genes in lex PCRs ,17,18. Set al. [Taq DNA polymerases and found that they displayed different specificity in PCR.Initially, the monoplex PCRs were carried out following reaction conditions as proposed by a previous report . Howeveret al.  had compPreferential amplification of one target sequence over another is a known phenomenon in mPCRs and it is usually overcome by increasing the amount of primers for the weaker amplification simultaneously with a decrease of primer concentrations for the stronger amplification. Buffer concentration may also affect mPCR amplifications despite it being seldom considered during monoplex optimization works . Upon adial and ipaH in strains of enteroinvasive Escherichia coli (EIEC) [Although other studies have demonstrated the presence of i (EIEC) ,13,21, wet al. [et al. [Shigella strains. Their studies showed that both set1A and set1B were present exclusively in S. flexneri 2a. The complete correlation between the presence of both set1A and set1B showed that both genes are indeed found in tandem in the Shigella genome. In this study, almost all the Shigella strains positive for the presence of set1A and set1B (41/45 strains) belonged to S. flexneri 2a, thus confirming previous works that both genes are highly conserved in this particular serotype [Our study supported the observations of Noriega et al.  and Varg [et al.  in localserotype .ial and ipaH were independent of the four different species of Shigella tested. Though both ial and ipaH are responsible for invasion-related processes and are found on the inv plasmid, the ial gene cluster resides near a region of the plasmid, which is a hot spot for spontaneous deletions [ial (45/110 strains) than ipaH (110/110 strains) in the Malaysian Shigella strains. Since invasiveness is a prerequisite for virulence in shigellae and since most of these virulence genes are located on the large plasmid, these strains would have possessed the plasmid when first isolated from patients. Due to storage/subculturing, the plasmid might have been lost together with the virulence-associated genes. By virtue of multiple copies being present on both the chromosome and the inv plasmid [ipaH seemed to be less compromised by plasmid loss and/or deletions. As the sole presence of ipaH is not indicative of the invasive phenotype, our mPCR design, which incorporated three other virulence genes, could determine the invasiveness of Shigella strains in epidemiological studies.Both the prevalence of eletions . This pr plasmid , ipaH seet al. [4 cfu shigellae ml-1 by amplifying the IS 630 sequences in shigella spp.. Yavzori et al. [4 cfu shigellae per gram of faeces with the use of virF primers. Although it has been reported that ingestion as low as 100 shigellae resulted in clinical disease [4 viable organisms. Thus, the average detection limit of mPCR described in this study (5.0 × 104 cfu/ml) is within the common infectious dose for shigellae.Dilution of the faecal sample with BHI was performed to lower the levels of PCR inhibitors such as bilirubin, bile salts and heme in the faeces . An addiet al.  detectedi et al.  reported disease , the higResults from the preliminary clinical screening were promising. Nevertheless, the consideration of other diarrhoeal pathogens being present in the clinical samples cannot be negated. More patient samples are warranted to thoroughly vet the robustness and applicability of the developed mPCR in clinical environments.Shigella spp., unlike the multiplex reactions based on specific rfc genes developed by Houng et al. [set1A or set1B may be omitted from the multiplex system as both genes are shown to exist tandemly. rfc primers of different Shigella origins maybe incorporated to enable the discrimination of Shigella spp. as well as the identification of virulent strains in one assay.One limitation of the present mPCR system is its inability to differentiate g et al. . For futial and ipaH genes.We conclude that the mPCR system is able to identify pathogenic strains of shigellae irrespective of the locality of the virulence genes. The described assay is reproducible, sensitive, can be easily performed and is able to give a presumptive identification of the causal pathogen, which could be confirmed by culture techniques using selective media. An added advantage would be that EIEC, which gives a similar illness, might also be detected by this method, as EIEC also harbours The author(s) declare that they have no competing interests.SLLH carried out the experiments, data analysis and wrote the manuscript. RMY provided the bacterial strains. SDP contributed to the writing of the manuscript. TKL conceived and co-designed the study, provided input for writing and supervision of the study. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Suction drains are routinely used after modified radical mastectomy and are an important factor contributing to increased hospital stay as the patients are often discharged only after their removal. Amongst various factors that influence the amount of postoperative drainage, the negative suction pressure applied to the drain has been reported to be of great significance. While a high negative suction pressure is expected to drain the collection and reduce the dead space promptly, it may also prevent the leaking lymphatics from closing and lead to increased drainage from the wound. Against this background a prospective randomized clinical study was conducted to compare the amount and duration of drainage between a half negative suction and full vacuum suction drainage in patients following modified radical mastectomy. The associated postoperative morbidity was also compared between the two groups.85 FNAC (fine needle aspiration cytology) proven cases of locally advanced breast cancer were randomized.  