Skip to main content
PMC home page
PLOS ONE logoLink to PLOS ONE
. 2022 Apr 14;17(4):e0266907. doi: 10.1371/journal.pone.0266907

Lower limb amputations among individuals living with diabetes mellitus in low- and middle-income countries: A systematic review protocol

Eyitayo Omolara Owolabi 1, Davies Adeloye 2, Anthony Idowu Ajayi 3,*, Michael McCaul 4, Justine Davies 5, Kathryn M Chu 1
Editor: Daoud Al-Badriyeh6
PMCID: PMC9009695  PMID: 35421192

Abstract

Background

The burden of diabetes mellitus (DM) and its associated complications continue to burgeon, particularly in low- and middle-income countries (LMICs). Lower limb amputation (LLA) is one of the most life-altering complications of DM, associated with significant morbidity, mortality and socio-economic impacts. High-income countries have reported a decreasing incidence of DM-associated LLA, but the situation in many LMICs is unknown. We aim to conduct a systematic review to determine the incidence and prevalence of DM-associated LLA in LMICs to better inform appropriate interventions and health system response.

Methods and analysis

A systematic search of the literature will be conducted on five databases: MEDLINE, Embase, Cumulative Index of Nursing and Allied Health Literature (CINAHL), Scopus and African Journal Online (AJOL). Only observational, quantitative studies reporting the incidence and/or prevalence of DM-related LLA will be considered. A validated study design-specific critical appraisal tool will be used to assess the risk of bias in individual studies. We will determine the incidence of LLA by examining the number of new cases of LLA among individuals with confirmed DM diagnosis during the specified period, while the prevalence will be based on the total number of all new and existing LLAs in a population. LLA will be considered as the resection of the lower limb from just above the knee to any point down to the toe. If heterogeneity is low to moderate, a random-effects meta-analysis will be conducted on extracted crude prevalence/incidence rates, with the median and interquartile range also reported. The systematic review will be performed in accordance with the JBI guideline for prevalence and incidence review. Study reporting will follow the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guideline.

Prospero registration number

CRD42021238656.

Introduction

The burden of Diabetes Mellitus (DM) continues to grow, especially in low- and middle-income countries (LMICs) [1]. Since 1980, the number of persons living with DM globally has nearly quadrupled [1], with almost 80% of them residing in LMICs [2]. The rising DM prevalence is largely attributable to demographic transition, population ageing, obesity and unhealthy lifestyle behaviours [1].

DM leads to several systemic complications, with lower limb amputation (LLA) being one of the most life altering [3]. Specifically, DM contributes to the development of microvascular and macrovascular complications such as peripheral arterial disease (PAD) and peripheral neuropathy (PN) which predispose to non-healing, infected or gangrenous foot ulcers, which ultimately lead to LLA [4, 5]. The risk of PAD, PN and LLA significantly increases with longer duration and poorly controlled DM [4]. LLA risk among individuals with poorly controlled DM is 26% higher with every percentage increase in glycated haemoglobin (HbA1c), a measure of glycaemic status [6].

LLA poses a substantial health, psychological [7] and socio-economic burden, both at individual and country level [8–10], and greatly affects quality of life [11]. It is also associated with disability and premature mortality [12]. In 2016, there were an estimated 1.5 million years lived with disability (YLD) resulting from amputations, a 32% increase from 1990 [13]. Not only does LLA have deleterious impacts in its own right, it is also associated with increased risk for other DM complications such as cardiovascular diseases [14].

The burden of diabetes-related complications is especially high across LMICs [1], where access to quality DM care is limited [15]. With regard to LLA among persons living with diabetes, perhaps, one of the challenges in the response so far has been a poor understanding and awareness of the disease epidemiology in LMICs, which limits targeted response. While individual studies on LLA prevalence and incidence do exist in LMICs [16–19], no study has synthesised data from this region. Existing reviews had a global inclusion criteria [20, 21] but only one of them included few LMICs in their final analysis but did not follow a systematic approach [21]. Reasons for low or no representation of LMICs in previous studies is not known and estimates from these studies may not accurately reflect the situation in LMICs. In this study, we will define LMICs according to the World Bank income categories [22], taking care to apply our data synthesis and analyses to the WHO regions. This, to the best of our knowledge, will be the first systematic review of LLA among persons with diabetes in LMICs using this approach. This study therefore offers up-to-date data on the incidence and prevalence of diabetes-related LLA that can inform a much-needed response, priorities setting and further research.

