A large number of statistical fallacies occur in medical research literature. These are mostly inadvertent and occur due to lack of understanding of the statistical concepts and terminologies. Many researchers do not fully appreciate the consequence of such fallacies on the credibility of their report.This article provides a general review of the issues that could give rise to statistical fallacies with focus on orthopedic research. Some of this is based on real-life literature and some is based on the actual experiences of the author in dealing with medical research over the past three decades. The text is in teaching mode rather than research mode.P-values that compromises conclusions; confusing correlation with cause-effect; and interpreting statistical significance as medical significance.Statistical fallacies occur due to inadequate sample that is used for generalized conclusion; incomparable groups presented as comparable; mixing of two or more distinct groups that in fact require separate consideration; misuse of percentages, means and graphs; incomplete reporting that suppresses facts; ignoring reality and depending instead on oversimplification; forgetting baseline values that affect the outcome; misuse of computer packages and use of black-box approach; misuse of Mere awareness of the situations where statistical fallacies can occur may be adequate for researchers to sit up and take note while trying to provide a credible report. Fallacies are anomalies that considerably reduce the credibility of a report. Statistical fallacies are common in medical research literature. This article enumerates a large number of such fallacies, particularly in orthopedic research, in the hope of creating awareness about situations where these can occur. Such awareness by itself may be enough for a researcher to try to produce a more credible report.Statistics show that more people die in hospital than at home. Also, there is a strong association between dying and being in bed. The nonsense of such associations is apparent. No one would advocate avoiding a hospital or bed to prolong life! These might seem like extreme examples, but the same sort of errors of logic sometimes pass unrecognized in medical literature.1abuse occurs when the data or the results are presented in a distorted form with the intention of misleading. Sometimes part of the information is deliberately suppressed to support a particular hypothesis. A misuse occurs when the data or the results of analysis are unintentionally misinterpreted due to lack of comprehension. The fault in either case cannot be ascribed to statistics. It lies with the user. The difficulty, however, is that the adverse effects of wrong biostatistical methods are slow to surface. And that makes these methods even more vulnerable to wrong uses.Abuse or misuse of statistics has precisely the same consequence. An The subjects of investigation should provide sufficient and valid data to take a decision one way or the other. Sometimes this does not happen for a variety of reasons.A sample is considered unbiased when it truly represents the target population. A frequent source of error in statistical conclusions is a biased sample. This can happen even when the selection is random or even when random allocation is made in experimental studies. A large sample tends to magnify these errors rather than to control them.Consider the relationship of bone mineral density (BMD) with age in women after the age of 60 years. It is well known that this density declines due to hormonal changes but the gradient differs from population to population. How do we find the exact effect of age in a particular population? Those with lower density are likely to be in poor health and thus may have less longevity. Any estimation based on survivors is bound to be biased in this situation. It may not be easy to find the correct gradient in this case.Similarly, a study based only on hospital cases will exclude those who die before admission. Serious cases, those residing in remote areas and those who are poor to afford hospitalization tend to be excluded. Similar bias occurs in a variety of other situations where the study is on prevalent cases rather than on incident cases. Both these fallacies may have occurred in investigating age influence on the ability of femoral BMD to predict hip fracture where the subjects were women aged 75 and over.2Early phases of clinical trials are in any case done on volunteers. Volunteers tend to be very different from the general class of subjects. Many of them are either hopeless terminal cases or are subjects with exceptional courage. Both affect the response. Notwithstanding this limitation, volunteer studies have a definite place in medicine as they do provide important clues on the toxicity of the regimen under test, the dose level that can be tolerated and the potential for further testing of the modality.Medical ethics require that the subject's consent must be taken for the research. Real consent, after fully explaining the underlying uncertainties, is difficult to obtain. Many researchers in developing countries just get the consent form signed, which a sick person may do under the force of circumstances, without properly understanding the consequences. When the real consent is taken, the subjects again self-select themselves and the sample may become biased. Some of this is eliminated if and when a random allocation strategy is adopted but that is feasible only for trials. Even then generalizability suffers. Conclusions based on all such research can be misleading. Not many researchers appreciate this fallacy and tend to wonder why their results do not apply to the practical situation.Clinic and hospital subjects too form a biased sample, as they tend to have a more severe form of disease and include mostly those who can afford these services. Mild cases tend to ignore their condition or self-treat themselves. An interesting example is migraine, which was once believed to be more common in the intelligent professional class.Statisticians are notorious for advising large samples. The number of subjects in a study should be adequate to generate sufficient confidence in the results. Considering this aspect, a larger sample is not harmful but a small sample can be a waste of resources. A small sample may fail to detect the differences really present in the target population. There is a growing concern among the medical community regarding the failure of many randomized controlled trials (RCTs) in detecting a clinically relevant difference because they do not have sufficient power. The driving force for power is the size of the trial and the inter-individual variability. In only 3% studies published in the year 1997 in American and British volumes of Clinical Orthopedics and Related Research, the power was adequate to detect a small difference.4In addition, a small sample has high likelihood of being not fully representative and thus of producing biased results. Statistical methods have an inbuilt provision to take care of the larger sampling fluctuations in small samples but they are not equipped to take care of the lack-of-representativeness bias that is more likely to creep into small samples.et alIn a rare situation, an exceedingly large sample could also be a problem. Schnitzer et al.Statistical nonresponse occurs when some cases are lost to follow-up. A large nonresponse can render an otherwise good sample ineffective in drawing a valid conclusion not only because of the bias it tends to introduce but also because it considerably reduces the size of the sample available for inference. See, for example, the study on quality of life after hemiarthroplasty for hip fracture by Poulain Meta analysis that tends to provide more valid and reliable conclusions by pooling results from different studies is surely an accepted statistical technique. However, two points deserve attention in this regard. First, literature is generally unduly loaded with “positive” results. Negative or indifferent results are either not sent for publication or are not published by the journals with the same frequency. Any conclusion based on commonality in publications thus can magnify this bias.It must be realized that many consistent results increase confidence but do not necessarily provide confirmatory evidence. A single contradictory finding with credence can put a question mark on the whole conclusion.If sufficient care is not exercised with regard to various features of the groups under comparison, fallacies can easily occur. For comparability, the control should undergo the same clinical maneuvers, such as transfer from one unit to another and duration and frequency of examination, which are used for the treatment group. This is what makes blinding so important. If a group of women receiving arthroscopic surgery of the knee is being observed for deep venous thrombosis, the same set of observations should be done on the women with other knee surgeries for a valid conclusion regarding excess incidence in the arthroscopic group. In practice, the group of women with other knee surgeries may not be observed for thrombosis with similar attention.Matching or randomization is advised as a strategy to minimize bias in results based on comparison of groups. Comparability should not be merely for age and gender but should be for all those prognostic factors also that might possibly affect the outcome. These include severity of disease, coexisting diseases, care of the subjects, etc. This equivalence is difficult to achieve in practice. Also, all prognostic factors may not be fully known. Randomization is a good strategy to average out the factors and to obtain two equivalent groups, and it works well in the long run. It may fail in a particular study. It is necessary that similarity of groups is checked as a posthoc procedure even when the groups are formed by genuine randomization. This similarity has to be cautiously interpreted because a large difference could be statistically not significant if the sample size is small.In a trial for performance of a new design trochanteric Gamma nail in comparison to compression hip screws in trochanteric fractures,In a study on the trend in contribution of osteoporosis to total morbidity over the past 50-60 years, an important factor is the change in the definition and detection of osteoporosis from 1950 to today. The disease is much better understood now than 50 years ago. The diagnostic procedures have greatly improved after the emergence of DEXA and the awareness is high. Thus, the detection rate has increased. This will surely affect the trend.Defining osteoporosis as BMD at least 2.5SD below the normal for 25-year-old femalesIn a clinical trial setup, subjects in the treatment group may drop out more because of discomfort or poor taste of the drug, even when the placebo looks like the drug and the trial is randomized. On the other hand, the subjects in the treatment group may stay if they see improvement in their condition whereas the placebo group can become noncompliant. The compliance rate in this case is related to the efficacy of the regimen and the comparison can be jeopardized.A related situation occurs when different groups do not have the same opportunity of being screened just as we mentioned earlier on thrombosis in arthroscopic surgery. Diabetes and gallstones may appear to be associated because diabetics are regularly checked for gallstones but the nondiabetics are rarely checked.If the distribution of ankylosing spondylosis in different blood groups is O, 45%; A, 35%; B, 15%; and AB, 5%, it would be naive to conclude that this disease occurs more commonly in subjects with blood