Reviewer's report
Title:Severity of acute hepatitis and its outcome in patients with dengue fever in
a tertiary care hospital Karachi, Pakistan (South Asia): An Analytic cross
sectional study.
Version: 2Date:26 November 2009
Reviewer: Dorothea Nitsch
Reviewer's report:
Review of Severity of acute hepatitis and its outcome in patients with dengue
fever in a tertiary care
hospital Karachi, Pakistan (South Asia): An Analytic cross sectional study.; Dr
Om Parkash et al.
This is a paper that wanted to look at the features of patients with Dengue
infection admitted to their hospital. This is a study that is retrospectively
reviewing case-notes and extracting information on patients, and I believe that
the authors interpreted this as a cross-sectional study, because they looked at
patients 'in a snap-shot'.
However, in epidemiological terms, what they have done, is to identify a cohort of
in-patients and follow them up:
'All inpatients of age > 14 years who had history of fever, positive dengue IgM
and whose ALT were done, were included in the study.', and they then looked at
their survival afterwards. Survival analysis is only possible if you have followed
up people over time. If this time-element of follow-up is present, epidemiologists
do call this a cohort study design. So I would advise to call this a cohort study
throughout. If the follow-up had been absent, then this would have been a
cross-sectional study.
I will go through the features of the study point by point:
The authors have to clarify much more their service methods to patients who are
admitted with fever:
=> Is everybody tested for Dengue fever using IgM antibodies?
if yes, then this is fine, if no, then they will perhaps have selection bias at the
outset, and not a representative picture of all those who have Dengue fever. If
testing for Dengue is not done uniformly, authors have to convince us how they
ensured that they did not miss dengue fever cases.
=> A similar question applies for ALT testing. If testing is not done uniformly, then
they might have a very select group of Dengue patients (i.e. selected towards a
suspicion of liver injury, see also below), and not a representative picture.
=> Exclusion of patients with other forms of liver disease already at baseline will
bias the picture. At this stage it is about getting everybody who has Dengue into
the study. If they have another infection at admission (e.g. Hep C) then they still
are patients with Dengue worth looking at. Could the authors clarify how many
patients they excluded because they had a liver problem due to another disease
at start? This exclusion will again bias the study.
'... we aim to assess the frequency of hepatitis in dengue infection.
=> Please see my point to the issue of ALT testing and exclusion of patients as
outlined above. Only if all patients with Dengue fever were consistently tested,
then they get representative frequencies at baseline. If there is selection to start
with they have a cross-section of patients at baseline that is biased towards high
rates of elevated ALT.
=> I am not a hepatologist or gastroenterologist- but to my knowledge I don't
diagnose hepatitis just with ALT. The authors need to clarify how they confirmed
their diagnosis.
=> if there are concurrent other liver problems at baseline then it is important to
describe them, rather than excluding these patients - this will introduce bias and
give a wrong impression of what doctors in Karachi have to deal with.
'We also aim to compare their outcome (mortality,length of stay and
complications) between patients with mild to moderate and severe hepatitis in
dengue infection.'
=> this type of question is what makes this study a cohort study (please see
above). Now, for doing this analysis correctly, there is the need to identify
correctly all people with hepatitis and distinguish them from others. It is also
important to think about when the clock for risk associated with hepatitis starts
ticking... is it when the ALT is slightly elevated, or three times as much? What
about patients who initially don't have a liver problem but then go into septic
multiorgan failure a day after admission with then a liver problem - would the
clock start ticking at time of admission or afterwards? When did the clock stop
ticking - when they left hospital or died? From what was written I am not sure that
a systematic approach was taken.
=> re other complications: 'Renal Failure (ARF) was defined as rise of creatinine
(Cr) >3 times of baseline.' How can you calculate renal failure if patients don't
have baseline creatinines because they come in septic shock with renal failure?
If they had only one time point at which they had measured creatinine, then I
would suggest using the MDRD equation to estimate glomerular filtration rate
based on serum creatinine. This equation is not brilliant in South Asian patients
but the authors could define those with eGFR<30 as having a functional kidney
impairment (which is quite severe kidney impairment and unlikely to be biased by
the equation used).