Aim and objectives

We aim to conduct a systematic review to determine the incidence and prevalence of DM-related LLA in LMICs.

Secondary objectives of the systematic review include:

  1. to determine the incidence of re-amputations and contralateral amputations and, where possible;

  2. to investigate time trends in the incidence and prevalence of LLA among DM individuals in LMICs.

Methods

This systematic review on the incidence and prevalence of LLA in LMICs will follow the Joanna Briggs Institute (JBI) methodology for systematic reviews of prevalence and incidence [23]. The study protocol is in accordance with the PRISMA protocol checklist for systematic reviews [24, 25].

Eligibility criteria

Inclusion criteria

Types of studies. Prospective and retrospective observational studies, specifically, descriptive and analytic cross- sectional studies reporting the incidence and/or prevalence of lower limb amputations among individuals with confirmed DM diagnosis for a specified period will be included. Also included will be randomised controlled trials (RCTs) with baseline data providing prevalence estimates. Studies involving both DM and non-DM individuals will also be included as long as estimates of LLA among the DM population are provided. There is no age or gender restriction for the participants. For duplicate or overlapping studies, the study with the most detailed data will be included, with additional data, if necessary, extracted from others.

Context. This review will be limited to studies conducted in LMICs. Countries currently listed by the World Bank as low-income, lower-middle-income and upper-middle-income based on income levels, will be considered LMICs [22].

Language. Only studies written in English or with an available English version, or with the possibility of translating the full article via Google Translate, will be included.

Study period. Our focus will be on the past three decades; we will therefore include studies conducted from 1990 until 28th February 2022.

Exclusion criteria

  • Qualitative studies on LLA among persons with diabetes;

  • Studies that reported traumatic LLA or cancer-related LLA;

  • Case reports, case series, case-control, reviews, viewpoints, letters or opinion-based articles, and

  • RCTs without a representative population denominator.

Information sources and search strategy

Electronic searches

A comprehensive systematic search of the literature will be conducted on five databases: MEDLINE, Embase, Scopus, CINAHL, and African Journals Online (AJOL) using a combination of MeSH terms and keywords such as “diabetes”, “amputation”, “lower limb amputation”, “lower extremity amputation”, “amputee” and “incidence” (see S1 Appendix). Terms representing similar concepts will be separated using the Boolean operator “OR” while terms representing different concepts will be separated using the Boolean operator “AND”. Hand searching for relevant articles from the reference list of reviews and included studies will be conducted. Where the full text of relevant studies cannot be retrieved, efforts will be made to request the full text from study corresponding authors.

Searching of other sources

Unpublished studies/grey literature will be hand searched through Google Scholar and grey literature databases such as WHO Library, OpenSIGLE and Open Grey using the study keywords.

Study records

Data management and study selection process

Articles retrieved from databases will be imported in Endnote to remove duplicates. Articles will then be exported into Covidence Systematic Review software (Veritas Health Innovation, Melbourne, Australia) for data management.

After duplicates have been removed from search results, initial screening of titles and abstracts will be conducted independently by two authors following the selection criteria; discrepancies will be resolved by discussion or with a third reviewer. Full text-review of the included studies will also be conducted independently by two authors. All disagreements will be resolved by discussion between two authors and if required, with a third reviewer. The reasons for the exclusion of full text articles will be given. A detailed description and summary of the search results and the selection process will be presented using a PRISMA flow diagram. Details of all the included studies will be reported in a table of included studies.

Data extraction

The standardised JBI data extraction tool for prevalence and incidence review will be adapted [23]. The data extraction tool will be pilot tested using three randomly selected (included) full-text articles after which the tool will be refined and adjusted as necessary. Double (independent) extraction of data will be conducted, and the extracted information will be compared. Where a discrepancy exists between the two extractions, both authors will re-assess identified studies and correct any errors. When necessary, study authors will be contacted to request missing information for clarifications.

Data items and description

General study information

General study information to be extracted include the first and last authors’ names, study title, year of publication, the main affiliation of the primary and senior authors and the data source.