group O. For a correct conclusion, this distribution should be compared with the proper denominator, which in this case is the blood group distribution in the concerned population.Another kind of problem with the denominator occurs when organs or episodes are counted instead of individuals. Modern medicine indeed seems to have fragmented human being into a conglomerate of different parts-organs, tissues, etc. An orthopedic surgeon may count the average number of vertebrae in a group of cases of spinal tuberculosisA similar problem arises when a subject is repeatedly counted in case of recurrent episodes. This can happen, for example, for low back pain.Mixing of distinct groups can give fallacious results in some situations. Two are illustrated next.An annoying feature of regression (and correlation) is that it can be influenced by a single outlier. The position is shown in Mixing of two distinct groups can give a false sense of regression. Consider a survey on boys of Grade IX belonging to three randomly selected schools from each of the two strata-schools in slums catering to a low socioeconomic (SE) class and schools in posh localities catering to an upper class. The objective was to find health correlates. Among the measurements made were body mass index (BMI) and BMD in left wrist. When these are plotted, a scatter of the type shown in The points within each cluster are randomly scattered and indicate no relationship whatsoever between BMD and BMI in either class. That is, there is no evidence that a high BMI in either class is accompanied by a high value of BMD. When the data for the two SE classes are mixed, a distinct relationship emerges. But that is false because neither group has that kind of relationship unless one wants to draw a composite conclusion for the two groups combined.Out of ignorance or deliberately, the presentation of data in medical reports sometimes lacks propriety. This can happen in a variety of ways.n or (b) based on an inappropriate total. If two patients out of five respond to a surgery, is it correct to say that the response rate is 40%? In another group of five, if three respond, the rate jumps to 60%. A difference of 20% looks like a substantial gain, but in fact the difference is just one patient. This can always occur due to sampling fluctuation. Thus, percentage based on small n can mislead. Suppose 200 subjects are asked about their preference for more convenient, less expensive, but less efficacious medical treatment versus less convenient, more expensive, but more efficacious surgical treatment. Only 60 (30%) reported preference for medical intervention and 84 (42%) preferred surgery. The remaining 56 (28%) were noncommittal. If this finding is reported as 42% preferring surgery, keeping silent about the others, it has the risk of being interpreted as saying that the remaining 58% preferred medication. This obviously is wrong. The nonrespondents or the neutrals should always be stated so that no bias occurs in the interpretation.Percentages can mislead if calculations are (a) based on small If 12% of critical patients in the control group die within one week and 8% in the treatment group, the risk reduction is 4% or 33%? Results are sometimes stated to magnify the effect without the corresponding explanation regarding the base of calculation.n must always be stated when reporting a mean. These two, n and SD, should be considered together when drawing any conclusion based on mean. Statistical procedures such as confidence intervals and test of significance have a built-in provision to take care of both of them. A mean based on large n naturally commands more confidence than the one based on small n. Similarly, a smaller SD makes the mean more reliable.A popular saying by detractors of statistics is, “Head in an oven, feet in a freezer and the person is comfortable!” There is no doubt that an inference on mean alone can sometimes by very misleading particularly when it is based on just two values as in this case. Mean should not be calculated unless there are at least four readings. In addition, it must always be accompanied by the standard deviation (SD) so that an indication is available about the dispersion of the values on which the mean is based. In the quoted phrase, the SD would be exceedingly high showing that the mean is useless. Sometimes, the standard error (SE) is stated in place of SD but that too might mislead unless its implications in the context are fully explained. Also, 2.2 in this case. The variation is much more-even more than ±2SD limits, 0.830 to 1.130 g/cm2. Thus it is better to state clearly that mean is 0.980 and SD is 0.075 g/cm2 without using a ± sign.General practice is to state mean and SD with a ± sign in between such as mean BMD in lumbar spine in healthy premenopausal women is 0.98±0.075 g/cmMean may not be an appropriate indicator for a particular data set. If in a group of eight persons, seven do not take alcohol and one consumes 200 mL per day, how correct is it to say that the average consumption in this group is 25 mL per person per day? If extreme values or outliers are present, mean is not a proper measure. Either use the median or recalculate mean after excluding the outliers. If exclusion is done, this must be clearly stated.Some fallacies can occur due to inadequate choice of scale in a graph. A steep slope can be represented as mild and vice versa. Similarly, a wide scatter may be shown as compact. Also, means in different groups or means over time can be shown without corresponding SDs. They can be shown to indicate a trend that does not really exist or is not statistically significant.n. A mean or a percentage based on n = 2 is represented the same way as the one based on n = 100. The perception, and possibly cognition, received from a graph is not affected even when n is explicitly stated. One such example is the box-and-whiskers plot drawn for the time elapsed between cancer and acquired immunodeficiency syndrome (AIDS) diagnoses among homosexual men with cancer diagnosed before or concurrently with AIDS in San Francisco during 1978 to 1990,n is 4 in one group yet maximum, minimum, first quartile, third quartile and median are shown.One of the main sources of fallacies in graphs is their insensitivity to the size of Among many problems that can occur with the reporting, two requiring specific attention are incomplete reporting and overreporting.All reports should state not only the truth but the whole truth. There is a growing concern in the medical fraternity that part of the information in reports is sometimes intentionally suppressed and sometimes unknowingly missed. If so, the reader gets a biased picture. This is easily illustrated by the bias of many medical journals for reporting of “positive” findings and ignoring the “negative” reports. Both should be reported in a balanced manner. Similarly, properly designed studies that do not reject a particular null hypothesis deserve a respectable place in the literature. That, at present, is sadly lacking although awareness for a balanced approach is increasing. Recently a Journal of Negative Results in Biomedicine has started to partly address this problem.A very serious problem is reporting only that part of a study that supports a particular hypothesis. The other parts are suppressed. An example is a series of studies on the carcinogenic effect of asbestos. According to an analysis of different studies, deliberate attempts were made by the industry to suppress information on the carcinogenicity of asbestos that affected millions of workers.15The statement of results in a report should generally be confined to the aspects for which the study was originally designed. If there are any unanticipated findings, these should be reported with caution. These can be labeled as “interesting” or “worthy of further investigation” but not presented as conclusions. A new study, specifically designed to investigate these findings, can then be conducted.3 25 may thus become much lower than obtained by actual measurements. Thus, only those characteristics should be self-reported that are so required for the fulfillment of the objectives of the study. All others should be objectively measured.Self-perception of health may be very different from an assessment based on measurements. A person with an amputated leg may consider himself absolutely healthy. This can particularly happen with social and psychological domains of quality of life. Besides such discrepancies, it has been observed, for example, that people tend to report lower than actual weight but higher height. This could make a substantial difference when BMI is calculated. The percentage of subjects with BMIAmong the most common sources of fallacies in data-based conclusions is the use of inappropriate method of analysis.Most statistical methods take a simplified view of the complex biological process. Because computers are available for intricate calculations, the statistical need to simplify is really not as great now as it used to be in the precomputer era. But simplification is still required for easy comprehension. This should not be done to an extent that could distort the essential features of a biological process.R2 is high.There is no doubt that hardly any relationship in medicine is linear. Yet, linear relationship is the most commonly studied form of relationship in health and medicine. This simplification seems to work fairly well in many situations but can destroy an otherwise very clear relationship in others. The rise and fall of lung function with increase in age is aptly represented by a parabolic curve but the relationship vanishes if only linearity is considered. Another example is the relationship between glomerular filtration rate and creatinine level. Kidney function can influence bone health in at least older peopleet alStatistical linearity also includes a parabola with square term of the regressor because the coefficient is still linear. McQuellon n, the central limit theorem can be invoked for inference on means but nonparametric methods should be used when n is small and the distribution is far from Gaussian. At the same time, note also that most parametric methods, such as t and F, are quite robust to mild deviation from the Gaussian pattern. Their use in such cases does limited harm so long as the distribution has a single mode.A Gaussian form of distribution of various quantitative measurements is so ingrained in the minds of some workers that they take it for granted. For large n is not too small. The assumptions of independence of observations and of equality of variance across groups are more important than that of a Gaussian pattern. Independence is threatened when the measurements are serial or longitudinal. Uniformity of variance is lost when, for example, SD varies with mean. And this is not so uncommon. For example, as the cell-densities of cultured osteoblast life MG63 cells increase, their SDs also increase.F-test.Transformations such as logarithm and square-root sometimes help to “Gaussianize” a positively skewed distribution. But these also make interpretation difficult and unrealistic. If the logarithm of blood lead concentration is weakly correlated with log of bone lead concentration,In the case of Chi-square for proportions, the basic assumption is that the expected frequency in most cells is five or more. This restriction is sometimes overlooked. Fisher's exact test for a 2×2 table has become an integral part of most statistical packages of repute but the multinomial test required for larger tables with expected frequencies less than five has not found a similar place.It is customary to calculate person-years of follow-up and