in to 50 patients with full vacuum suction (pressure = 700 g/m2) and 35 cases in to half vacuum suction drainage (pressure = 350 g/m2) groups. The two groups were comparable in respect of age, weight, and technique of operation and extent of axillary dissection. Surgery was performed by the same surgical team comprising of five surgeons (two senior and three resident surgeons) using a standardized technique with electrocautery. External compression dressing was provided over the axilla for first 48 hrs and following that patients were encouraged to do active and passive shoulder exercises. The outcomes measured were postoperative morbidity and the length of hospital stay.Statistical methods used: Descriptive studies were performed with SPSS version 10 and group characteristics were compared using student t-test.Half vacuum suction drains were removed earlier than the full suction vacuum suction drains. There was no significant difference in the incidence of seroma formation in the two groups and there was a significant reduction in the total hospital stay in patients with half vacuum suction drainage systems as compared to the full suction drainage group (p < 0.001) without any added morbidity.Half negative suction drains provide an effective compromise between no suction and full or high suction drainage after modified radical mastectomy by reducing the hospital stay and the post operative morbidity including post operative seromas. This on drain . The amoThe study also compared the drain volume, average hospital stay and postoperative morbidity between full vacuum and half vacuum suction groups.The study was conducted in one surgical unit of a tertiary care center over a period of two years.85, FNAC (fine needle aspiration cytology) proven cases of locally advanced breast cancer were randomized  into full vacuum suction (pressure = 700 g/m2) group – (A) and 35 cases into half vacuum suction (pressure = 350 g/m2) group – (B). The two groups were comparable in respect of age, weight and type of operation i.e. modified radical mastectomy (MRM). Following complete routine and metastatic work up, all patients received three cycles of Neoadjuvant chemotherapy (NACT) using CAF regime  and underwent Patey's modified radical mastectomy after three weeks of the last cycle. Surgery was performed by the same surgical team comprising of five surgeons (two senior and three resident surgeons) using a standardized technique with electro cautery. Axillary dissection was done up to level- III in all the cases. The boundaries of axillary dissection were defined by superior limit as the posterolateral border of the Pectoralis major muscle and axillary vein, medial limit being clavipectoral fascia or Hallstead's ligament, lateral limit as the anterior border of lattismus dorsi and the inferior limit being the angular vein joining the thoracodorsal vein. The long thoracic and thoracodorsal nerves were identified, dissected and preserved. Two silicone tube drains 12Fr)  were inserted in all the patients. All resected specimens were examined and the lymph nodes dissected, counted and assessed histo-pathologically for metastases. No patient received intra-operative blood transfusion. Both the drains were connected to a single 600 ml suction bottle (Romovac -Romson). In-group A (n = 50), drainage was performed using complete vacuum negative suction (700 g/m2) and in-group B (n = 35) with half vacuum suction drainage (350 g/m2). The pressure was also measured by attaching a manometer to the exit opening of the drainage bottle. The two groups were comparable with respect to age, weight (body mass index), type of operation indicating the success of randomization 1.Technique: Use of elctrocautery has been reported to be associated with increased incidence of seroma formation as compared to cold knife. It has also been reported that tissue ligation around the axillary vein rather than mere transection with knife or diathermy may reduce the amount of postoperative discharge, the technique was followed in the presented study [2. ed study .Drains themselves encourage drainage by stimulating tissue reactions or by suction [3  suction Early shoulder exercises have been implicated but were not observed to be a factor in the present study [4.nt study ,11 Althont study ,11.The negative suction applied may prevent the lymphatics from closing leading to continuous leakage and discharge [5 ischarge .Extent of axillary dissection. More seromas were seen when more lymph nodes were dissected from the axilla. The higher lymph node yield may well be an indirect measure of more extensive dissection performed. [6.rformed. . The draIt is an accepted fact that negative suction prevents seroma collection and helps in the adherence of the walls of the axilla thus reducing the dead space and allowing the lymphatics to close. High negative suction pressure generated by the drain can maintain lymph drainage by a negative pressure gradient . It is aReducing the negative suction pressure applied to the drain  along with external compression dressings applied for first 48 hours can significantly reduce drainage from the axilla following modified radical mastectomy without increasing the incidence of seroma formation as was observed in this randomized prospective clinical study. The hospital stay was reduced considerably compared to a matched group with full suction drain (p < 0.001). Half suction drain following axillary dissection in patients with carcinoma breast may thus be recommended as an effective approach to reducing the hospital stay and the cost of treatment without adding to the morbidity.The author(s) declare that they have no competing interests.CM was the surgeon in charge of the project and prepared the study design. VS was the first surgical assistant and did the data processing and statistical analysis. JP, the second surgical assistant assisted in the preparation of the manuscript. SS the Director of ICMR and AB the research officer, Tumor Biology Lab ICMR were responsible for the histopathological analysis and contributed to the preparation of the manuscript.The pre-publication history for this paper can be accessed here:


This contrast is typically used to distinguish the exposure's indirect effect, through the specified intermediate variables, from its direct effect, transmitted via pathways that do not involve the specified intermediates.Epidemiologic research is often devoted to etiologic investigation, and so techniques that may facilitate mechanistic inferences are attractive. Some of these techniques rely on rigid and/or unrealistic assumptions, making the biologic inferences tenuous. The methodology investigated here is We apply a causal framework based on latent potential response types to describe the limitations inherent in effect decomposition analysis. For simplicity, we assume three measured binary variables with monotonic effects and randomized exposure, and use difference contrasts as measures of causal effect. Previous authors showed that confounding between intermediate and the outcome threatens the validity of the decomposition strategy, even if exposure is randomized. We define exchangeability conditions for absence of confounding of causal effects of exposure and intermediate, and generate two example populations in which the no-confounding conditions are satisfied. In one population we impose an additional prohibition against unit-level interaction (synergism). We evaluate the performance of the decomposition strategy against true values of the causal effects, as defined by the proportions of latent potential response types in the two populations.We demonstrate that even when there is no confounding, partition of the total effect into direct and indirect effects is not reliably valid. Decomposition is valid only with the additional restriction that the population contain no units in which exposure and intermediate interact to cause the outcome. This restriction implies homogeneity of causal effects across strata of the intermediate.Reliable effect decomposition requires not only absence of confounding, but also absence of unit-level interaction and use of linear contrasts as measures of causal effect. Epidemiologists should be wary of etiologic inference based on adjusting for intermediates, especially when using ratio effect measures or when absence of interacting potential response types cannot be confidently asserted. A large portion of epidemiologic research is devoted to etiologic investigation, and so techniques that may facilitate mechanistic inferences are sought by researchers and are applied frequently in their work. Unfortunately, some of these techniques have been found to provide far more ambiguous evidence on which to base mechanistic conclusions than was first believed. For example, analysis of patterns of joint effects has been proposed as a means of identifying causal structure , but simThe list of such untenable overgeneralizations in epidemiologic practice is surely large and varied, and has led to any number of false conclusions and misunderstandings. We describe here one particular epidemiologic technique that is applied frequently in practice, and yet is invalid in all but a surprisingly narrow range of circumstances. It is a remarkable example in that the analytic strategy is exceedingly common, and yet is described infrequently in epidemiologic texts or methodologic articles. The few textbook citations that do exist provide no formal justification, and therefore there is little guidance available from within the sources in our field to guide users and warn them of important limitations of this approach. This situation motivates the present article, in which we will show that although widely applied, this analytic approach is almost never justifiable on the basis of reasonable assumptions about the data.indirect effect, through the specified intermediate variables, from its direct effect, transmitted via pathways that do not involve the specified intermediate variables. If control of hypothetical causal intermediates greatly attenuates an exposure's estimated effect, it is generally inferred that the exposure's effect is mediated primarily through pathways involving these quantities; a small degree of attenuation is interpreted as evidence that other pathways predominate. These mechanistic inferences then inform policy recommendations concerning the utility of potential interventions. Although this effect decomposition approach is quite common in the epidemiologic literature, its general validity has not been adequately investigated.The methodologic approach of interest in this article is the decomposition of effects purportedly accomplished by contrasting two adjusted effect estimates for the exposure of interest: an estimate adjusted for potential confounders, and an estimate adjusted for the same set of potential confounders plus one or more additional variables hypothesized to be causal intermediates, i.e., to lie on pathway(s) through which the exposure exerts its effect. This contrast is then typically used to distinguish the exposure's This analytic strategy for effect decomposition in epidemiologic research is recommended by Susser , pp. 121, pp. 184U/RRA, or the percent excess risk explained by the variables adjusted for:  "." The degree to which a given mechanism...explains the relationship of interest is