Study characteristics

Study characteristics to be extracted include study population (described by age and sex), study setting/country, study design and period, funding source, year of data collection, sample size, and study denominator (population-level or health facility).

Outcome data

We will extract data on LLA type and location, number of DM individuals in the setting at the specified time, the incidence of LLA reported among DM individuals, the prevalence of LLA reported among DM individuals, the type of LLA (major, minor or both), with a description of it (first, re-amputation or contralateral amputation), the confidence interval and the absolute number of cases.

Case definitions

DM will be defined as specified by the study authors; we will capture the criteria used by authors in order to appraise heterogeneity.

LLA will be defined as the resection of a segment of the lower limb through the tibia and fibula, knee or ankle joint, or femur down to the toe. Major amputations are resections proximal to the tarsometatarsal joint while minor amputations are resections occurring distal or through the tarsometatarsal joint [26].

Study outcomes and prioritisation

The primary outcome of this review is the incidence and prevalence of DM-related LLA in LMICs. Incidence will be defined as the number of new cases of LLA divided by the total DM population in the study during the specified period. Incidence measures will include incidence rate and cumulative incidence. Reporting of incidence at person level will be one amputation per person (the first or the highest) and both levels of amputation, major and minor will be considered. Prevalence will be defined as the total number of DM-related LLAs in the population for a given period.

Assessment of methodological quality of studies

Eligible studies reporting prevalence data that meet the inclusion criteria will be critically appraised for methodological quality using the validated JBI critical appraisal tool for prevalence studies [23]. Studies reporting incidence data will be appraised using a validated tool appropriate for the study design. For instance, cohort studies will be critically appraised using the validated Newcastle-Ottawa quality appraisal tool for non-randomised studies [27]. Critical appraisals will be done at the study level by two independent reviewers. Discrepancies will be resolved by discussion, or with a third reviewer. Studies rated as high (score of >8 of 10) to moderate quality (score of 6–8) will be included in the analysis while low-quality studies (score of 0–5) will be excluded.

Data analysis and presentation of results

The median and interquartile range of all crude incidence rates will be reported. A Freeman–Tukey double-arcsine transformation will be applied to normalise data, given an expected wide variation in extracted crude estimates from studies. Transformed data will be used to calculate summary proportion and 95% CI using a random effects model. A meta-analysis of the estimates of prevalence and incidence will be conducted if studies are sufficiently homogenous. We will assess heterogeneity using the X2 and I2 tests. I2 cut-off values of 0%, 25%, 50% and 75% will represent no, low, moderate and high level of heterogeneity respectively [28]. We will conduct the meta-analysis following the DerSimonian and Laird method [29]. Due to potential of high level of heterogeneity, the DerSimonian-Laird random-effects model is preferred. The DerSimonian and Laird method is widely adopted in the literature and performs robustly in various scenarios including skew-normal and extreme distributions for the effects [30].

Where meta-analysis is not possible, a narrative synthesis of results will be done, using tables and figures as appropriate for data visualisation. Also, in case of heterogeneity, we will carry out sub-group analysis and meta-regression analyses to show the potential sources of heterogeneity. Sub-group analysis will show the distribution across age group, sex and study regions. There should be at least ten studies for each variable in the model for meta-regression analysis to be performed [31]. A sensitivity analysis will be performed to assess the robustness of the study estimates, enabling us to assess the effect of omitting onestudy at a time on the pooled estimate [31]. Lastly, a funnel plot asymmetry test and Egger’s test will be used to assess publication bias, if there are more than ten included studies [31].

Assessment of certainty of evidence

We will use the grading of recommendations, assessment, development and evaluation (GRADE) instrument and Gradepro Software to assess the quality of the synthesised findings. Included studies will be assessed by study design, heterogeneity, consistency, directness, precision and publication bias. The evidence will be described as high, moderate, low or very low quality.

