HemoDownloader: Open source software utility to extract data from HemoCue HbA1c 501 devices in epidemiological studies of diabetes mellitus.

Diabetes mellitus is a serious disease with increasing global prevalence. Point-of-care analysis of glycated hemoglobin A (HbA1c) holds promise as a diagnostic test for diabetes mellitus in epidemiological studies in challenging environments with limited access to centralized biochemical labs. The HemoCue HbA1c 501 device can be used for point-of-care determination of HbA1c, but its usability in epidemiological studies is limited by its inability to export results in digital format. We have developed the open source HemoDownloader software to overcome this limitation of the device. HemoDownloader has an easy-to-use graphical user interface and can export data from HemoCue HbA1c 501 to standard spreadsheet file formats. The program has the potential to improve data collection and management in epidemiological studies of diabetes mellitus.

Introduction

Diabetes mellitus is a group of medical conditions characterized by insulin resistance and/or decreased insulin production, resulting in hyperglycemia [1]. The Global Burden of Disease Study estimated that in 2017, the global prevalence of diabetes mellitus was 476 million, and the diseases caused 1.4 million deaths [2].

The diagnosis of diabetes mellitus is often made based on measurement of fasting plasma glucose (FPG) or an oral glucose tolerance test (OGTT). Both of these tests require patients to fast [3], which can pose a logistical challenge. Glycated hemoglobin A (HbA1c) is a compound formed in the bloodstream by a non-enzymatic chemical reaction between glucose and hemoglobin. HbA1c is a measure of the average plasma glucose levels in the last 8–12 weeks [3], and it is approved by the World Health Organization for the diagnosis of diabetes mellitus, provided that appropriate quality control measures are in place, and the patient does not have other medical conditions rendering the results unreliable [3]. HbA1c analysis does not require fasting [3], making it an attractive alternative to diagnosis based on FPG and/or OGTT. Furthermore, HbA1c is recommended by the American Diabetes Association as the main measure of glycemic control among patients already diagnosed with diabetes [4].

Epidemiological studies of diabetes mellitus are needed to monitor the burden of the disease and to investigate novel risk factors for its development. Many of the world’s diabetic patients live in low- and middle-income countries [2] where conducting epidemiological studies is challenging, especially if biological samples have to be transported long distances for analysis at centralized biochemical labs. Point-of-care devices for the measurement of HbA1c exist and have the potential to simplify data collection for studies of diabetes mellitus in such settings. Our partners and we recently carried out an epidemiological study on glycemic regulation in Uganda [5, 6]. Our main outcome was HbA1c, determined by the point-of-care device HemoCue HbA1c 501 (HemoCue AB, Ängelholm, Sweden, www.hemocue.com). No software is currently available for extracting the analysis results from the device memory, so we developed the open source HemoDownloader utility to perform this task, in order to not rely solely on data collectors’ manual recording of results.

Methods

The software was developed for use in and tested during data collection for the “Pesticide Exposure, Asthma and Diabetes in Uganda” (PEXADU) study, which was a short-term observational cohort study on health effects of pesticide exposure among smallholder farmers in the semi-urban Wakiso District of Uganda. We recruited 364 farmers, most of whom underwent three HbA1c tests each from September 2018 to February 2018. Hence, more than 1000 HbA1c analyses were conducted during the study. Study findings have been reported elsewhere [5, 6].

The PEXADU study was conducted in accordance with the Declaration of Helsinki. Study participants gave written informed consent before inclusion and were financially compensated for lost earnings on examination days. The study was approved by the Higher Degrees Research and Ethics Committee at Makerere University School of Public Health (registration number 577) and the Uganda National Council for Science and Technology (registration number HS234ES).

Software description

The HemoCue HbA1c 501 device saves analysis results to its internal non-volatile memory with a capacity for 200 measurements [7]. Each result is tagged with the date and time of analysis. In addition, a barcode scanner used at the time of analysis can be used to tag each measurement with the IDs of the patient and of the technician performing the analysis [7].