Now, if management of patients is very consistent, then these questions above
can all be answered. If recording of what happened is poor, or if patients are
tested for problems in an irregular fashion based on doctor's perceptions then
half of the data are absent, and this study won't give us representative and
accurate information.
Regarding study size:
'We required a minimum sample size of 350 patients by assuming the 35%
prevalence of liver dysfunction in patients with dengue fever, with 0.05 bound on
error and 95% confidencelevel.(11)'
=> This sentence is definitely not written by somebody who understands
statistics - a 0.05 alpha implies that 95% confidence intervals will be calculated,
typically power calculations are done for a fixed alpha and for a given effect size
and a given power. I am not clear what the power will be. I am not sure which is
the main question they wanted to address with their sample size calculation- for
what did the researchers power:
- to find a given prevalence of hepatitis with a given accuracy?
- or to find an association with mortality? If yes, how big was the difference in
outcome they were powering for?
I would not request power calculations for a descriptive study if there are no prior
data on the problem. Somewhere one has to start. However I would request to
be very systematic in the approach to collecting data to really describe the
problem, and I am not convinced that has been done.
Regarding statistical analyses:
'Results are presented as mean + standard deviation (SD) for continuous
variables'
=> The descriptive analyses of continuous variables in this way are only
meaningful if the variables were normally distributed. If data were skewed (i.e.
non-symmetric around the mean), then perhaps other measures (e.g median,
upper and lower quartile values) might be more meaningful descriptors of the
summary data.
', frequency and percentage are given for qualitative variables. Chi square test
was used to compare categorical variables and
fischer exact test where applicable. Student t test was used to compare
continuous variables.'
=> This is all fine in terms of methods. If continuous data were skewed a t-test is
perhaps not ideal and non-parametric tests should be used. I am surprised that
the authors have no missing data - how did they deal with missing information?
'In survival analysis cox proportion hazard ratio (Cox regression) was determined
for mortality in DHF/DSS and severe hepatitis.'
=> how did the authors test that the assumptions of the Cox regression were
satisfied?
'Conclusions: ....Dengue fever should be considered when liver functions are
deranged apart from routine hepatotropic viruses.'
=> I would suggest to delete 'apart from routine hepatotropic viruses', because
dependent on the setting there are also bacteria (e.g. Leptospira) that cause a
very similar clinical picture.
I believe this paper reflects a fair bit of reviewing of case notes. Unfortunately it
needs some more work. Readers need to better understand whether this is a
representative study of in-hospital patients or not.
Statistical review: Yes, and I have assessed the statistics in my report.
Declaration of competing interests:
no competing interests
Reviewer's report
Title:Severity of acute hepatitis and its outcome in patients with dengue fever in
a tertiary care hospital Karachi, Pakistan (South Asia): An Analytic cross
sectional study.
Version: 2Date:26 November 2009
Reviewer: Dorothea Nitsch
Reviewer's report:
Review of Severity of acute hepatitis and its outcome in patients with dengue
fever in a tertiary care
hospital Karachi, Pakistan (South Asia): An Analytic cross sectional study.; Dr
Om Parkash et al.
This is a paper that wanted to look at the features of patients with Dengue
infection admitted to their hospital. This is a study that is retrospectively
reviewing case-notes and extracting information on patients, and I believe that
the authors interpreted this as a cross-sectional study, because they looked at
patients 'in a snap-shot'.
However, in epidemiological terms, what they have done, is to identify a cohort of
in-patients and follow them up:
'All inpatients of age > 14 years who had history of fever, positive dengue IgM
and whose ALT were done, were included in the study.', and they then looked at
their survival afterwards. Survival analysis is only possible if you have followed
up people over time. If this time-element of follow-up is present, epidemiologists
do call this a cohort study design. So I would advise to call this a cohort study
throughout. If the follow-up had been absent, then this would have been a
cross-sectional study.