use this for various inference purposes. Person-years of exposure is a valid epidemiological tool only when each year of exposure has the same risk. Calculation of the mortality rate per thousand person-years after fracture in patients on dialysisThe blame lies mostly with statisticians who fancy quantity than quality. Although quantitation in many cases does help in achieving exactitude in thinking and in conclusions, it can sometimes suppress important findings.Consider a rise in BMD in lumbar spine after a high single dose of vitamin D  orally in 10 children of age 5 to 13 months diagnosed as nutritional rickets.2)BMD before the drug (g/cm0.25 0.23 0.19 0.27 0.20 0.32 0.24 0.30 0.24 0.262)BMD after one month of single dose of vitamin D (g/cm0.28 0.29 0.27 0.27 0.28 0.31 0.28 0.29 0.29 0.242)Increase . However, the increase occurred in six cases and not in the other four cases. A marginal fall in BMD one month after the dose can occur in some cases due to biological variation or instrumentation. If the dose is not effective, the probability of increase in BMD is the same as the probability of decrease. Under this null hypothesis (H0: P = ½), the exact probability of decrease in three or less subjects out of 10 by binomial is 0.17. This is more than 0.05. Thus the null cannot be rejected.Mean increase from 0.25 g/cmThe proportion gives a negative result about the effect of the dose in this example whereas the mean difference gives positive result. Depending upon the preference of the investigator, the finding can be presented either way.t-test and second on binomial ignores this important aspect. The conclusion in this example is that dose generally helps nutrition rickets children with BMD≤0.025 g/cm2. This can be statistically established by running a regression.The conclusion in the preceding example is based on the absolute increase in BMD in different subjects. Critical examination of the data reveals that increase occurred mostly in the subjects with low baseline values. The pattern generally is lower the baseline BMD, higher the rise. The above analysis based first on paired Computers have revolutionized the use of statistical methods for empirical inferences. Methods requiring complex calculations are now done in seconds. This is a definite boon when appropriately used but is a bane in the hands of nonexperts. Understanding of the statistical techniques has not kept pace with the spread of their use, particularly in medical and health professionals.α = 0.05, the total error rate increases enormously. Also, α = 0.05 implies that one in 20 correlations can be concluded to be significant when it actually is not. If measurements on 16 variables are available, the total number of pair-wise correlations is 16×15/2 = 120. At the error rate of 5%, six of these 120 can turn out to be falsely significant. HofackerData are sometimes overanalyzed, particularly in the form of post hoc analysis. A study may be designed to investigate the relationship between two specific measurements but correlations between pairs of a large number of other variables which happen to be available, are calculated and examined. If each correlation is tested for statistical significance at Because of the availability of computer packages, it is now easy to reanalyze data after deleting some inconvenient observations. Valid reasons for this exercise, such as outliers, are sometimes present, but this can be misused by excluding some data that do not fit the hypothesis of the investigator. It is extremely difficult to get any evidence of this happening in a finished report. Integrity of the workers is not and cannot be suspected unless evidence to the contrary is available. Thus, data dredging can go unnoticed.Most computer programs, for the time being, do not have the capability to distinguish numeric codes from quantitative data. If disease severity is coded as 0, 1, 2, 3, 4 for none, mild, moderate, serious and critical conditions respectively, statistical calculations may treat them as the usual quantitative measurements. This runs the risk of considering three mild cases equal to one serious case and so on. That is, codes can be mistreated as scores. This can happen even with nominal categories such as signs and symptoms when coded as 1, 2, 3, etc. Extra caution is needed in analyzing such data so that codes do not become quantities.Misinterpretation of statistical results mostly occurs due to failure to comprehend them in their totality and inability to juxtapose them with the realities of the situation. This can happen either because of the limited knowledge of many medical professionals about statistical conceptsP-values seem to be gaining acceptance as a gold standard for data-based conclusions. However, biological plausibility should not be abandoned in favor of P-values. Inferences based on P-values can also produce a biased or incorrect result.Statistical P = 0.051 is statistically almost as significant as one with P = 0.049, yet the conclusion reached would be very different if P = 0.05 is used as the threshold. Borderline values always need additional precaution.A threshold 0.05 of Type I error is customary in health and medicine. Except for convention, there is no specific sanctity of this threshold. A result with P-values so that the reader can draw his own conclusion. A value of P around 0.10 can possibly be considered weak evidence against the null hypothesis and a small P, say less than 0.01, as strong evidence. This way it acquires continuum.The practice now generally followed is to state exact 0 more difficult. Most statistical packages provide two-tail P-values as a default and many workers would not worry too much about this aspect. Scientifically, a conservative test does not do much harm, although some real differences may fail to be detected when a two-tail test is used instead of a one-tail test. Our advice is to use a one-tail test wherever clear indication is available but not otherwise.If a regimen can do no harm, such as iron supplementation for augmentation of low Hb level, one-tail test is appropriate. Use of two-tail test in this case makes it unnecessarily restrictive and makes rejection of HP-values. James et alP < 0.000,000,000,01 for difference in seroconversion rate against Epstein-Barr virus between lupus patients and controls. Such accuracy is redundant. It really does not matter whether P < 0.001 or P < 0.000,001 as far as its practical implication is concerned.Attempts are sometimes made to dramatize the Consider individual persons instead of groups. The reference range for most quantitative medical parameters is obtained as mean ± 2SD of healthy subjects. These statistical limits carry a risk of excluding 5% healthy subjects who have levels in the two extremes. When such limits are applied on several parameters, it becomes very unlikely that all parameters in any person are within such statistical range - even if he is fully healthy. This anomaly is sometimes forgotten while devising inclusion and exclusion criteria for subjects in the study.t-test is used to compare osteoblast-like cells at several points of time when exposed and unexposed to a static magnetic field.This fallacy is similar to multivariate conclusion based on several univariate analyses and the one inherent in multiple comparisons. When the study is based on more than two groups, the Type I error swells when each group is compared with each of the others. To control this, methods such as Tukey and Dunnett are used. Few trials in surgery and medicine consider such adjustment for multiple comparison.An association or a correlation in health can arise due to a large number of intervening factors. It is rarely a cause-effect type of relationship unless established by a carefully designed study that rules out the possibility of a significant role of any confounding factor.A strong correlation between heights of siblings in a family exists not because one is the cause of the other but because both are affected by parental height. Similarly, correlation between visual acuity (VA) and metacarpal index in subjects of age 50 years and above is not cause-effect type but arises because both are products of the same degeneration process. We do not expect VA to improve if metacarpal index is improved by some therapy.An unusual confounding factor may provide useful information in some cases. Comparison of surgical and nonsurgical treatment of nondisplaced acute scaphoid fracturesDistinction may be made between a necessary cause and a sufficient cause. Sexual intercourse is necessary for initiating pregnancy but it is not sufficient. In fact, the correlation between the number of intercourses and number of pregnancies, even without barriers, is negligible.The list of statistical fallacies seems to never end. Some of those not discussed above are as follows.n is large but may not have any medical significance in terms of condition of the patient or in terms of management of the condition. Statistical methods check statistical significance only and medical significance needs to be examined separately.An improvement of one point in quality of life after a surgery can be statistically significant if 0) as insignificance. A very important difference between two groups may be present but it will be statistically not significant if n is small or if the variability between the subjects who happened to be in the samples is high. The null hypothesis cannot be rejected unless there is sufficient evidence against it. Thus, conceding a null should not be implied to mean that the difference is not present. Nonsignificance is not necessarily the equivalent of ‘no difference”.The other potentially hazardous error is in interpreting statistical nonsignificance (failure to reject HNo risk can exceed one. Five-year risk of death in leukemia may be 0.97 and in arthritis only 0.02. Then the relative risk (RR) of death in leukemia is nearly 48. Opposed to this, if the comparison is with bone cancer cases where the five-year risk of death is 0.70, the RR is only 0.97/0.70 = 1.4. This is nearly as high as it can get in this situation. Note the physical limitation imposed by high risk in the baseline group. This aspect is many times forgotten while interpreting the value of relative risk.No decision is more important than the one concerning the life and health of people. The medical fraternity has a tall order. They are expected to prolong life and reduce suffering that occurs as a consequence of complex and often poorly understood interaction of a large number of factors. Some of these factors are explicit but many remain obscure and some behave in a very unpredictable manner. Uncertainties in health and medicine are indeed profound. Knowingly for some but unknowingly for many, statistical methods play a vital role in all empirical inferences. Statistical methods can be a dangerous tool when used carelessly. Computer-based statistical packages have not yet been given expertise to decide the correct method although they sometimes generate a warning message when the data are not adequate. The user of the package decides the method. If you are not sufficiently confident, do not hesitate to consult an expert biostatistician.Medical journals too have a responsibility to ensure that the results of dubious quality are not published. Statistical refereeing is a norm for some journals but some are lax on this issue.Our last advice is not to rely solely on statistical evidence. Statistical tools are surely good as an aid but rarely as a master. Depend on your intuition more than science. If scientific results fail intuitional judgment, look for gaps. They would most likely lie with 'science' than with intuition.