given by the comparison of adjusted (A) and unadjusted (U) measures of association . This comparison can be made using the ratio of the unadjusted RRs, RRCalculations similar to this "% Excess Risk Explained" are the most common framework for describing the effect decomposition analysis in epidemiologic research.For example, a study by Heck and Pamuk investigated the relation between education and postmenopausal breast cancer incidence using data from the National Health and Nutrition Examination Survey I Epidemiologic Follow-up Study. ProportIn a seminal article on the topic, Robins & Greenland employedOur critique would appear to contradict standard practice in the social sciences, in which decomposition analysis is also commonly applied,18. We sFor clarity, we limit our exposition to the simplest possible decomposition problem, which is the structure that includes three measured binary variables and sample size sufficiently large to justify the assumption of zero sampling error (see endnote 1). The three variables are designated as X, Y and Z. The causal relationships between these nodes are described by the directed acyclic graph (DAG) in Figuru at node Z is denoted by Zux where index u identifies the individual unit and index x specifies the X value factually or counterfactually experienced by that unit. Given the deterministic model at the individual unit level, there are four possible patterns of response Zux to input x that unit u can exhibit, and these have received various appellations in the literature, such as "doomed" for Zux= 1 regardless of x, "causal" for Zux= x, "preventive" for Zux= 1-x, and "immune" for Zux = 0 regardless of x = average causal effectACE= Pr(Y = 1|SET[X = 1]) - Pr(Y = 1|SET[X = 0])122 + q241 + q222 + q421 + q422 + q221 + q142 + q242)=  direct effect (ACDE) of the treatment X in the population is the proportion of individuals who would experience outcome Y if they were treated, but not if they were untreated, if Z were forced (SET) to have a specific value z (thus blocking any indirect effects). In general, there is no reason for this effect to take the same value if Z were forced (SET) to 0 as it would take if Z were forced (SET) to 1, and so for binary Z in our DAG there are two distinct average causal direct effects. Given the monotonicity assumption, these effects are the sums of 6 of the 18 potential response type proportions in the population:[X→Y] | SET[Z = 0] = average causal direct effect for Z forced (SET) to 0ACDE= Pr - Pr122 + q222 + q422 + q121 + q221 + q421)=  to 1ACDE= Pr - Pr122 + q222 + q422 + q142 + q242 + q442)=  by external intervention, then Y = Z = 0, regardless of X. Alternatively, if Z were to be forced to occur (i.e. SET to Z = 1) by external intervention, then Y = Z = 1. For potential response types {242} and {221}, however, the common-sense meaning of an indirect effect may also apply, depending on the specific intervention applied to Z. Specifically, if the external intervention on the intermediate is SET[Z = 0], then potential response type {242} is an indirect type, whereas if the external intervention on the intermediate is SET[Z = 1], then potential response type {221} is an indirect type  of the treatment X on the intermediate covariate Z, which is the proportion of individuals who would experience intermediate Z if they were treated, but not if they were untreated. Given the monotonicity assumption, this effect is the sum of 6 of the 18 potential response type proportions in the population:[X→Z] = average causal effect of X on ZACE= Pr(Z = 1|SET[X = 1]) - Pr(Z = 1|SET[X = 0])211 + q241 + q222 + q244 + q221 + q242)=  to 1, but not if Z were forced (SET) to 0, conditional on X = x. In general, there is no reason for this effect to take the same value in the X = 0 subpopulation as it does in the X = 1 subpopulation, and so for binary X in our DAG there may be two distinct effects of Z on Y given strata of X. Given the monotonicity assumption, these effects are the sums of 6 of the 18 potential response type proportions in the population:[Z→Y] | X = 0 = Average causal effect of Z on Y in the X = 0 stratumACE= Pr - Pr141+ q241 + q441 + q121 + q221 + q421)=  - Pr141 + q241 + q441 + q142 + q242 + q442)=  to 1, but not if Z were forced (SET) to 0, over the entire population. As this is not a stratum-specific quantity, there is only a single value, although this depends on the marginal distribution of X in the population  = Pr(Y = 1|SET[Z = 1]) - Pr(Y = 1|SET[Z = 0])ACE= Pr - Pr + Pr - PrGiven that X is not affected by Z in the specified DAG, this can be re-written as: - Pr )Pr(X = 1) + - Pr )Pr(X = 0)[Z→Y] | X = 1 + Pr(X = 0) ACE[Z→Y] | X = 0 = Pr(X = 1) ACE[Z→Y] | X = x terms are each comprised of the sums of 6 of the 18 potential response type proportions in the population, 3 of which are common across the two strata of X and 3 of which are unique to one or the other stratum, so that ACE[Z→Y] involves a weighted sum of 9 of the 18 potential response type proportions, with weights dependent upon the marginal distribution of X.As shown above, the ACExz as the risk (proportion) of Y = 1 among those with X = x and Z = z, i.e., Pr. With binary variables, exogeneity of X and the monotonicity assumption, these observable quantities are related to the latent response type proportions as follows:The causal effects defined above are counterfactual, in that they involve hypothetical manipulation of the treatment or intermediate or both. The realized data are the risks that arise in the form of observed proportions in the population. We define Rxz are used to compute the associational estimates of effect (see endnote 3), as follows:The observed risk values R[X→Y] = R1• - R0• is the associational estimate