I will go through the features of the study point by point:
The authors have to clarify much more their service methods to patients who are
admitted with fever:
=> Is everybody tested for Dengue fever using IgM antibodies?
if yes, then this is fine, if no, then they will perhaps have selection bias at the
outset, and not a representative picture of all those who have Dengue fever. If
testing for Dengue is not done uniformly, authors have to convince us how they
ensured that they did not miss dengue fever cases.
=> A similar question applies for ALT testing. If testing is not done uniformly, then
they might have a very select group of Dengue patients (i.e. selected towards a
suspicion of liver injury, see also below), and not a representative picture.
=> Exclusion of patients with other forms of liver disease already at baseline will
bias the picture. At this stage it is about getting everybody who has Dengue into
the study. If they have another infection at admission (e.g. Hep C) then they still
are patients with Dengue worth looking at. Could the authors clarify how many
patients they excluded because they had a liver problem due to another disease
at start? This exclusion will again bias the study.
'... we aim to assess the frequency of hepatitis in dengue infection.
=> Please see my point to the issue of ALT testing and exclusion of patients as
outlined above. Only if all patients with Dengue fever were consistently tested,
then they get representative frequencies at baseline. If there is selection to start
with they have a cross-section of patients at baseline that is biased towards high
rates of elevated ALT.
=> I am not a hepatologist or gastroenterologist- but to my knowledge I don't
diagnose hepatitis just with ALT. The authors need to clarify how they confirmed
their diagnosis.
=> if there are concurrent other liver problems at baseline then it is important to
describe them, rather than excluding these patients - this will introduce bias and
give a wrong impression of what doctors in Karachi have to deal with.
'We also aim to compare their outcome (mortality,length of stay and
complications) between patients with mild to moderate and severe hepatitis in
dengue infection.'
=> this type of question is what makes this study a cohort study (please see
above). Now, for doing this analysis correctly, there is the need to identify
correctly all people with hepatitis and distinguish them from others. It is also
important to think about when the clock for risk associated with hepatitis starts
ticking... is it when the ALT is slightly elevated, or three times as much? What
about patients who initially don't have a liver problem but then go into septic
multiorgan failure a day after admission with then a liver problem - would the
clock start ticking at time of admission or afterwards? When did the clock stop
ticking - when they left hospital or died? From what was written I am not sure that
a systematic approach was taken.
=> re other complications: 'Renal Failure (ARF) was defined as rise of creatinine
(Cr) >3 times of baseline.' How can you calculate renal failure if patients don't
have baseline creatinines because they come in septic shock with renal failure?
If they had only one time point at which they had measured creatinine, then I
would suggest using the MDRD equation to estimate glomerular filtration rate
based on serum creatinine. This equation is not brilliant in South Asian patients
but the authors could define those with eGFR<30 as having a functional kidney
impairment (which is quite severe kidney impairment and unlikely to be biased by
the equation used).
Now, if management of patients is very consistent, then these questions above
can all be answered. If recording of what happened is poor, or if patients are
tested for problems in an irregular fashion based on doctor's perceptions then
half of the data are absent, and this study won't give us representative and
accurate information.
Regarding study size:
'We required a minimum sample size of 350 patients by assuming the 35%
prevalence of liver dysfunction in patients with dengue fever, with 0.05 bound on
error and 95% confidencelevel.(11)'
=> This sentence is definitely not written by somebody who understands
statistics - a 0.05 alpha implies that 95% confidence intervals will be calculated,
typically power calculations are done for a fixed alpha and for a given effect size
and a given power. I am not clear what the power will be. I am not sure which is
the main question they wanted to address with their sample size calculation- for
what did the researchers power:
- to find a given prevalence of hepatitis with a given accuracy?
- or to find an association with mortality? If yes, how big was the difference in
outcome they were powering for?
I would not request power calculations for a descriptive study if there are no prior
data on the problem. Somewhere one has to start. However I would request to
be very systematic in the approach to collecting data to really describe the
problem, and I am not convinced that has been done.