Venous thromboembolism is a common, fatal, and costly injury which complicates major surgery in older adults. The American College of Chest Physicians recommends high potency prophylaxis regimens for individuals undergoing total hip or knee replacement (THR or TKR), but surgeons are reluctant to prescribe them due to fear of excess bleeding. Identifying a high risk cohort such as older adults with comorbidities and co-occurring comorbidities who might benefit most from high potency prophylaxis would improve how we currently perform preoperative assessment.Using the Nationwide Inpatient Sample, we identified older adults who underwent THR or TKR in the U.S. between 2003 and 2006. Our outcome was VTE, including any pulmonary embolus or deep venous thrombosis. We performed multivariate logistic regression analyses to assess the effects of comorbidities on VTE occurrence. Comorbidities under consideration included coronary artery disease, congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), diabetes, and cerebrovascular disease. We also examined the impact of co-occurring comorbidities on VTE rates.CHF increased odds of VTE in both the THR cohort (OR = 3.08 95% CI 2.05-4.65) and TKR cohort (OR = 2.47 95% CI 1.95-3.14). COPD led to a 50% increase in odds in the TKR cohort (OR = 1.49 95% CI 1.31-1.70). The data did not support synergistic effect of co-occurring comorbidities with respect to VTE occurrence.Older adults with CHF undergoing THR or TKR and with COPD undergoing TKR are at increased risk of VTE. If confirmed in other datasets, these older adults may benefit from higher potency prophylaxis. Medical injury, or harm associated with a therapeutic or diagnostic intervention , commonlVenous thromboembolism (VTE) is a common, often fatal, and costly injury which complicates major surgery in older adults. VTE is particularly common following total hip and knee replacement (THR and TKR), with venographic rates of up to 60% without prophylaxis . Newer, Comorbidities such as congestive heart failure (CHF) and chronic obstructive pulmonary disease (COPD) have been associated with increased VTE risk in some studies -8 but noIn this investigation, we assessed the Nationwide Inpatient Sample to determine the risk of VTE in older adults with prevalent comorbidities and co-occurring comorbidities undergoing THR or TKR. We hypothesized that CHF, CAD, CVD, and COPD would predict increased risk of VTE. We also proposed that the joint effect of co-occurring comorbidities -- composed of comorbidities with distinct pathogenesis, such as CAD and COPD -- would equal the sum of the component effects or possibly exceed their sum, indicating a positive interaction.We used the Nationwide Inpatient Sample (NIS) from 2003-2006 for our analysis . This woWe determined VTE to have occurred if any one of eight ICD-9-CM DVT codes, three PE codes, and two non-specific VTE codes were present at discharge  produced statistically significant associations with VTE in multivariate models. Because we found these to be present in the TKR cohort, for the ease of interpretability, we report the associations between co-occurring comorbidities and outcomes using a categorical comorbidity variable for both the THR and TKR cohorts. We created a ten level categorical variable with a separate, mutually exclusive, level for each of nine comorbidities or co-occurring comorbidities . While this limited the population size for each comorbidity group, it allowed us to compare the risk of VTE for groups of older adults with single or co-occurring comorbidities against a common reference group of older adults without any of the nine comorbidities.Finally, we built multivariate logistic regression models to assess the independent effects of comorbidities. In our analysis we retained age and sex in all models. For remaining potential confounders, we retained any variable that changed the effect estimate for any comorbidity by more than 10%.In NIS 2003-2006, we identified 93,071 primary THR and 223,600 primary TKR surgeries. Overall, the age of older adults was evenly distributed into quartiles 65-69, 70-74, 75-79, and 80 or older. Sixty-three percent of subjects were female.  also suggests a potential source of a selection bias. Older adults with co-occurring comorbidities deemed to be suitable surgical candidates are presumably healthier in other ways than other older adults with the same comorbidities.In the case of COPD, we only detected an increase in risk for older adults undergoing knee surgery. This could be explained by the generally weak predictor effect of COPD on VTE or it could be related to the inherent differences between hip and knee surgery. Postoperative mobility may be significantly less for hip surgery and the effect of immobility in this group may dwarf other predictors such as COPD. Future work should examine the interaction between mobility and surgery type in data where this information is available.The association of CHF and COPD with postoperative VTE has important implications. Although the American College of Chest Physicians currently recommends high potency prophylaxis such as fondaparinux or LMWH for all individuals undergoing THR and TKR , surgeonThere are limitations to the work we presented. Due to the nature of the NIS administrative data we have limited ability to capture VTE. A recent study , suggestWe did not have information about events which took place after hospitalization. Given that the median time for development of DVT is 17 days for THR and 7 days for TKR  and the Administrative data are susceptible to upcoding where medical coders assign a diagnosis that may have only been considered but not proven. We did not have information about those VTE events that were present on admission compared to those that occurred during hospitalization. We plan to conduct further validation studies in other databases where pre-existing diagnosis modifiers are available. We cannot firmly establish causality between comorbidities and VTE using the data available to us. Comorbidities may be linked to other processes such as increased operative time or difficulty weaning from a ventilator after surgery. Future research with datasets containing these clinical variables may clarify the exact causal pathway. Lastly, although in our analysis we controlled for the presence of several factors that might increase the risk of VTE, we did not have data on the smoking status of individuals, which might be related to both the exposure and outcome.CHF is strongly associated with an increased risk of VTE after THR and TKR; COPD is associated with an increased risk of VTE after TKR. The absence of risk associated with other comorbidities and co-occurring comorbidities may be explained by the selection of healthier older adults for these surgeries or by some of the limiting factors described above. If these findings are confirmed in other datasets, higher risk older adults with comorbidities could potentially benefit from more aggressive preventive interventions including high potency pharmacologic prophylaxis.None of the authors have any financial or non-financial competing interests to declare as related to the contents of this manuscript.AK and AL were responsible for the study design, analysis, interpretation, and manuscript write-up. RAS, JNK, EL, and DB were responsible for the study design, interpretation, and manuscript write-up. MW was responsible for the study analysis and interpretation, and JBS was responsible for the study interpretation and manuscript write-up. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2318/10/63/prepubAppendix I - ICD-9-CM Procedure and Diagnosis Codes. total Joint Replacement Procedure Codes and Venous Thromboembolism Diagnosis Codes.Click here for file


Published data regarding the associations between genetic variants and asthma risk in Chinese population were inconclusive. The aim of this study was to investigate asthma susceptible genes in Chinese population.The authors conducted 18 meta-analyzes for 18 polymorphisms in 13 genes from eighty-two publications.A Disintegrin and Metalloprotease 33 (ADAM33) T1-C/T , Angiotensin-Converting Enzyme (ACE) D/I , High-affinity IgE receptor β chain (FcεRIβ) -6843G/A , Interleukin 13(IL-13) -1923C/T , IL-13 -2044A/G , Regulated upon Activation, Normal T cell Expressed and Secreted (RANTES) -28C/G , Tumor Necrosis Factor-α (TNF-α) -308G/A. After subgroup analysis by age, the ACE D/I, β2-Adrenergic Receptor (β2-AR) -79G/C, TNF-α -308G/A, Interleukin 4 receptor(IL-4R) -1902G/A and IL-13 -1923C/T polymorphisms were found significantly associated with asthma risk in Chinese children. In addition, the ACE D/I, FcεRIβ -6843G/A, TNF-α -308G/A, IL-13 -1923C/T and IL-13 -2044A/G polymorphisms were associated with asthma risk in Chinese adults.Seven polymorphisms were found being associated with risk of asthma, namely: ADAM33, FcεRIβ, RANTES, TNF-α, ACE, β2-AR, IL-4R and IL-13 genes could be proposed as asthma susceptible genes in Chinese population. Given the limited number of studies, more data are required to validate these associations. Asthma is one of the most common chronic respiratory diseases, affecting about 300 millions of children and adults worldwide. In ChinIt is well accepted that asthma is a complex disease and both genetic and environmental factors contribute to its inception and evolution,5. Many In recent years, host genetic susceptibility to asthma has been a research focus in scientific community in China. Many genes were suggested as asthma risk factors for Chinese population; however, many of the studies drew incompatible or even contradictory results. Considering a small number of sample size may be lack of power to reveal the reliable conclusion, we carried out a meta-analysis to assess the susceptible genes for asthma in Chinese population. To our knowledge, this is the first comprehensive and largest genetic meta-analysis conducted in people of Chinese descent for any respiratory diseases.asthma or asthmatic', in combination with 'polymorphism or variant or mutation' and 'Chinese or China' for Medline (Ovid), Pubmed, Embase, ScienceDirect, Springer database; 'asthma or asthmatic', in combination with 'polymorphism or variant or mutation' for CNKI database, Wanfang database, Weipu database and CBM database. All languages were included. The following criteria were used for selecting literatures in the meta-analysis: (1) the study should evaluate the association between genetic variants and risk of asthma in Chinese population from either mainland, overseas or both, (2) the study should be a case-control design published in a journal (3) genotype distributions in both cases and controls were available for estimating an odds ratio with 95% confidence interval (CI) and P value, (4)genotype distributions of control population must be consistent with Hardy-Weinberg equilibrium(HWE), P > 0.05 (5) the polymorphism for data synthesis should be studied in at least three case-control studies, (6) polymorphisms for data synthesis should be characterized as -A/B, with the following genotypes: AA, AB and BB. Accordingly, the following exclusion criteria were used: (1) abstracts and reviews, (2)genotype frequency not reported, (3) repeated or overlapping publications (4) polymorphisms with data less than three case-control studies (5) genotype distributions of control population not consistent with HWE, (6)genetic variants not characterized as -A/B. For duplication or overlapping publications, the studies with larger number of cases and controls or been published latest were included.We conducted a literature search by using the electronic database Medline (Ovid), Pubmed, Embase, ScienceDirect, Springer, CNKI, Wanfang database, Weipu database and CBM database to identify articles that evaluated the association between genetic variants and the risk of asthma in Chinese population . The search terms were used as follows: 'Two independent authors (Xiaobo Li and Yonggang Zhang) checked all potentially relevant studies and reached a consensus on all items. In case of disagreement, a third author(Jie Zhang) would assess these articles. The following data were collected from each study: first author, year of publication, location of the people, ages, genotype frequencies in cases and controls.2 Xtest http://ihg2.helmholtz-muenchen.de/cgi-bin/hw/hwa1.pl.For each case-control study, we first examined whether the genotype distribution in control group was according to Hardy-Weinberg equilibrium by Pearson's 2X-based Q statistic and was considered statistical significant at P value < 0.10. 