Discussion

The burden of DM has been projected to grow exponentially in LMICs in the near future, while the quality of care remains poor [15]. The incidence of LLA among diabetics is considered one of the markers of diabetes care quality, while the prevalence helps us to understand the extent and depth of the disease burden. Also, the worldwide prevalence of LLA is varies. To the best of our knowledge, this proposed study will be the first to provide an estimate of the incidence and prevalence of LLA among persons living with DM in LMICs. An understanding of the LLA burden will inform targeted response. Also, its distribution across various socio-demographic groups, as defined by age or gender, for instance, may help in identifying populations at risk and designing appropriate interventions targeting those groups. Likewise, variance across countries may inform future research studies which might look at the DM care in settings with a lower incidence of LLA and identify lessons that may be translated to other resource-limited settings. This review will follow a systematic approach using a predefined protocol and following standard recommendations for data extraction [32]. Potential limitations that may be encountered include heterogeneity in the individual studies related to the quality of the study designs, definitions used, or methods of assessing outcomes. We will, however, provide a detailed narrative report highlighting these discrepancies and provide suggestions for improving future studies.

Supporting information

S1 Appendix. Search strategy.

(DOCX)

Click here for additional data file. (19.2KB, docx)
S1 Checklist

(DOCX)

Click here for additional data file. (32.9KB, docx)

Funding Statement

The author(s) received no specific funding for this work.