The manufacturer of the HemoCue HbA1c 501 device does not provide software capable of exporting the contents of the internal device memory in digital format. This limits the usability of the device in epidemiological studies with hundreds or thousands of measurements, as results have to be manually recorded. The software that we have created (HemoDownloader) allows a PC to download the entire memory of the HemoCue HbA1c 501 device and save it in a structured file for further processing using standard statistical software. This makes the use of the device for epidemiological studies easier, faster and less error-prone.

HemoDownloader takes advantage of the fact that the HemoCue HbA1c 501 device supports printing all results in memory using a stand-alone thermal printer connected by a serial (RS232) cable [7]. To use HemoDownloader, the PC is connected to the printer port of the HemoCue HbA1c 501 device using a generic RS232 null-modem cable, and the printer function on the HemoCue HbA1c 501 device is activated [7]. HemoDownloader records the binary stream of data intended for the thermal printer, parses the data and saves the dataset on the hard drive of the PC. The software can export to CSV (Comma-Separated Values), TSV (Tab-Separated Values), XLSX (Microsoft Excel workbook) and XLS (Microsoft Excel 97–2003 workbook) file formats. The resulting file lists the date, time, technician ID, patient ID, and HbA1c analysis result for each measurement, with one line per observation. Fig 1 shows an example Microsoft Excel workbook, demonstrating the structure of the data saved by HemoDownloader. For reasons of confidentiality, the data in the example file are fictional.

Fig 1

Example data structure of exported file.

Note: The variables “operator_id” and “patient_id” will be blank if no barcode scanner was used to enter this information before sample analysis. If the HbA1c value in percent is <4% or >14%, the HemoCue HbA1c 501 device does not convert it to mmol/mol, and the latter field is left blank.

Practical use of the software

HemoDownloader is compatible with computers running Microsoft Windows (32 and 64 bit). The compiled versions of the software can be executed directly, do not require installation, and do not depend on any other installed software. Since the HemoDownloader software was developed in the Python 3 programming language, users who want to run the program from source code instead need to install Python 3 (Python Software Foundation, https://www.python.org), as well as the open source Python libraries pyserial, XlsxWriter and xlwt that are used by HemoDownloader. Installation scripts for these third-party libraries are included in S1 File in the online appendix.

Before using the HemoDownloader software, the user has to connect the PC to the HemoCue HbA1c 501 device using a RS232 null modem cable (a standard RS232 serial cable will not work). The user now starts the software and is presented with a simple graphical user interface (Fig 2). Before data can be recorded, the user must specify where to save the resulting file, and which of the PC’s serial ports to use. The user clicks the button “RECEIVE DATA” in HemoDownloader, and the utility is now ready to receive data.

Fig 2

Main program window.

The printer function of the HemoCue Hba1c 501 device is activated in the normal manner [7]: With the HemoCue HbA1c 501 device in stand-by mode, the user presses the device’s MODE button for three seconds, followed by the UP or DOWN buttons to select “Data”, and confirming by pressing the MODE button briefly. The HemoCue HbA1c 501 device will now display all results in memory. The user presses the PRINTER button briefly to bring up the print menu. Using UP or DOWN buttons, the user selects “ALL” and confirms by briefly pressing the MODE button. This will initiate the data transfer.

HemoDownloader will automatically close the serial connection when the transfer is complete. The HemoCue HbA1c 501 device only supports data transfer at 9600 baud, but the entire memory of the device can be downloaded in a few minutes.

HemoDownloader understands all date-time formats supported by the HemoCue HbA1c 501 device. The software automatically checks the recorded data for consistency and warns the used in case the data structure is not exactly as expected from the HemoCue HbA1c 501 device.

Discussion

Measurement of HbA1c instead of FPG or OGTT can simplify the logistics of epidemiological studies on diabetes mellitus, as HbA1c testing does not require fasting [3]. It is an advantage if the analysis can be carried out at the point-of-care, especially in studies in areas with poor access to centralized biochemical labs. The usefulness of the HemoCue HbA1c 501 device for point-of-care analysis of HbA1c in epidemiological studies is hampered by its inability to export data in digital format. HemoDownloader fulfills the need for a utility that can perform this extraction for more efficient data management, and its graphical user interface means that it can be utilized by non-technical users.