2 Iwas used to measure the percentage of variability in point estimated that due to heterogeneity rather than sampling error. When the P-value is > 0.10, the pooled OR was calculated by the fixed-effects model, otherwise, a random-effects model was used. To evaluate the age-specific effects, subgroup analyses were performed by age for polymorphisms which were investigated in a sufficient number of studies(data were available from at least three case-control studies for at least one subgroup). Publication bias was examined by using the funnel plots, Begg's test and Egger's test[Any polymorphism that had been studied in at least three case-control studies was included in the meta-analysis. The strength of the associations between asthma risk and genetic variants were estimated by ORs and 95% CIs. The statistical significance of summary ORs were assessed by Z-test. The evaluated genetic models for each study were based mostly on those used in primary studies. Heterogeneity was evaluated by a er's test. The funThe selection process is shown in Figure 2X-based Q statistic and was considered statistical significant at P-value <0.10. When the P-value is less than 0.10, the pooled OR of each meta-analysis was calculated by the fixed-effects model; otherwise, a random-effects model was used. The chosen models to synthesize the data for each polymorphism can be seen in Table For each polymorphism, heterogeneity was analyzed by a ADAM33 T1-C/T , ACE D/I, FcεRIβ -6843G/A , IL-13 -1923C/T, IL-13 -2044A/G, RANTES -28C/G , TNF-α -308G/A . These results indicated that these polymorphisms were significant associated with asthma risk in Chinese population. All results for all 18 meta-analyzes are summarized in table Forest plots of each polymorphism can be seen in Figure ACE D/I, β2-AR -79G/C, TNF-α -308G/A, IL-4R -1902G/A and IL-13 -1923C/T) in children and five polymorphisms in adults.To evaluate the age-specific effects, subgroup analyses were performed by age for polymorphisms which were investigated in a sufficient number of studies(data were available from at least three case-control studies for at least one subgroup). Three subgroups were used: adults, children, others(ages in these case-control studies were not mentioned or mixed with adults and children). Briefly, we obtained significant results from five polymorphisms were statistically associated with increased risk of asthma. In order to analysis the age-specific associations, subgroup analysis were performed by age. The ACE D/I, β2-AR -79G/C, TNF-α -308G/A, IL-4R -1902G/A and IL-13 -1923C/T polymorphisms were found being associated with asthma risk in Chinese children, while the ACE D/I, FcεRIβ -6843G/A, TNF-α -308G/A, IL-13 -1923C/T, IL-13 -2044A/G polymorphisms were associated with asthma risk in Chinese adults. Given that the data for each polymorphism were from at least three case-control studies, the obtained results could be more precise than results obtained form any individual study.The aim of meta-analysis is to combine results from studies on the same topic and to produce more precise results. The current study is to reveal the roles of genetic variants and their associations with risk of asthma in Chinese population. In summary, we finally identified 18 polymorphisms in 13 genes. Among them, seven polymorphisms  in Chinese population. For A vs G, the pooled OR is 1.26 with 95%CI: 1.08-1.47 in this study, which suggested a weaker association between this polymorphism and asthma risk in Chinese population.The TNF-α gene, encodes a key proinflammatory cytokine in airway, is located on an asthma susceptible region-chromosome 6p. The TNF-α protein plays a central role in inflammation and involves in pathogenesis of asthma. Several polymorphisms have been identified in this gene, such as -308A/G, -238A/G. The -308A/G polymorphism in the promoter may affect the expression of this cytokine, which may affect the occurrence of asthma. In the meta-analysis performed by Gao and colleagues, they foIL-4 gene is located on chromosome 5q31, it was suggested to be associated with asthma risk, including elevated serum IgE levels and airway hypersensitiveness. A few studies indicated the -589C/T polymorphism in the promoter as a risk factor for asthma, but with inconclusive results. Li and colleagues performed a meta-analysis and found the T allele was associated with decrease risk of asthma[.78-0.94). HoweverIL-4 receptor gene is located on chromosome 16 p12.1-p11.2. Some polymorphisms had been identified as risk factors for asthma, such as -1902G/A and -223G/A. Our results indicated the -1902G/A polymorphism was associated with increased risk of asthma in Chinese children, but not in Chinese adults. The results also indicated the -223G/A polymorphism was not associated with risk of asthma in Chinese population.IL-4 and IL-13 signal through binding to a receptor complex comprised of the IL-13Rα1 and IL-4Rα with subsequent phosphorylation of JAKs and STAT6. IL-4 reFcεRIβ gene is a major candidate gene, involving in the pathogenesis of asthma. It is located on the chromosome 11q13. The -6843G/A polymorphism, leading change in an amino acid sequence at residue 237 from glutamic acid to glycine, is associated with increased IgE levels in atopic asthmatic children. In Chinese population, the -6843G/A polymorphism is the most extensively studied polymorphism in FcεRIβ gene. Our study revealed this polymorphism as a risk factor of asthma in Chinese population. Chinese who carry the GG or GA genotype have an 49% increased risk of asthma than AA carriers. Our results also demonstrated the -109C/T polymorphism in this gene was not associated with increased risk of asthma in Chinese population.The ADAM33 T1-C/T, ACE D/I, IL-13 -1923C/T, RANTES -28C/G and IL-13 -2044A/G polymorphisms were associated with risk of asthma in Chinese population by using meta-analyzes. Some results are similar to other studies performed in other ethnic- groups and some are not. In future, more published results should be included to update and validate these associations in Chinese population.Up to date, we first found that ADAM33 T1-C/T, ACE D/I, IL-13 -1923C/T, RANTES -28C/G, as risk factors for asthma was greater than that of FcεRIβ -6843G/A, IL-13 -2044A/G and TNF-α -308G/A.In this study, the rigorous inclusive criteria made the results more precise. Any study in which genotype distribution of control group divorced from HWE was excluded. In this meta-analysis, 11 polymorphisms were synthesized by using the fixed-effect model, 7 used random-effects model. Because the fixed-effect model is more precise than random effect model, the strength of evidence of FcεRIβ -6843G/A. After subgroup analyses by age, the heterogeneity was effectively decreased or removed in adults. Possible explanation may be that differences in etiology may exist in difference age groups. Another important factor contributing to heterogeneity was that homogeneity in either the case and control groups was uncertain. Ideally, all cases and controls in this meta-analysis should be matched for age, sex, atopic status and environmental exposures. However, these issues could not all be explained precisely because of insufficient clinical information for individual person. In addition, because this study is based on population of Chinese descent with the same genetic background, so the similarity of these studies might be very good, despite most studies were conducted in different areas of China.The heterogeneity of clinical information among studies should also be mentioned. Heterogeneity is an important issue when interpreting the results of meta-analysis. Significant heterogeneity existed in overall comparisons in a few meta-analyses, such as P values of Begg's test were more than 0.05 in 18 meta-analyses, we could not rule out this possibility, because for some polymorphisms, the included number of studies were relatively small. Third, this study didn't included some polymorphisms with lack of number of studies, or polymorphisms which were not characterized as -A/B for lack of quality analysis for HWE, some polymorphism, such as GSTM1-P/N, or HLA DR1 alleles and MHC alleles were not included, future studies should performed to analysis the effect of these polymorphism in Chinese population.Some limitations of this meta-analysis should be acknowledged when explaining our results. First, only published articles in the selected electronic databases were included in this study, it may be possible that some studies were not included in those databases or some unpublished studies which had null results, which might bias the results. Second, due to lack of sufficient data, the homogeneity in either the case and control groups was uncertain and data were not stratified by other factors such as atopic status or sex. The tests for gene-environment interactions were not carried out either. Third, publication bias may affect the results. Although ADAM33 gene, the D/I polymorphism in ACE gene, the -6843G/A polymorphism in FcεRIβ gene, the -1923C/T polymorphism in IL-13 gene, the -2044A/G polymorphism in IL-13 gene, the -28C/G polymorphism in RANTES gene and the -308G/A polymorphism in TNF-α gene are associated with asthma risk in Chinese population. And these results may also implicate in personalized therapy for asthma in Chinese population. In future, more studies should be conducted to investigate the gene-gene and gene-environment interactions between these polymorphisms in Chinese population.To our knowledge, this is the first and most comprehensive genetic meta-analysis to date conducted in Chinese descent for any respiratory diseases. In conclusion, this meta-analysis indicated the T1-C/T polymorphism in ADAM33: A Disintegrin and Metalloprotease 33; FcεRIβ: High-affinity IgE receptor β chain; ACE: Angiotensin-Converting Enzyme; β2-AR: β2-Adrenergic Receptor; IL-4: Interleukin 4; IL-13: Interleukin 13; IL-1β: Interleukin 1β; LT-α: Lymphotoxin-α; RANTES: Regulated upon Activation, Normal T cell Expressed and Secreted; TNF-α: Tumor Necrosis Factor-α; TGF-β1: Transforming Growth Factor β1.The authors declare that they have no competing interests.HF designed the study, provided resources, coordinated the study and directed its implementation; XBL, YGZ and JZ searched the publications, extracted the data and wrote the materials and methods, results; YLX wrote the discussion and checked all data, JH was responsible for data synthesis, CT and CH helped designed the study's analytic strategy, YD edited the manuscript, YYY wrote the introduction. All authors read and approved the final manuscript.Begg's funnel plots for publication bias in selection of studies on asthma susceptibility genes in Chinese. Figure S1 Begg's funnel plots for publication bias in selection of studies on β2-AR -46G/A polymorphism. Figure S2 Begg's funnel plots for publication bias in selection of studies on β2-AR -79G/C polymorphism. Figure S3 Begg's funnel plots for publication bias in selection of studies on IL-4R -1902G/A polymorphism. Figure S4 Begg's funnel plots for publication bias in selection of studies on IL-4R -223G/A polymorphism. Figure S5 Begg's funnel plots for publication bias in selection of studies on IL-4 -589C/T polymorphism. Figure S6 Begg's funnel plots for publication bias in selection of studies on TNF-α -308A/G polymorphism. Figure S7 Begg's funnel plots for publication bias in selection of studies on FcεRIβ -6843G/A polymorphism. Figure S8 Begg's funnel plots for publication bias in selection of studies on FcεRIβ -109C/T polymorphism. Figure S9 Begg's funnel plots for publication bias in selection of studies on ACE D/I polymorphism. Figure S10 Begg's funnel plots for publication bias in selection of studies on IL-13 -2044A/G polymorphism. Figure S11 Begg's funnel plots for publication bias in selection of studies on IL-13 -1923C/T polymorphism. Figure S12 Begg's funnel plots for publication bias in selection of studies on IL-1β-511C/T polymorphism. Figure S13 Begg's funnel plots for publication bias in selection of studies on LT-α +252A/G polymorphism. Figure S14 Begg's funnel plots for publication bias in selection of studies on TGF-β1 -509C/T polymorphism. Figure S15 Begg's funnel plots for publication bias in selection of studies on CD14 -159C/T polymorphism. Figure S16 Begg's funnel plots for publication bias in selection of studies on ADAM33 T1-C/T polymorphism. Figure S17 Begg's funnel plots for publication bias in selection of studies on RANTES -28G/C polymorphism. Figure S18 Begg's funnel plots for publication bias in selection of studies on RANTES -403A/G polymorphismClick here for file