References

  • 1.World Health Organization. Diabetes 2021 [cited 2021 24 May]. https://www.who.int/news-room/facts-in-pictures/detail/diabetes
  • 2.International Diabetes Federation. IDF Diabetes Atlas, 9th edition 2019. https://www.diabetesatlas.org/en/
  • 3.Schaper N, Apelqvist J, Bakker K. Reducing lower leg amputations in diabetes: a challenge for patients, healthcare providers and the healthcare system. Diabetologia. 2012;55(7):1869–72. doi: 10.1007/s00125-012-2588-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Association AD. Peripheral arterial disease in people with diabetes. Diabetes care. 2003;26(12):3333–41. doi: 10.2337/diacare.26.12.3333 [DOI] [PubMed] [Google Scholar]
  • 5.Thiruvoipati T, Kielhorn CE, Armstrong EJ. Peripheral artery disease in patients with diabetes: Epidemiology, mechanisms, and outcomes. World J Diabetes. 2015;6(7):961–9. doi: 10.4239/wjd.v6.i7.961 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Adler A, Erqou S, Lima T, Robinson A. Association between glycated haemoglobin and the risk of lower extremity amputation in patients with diabetes mellitus—review and meta-analysis. Diabetologia. 2010;53(5):840–9. doi: 10.1007/s00125-009-1638-7 [DOI] [PubMed] [Google Scholar]
  • 7.Sahu A, Sagar R, Sarkar S, Sagar S. Psychological effects of amputation: A review of studies from India. Industrial psychiatry journal. 2016;25(1):4. doi: 10.4103/0972-6748.196041 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Mapa-Tassou C, Katte J-C, Mba Maadjhou C, Mbanya JC. Economic Impact of Diabetes in Africa. Current Diabetes Reports. 2019;19(2):5. doi: 10.1007/s11892-019-1124-7 [DOI] [PubMed] [Google Scholar]
  • 9.Bommer C, Sagalova V, Heesemann E, Manne-Goehler J, Atun R, Bärnighausen T, et al. Global Economic Burden of Diabetes in Adults: Projections From 2015 to 2030. Diabetes Care. 2018:dc171962. doi: 10.2337/dc17-1962 [DOI] [PubMed] [Google Scholar]
  • 10.American Diabetes Association. The cost of Diabetes 2018. https://www.diabetes.org/resources/statistics/cost-diabetes
  • 11.Zidarov D, Swaine B, Gauthier-Gagnon C. Quality of life of persons with lower-limb amputation during rehabilitation and at 3-month follow-up. Archives of physical medicine and rehabilitation. 2009;90(4):634–45. doi: 10.1016/j.apmr.2008.11.003 [DOI] [PubMed] [Google Scholar]
  • 12.De Klerk C, Du Plessis G, Fourie J, O’Neill A, Smit S, Joubert G. The eventual outcome of patients who had lower limb amputations due to peripheral vascular disease at Pelonomi Hospital, Bloemfontein. South African Family Practice. 2017;59(1):1–4. [Google Scholar]
  • 13.Zhang Y, Lazzarini PA, McPhail SM, van Netten JJ, Armstrong DG, Pacella RE. Global disability burdens of diabetes-related lower-extremity complications in 1990 and 2016. Diabetes Care. 2020;43(5):964–74. doi: 10.2337/dc19-1614 [DOI] [PubMed] [Google Scholar]
  • 14.Creager MA, Matsushita K, Arya S, Beckman JA, Duval S, Goodney PP, et al. Reducing nontraumatic lower-extremity amputations by 20% by 2030: time to get to our feet: a policy statement from the American Heart Association. Circulation. 2021;143(17):e875–e91. doi: 10.1161/CIR.0000000000000967 [DOI] [PubMed] [Google Scholar]
  • 15.Flood D, Seiglie JA, Dunn M, Tschida S, Theilmann M, Marcus ME, et al. The state of diabetes treatment coverage in 55 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data in 680 102 adults. The Lancet Healthy Longevity. 2021;2(6):e340–e51. doi: 10.1016/s2666-7568(21)00089-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Agu TC, Ojiaku ME. The indications for major limb amputations: 8 years retrospective study in a private orthopaedic and trauma centre in the south-east Nigeria. Journal of clinical orthopaedics and trauma. 2016;7(4):242–7. doi: 10.1016/j.jcot.2016.03.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Baidoo R, Debrah S. Major extremity amputations: the Koforidua experience. Postgraduate Medical Journal of Ghana. 2016;5(2):68–70. [Google Scholar]
  • 18.Ogbera A, Fasanmade O, Ohwovoriole A, Adediran O. An assessment of the disease burden of foot ulcers in patients with diabetes mellitus attending a teaching hospital in Lagos, Nigeria. The international journal of lower extremity wounds. 2006;5(4):244–9. doi: 10.1177/1534734606294538 [DOI] [PubMed] [Google Scholar]
  • 19.Sarfo-Kantanka O, Sarfo FS, Kyei I, Agyemang C, Mbanya JC. Incidence and determinants of diabetes-related lower limb amputations in Ghana, 2010–2015-a retrospective cohort study. BMC endocrine disorders. 2019;19(1):1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Moxey P, Gogalniceanu P, Hinchliffe R, Loftus I, Jones K, Thompson M, et al. Lower extremity amputations—a review of global variability in incidence. Diabetic Medicine. 2011;28(10):1144–53. doi: 10.1111/j.1464-5491.2011.03279.x [DOI] [PubMed] [Google Scholar]
  • 21.Narres M, Kvitkina T, Claessen H, Droste S, Schuster B, Morbach S, et al. Incidence of lower extremity amputations in the diabetic compared with the non-diabetic population: a systematic review. PloS one. 2017;12(8):e0182081. doi: 10.1371/journal.pone.0182081 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.The World Bank. World Bank and Lending Groups: Countries classification 2021. https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups
  • 23.Munn Z, Moola S, Lisy K, Riitano D, Tufanaru C. Systematic reviews of prevalence and incidence. Joanna Briggs Institute reviewer’s manual Adelaide, South Australia: The Joanna Briggs Institute. 2017:5–1.
  • 24.Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic reviews. 2015;4(1):1–9. doi: 10.1186/2046-4053-4-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Page MJ, Moher D, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. Bmj. 2021;372. doi: 10.1136/bmj.n160 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Frykberg RG, Zgonis T, Armstrong DG, Driver VR, Giurini JM, Kravitz SR, et al. Diabetic foot disorders: a clinical practice guideline (2006 revision). The journal of foot and ankle surgery. 2006;45(5):S1–S66. [DOI] [PubMed] [Google Scholar]
  • 27.Wells G, Shea B, O’Connell D, Peterson J, Welch V, Losos M, et al. Newcastle-Ottawa quality assessment scale cohort studies. University of Ottawa. 2014.
  • 28.Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. Bmj. 2003;327(7414):557–60. doi: 10.1136/bmj.327.7414.557 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.DerSimonian R, Laird N. Meta-analysis in clinical trials. Controlled clinical trials. 1986;7(3):177–88. doi: 10.1016/0197-2456(86)90046-2 [DOI] [PubMed] [Google Scholar]
  • 30.Kontopantelis E, Reeves D. Performance of statistical methods for meta-analysis when true study effects are non-normally distributed: a simulation study. Statistical methods in medical research. 2012;21(4):409–26. doi: 10.1177/0962280210392008 [DOI] [PubMed] [Google Scholar]
  • 31.Deeks JJ, Higgins JPT, Altman DG, Cochrane Statistical Methods G. Analysing data and undertaking meta-analyses. Cochrane handbook for systematic reviews of interventions. 2019:241–84. [Google Scholar]
  • 32.Collaboration C. Cochrane Consumers and Communication Review Group: data extraction template for Cochrane reviews. Internet)(nd) cccrg.cochrane.org/author-resources. 2011.