In the course of the PEXADU project, the HemoDownloader utility was used for the management of results from more than one thousand HbA1c analyses carried out over the course of several months. HbA1c results were recorded both manually and using HemoDownloader, and any inconsistencies between the recorded values were used to identify and correct bugs in the software. We are therefore confident that the software works as intended, and we hope that HemoDownloader will prove just as useful to other field researchers studying diabetes mellitus.

Please note that HemoDownloader is intended for use in epidemiological studies only. The software is not approved as a medical device and must not be used as such. That means the software must not be used on human beings for diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of disease or any other medical purposes.

Conclusions

We have presented our utility HemoDownloader that can be used to export HbA1c data recorded by the HemoCue HbA1c 501 device to standard file formats. We believe that HemoDownloader has the potential to improve data management in research projects utilizing the HemoCue HbA1c 501 for the study of diabetes mellitus in challenging environments such as low- and middle-income countries.

Source code for and compiled versions of HemoDownloader 1.1.

(ZIP)

Click here for additional data file.

22 Sep 2020

PONE-D-20-09858

HemoDownloader: Open source software utility to extract data from HemoCue HbA1c 501 devices in epidemiological studies of diabetes mellitus

PLOS ONE

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Reviewer #1: This manuscript shows good sound that there is a new way to get data from epidemiological studies only about HbA1c in diabetes melitus. The authors said that this software can be used for analysing thousand samples and it has been implemented in Uganda Research, but the total samples in Uganda research were 370 and it was cohort, which one is true, please explain more detail because the total samples are different. Data were transfered in excel form, this condition was rather difficult to analyse thousands (whole) data in research setting, did it need to integrate with other programme (application)?

I see the software just for transfering data that is in Hemocue and there is not special command in software for analysis. is it true? How did the software analyse 370 or thousand samples? please explain more to know the usefull of the software. How did this software identify the subjects (370 or thousand) if the research was cohort that need many times to perform? Did the author identify data one by one or separate with some instructions in software? The authors may show how data was grouped and analysed with this software (cohort and or cross sectional maybe), also show the benefit and minus of using this software, like in Uganda research that has been done.

The limitation of this software is only for epidemiological research, but may be the author can be improve this software in clinical setting.

Reviewer #2: This is an interesting article that describes the effort to create a software to export results in digital format from point of care device of HbA1c measurement. The development of this software was expected to help the researcher to improve data collection and management in epidemiological study of diabetes.

This study is supposed to be about software development to export stored data from Hemacue system and diabetes.

Critiques

1. The article is too basic discussing information that is more suitable for a software development article than for a research article. This is particularly true for the sections after introduction that describe the software and its practical use.

2. Beyond this much of the article appears to be a series of statements regarding the software and its benefit without presenting evidence to support the statements.

3. The article was written with unusual style in scientific paper in medicine or life science. As a scientific research, the article does not present any method and result to support the authors’ conclusions. Since this article was claimed as research article, the authors should explain the method of the study clearly.

4. Since diabetes is a major health problem, the information regarding diabetes is updated frequently by International Diabetes Federation and WHO. Therefore, the use of reference regarding the incidence and mortality rate of diabetes (line 30) from the report article published more than 5 years ago is not acceptable.

4. The Authors wrote “Epidemiological studies of diabetes mellitus are needed to monitor the spread of the disease and to investigate novel risk factors for its development” (line no.44). I think the use of phrase “the spread of the disease” is not appropriate with the context of diabetes since it is not a transmitted disease.

5. The sentence “Our partners and we recently carried out an epidemiological study on health effects of pesticide exposure among small-scale farmers in the semi-urban Wakiso District of Uganda” (line 49) is not relevant with this article.

6. The authors do not give any strong reason why the project is important. Since the device for measuring HbA1c are available from many companies, the project to provide a software from the only one device from certain company is not relevant if the aim is for epidemiological study.