Regarding statistical analyses:
'Results are presented as mean + standard deviation (SD) for continuous
variables'
=> The descriptive analyses of continuous variables in this way are only
meaningful if the variables were normally distributed. If data were skewed (i.e.
non-symmetric around the mean), then perhaps other measures (e.g median,
upper and lower quartile values) might be more meaningful descriptors of the
summary data.
', frequency and percentage are given for qualitative variables. Chi square test
was used to compare categorical variables and
fischer exact test where applicable. Student t test was used to compare
continuous variables.'
=> This is all fine in terms of methods. If continuous data were skewed a t-test is
perhaps not ideal and non-parametric tests should be used. I am surprised that
the authors have no missing data - how did they deal with missing information?
'In survival analysis cox proportion hazard ratio (Cox regression) was determined
for mortality in DHF/DSS and severe hepatitis.'
=> how did the authors test that the assumptions of the Cox regression were
satisfied?
'Conclusions: ....Dengue fever should be considered when liver functions are
deranged apart from routine hepatotropic viruses.'
=> I would suggest to delete 'apart from routine hepatotropic viruses', because
dependent on the setting there are also bacteria (e.g. Leptospira) that cause a
very similar clinical picture.
I believe this paper reflects a fair bit of reviewing of case notes. Unfortunately it
needs some more work. Readers need to better understand whether this is a
representative study of in-hospital patients or not.
Statistical review: Yes, and I have assessed the statistics in my report.
Declaration of competing interests:
no competing interests
Please review this paper.
user
Reviewer's report
Title:Severity of acute hepatitis and its outcome in patients with dengue fever in
a tertiary care hospital Karachi, Pakistan (South Asia): An Analytic cross
sectional study.
Version: 2Date:26 November 2009
Reviewer: Dorothea Nitsch
Reviewer's report:
Review of Severity of acute hepatitis and its outcome in patients with dengue
fever in a tertiary care
hospital Karachi, Pakistan (South Asia): An Analytic cross sectional study.; Dr
Om Parkash et al.
This is a paper that wanted to look at the features of patients with Dengue
infection admitted to their hospital. This is a study that is retrospectively
reviewing case-notes and extracting information on patients, and I believe that
the authors interpreted this as a cross-sectional study, because they looked at
patients 'in a snap-shot'.
However, in epidemiological terms, what they have done, is to identify a cohort of
in-patients and follow them up:
'All inpatients of age > 14 years who had history of fever, positive dengue IgM
and whose ALT were done, were included in the study.', and they then looked at
their survival afterwards. Survival analysis is only possible if you have followed
up people over time. If this time-element of follow-up is present, epidemiologists
do call this a cohort study design. So I would advise to call this a cohort study
throughout. If the follow-up had been absent, then this would have been a
cross-sectional study.
I will go through the features of the study point by point:
The authors have to clarify much more their service methods to patients who are
admitted with fever:
=> Is everybody tested for Dengue fever using IgM antibodies?
if yes, then this is fine, if no, then they will perhaps have selection bias at the
outset, and not a representative picture of all those who have Dengue fever. If
testing for Dengue is not done uniformly, authors have to convince us how they
ensured that they did not miss dengue fever cases.
=> A similar question applies for ALT testing. If testing is not done uniformly, then
they might have a very select group of Dengue patients (i.e. selected towards a
suspicion of liver injury, see also below), and not a representative picture.
=> Exclusion of patients with other forms of liver disease already at baseline will
bias the picture. At this stage it is about getting everybody who has Dengue into
the study. If they have another infection at admission (e.g. Hep C) then they still
are patients with Dengue worth looking at. Could the authors clarify how many
patients they excluded because they had a liver problem due to another disease
at start? This exclusion will again bias the study.
'... we aim to assess the frequency of hepatitis in dengue infection.
=> Please see my point to the issue of ALT testing and exclusion of patients as
outlined above. Only if all patients with Dengue fever were consistently tested,
then they get representative frequencies at baseline. If there is selection to start
with they have a cross-section of patients at baseline that is biased towards high
rates of elevated ALT.
=> I am not a hepatologist or gastroenterologist- but to my knowledge I don't
diagnose hepatitis just with ALT. The authors need to clarify how they confirmed
their diagnosis.