Decision Letter 0

Daoud Al-Badriyeh

27 Jan 2022

PONE-D-21-29205Lower limb amputations among individuals living with diabetes mellitus in low- and middle-income countries: a systematic review protocolPLOS ONE

Dear Dr. Ajayi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised major version of the manuscript that addresses the points raised during the review process. Please find these below. Please submit your revised manuscript by Mar 10 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Daoud Al-Badriyeh

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

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 

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

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. 

3. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information. 

Additional Editor Comments:

Please provide detailed responses to the reviewer's comments and suggestions, including clarifying the rationale behind this study in LMICs when similar studies in other settings exist already. Why/how would LLAs differ in LMICs, and what are the anticipated implications of this, needs elaboration. This is an important aspect of a study protocol.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does the manuscript provide a valid rationale for the proposed study, with clearly identified and justified research questions?

The research question outlined is expected to address a valid academic problem or topic and contribute to the base of knowledge in the field.

Reviewer #1: Partly

**********

2. Is the protocol technically sound and planned in a manner that will lead to a meaningful outcome and allow testing the stated hypotheses?

The manuscript should describe the methods in sufficient detail to prevent undisclosed flexibility in the experimental procedure or analysis pipeline, including sufficient outcome-neutral conditions (e.g. necessary controls, absence of floor or ceiling effects) to test the proposed hypotheses and a statistical power analysis where applicable. As there may be aspects of the methodology and analysis which can only be refined once the work is undertaken, authors should outline potential assumptions and explicitly describe what aspects of the proposed analyses, if any, are exploratory.

Reviewer #1: Partly

**********

3. Is the methodology feasible and described in sufficient detail to allow the work to be replicable?

Descriptions of methods and materials in the protocol should be reported in sufficient detail for another researcher to reproduce all experiments and analyses. The protocol should describe the appropriate controls, sample size calculations, and replication needed to ensure that the data are robust and reproducible.

Reviewer #1: Yes

**********

4. Have the authors described where all data underlying the findings will be made available when the study is complete?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception, at the time of publication. The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above and, if applicable, provide comments about issues authors must address before this protocol can be accepted for publication. You may also include additional comments for the author, including concerns about research or publication ethics.

You may also provide optional suggestions and comments to authors that they might find helpful in planning their study.

(Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The study aimed to assess the incidence and prevalence of LLA as a complication of DM in LMICs. The study objectives are methodology clear, yet the significance, novelty, and implications were not highlighted clearly. There are several ideas that were repeated in different sections which negatively affected the flow and readability of the text. While the study appears to be sound, there are several grammatical errors. I advise the authors to work with a writing coach or copy editor.

Introduction: The flow of the introduction is a bit confusing and not easy to follow. There are several ideas that were repeated in this section.

Line 55-57: The sentence is long with 3 different ideas; I suggest splitting it into sentences.

Line 74: This idea was already stated earlier in the previous paragraphs.

Line 82: The sentence is long with 3 different ideas; I suggest splitting it into sentences.

Line 83: This sentence is about the decrease of LLA in HICs which was already mentioned before in the same paragraph (lines 75-77). Also, why Africa is mentioned as part of the sentence?

The last paragraph of the introduction does not clearly emphasize rationale of this study or the current research gaps.

Methods and analysis: There are several ideas that were repeated in this section.

I suggest using the Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols (PRISMA-P) guidelines for this protocol.

Line 124: Why would you limit the search to studies conducted from 1999? There is no clear epidemiological reason to limit the search to a specific time period.

In the inclusion criteria: Is there is any minimum sample size for each study or measure to be included?

In the exclusion criteria, will you exclude RCTs (which may report a prevalence measure at the baseline), case reports, or case series?