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3 Oct 2020

Academic Editor's Comment

Comment

The paper does not describe any research and cannot be published as a Research Article. Nevertheless, PLOSONE can publish another type of papers. This manuscript may be published as a type: new software and tools. For details see: https://journals.plos.org/plosone/s/submission-guidelines#loc-methods-software-databases-and-tools

If you agree with the paper type reclassification, please consider minor changing in the paper as stated in the reviews. Don't pay attention on the research related comments.

Response

We agree with the paper type reclassification. Unfortunately, we have been unable to change the type in Editorial Manager ourselves, as the only paper types that can be selected in the system are "Collection Review", "Overview", "Research Article", "Clinical Trial", "Registered Report Protocol" and "Registered Report". We kindly request that you help us change the paper type to “new software and tools”.

Journal Requirements

Comment

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

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Comment

2. Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please move it to the Methods section and delete it from any other section. Please ensure that your ethics statement is included in your manuscript, as the ethics statement entered into the online submission form will not be published alongside your manuscript.

Response

We have created a “Methods” section and moved the ethics statement there, deleting the separate “Ethics” section.

Reviewers' comments

Reviewer #1

Comment

This manuscript shows good sound that there is a new way to get data from epidemiological studies only about HbA1c in diabetes melitus. The authors said that this software can be used for analysing thousand samples and it has been implemented in Uganda Research, but the total samples in Uganda research were 370 and it was cohort, which one is true, please explain more detail because the total samples are different.

Response

We have now added a “Methods” section, where we have provided more information on the number of participants and samples analyzed.

Comment

Data were transfered in excel form, this condition was rather difficult to analyse thousands (whole) data in research setting, did it need to integrate with other programme (application)?

Response

We used Stata to analyze the extracted data. We have not added this information to the current manuscript, as we do not present any results from the analysis here.

Comment

I see the software just for transfering data that is in Hemocue and there is not special command in software for analysis. is it true?

Response

Before data collection for the study started, we contacted HemoCue (the manufacturer of the HbA1c 501 device), as we wished to purchase data management software for the device. We were informed by the company that such software did not exist.

Comment

How did the software analyse 370 or thousand samples? please explain more to know the usefull of the software.

Response

The HemoCue HbA1c 501 device analyzed more than one thousand samples from 364 individuals. The HemoDownloader software was used to download the data from the analyzer to a PC. HemoDownloader cannot be used for data analysis – this has to be conducted in other software, e.g. Excel, Stata or R.

Comment

How did this software identify the subjects (370 or thousand) if the research was cohort that need many times to perform?

Response

Please see the new “Methods” section as described above.

Comment

Did the author identify data one by one or separate with some instructions in software?

Response

As described in the section “Practical use of the software”, HemoDownloader can be used to simultaneously download all results saved in the memory of the HemoCue HbA1c 501 device (the device has a capacity of 200 results). The software parses to data received to identify individual measurements and saves each measurement as a separate observation in the output file.

Comment

The authors may show how data was grouped and analysed with this software (cohort and or cross sectional maybe), also show the benefit and minus of using this software, like in Uganda research that has been done.

Response

As described above, HemoDownloader was not used to analyze the data, only to download it from the HemoCue HbA1c 501 to a PC.

In the new “Methods” section, we have provided references to two publications in which the results from statistical analyses can be found: The PhD thesis of the first author, and a recent publication in Occupational and Environmental Medicine.

As described in the “Discussion” section, the advantage of using HemoDownloader is that it can make data management easier in epidemiological studies of diabetes mellitus, as researchers using the HemoCue HbA1c 501 do not have to rely on manual data entry. Theoretically, using software to extract the data will lead to a small risk of data corruption due to data transfer errors. However, we implemented a number of data consistency checks in the HemoDownloader software, and we used the software every day for several months of data collection. More than one thousand HbA1c analyses were recorded both manually and using HemoDownloader, and any inconsistencies in data were used to correct software bugs so that the inconsistencies disappeared. We are therefore confident that HemoDownloader functions as intended. To keep the manuscript concise, we have not elaborated in detail on this in the manuscript.