=> if there are concurrent other liver problems at baseline then it is important to
describe them, rather than excluding these patients - this will introduce bias and
give a wrong impression of what doctors in Karachi have to deal with.
'We also aim to compare their outcome (mortality,length of stay and
complications) between patients with mild to moderate and severe hepatitis in
dengue infection.'
=> this type of question is what makes this study a cohort study (please see
above). Now, for doing this analysis correctly, there is the need to identify
correctly all people with hepatitis and distinguish them from others. It is also
important to think about when the clock for risk associated with hepatitis starts
ticking... is it when the ALT is slightly elevated, or three times as much? What
about patients who initially don't have a liver problem but then go into septic
multiorgan failure a day after admission with then a liver problem - would the
clock start ticking at time of admission or afterwards? When did the clock stop
ticking - when they left hospital or died? From what was written I am not sure that
a systematic approach was taken.
=> re other complications: 'Renal Failure (ARF) was defined as rise of creatinine
(Cr) >3 times of baseline.' How can you calculate renal failure if patients don't
have baseline creatinines because they come in septic shock with renal failure?
If they had only one time point at which they had measured creatinine, then I
would suggest using the MDRD equation to estimate glomerular filtration rate
based on serum creatinine. This equation is not brilliant in South Asian patients
but the authors could define those with eGFR<30 as having a functional kidney
impairment (which is quite severe kidney impairment and unlikely to be biased by
the equation used).
Now, if management of patients is very consistent, then these questions above
can all be answered. If recording of what happened is poor, or if patients are
tested for problems in an irregular fashion based on doctor's perceptions then
half of the data are absent, and this study won't give us representative and
accurate information.
Regarding study size:
'We required a minimum sample size of 350 patients by assuming the 35%
prevalence of liver dysfunction in patients with dengue fever, with 0.05 bound on
error and 95% confidencelevel.(11)'
=> This sentence is definitely not written by somebody who understands
statistics - a 0.05 alpha implies that 95% confidence intervals will be calculated,
typically power calculations are done for a fixed alpha and for a given effect size
and a given power. I am not clear what the power will be. I am not sure which is
the main question they wanted to address with their sample size calculation- for
what did the researchers power:
- to find a given prevalence of hepatitis with a given accuracy?
- or to find an association with mortality? If yes, how big was the difference in
outcome they were powering for?
I would not request power calculations for a descriptive study if there are no prior
data on the problem. Somewhere one has to start. However I would request to
be very systematic in the approach to collecting data to really describe the
problem, and I am not convinced that has been done.
Regarding statistical analyses:
'Results are presented as mean + standard deviation (SD) for continuous
variables'
=> The descriptive analyses of continuous variables in this way are only
meaningful if the variables were normally distributed. If data were skewed (i.e.
non-symmetric around the mean), then perhaps other measures (e.g median,
upper and lower quartile values) might be more meaningful descriptors of the
summary data.
', frequency and percentage are given for qualitative variables. Chi square test
was used to compare categorical variables and
fischer exact test where applicable. Student t test was used to compare
continuous variables.'
=> This is all fine in terms of methods. If continuous data were skewed a t-test is
perhaps not ideal and non-parametric tests should be used. I am surprised that
the authors have no missing data - how did they deal with missing information?
'In survival analysis cox proportion hazard ratio (Cox regression) was determined
for mortality in DHF/DSS and severe hepatitis.'
=> how did the authors test that the assumptions of the Cox regression were
satisfied?
'Conclusions: ....Dengue fever should be considered when liver functions are
deranged apart from routine hepatotropic viruses.'
=> I would suggest to delete 'apart from routine hepatotropic viruses', because
dependent on the setting there are also bacteria (e.g. Leptospira) that cause a
very similar clinical picture.
I believe this paper reflects a fair bit of reviewing of case notes. Unfortunately it
needs some more work. Readers need to better understand whether this is a
representative study of in-hospital patients or not.
Statistical review: Yes, and I have assessed the statistics in my report.
Declaration of competing interests:
no competing interests
assistant