Phlebotomous argentipes and housing characteristics between two districts e.g. endemic and non-endemic.In visceral leishmaniasis (VL), phlebotomine vectors are the main target to reduce for control measures. An attempt has been taken to delineate the association between P. argentipes. Vector density estimated using a CDC light trap.A cross-sectional survey was conducted on 240 households for both the endemic  and non-endemic (Lohardaga district) site. Logistic regression analysis was used to identify factors related to housing characteristics influencing suitable habitats for P. argentipes in both endemic and non-endemic areas was significantly much higher (P < 0.001) when compared with the proportion of Sergentomiya and P. papatasi. The results of multilevel logistic regression analysis showed that mud plastered wall , mixed dwelling  and area  were strongly associated with the presence of vectors.The proportion of Result of the studied household characteristics provides an accurate, rapid assessment of house-level variation in risk. The results also have implications for maximizing surveillance efficacy of sandflies, which is likely to become increasingly important while formulating any control strategy. Leishmania, which is transmitted by phlebotomine sandflies. A large portion of 500, 000 annual cases and 60,000 deaths occur in the poor rural communities within the Indian subcontinent [Visceral leishmaniasis (VL) or Kala-azar is a serious public health problem and has worldwide distribution. It is caused by the intracellular protozoan parasite of genus ontinent ,2. At prontinent ; these continent .Phlebotomous argentipes, the vector of kala-azar in the Indian subcontinent [ontinent , being iontinent . The vecontinent ,8. Largeontinent -12, but ontinent  suggestsP. argentipes. This study can serve to identify of house-level risk factors which may provide additional information on risk that is relatively rapid and inexpensive to collect, and complements other sources of risk information that are more specific; and this will ultimately help in the successful implementation a control strategy.Previously, very little work has been done at household level and they have mentioned poor housing construction as characteristics of the study area where visceral leishmaniasis was prevalent and vector density is also high -16. In aThe present study evaluates standardize cross-sectional survey of vector infestation and physical characteristics of the houses within the Kala-azar endemic and non-endemic region in India. It should be therefore support current efforts to scale-up control activities within the region.Two study sites were selected: Vaishali district (Latitude 25°43'N -26°00'N to longitude 85°04'E -85°38'E), one of the high endemic areas of Kala-azar in north Bihar, as endemic foci and Lohardagga district (23°30'N -23°40'N latitude to 84°40'E -84°50'E longitude), having no cases during the last decade, as non-endemic foci. The total areas of the selected village in endemic and non-endemic sites are 7008.74 and 15829.01 hectares respectively. The numbers of households are approximately 8206 and 4221 having populations of 54321 and 23082, in the endemic and non-endemic site, respectively.A cross-sectional descriptive study was designed and conducted in the two districts from October 2007 to July 2008 in an endemic site  and February 2009 to July 2009 in a non-endemic site (Lohardaga District).In each district, twenty four villages were selected randomly to carry out the research work. In each village 10 houses were selected randomly and were sampled for indoor day-resting sandflies by a Communicable Disease Centre (CDC) Light trap. Thus two hundred and forty households of the twenty four villages were taken from Vaishali district, suspected to have VL cases and two hundred and forty households of the twenty four villages were taken from Loharadaga district with no recorded VL cases.Sandflies were collected through Communicable Disease Centre (CDC) light trap from the living rooms as well as cattle sheds respectively from the endemic and non-endemic houdeholds. Collected sand flies were preserved in 70% alcohol and transported to the laboratory; sandfly number, type and gender, and vector species were also recorded for each site in the laboratory.Since multilevel cluster sampling design was used taking a village as primary selection unit (PSUs) and randomly selected houses from each cluster, Stata version 10.0 'xt' command was used for performing multilevel logistic regression analysis to investigate the effect of the house-level characteristics on the presence or absence of vectors in the household. The majority of housing characteristics are categorical variables , presence of cattle shed, and cattle population) Table . VariablP.argentipes (in an endemic site -65.98% and non-endemic site-61.48%), followed by Sergentomiya (32.53% in endemic site and 38.52% in non-endemic site) and very small percentage of P. papatasi (1.49% in an endemic site only). In an endemic area, out of ten houses in each village, 60% of houses had shown the presence of vectors, whereas, in non-endemic area only 30% of houses had the vector present.During October 2007 to July 2009, a total of 535 sandflies were collected from the twenty four villages (240 households) in an endemic site , which consisted of 53.90% males and 46.10% females. Similarly, from the non-endemic sites (Lohardaga District), a total of 268 Phlebotomine sandflies were collected from twenty four villages (240 households), among them 57.41% were male and 42.59% were female. The major percentage of phlebotomine sandflies collected from endemic and non-endemic sites belong to P. argentipes in both endemic and non-endemic areas was significantly much higher (P < 0.001) as compared with the proportion of the Sergentomiya and P. papatasi. However, there was no significant difference in the proportion of P. argentipes and Sergentomiya in the endemic area as compared with the non-endemic area. This indicates that the distinction of different species of sandfly is similar in endemic and non-endemic area.Overall, the proportion of First univariate analysis was performed for estimating crude odds ratios with 95% confidence intervals Table . Among aP value = 0.004), thatched roof , mixed dwelling  and area  were found associated with presence of absence of vectors.The results Table  showed tP-value = 0.001), mixed dwellings i.e. cattle and human being  living together in high endemic area  of Kala-azar could be the possible independent risk factors for presence of vector population without having any significant joint effect. The intra-class correlation  was very low indicating heterogeneity among the PSUs (villages) but not statistically significant (p = 0.318).The final model Table  indicateP. argentipes infestation in India provides an important source of information to inform control programmes for Kala-azar, and specifically to identify house-level risk factors for P. argentipes. The most important characteristics of the survey are (i) standardize collection method of P. argentipes and housing quality, (ii) geographic coverage of Kala-azar endemic and non-endemic region, and (iii) use of non-endemic region for positive control services, in a manner that could be replicated in future large scale surveys and monitoring programmes.The cross-sectional survey of P.argentipes. Hence, they may be considered as a risk factor for disease transmission. Generally, poor housing construction was found to be characteristics of the study area where visceral leishmaniasis was prevalent and vector density is also high. The reports of earlier workers, also support these findings and have been reported that mud plastered household and cattle shed are suitable for the development of phlebotomine species in Indian sub-continent [Analysis of the survey results indicates statistically significant relationships between specific house-level characteristics and the domestic infestation with the phlebotomine vector. The results of our study, including housing structure with mud plastered wall, thatched roof, mixed dwelling and area are suitable for breeding and the propagation of ontinent ,17, Brazontinent  and Kenyontinent  respectiP value = 0.002) strongly associated with the presence/absence of vector. Sandflies were collected from the cattle shed of endemic and non-endemic sites, and in most instances the cattle sheds were poorly ventilated with high organic contents (cow dung and urine of the cattle) and loose wooden planks. Thus it appears that a cattle shed provides a surrogate effect for breeding and resting site of P.argentipes, and to ensure continuous transmission of infection to humans. Hence, the cattle population could also influence the presence of vector and transmission of the disease and thus increase exposure to infection as has been previously observed in Bihar [Favorable transmission conditions resulting in significant disease may thus be associated with the presence of cattle sheds . Our stuin Bihar ,22, in Nin Bihar  and in Bin Bihar . HoweverThe results of this study have implications for maximizing surveillance efficacy of sandflies, which is likely to become increasingly important in formulating any control strategy. In order to maximize efficacy, however, it is also essential to investigate risk patterns over large spatial scale, and to combine vector data with other sources of risk information. These analyses suggests that future surveys could capture a large proportion of the inter-house variability in disease risk by recording a limited number of key structural factors, and that most important of these  could be recorded without needing to enter individual houses. Further analysis will investigate environmental determinants of the geographic distribution of vectors, as well as the inter-relationship between measures of vector infestation and infection risk in humans, in order to optimize allocation of surveillance and control effort. It is the first experimental proof regarding risk factors associated with hose-level characteristics involved in the propagation and multiplication of Kala-azar vector in India.The authors declare that they have no competing interests.SK carried out in the article's conceptualization and conducted the literature review and the design of this study. GSB participated in field data collection, analyzed, interpreted the compiled data and drafted the manuscript. VK helped to draft the manuscript. AR participated in statistical analysis. AJ helped to interpret the results and co-ordination in its design. PD helped envisage this research and contributed to the analysis and interpretation of the results. All authors read and approved the final manuscript.