of the total average causal effect of X on Y on the additive scale, where Rx• indicates the risk under X = x collapsed over levels of Z, i.e., Rx• = Pr(Z = 0|X = x)Rx0 + Pr(Z = 1|X = x)Rx1. Because X is assumed to be randomized and therefore Pr(Z = z|X = x) = Pr(Z = z), RD[X→Y] equals the causal RD Pr - Pr.The direct risk difference DRD[X→Z] = Pr(Z = 1|X = 1) - Pr(Z = 1|X = 0) is the associational estimate on the additive scale of the effect of X on Z. Because X is assumed to be randomized, however, this associational estimate equals the analogous causal quantity Pr(Z = 1|SET[X = 1]) - Pr(Z = 1|SET[X = 0]).RD[Z→Y] | X = x = Rx1 - Rx0 is the associational estimate on the additive scale of the effect of Z on Y within stratum X = x. Because randomization of X does not imply that the effect of Z on Y is unconfounded, it may be a biased estimate of the analogous causal quantity, i.e., RD[Z→Y] | X = x is not necessarily equal to Pr - PrRD[Z→Y] = Pr(X = 1)RD[Z→Y] | X = 1 + Pr(X = 0)RD[Z→Y] | X = 0 is the associational estimate on the additive scale of the effect of Z on Y standardized to the distribution of X.sRDThe associational estimate for the indirect effect is generally computed by one of two methods:[X→Y] | Z = z from RD[X→Y], or1) by subtracting DRD[X→Z] by sRD[Z→Y]2) by multiplying RD[X→Y] | Z = z from RD[X→Y] is also recommended in the social sciences methodology literature. For example, Stolzenberg writes: "Once the total and direct effects are calculated, indirect effects may be computed merely by subtracting the direct effect of an antecedent variable from its total effect. This subtraction procedure is applicable both to linear additive models ... and to nonlinear / nonadditive models." .odels."  | Z = 0 = DRD[X→Y] | Z = 1). The usual regression-based approach for the second method involves the regression of Z on X, followed by the regression of Y on both X and Z, and finally the multiplication of the coefficient estimate for X in the first model by the coefficient estimate for Z in the second model. This conditional estimation of the Z→Y effect in the second model is analogous to taking a weighted average over stratum-specific values as we have done for sRD[Z→Y]. Any presumed equivalence of the two approaches shown above by virtue of a homogeneity assumption for the stratum-specific estimates would often be unwarranted, as even under monotonicity it would generally require the additional restrictions that q142 = q242 = q442 = q121 = q221 = q421 = 0 (see endnote 4).There will generally be two distinct estimates by the first method above, depending the level chosen for Z. This is a necessary consequence of the manipulative definition of the controlled direct effect, since it involves deactivation of the indirect pathway by preventing variation in Z, and so if Z is to be fixed to a unique value, this value must be specified. In the second method shown above, however, only the two components of the indirect pathway are involved, and so no explicit fixing of Z is specified. This leads to a single estimate of the direct effect, and so the two methods can only be consistent with one another when there is homogeneity of the ACDE over strata of Z  to take the value 0 rather than the actually occurring value 1.The second set of counterfactual parameters are the risks of outcome Y among those with X = x and Z = 0 that would have been observed had Z been forced (SET) to take the value 1 rather than the actually occurring value 0.It is now possible to specify exchangeability conditions that are sufficient to guarantee that there is no confounding, meaning that associational measures and causal effects are equivalent. The fou11|SET[Z = 0] = R10R01|SET[Z = 0] = R00R10|SET[Z = 1] = R11R00|SET[Z = 1] = R01R[X→Y] | Z = 0 is unconfounded, whereas the latter two sets of exchangeability conditions imply that DRD [X→Y] | Z = 1 is unconfounded. Under the general scenario in which stratum-specific direct effects may differ, all four conditions are needed to guarantee that there is no confounding in either stratum of Z for any arbitrary choice of effect contrast that may be constructed from the four component risks.These conditions assert that the risk that is observed among those with X = x and Z = 0 is the same risk that would have been observed among those with X = x and Z = 1 had Z been forced (SET) from 1 to 0, and that the risk that is observed among those with X = x and Z = 1 is the same risk that would have been observed among those with X = x and Z = 0 had Z been forced (SET) from 0 to 1. The first two sets of exchangeability conditions imply that DRD[X→Y] | SET[Z = 0] and ACDE[X→Y] | SET[Z = 1]. Under the monotonicity assumption, this requires that 6 of the 18 types, namely {142}, {242}, {442}, {121}, {221}, and {421} be absent from the population. For example, potential response type {242} refers to a unit in which Z will equal x. When X = Z = 1, outcome Y will occur (Y = 1), and when X = Z = 0, outcome Y will not occur (Y = 0), leading to a unit-level casual effect of X on Y equal to (1-0) = 1. However, if Z were to be manipulated by external intervention (SET) to equal 0, then the unit-level effect of X on Y becomes (0- 0) = 0. That is to say, there is no direct effect at this controlled level of Z. In contrast, if Z were to be manipulated by external intervention (SET) to equal 1, the unit-level effect of X on Y remains (1-0) = 1. The direct causal effects of X on Y are heterogeneous for these 6 omitted potential response types because there is unit-level interaction; the value obtained by Y depends not only on the value taken by X, but also on the level to which Z is held by external manipulation. Homogeneity of the stratum-specific direct effects