In the exclusion criteria, will you consider duplicate or overlapping studies (i.e., if two published studies are using the same population sample but there are conducting different analyses)?

Line 141: Why only from the first ten pages?

The data management section implies the same information as the screening process. Thus, I suggest merging them into one paragraph to avoid repetition.

Line 161: I suggest specifying what are study population measures that will be extracted, like "study population and its characteristics (sex, age, etc)".

Line 164: "time trend reported where available". This is not clear. What is the time trend you are going to extract is it the time since diagnosis of DM, time since LLA, years of data collection?

For the quality assessment tool, since it was adapted, a validation method should be considered before applying it (e.g., face validity, content validity, etc.).

Study outcomes paragraph: A clear definition of the outcomes should be mentioned. Also, it seems that it is written in separate lines, not as one paragraph.

Data analysis and result presentation: No clear or detailed plan for data synthesis and analysis is presented.

Line 178: I suggest removing this sentence as it is already mentioned under "data items and description".

Lines 181-183: The two sentences should be moved to the "study outcomes paragraph" as they represent a definition of the study's primary outcome (i.e., incidence).

Lines 182-183: How you are going to combine two incidence measures in the data synthesis and analysis while they have different denominators (i.e., either DM population at a country level or DM population presenting at healthcare facility). More clarification should be provided.

Lines 185-187: I think it would be good to add any potential reasons for not conducing a meta-analysis. A justification for using DerSimonian-Laird random-effects model should be stated. Also, will you consider any method for data transformation?

Discussion: This section does not reflect the significance and novelty of the current study, as well as the implications of the future findings.

Minor issues

Line 66: HbA1c was abbreviated without prior definition.

Line 59: Better to write it as "access to healthcare services"

Lines 130-133: Be consistent in the letter case of keywords.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2022 Apr 14;17(4):e0266907. doi: 10.1371/journal.pone.0266907.r002

Author response to Decision Letter 0

21 Mar 2022

Editor’s Comment: Please provide detailed responses to the reviewer's comments and suggestions, including clarifying the rationale behind this study in LMICs when similar studies in other settings exist already. Why/how would LLAs differ in LMICs, and what are the anticipated implications of this, needs elaboration. This is an important aspect of a study protocol.

Response: The burden of diabetes-related complications is especially high across LMICs where access to quality DM care is limited. With regard to LLA among persons living with diabetes, perhaps, one of the challenges in the response so far has been a poor understanding and awareness of the disease epidemiology in LMICs, which limits targeted response. While individual studies on LLA prevalence and incidence do exist in LMICs [16-19], no study has synthesised data from this region. Existing reviews had a global inclusion criteria [20, 21] but only one of them included few LMICs in their final analysis and that specific one did not follow a systematic approach [21]. Reasons for low or no representation of LMICs in previous studies is not known and estimates from these studies may not accurately reflect the situation in LMICs. In this study, we will define LMICs according to the World Bank income categories [22], taking care to apply our data synthesis and analyses to the sub-regions. This, to the best of our knowledge, will be the first systematic review of LLA among persons with diabetes in LMICs using this approach. This study therefore offers up-to-date data on the incidence and prevalence of diabetes-related LLA that can inform a much-needed response, priorities setting and further research.

Reviewer 1

Comment 1: Introduction: The flow of the introduction is a bit confusing and not easy to follow. There are several ideas that were repeated in this section.

Line 55-57: The sentence is long with 3 different ideas; I suggest splitting it into sentences.

Response: Thank you for the correction. We have now done a professional language editing to ensure clarity and flow of the write-up. We have separated these sentences and now reads:

“The burden of Diabetes Mellitus (DM) continues to grow, especially in low- and middle-income countries (LMICs) [1]. Since 1980, the number of persons living with DM globally has nearly quadrupled [1], with almost 80% of them residing in LMICs [2]. The rising DM prevalence is largely attributable to demographic transition, population ageing, obesity and unhealthy lifestyle behaviours”

Comment 2: Line 74: This idea was already stated earlier in the previous paragraphs.

Response: We have deleted the repeated statement on line 74.

Comment 3: Line 82: The sentence is long with 3 different ideas; I suggest splitting it into sentences.