Disturbance of the pro-coagulatant and anti-coagulant balance is associated with a poor outcome from critical illness. The objective of this study is to determine whether the Factor V Leiden (FVL) mutation is associated with susceptibility to or death from critical illness.A genetic association study involving four case cohorts comprising two Gram negative sepsis, one invasive pneumococcal disease and one intensive care unit cohort with a total of 1,249 patients. Controls were derived from a population-based cohort study . DNA from patients and controls was genotyped for the FVL mutation.Escherichia coli or Streptococcus pneumoniae sepsis.When all patients were investigated together no significant difference in the frequency of FVL mutation was observed compared with controls (odds ratio (OR), 1.03; 95% confidence interval (CI), 0.83 to 1.29). However, when stratified among patients admitted to intensive care (N = 237), susceptibility and the likelihood of long-term death was influenced by the FVL mutation. In adjusted logistic regression analysis, FVL carriers had an increased risk of ICU admission compared to non-carriers . In adjusted Cox regression analysis, FVL carriers were at increased risk of long-term death compared to non-carriers . FVL carrier status did not predict either susceptibility to or outcome from Gram negative, Overall, the FVL mutation did not appear to increase the risk of admission due to severe invasive infections. Nevertheless, in the subgroup of patients admitted to intensive care an increased risk and a poorer long-term outcome for individuals with critical illness were observed for FVL mutation carriers. Critical illness associated with sepsis and the systemic inflammatory response syndrome (SIRS) is an important cause of morbidity and mortality -3. In reper se is associated with an increased risk of thromboembolism [One human genetic factor that may be involved is factor V but its role is controversial. A single non-synonymous amino acid substitution Arg506Gln) in factor V, the factor V Leiden (FVL) mutation, causes resistance to activated protein C (APC) leading to increased levels of thrombin [06Gln in embolism .Clinical and experimental studies that have investigated the effect of the FVL mutation on sepsis outcomes have come to conflicting conclusions. In one clinical trial, FVL carriers with severe sepsis had a survival benefit compared to non-carriers . SimilarStreptococcus pneumoniae. The allele and carrier frequencies were analyzed for association with susceptibility to infection and outcome from infection.The aim of the present study was to study the possible association of FVL with critical illness caused by sepsis and SIRS. To this end, we genotyped five cohorts including individuals without infection, individuals with SIRS and individuals with sepsis caused by Gram negative bacteria and All subjects who participated in the 1991 to 1994 Copenhagen City Heart Study (CCHS) were included in the control group if they had not had an infectious disease hospitalization by 31 December 2001 or a case of invasive pneumococcal disease (IPD) by 1 October 2007. Subjects ≥ 20 years old were selected randomly after age stratification from among residents of Copenhagen. Of the 17,180 individuals invited, 10,135 participated, 9,259 provided blood samples, and 9,253 were genotyped for factor V Leiden. A total of 1,106 individuals were excluded because they had been hospitalized at least once with an infectious disease. Thus, a total of 8,147 adults comprised the control group. Ninety-nine percent were of Danish decent . DetailsThere were 452 consecutive episodes of Gram negative bacteremia among 427 individuals admitted to Hvidovre Hospital from June 2000 through May 2002. Of these, 319 were a first episode of bacteremia during the study period and had DNA collected. None of the patients were lost to follow-up. Ninety-five percent were of Danish decent. Details of the study are described elsewhere . The stuEscherichia coli were included in the study. A total of 575 consecutive episodes of E. coli bacteremia with bacturia were included. None of the patients were lost to follow-up. The study was approved by the Ethics Committee for Copenhagen and Frederiksberg counties (record no. 01-2006-6173).All patients older than 18 years admitted to Amager Hospital, Bispebjerg Hospital, Frederiksberg Hospital or Hvidovre Hospital in Copenhagen from January 2003 through May 2005 with a positive blood and urine culture yielding From February 1998 to July 1999, 272 individuals admitted to the academic, multidisciplinary ICU at Glostrup Hospital, who met the criteria for SIRS, as outlined by Bone et al. , were inTwo studies contributed cases to the IPD cohort. In the 1991 to 1994 CCHS, cases  were identified through linkage with the National Streptococci Reference laboratory (NSR), Statens Serum Institut . In tota® MGB assay, Applied Biosystems, Foster City, CA, USA) according to the manufacturer's instructions. Four controls were added for every 44 reactions: two allelic controls  and two non-template controls. PCR was performed under the following conditions: 1 × 10 minutes 95°C and 40× . Results were analyzed on ABI PRISM 7700 Sequence Detection platform using the SDS software v1.9 (Applied Biosystems), and using the allele discrimination plate read function to detect the end-point fluorescence in each well. Genotype results were manually assigned. Sanger-sequencing was applied to two randomly chosen patients on each plate .Genomic DNA was extracted and stored at -20°C. The FVL mutation Arg506Gln) was identified by one of three methods. Restriction fragment length polymorphism PCR was used for the CCHS control group, G1 and IPD cohort as described Gln was i,22. Ligh2 tests. Allele, genotype, carrier frequency and demographic features were evaluated by using χ2 or Fisher exact tests, whenever appropriate. We calculated odds ratios (ORs) and 95% confidence intervals (CI) when appropriate. Multiple logistic regression analysis was done to evaluate the association between FVL and susceptibility to infection after adjusting for age and sex.Genotype distributions were tested for Hardy-Weinberg equilibrium by using χP values of < 0.05 to be statistically significant.In survival analysis, heterozygous and homozygous individuals were combined (carriers) and compared with noncarriers. Cox regression analysis examined time to death by using hazard ratios (HR) with 95% CIs. Covariates that were associated with death in univariate analysis were included in the multivariate model. Short-term survival was defined as outcome at Day 30 after admission for infection or critical illness. Long-term outcome was defined survival status at the end of follow up. Statistical analysis was performed with SPSS 17.0 . We considered two-tailed P > 0.2 for all). Characteristics of subjects in each cohort are shown in Table The genotype distribution did not differ from that predicted by Hardy-Weinberg equilibrium for any of the five cohorts (P = 0.006) than individuals included but did not differ with respect to sex or markers of disease severity at baseline. Overall the ICU cohort was slightly younger and had more males than the control cohort  and 1.62 (1.08 to 2.42), respectively; Table From the ICU cohort, 237 individuals (87%) had DNA available for analysis. Individuals excluded because DNA was unavailable were significantly younger  from survival . Sun et survival . Brüggemsurvival . The fivsurvival -10,13,14survival . Adamziksurvival . FVL wasThe increased risk of critical illness associated with FVL carriage is not immediately explained. FVL leads to greater risk of thromboembolism and confers resistance to APC . TreatmeFVL affected long-term survival from critical illness. It is unclear what may explain this correlation. One explanation may be that critical illness altered the comorbid risk profile of patients after discharge. Smeeth et al. have shown that acute lower respiratory tract infections and urinary tract infections are associated with a transient increase in the risk of a vascular event  ,26. The Our study has several limitations. Individuals in the case cohorts were either younger or older than individuals in the control cohort. This may influence the estimates of disease susceptibility because age is one of the most important risk factors for acquisition of infectious disease. However, the effects of Factor V Leiden carrier status did not change significantly when age was included or omitted from the logistic regression analysis.Ethnicity was unknown in three of the five cohorts. Population stratification may lead to findings that are due to the underlying structure of the population and not the genetic variation being studied. However, we find it unlikely that population stratification has affected our results. In the two cohorts with known ethnic background 99% and 95% of individuals were of Danish decent. The remaining three cohorts were recruited from similar populations in the same geographical area as the cohorts with known ethnic backgrounds.The G1 and ICU cohorts were established prior to the approval of activated protein C (APC) for treatment of severe sepsis. However, cohort G2 and, in part, the IPD cohort were established after 2002. In theory, use of APC could modulate the effect of the Factor V Leiden mutation. Information on APC use in these two cohorts was unavailable but a very limited number of individuals in all of Denmark received APC during the study period (the average number of APC treatments in Denmark between 2004 and 2008 were 20 per year). Thus, it appears unlikely that use of APC affected our results. The sample size was small to moderate for the four disease cohorts. Consequently, the study may have had insufficient statistical power to detect small and moderate associations between FVL carrier status and disease or disease outcome.Overall, the FVL mutation did not appear to increase the risk of admission due to severe invasive infections and was not associated with overall outcome. However, the present study suggests that the FVL mutation may increase the susceptibility to critical illness and may confer a poor long-term outcome of critical illness.• The FVL mutation was significantly associated with an increased risk of admission to intensive care.• The FVL mutation was significantly associated with an increased risk of long-term mortality after admission to intensive care.• The FVL mutation was not associated with an increased risk of severe invasive infections.APC: activated protein C; ARDS: adult respiratory distress syndrome; CCHS: Copenhagen City Heart Study; CI: confidence interval; DNA: dioxynucleotide acid; FVL: factor V Leiden; G1: Gram negative sepsis cohort 1; G2: Gram negative sepsis cohort 2; GAS: group A streptococcus; HR: hazard ratio; ICU: intensive care unit; IPD: invasive pneumococcal disease; LPS: lipopolysaccharide; OR: odds ratio; RCT: randomized controlled trial; SAPS: sepsis acute physiology score; SIRS: systemic inflammatory response syndrome.The authors declare that they have no competing interests.TB conceived the collaborative study. JHL, CØ and TB designed and collected data and samples for the Gram negative sepsis cohort 1. KE and TB designed and collected data and samples for the Gram negative sepsis cohort 2. NW and GK designed and collected data and samples for the invasive pneumococcal disease cohort. ATH and BGN designed and collected data and samples for the Copenhagen City Heart Study. PG designed and collected data and samples for the intensive care unit cohort. KJ, LMF and MRA performed factor V genotyping. TB and PG drafted the first version. All authors read, revised and approved the final version.