ACDE[X→Y] | SET[Z = 0] and ACDE[X→Y] | SET[Z = 1] also corresponds to absence of effect measure modification on the additive scale.We now impose an additional restriction which, as we will see in Section 6, is necessary for the general validity of the decomposition strategy described above. This restriction is that for no individual in the population may there exist both a causal effect of X on Y and a causal effect of Z on Y. For this condition to hold in general, it must be the case that Z does not modify the effect of X for any unit. This restriction, which can be characterized as the absence of unit-level synergism or interaction, implies homogeneity of the stratum specific direct effects ACDE[X→Y] = q241. The total effect is indeed decomposable into the sum of direct and indirect effects under this restriction, and in the absence of confounding may be estimated without bias. The decomposition is valid because the ACE[X→Y] reduces to the sum of only 4 proportions , since 4 of the previous 8 are restricted to be 0 . The average causal direct effects (ACDE) of X on Y are the sums of 3 potential response type proportions (rather than 6), which are identical in the two strata: ACDE[X→Y] | SET[Z = 0] = ACDE[X→Y] | SET[Z = 1] = (q122 + q222 + q422). Likewise, ACE[X→Z] is the sum of four proportions, ACE[Z→Y] = ACE[Z→Y] | SET[X = 0] = ACE[Z→Y] | SET[X = 1] is the sum of three proportions, and the observed risks RXZ are similarly restricted by deleting the prohibited interacting potential response types from the quotients shown above  of the treatment X in the population as the proportion of all individuals who would experience outcome Y if they were treated, but not if they were untreated, by virtue of the effect that X has on Z and then the effect that Z has on Y. In this mechanism, therefore, external intervention to hold Z fixed will prevent X from having the effect on Y, regardless of the specific value to which Z is SET. Given the restrictions, the average causal indirect effect is merely a single potential response type proportion in the population: ACIEijk as shown in Table XZ of R11 = 0.9170, R01 = 0.5377, R10 = 0.6101 and R00 = 0.2307. These observed risk values then determine the various associational estimates of effect. The total effect RD[X→Y] = (0.8763- 0.3117) = 0.5646. The observed stratum-specific risk differences DRD[X→Y] | Z = 0 = DRD[X→Y] | Z = 1 = (R1z - R0z) = 0.3793. Likewise the observed risk difference and stratum-specific risk differences for the effect of Z on Y are also homogeneous, sRD[Z→Y] = RD[Z→Y] | X = 0 = RD[Z→Y] | X = 1 = 0.3070. The observed effect of X on Z, RD[X→Z] = 0.6036.Consider data arising from a population of unit-level potential response type proportions q11|SET[Z = 0] = 0.6101; R01|SET[Z = 0] = 0.2307; R10|SET[Z = 1] = 0.9170; and R00|SET[Z = 1] = 0.5377. The absence of confounding is implied by the following set of equalities, the first two of which imply an absence of confounding of DRD[X→Y] | Z = 0 and the latter two of which imply an absence of confounding of DRD[X→Y] | Z = 1:Furthermore, the data in this example are constructed such that there is no confounding of the relation between Z and Y. To verify this property, we use the proportions in Table 11|SET[Z = 0] = R10 = 0.6101R01|SET[Z = 0] = R00 = 0.2307R10|SET[Z = 1] = R11 = 0.9170R00|SET[Z = 1] = R01 = 0.5377R[X→Y] = (q241) = 0.1853. As described above, there are two common approaches for estimating the associational measure of the indirect effect. The first is to subtract DRD[X→Y] | Z = z from RD[X→Y], which in this case yields (0.5646- 0.3793) = 0.1853. The second is to multiply RD[X→Z] by sRD[Z→Y], which yields (0.6036 × 0.3070) = 0.1853. The estimation of direct and indirect effects and their decomposition from total effects is valid, as will always be the case with this set of assumptions. The justification for this assertion is trivial: this set of assumptions is sufficient to guarantee that the true total ACE is the sum of three ACDE type proportions and one ACIE type proportion, whereas in general, without these restrictions, the ACDE is not constrained to be a subset of the total ACE. We have demonstrated a valid and unbiased estimation of the portion of a total effect that is transmitted through a specified intermediate when there is both absence of confounding and absence of unit-level interaction. We next relax this second constraint in order to demonstrate that the decomposition analysis can then fail.In this example, which was constructed to have no confounding and in which potential response types corresponding to unit-level synergism have been eliminated, the associational estimates of the total and direct effects are unbiased. That is, the true total average causal effect equals the observed risk difference (0.5646) and the homogeneous average causal direct effects equal the stratum-specific risk differences (0.3793). It only remains to show that the indirect estimate is valid and that the total effect is decomposable. The true average causal indirect effect in the table is the single potential response type proportion, ACIE142 = q242 = q121 = q221 = q421 = q442 = 0. Therefore we have, under the monotonicity restriction alone, 18 potential response types in the population. Consider data arising from a population of unit-level potential response type proportions qijk as shown in Table XZ of R11 = 0.9580, R01 = 0.3910, R10 = 0.4180 and R00 = 0.3170. These observed risk values then determine the various associational estimates of effect. The associational estimate of the total ACE is RD[X→Y] = (0.8166- 0.3470) = 0.4696. The observed stratum-specific risk differences are no longer constrained to be homogeneous: DRD[X→Y] | Z = 0 = (R10 - R00) = 0.1010 and DRD[X→Y] | Z = 1 = (R11 - R01) = 0.5670. The observed stratum-specific risk differences for the effect of Z on Y similarly need not be homogeneous: RD[Z→Y] | X = 0 = 0.0740 and RD[Z→Y] | X = 1 = 0.5400. sRD[Z→Y] will now depend on the observed marginal distribution of X. If values were assigned with equal probability, then sRD[Z→Y] = (0.5 × 0.0740) + (0.5 × 0.5400) = 0.3070. The observed effect of X on Z, RD[X→Z], equals 0.3327.Now we relax one assumption, the prohibition of unit-level interaction, which was operationalized in Section 5 by requiring that q11|SET[Z = 0] = 0.4180; R01|SET[Z = 0] = 0.3170; R10|SET[Z = 1] = 0.9580; and R00|SET[Z = 1] = 0.3910. The absence of confounding is implied by the following set of equalities, the first two of which imply an absence of confounding of DRD[X→Y] | Z = 0and the latter two of which imply an absence of confounding of DRD[X→Y] | Z = 1 :To verify that, as in the previous example, the data in this example are unconfounded, the proportions in Table 11|SET[Z = 0] = R10 = 0.4180R01|SET[Z = 0] = R00 = 0.3170R10|SET[Z = 1] = R11 = 0.9580R00|SET[Z = 1] = R01 = 0.3910R[X→Y] = ACE[X→Y] = 0.4696. Furthermore, because we have established that there is no confounding, the average causal direct effect of X on Y is identified by the observed associational measure of effect: ACDE[X→Y] | SET[Z = z] = DRD[X→Y] | Z = z. In this example, ACDE[X→Y] | SET[Z = 0] = DRD[X→Y] | Z = 0 = 0.1010 and ACDE[X→Y] | SET[Z = 1] = DRD[X→Y] | Z = 1 = 0.5670. However, in this scenario in which the only assumption we have relaxed is to allow the presence of unit-level synergism, the total average causal effect is no longer decomposable into direct and indirect effects. The average causal indirect effect no longer has single unambiguously true value. If the external manipulation contemplated is to SET[Z = 0], then ACIE[X→Y] = (q241 + q242) = (0.0100 + 0.1517) = 0.1617. On the other hand, if the external manipulation contemplated is to SET[Z = 1], then ACIE[X→Y] = (q241+ q221) = (0.0100 + 0.0200) = 0.0300.Because X is randomized, the average causal effect of X on Y is identified by the observed associational measure of effect: RD[X→Y] | Z = z from RD[X→Y], which in this case yields either (0.4696- 0.5670) = -0.0974 or (0.4696-0.1010) = 0.3686, depending on the stratum of Z, neither of which equals either of the corresponding true values of 0.0300 or 0.1617. The second approach is to multiply RD[X→Z] by sRD[Z→Y], which yields (0.3327 × 0.3070) = 0.1021, a value that equals neither of the corresponding true values of 0.0300 or 0.1617, nor is it the weighted average formed from any meaningful set of weights. In this scenario, the estimation of direct and indirect effects and their decomposition from total effects is not valid. It is immediately apparent that once unit-level interaction is permitted, there are potential response types that contribute to the ACDE but which do not contribute to the total ACE, making it incorrect to view the ACDE as a partition of the total ACE. Likewise, there are potential response types that contribute to the ACDE in one stratum of the intermediate, but which contribute to the ACIE in the alternate stratum, making it incorrect to view ACDE and ACIE as adding together to sum to a total effect. Therefore, for the decomposition methodology to be reliable, there must be both absence of confounding and absence of unit-level interaction. Because the absence of unit-level interaction would be difficult to assert with any confidence in a real-world application, the practical utility of decomposition as an analytic strategy is doubtful.As described above, there are two common approaches for estimating the associational measure of the indirect effect. The first is to subtract DRD[X→Y] / ACE[X→Z]) = (q241 / q211 + q241+ q222 + q244 + q221 + q242) = (0.1853 / 0.5646) = 32.8%. We note that a valid contrast between total and direct effects for ratio measures of effect was described by Joffe & Colditz[The demonstration above would appear to be somewhat gloomy as regards the potential for analytic epidemiology to identify biologic pathways through the contrast of variously specified statistical models. Indeed, the situation is even more grim than stated above, because even the optimistic scenario in Example 1 (Section 5) relies on the linear causal contrast estimator . Epidemiologic applications, such as those recommended by Szklo and Nieto [, pp. 184& Colditz, but thaEven if one steadfastly utilized the risk difference as the causal contrast and justified the no-confounding assumption, in order to reliably decompose the effect, one would still have to believe that there are no units in the population for whom Z and X both affect Y. Under the sharp null hypothesis for the exposure effect, this might be plausible. That is, if X has no effect on Y for any unit, then it follows that there are no units in the population for whom both X and Z have an effect on Y. However an average causal effect equal to the null does not imply this condition. If one were able to assert the no-confounding assumption, then observing that the association parameter is equal to the null would imply that the average causal effect is null, but no observation would imply the absence of unit-level interaction. The observation of heterogeneity would be sufficient to reject the assumption, but the observation of homogeneity would have no implications for this assumption. Nevertheless, as a practical matter, the incidental balancing out of unit-level causal effects leading to homogeneity might be considered unlikely, and therefore as a feasible approximation, the observation of risk difference homogeneity under a substantively defensible