Comment

The limitation of this software is only for epidemiological research, but may be the author can be improve this software in clinical setting.

Response

To allow HemoDownloader to be used in clinical settings, it would have to be approved as a medical device. Unfortunately, we do not have the financial resources to apply for such approval. However, as we are releasing the software as open source, anyone wishing to use the software in a clinical setting is free to apply for this approval him- or herself.

Reviewer #2

Comment

This is an interesting article that describes the effort to create a software to export results in digital format from point of care device of HbA1c measurement. The development of this software was expected to help the researcher to improve data collection and management in epidemiological study of diabetes.

This study is supposed to be about software development to export stored data from Hemacue system and diabetes.

Critiques

1. The article is too basic discussing information that is more suitable for a software development article than for a research article. This is particularly true for the sections after introduction that describe the software and its practical use.

Response

We agree and request that the editor change the manuscript type to “new software and tools”.

Comment

2. Beyond this much of the article appears to be a series of statements regarding the software and its benefit without presenting evidence to support the statements.

Response

As described in the section “Source code availability”, we are releasing the source code for the software in S1 File as well as on GitHub (https://github.com/martinrunehassanhansen/HemoDownloader). While knowledge of the Python programming language is needed to understand the source code, readers can review the source code to confirm how the software works, including the automatic checks for data consistency. Numerous comments have been added in the source code files to make it easier for third parties to review and understand the code.

Comment

3. The article was written with unusual style in scientific paper in medicine or life science. As a scientific research, the article does not present any method and result to support the authors’ conclusions. Since this article was claimed as research article, the authors should explain the method of the study clearly.

Response

We have added a “Methods” section providing basic information on the study for which the software was developed.

Comment

4. Since diabetes is a major health problem, the information regarding diabetes is updated frequently by International Diabetes Federation and WHO. Therefore, the use of reference regarding the incidence and mortality rate of diabetes (line 30) from the report article published more than 5 years ago is not acceptable.

Response

We have revised this section to use the newest available estimates for the global prevalence and number of deaths caused by diabetes mellitus, based on the Global Burden of Disease Study 2017.

Comment

4. The Authors wrote “Epidemiological studies of diabetes mellitus are needed to monitor the spread of the disease and to investigate novel risk factors for its development” (line no.44). I think the use of phrase “the spread of the disease” is not appropriate with the context of diabetes since it is not a transmitted disease.

Response

We understand how the term “spread” could be misleading and have replaced it with the word “burden”.

Comment

5. The sentence “Our partners and we recently carried out an epidemiological study on health effects of pesticide exposure among small-scale farmers in the semi-urban Wakiso District of Uganda” (line 49) is not relevant with this article.

Response

We have revised this sentence to make it more concise and relevant, and have moved background information on the PEXADU study to the new “Methods” section.

Comment

6. The authors do not give any strong reason why the project is important. Since the device for measuring HbA1c are available from many companies, the project to provide a software from the only one device from certain company is not relevant if the aim is for epidemiological study.

Response

In addition to our own project, the HemoCue HbA1c 501 has been used or evaluated for the assessment of glycemic regulation in at least 12 previous scientific papers. This indicates that software to improve data management from the device could be of use to the scientific community.

While we agree that it would be optimal to have software that could interface with HbA1c analyzers from many different companies, developing such software was outside the scope of our project. However, since we are releasing the HemoDownloader software under the GNU General Public License, anyone will be free to reuse the code and incorporate it in software that can interface with multiple devices.

27 Oct 2020

HemoDownloader: Open source software utility to extract data from HemoCue HbA1c 501 devices in epidemiological studies of diabetes mellitus

PONE-D-20-09858R1

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Academic Editor

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3 Nov 2020

PONE-D-20-09858R1

HemoDownloader: Open source software utility to extract data from HemoCue HbA1c 501 devices in epidemiological studies of diabetes mellitus

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