Theoretical modeling is a technique widely used to study the electrical-thermal performance of different surgical procedures based on tissue heating by use of radiofrequency (RF) currents. Most models employ a parabolic heat transfer equation (PHTE) based on Fourier’s theory, which assumes an infinite propagation speed of thermal energy. We recently proposed a one-dimensional model in which the electrical-thermal coupled problem was analytically solved by using a hyperbolic heat transfer equation (HHTE), i.e. by considering a non zero thermal relaxation time. In this study, we particularized this solution to three typical examples of RF heating of biological tissues: heating of the cornea for refractive surgery, cardiac ablation for eliminating arrhythmias, and hepatic ablation for destroying tumors. A comparison was made of the PHTE and HHTE solutions. The differences between their temperature profiles were found to be higher for lower times and shorter distances from the electrode surface. Our results therefore suggest that HHTE should be considered for RF heating of the cornea , and for rapid ablations in cardiac tissue (less than 30 s). Theoretical modeling has been widely used to investigate and develop new techniques of RF heating (RFH) in biological tissue and to study in depth the electrical and thermal phenomena involved in the process . To datek is the thermal conductivity and   Tr→,t the temperature at point r→ at time t. As a result, a parabolic heat transfer equation (PHTE) was employed as the governing equation. Fourier’s theory assumes an infinite thermal energy propagation speed, i.e. any local temperature disturbance causes an instantaneous perturbation in the temperature at each point in the medium [τ) for the tissue ≠0 [where e medium . Althouge medium ), a non-issue ≠0 . As it iissue ≠0 , Cattaneissue ≠0  and Vernissue ≠0  simultanτ is the thermal relaxation time of the biological tissue. This equation assumes that the effect (heat flux) and the cause (temperature gradient) occur at different times and that the delay between heat flux and temperature gradient is τ [τ = 0 obviously corresponds to the Fourier theory.where ent is τ . The parIn order to make a theoretical study of the differences in the temperature profiles obtained from both equations in a general case of RFH, we recently built a one-dimensional model in which the electrical-thermal coupled problem was analytically solved by using both PHTE and HHTE . In this0r radius spherical electrode completely imbedded in and in close contact with the biological tissue , which had an infinite dimension.Model geometry similar to those proposed by Erez and Shitzer  was consQ) can be expressed as:The model thus presented radial symmetry and a one-dimensional approach was possible. Regarding the electrical problem, the source term for the RFH modeling , r0 the electrode radius, and H(t) is the Heaviside function. Here we are modeling a protocol of constant power step at t=0. We then considered Özişik and Tzou’s heat transfer model [where er model :which combined with the energy equation:ρ is the density and c the specific heat, allows to obtain:where α is the thermal diffusivity.where Finally, we combined (3) and (6), and we obtained the governing equation (HHTE) for the hyperbolic case:δ(t) is Dirac’s function. To write the boundary condition in r = r0 we adopted a simplification assuming the thermal conductivity of the electrode to be much larger than that of the tissue  [where ectrode) . This coectrode) . The PHTectrode) .1 [Once the two analytical solutions had been obtained by HHTE and PHTE, they were applied in a theoretical study of temperature distributions in three types of biological tissues: cornea, heart and liver. Electrical and thermal characteristics of these tissues are shown in Table 1 ,10,11.τ(t). For cardiac and hepatic tissue we considered a value of τ = 16 s . Valuessed meat , suggestτ = 0.1 s for it. This is obviously a first approximation and experimental data obtained from further studies could give different results. Since the cornea has a more homogeneous inner structure than these tissues, we considered the lower value of 3 kg/m3, specific heat 132 J/kg.K, and thermal conductivity 71 W/m·K [Regarding the active electrode, even though a stainless steel active electrode is used in various RFH procedures, in this study we only employed an active electrode made of platinum-iridium, as used in RF cardiac ablation. The characteristics of this electrode were: density 21.5×1071 W/m·K . In the 2) shows the temperature distributions along the radial axis for different times from 10 ms to 600 ms for the two heat transfer equations. For shorter times , the HHTE produced temperatures higher than the PHTE. However, this trend became negligible for a longer time t = 600 ms, when both equations gave similar temperatures . This phenomenon can also be observed in Fig. (3), which plots temperature progress at three locations. As can be seen from this figure, at the beginning of heating, the rate of temperature change with HHTE was faster than PHTE and differences became small for longer times. The most remarkable characteristic of the HHTE analytical solution was the presence of cuspidal type singularities. This was materialized as a temperature peak which traveled through the medium at the finite speed of ≈1.25 mm/s .Firstly, we considered the case of conductive keratoplasty (CK), in which a small active electrode is inserted into the cornea and a small amount of energy is delivered to the corneal stroma (less than 600 mW for 600 ms) . As the 4) shows the temperature distributions along the radial axis for times from 5 s to 120 s for the two heat transfer equations. The differences in both solutions were considerable at the beginning of heating, especially for t ≤ 30 s .Secondly, we modeled an RF cardiac ablation. In this case, we considered an electrode radius of 1.5 mm, and a power of 3 W for 120 s. The initial temperature was assumed to be 37ºC. Fig. (4A).Once more, in the initial stages HHTE produced higher temperatures than PHTE. Likewise, the presence of cuspidal type singularities from the HHTE were also observed in the case of cardiac ablation as a temperature peak which traveled through the medium at the finite speed of ≈0.1 mm/s  shows the temperature distributions along the radial axis for five different times  for both heat transfer equations. In this third case, which involved longer times, the differences between the equations were almost negligible. Temperature peaks associated with the cuspidal type singularities from the HHTE were only observed for shorter times .Finally, we modeled the RF liver ablation without blood perfusion . In this case, we considered an electrode radius of 1.5 mm and power of 1 W for 720 s. Initial temperature was assumed to be 37ºC. Fig. . This is in agreement with the results obtained by Banerjee et al. [In all three cases we observed similar behavior in the results, which allows us to discuss them jointly. On one hand we observed that at the beginning of the heating , PHTE provided temperature values lower than those provided by HHTE . This phenomenon has also been observed in other modeling studies on tissue heating and can be explained by the fact that when using HHTE, a period of time is needed for the heat to travel to a particular location in the tissue [On the other hand, the temperature evolution in HHTE was delayed compared to PHTE. In our study this delay was small and only apparent in some plots of Figs. , it can be checked that they traveled at speeds of ≈1.25 mm/s and ≈0.1 mm/s respectively. These correspond approximately with the finite propagation speeds of the thermal wave (v) for cornea and cardiac tissue respectively, obtained from the following formula [Regarding the temperature peaks shown in Figs. ( formula :t=ταr−r0),However, this is not surprising since the mathematical solution of HHTE  showed twhich is implicitly contained in equation (8).To date, different aspects of the hyperbolic heat transfer equation have been proposed and studied. For example, more general versions using two relaxation parameters, one for the heat flux (coincident with our constant τ) and another for the temperature gradient have been considered -21. HoweThis modeling study has several limitations which should be pointed out. Firstly, the geometry of our model  is very simple compared not only to the realistic geometry of the electrodes employed in clinical practice , but also to the heterogeneity of different types of tissue. However, it is necessary to point out that the main purpose of this study was to particularize an analytical solution of HHTE in RFH modeling for three examples of RFH applications. We therefore think that the differences found in this study between both heat transfer equations might be even higher if more realistic electrode geometries were considered (since electrodes with a sharper tip might involve higher temperature gradients). Further modeling studies considering realistic geometries for the active electrodes and obviously based on numerical methods could assess this hypothesis.Since we employed a constant-power protocol, we did not consider changes in electrical conductivity (σ) of the tissue with temperature (which would be important in constant-voltage or constant-current protocols). We think that the differences found in our study between the two heat transfer equations might be even higher if this thermal dependence were to be taken into account, especially by applying a constant voltage protocol. We support the hypothesis on the well-known effect of thermal feedback in electrosurgical heating . BrieflyFinally, future studies should take the tissue damage process into account, using for instance a first order kinetics model rather than a single temperature value . In relaConsequently, we think that future studies on numerical RFH modeling, including realistic electrode geometries, changes in electrical conductivity with temperature and a tissue damage function will provide greater differences between the solutions obtained.In addition, even though under certain circumstances the difference between the temperatures obtained from the two equations were sizable, it is necessary to emphasize that in the simulations we had to assume values for the tissue thermal relaxation times due to the lack of experimental data. In spite of these limitations, we believe that this study is the first step in the development of theoretical models for RFH which include the hyperbolic heat transfer equation and hence are able to provide more accurate RFH modeling. The following section calls attention to some ideas for future work in this area.2), we think that the differences between the two equations could be higher in the case of pulsed power due to the accumulated differences (pulse by pulse) between the temperatures obtained from each heat transfer equation. In fact, the hyperbolic heat transfer equation has been specially employed for heating techniques based on short energy pulses [τ) of different biological tissues under different conditions. This could mean significant changes in some of the results of our study related to specific RFH cases.As we have mentioned, the analytical solution obtained for the simple geometry model presented in this study will allow us to validate other numerical models based on, for instance, the finite element method. However, future studies could be conducted using the one-dimensional model presented here. To be more precise, we are interested in modeling not only the heating phase but also the cooling phase  . We thery pulses ,16. FinaFrom a mathematical point of view, the HHTE solution has cuspidal type singularities which reflect the wave nature of the thermal problem. At the beginning of the heating  PHTE provided temperature values lower than those from HHTE. The HHTE temperature evolution was delayed compared to those from PHTE due to the fact that heat needs a period of time to travel to a particular location inside the tissue.The differences between PHTE and HHTE temperature profiles were greater for lower times and shorter distances. For this reason, our results suggest that the HHTE should be considered in the case of RF heating of the cornea (heating time 0.6 s), and for short time ablation in cardiac tissue (less than 30 s).