assertion of no-confounding might be taken as a setting in which effect decomposition can be attempted with a modicum of credence.Several previous authors working with latent potential response models have commented on the non-decomposibility of total effects into direct and indirect effects, most notably Robins, Robins controlled direct effect, which is to say, the proportion of individuals who would experience outcome Y if they were treated, but not if they were untreated, if Z were to be fixed to have a specific value z (thus blocking any indirect effects). Rather than impose through external intervention a uniform value of Z = z for all units, it is possible to define the average causal direct effect of X on Y that results from fixing Z to the value that would naturally occur under a specific single value of X, for example the unexposed level X = 0. This is referred to by Robins as the "pure direct effect"[We note that our specification of average causal direct effects in this manuscript corresponds to the t effect" and by Pt effect". It is nAlthough it allows for decomposition without the assumption of no unit-level interaction, the approach involving pure  direct and indirect effects has a substantial deficiency. The exchangeability conditions shown above (Section 4) characterize confounding in relation to hypothetical but defined manipulations of the target population. That is, X and Z are controlled to specific values. Because the pure  direct and indirect effects are defined based on intermediate Z being manipulated to an unobserved value that it would have taken under an exposure X value that may not have occurred, the exact nature of this intervention remains obscure. Because the hypothetical manipulation cannot be specified, the decomposed effects no longer have any possible relevance to a specific public health intervention or policy [, SectionFor example, if one were to estimate that the pure  indirect effect through intermediate Z equals 50% of the total effect, one could not infer that 50% of the outcomes attributable to the exposure could be prevented by blocking Z from occurring. Controlled direct effects can be used to make statements such as "The effect that postmenopausal hormone therapy would have on breast cancer risk if we were to persuade every woman to receive a screening mammography is ...." No similarly practical statement could be made for a pure  direct effect, however, which would correspond to something like "The effect that postmenopausal hormone therapy would have on breast cancer risk if every woman were to engage in the screening mammography behavior that she would have exhibited under the absence of treatment is ...." This latter statement obviously has no clear public health policy implications, since it requires a policy of fixing the intermediate to different values, some of which are unobserved .In summary, the ubiquitous strategy of adjusting for one or more putative causal intermediates in order to estimate the portion of the effect that it mediated by this pathway, in epidemiology and in other fields, lacks a reliable foundation. There are highly constrained sets of assumptions which allow this strategy to be valid, but it is often difficult to know when, if ever, these assumptions are approximately satisfied. Previous critiques have focused on confounding between the intermediate and the outcome, but we show that even when there is no confounding, the total causal effect of treatment is not generally decomposable into direct and indirect effects. Valid estimation of the direct or indirect effects, or of the proportion of the total effect that is due to an intermediate variable, requires not only the assumption of no confounding, but also the assumed absence of unit-level synergism, the latter of which may be particularly difficult to assert in a real-world analysis. Furthermore, even under these conditions, the decomposition is only valid for the difference contrast as the measure of causal effect, not for ratio measures of effect such as risk ratios, rate ratios, hazard ratios or odds ratios. In circumstances when it is possible to estimate (controlled) average causal direct effects, these should not generally be interpreted as portions of the total average causal effect, nor should they generally be used to make any statement about the proportion of the effect that is attributable to the measured intermediate variable.ACE average causal effectACDE average causal (controlled) direct effectACIE average causal (controlled) indirect effectCHD coronary heart diseaseDAG directed acyclic graphDRD direct risk differenceLRC Lipid Research ClinicsRD risk differenceRR relative risk or risk ratiosRD standardized risk differenceSUTVA stable-unit-treatment-value assumptionThe authors declare that they have no competing interests.1. Because of the assumption of zero sampling error "proportions" (in the observed sample) and "probabilities" (in the source population)are interchangeable.strong is intended to distinguish it from a weaker stochastic monotonicity assumption that may be defined:2. The characterization of this monotonicity assumption as 0 = 1) ≤ Pr(Z1 = 1)Pr(Z0z = 1) ≤ Pr(Y1z = 1); z = 0,1Pr(Yx0 = 1) ≤ Pr(Yx1 = 1); x = 0,1Pr = (q121 + q221 + q421), but this incidental cancellation would be difficult to anticipate, whereas the absence of some potential outcomes types is a more plausible form of background knowledge that an investigator could bring to the analysis.4. Strictly, equivalence of the two approaches for specifying the indirect effect requires merely that (qJSK led the writing, but all three authors contributed heavily to editing and revision. RFM devised the notational system and the numeric examples.