Response: We have revised this section of the manuscript, which is the study justification section and it now reads:

“ The burden of diabetes-related complications is especially high across LMICs [1], where access to quality DM care is limited [15]. With regard to LLA among persons living with diabetes, perhaps, one of the challenges in the response so far has been a poor understanding and awareness of the disease epidemiology in LMICs, which limits targeted response. While individual studies on LLA prevalence and incidence do exist in LMICs [16-19], no study has synthesised data from this region. Existing reviews had a global inclusion criteria [20, 21] but only one of them included few LMICs in their final analysis but did not follow a systematic approach [21]. Reasons for low or no representation of LMICs in previous studies is not known and estimates from these studies may not accurately reflect the situation in LMICs. In this study, we will define LMICs according to the World Bank income categories [22], taking care to apply our data synthesis and analyses to the sub-regions. This, to the best of our knowledge, will be the first systematic review of LLA among persons with diabetes in LMICs using this approach. This study therefore offers up-to-date data on the incidence and prevalence of diabetes-related LLA that can inform a much-needed response, priorities setting and further research.”

Comment 4: Line 83: This sentence is about the decrease of LLA in HICs which was already mentioned before in the same paragraph (lines 75-77). Also, why Africa is mentioned as part of the sentence?

Response: We have revised this section as shown in response to comment 3.

Comment 5: The last paragraph of the introduction does not clearly emphasize the rationale of this study or the current research gaps.

Response: The last paragraph, that is, the justification for the study now reads:

“The burden of diabetes-related complications is especially high across LMICs [1], where access to quality DM care is limited [15]. With regard to LLA among persons living with diabetes, perhaps, one of the challenges in the response so far has been a poor understanding and awareness of the disease epidemiology in LMICs, which limits targeted response. While individual studies on LLA prevalence and incidence do exist in LMICs [16-19], no study has synthesised data from this region. Existing reviews had a global inclusion criteria [20, 21] but only one of them included few LMICs in their final analysis but did not follow a systematic approach [21]. Reasons for low or no representation of LMICs in previous studies is not known and estimates from these studies may not accurately reflect the situation in LMICs. In this study, we will define LMICs according to the World Bank income categories [22], taking care to apply our data synthesis and analyses to the sub-regions. This, to the best of our knowledge, will be the first systematic review of LLA among persons with diabetes in LMICs using this approach. This study therefore offers up-to-date data on the incidence and prevalence of diabetes-related LLA that can inform a much-needed response, priorities setting and further research.”

Methods and analysis:

Comment 6: There are several ideas that were repeated in this section.

I suggest using the Preferred Reporting Items for Systematic Reviews and Meta-analyses Protocols (PRISMA-P) guidelines for this protocol.

Response: The section has been re-ordered using the PRISMA-P guideline.

Comment 7: Line 124: Why would you limit the search to studies conducted from 1999? There is no clear epidemiological reason to limit the search to a specific time period.

Response: Given that we are also interested in exploring trends in epidemiology, with our focus on the past three decades, we will limit our analyses to studies conducted from 1990-2022.

Comment 8: In the inclusion criteria: Is there any minimum sample size for each study or measure to be included?

Response: As our study will involve multiple hierarchical datasets from each study (ie., prevalence across age- and sex- specific groups in each study), we are considering population denominators across each data point, and not necessarily sample size from the study, which is set at a minimum of 50.

Comment 9: In the exclusion criteria, will you exclude RCTs (which may report a prevalence measure at the baseline), case reports, or case series?

Response: Case reports and case series will be excluded. RCTs without a representative population denominator will be excluded.

Comment 10: In the exclusion criteria, will you consider duplicate or overlapping studies (i.e., if two published studies are using the same population sample but there are conducting different analyses)?

Response: For duplicate or overlapping studies, the study with the most detailed data will be included, and additional data, if necessary, extracted from others. We have now added a statement on this.

Comment 11: Line 141: Why only from the first ten pages?

Response: We have now removed this restriction.

Comment 12: The data management section implies the same information as the screening process. Thus, I suggest merging them into one paragraph to avoid repetition.

Response: We have now merged these sections:

“Articles retrieved from databases will be imported in Endnote to remove duplicates. Articles will then be exported into Covidence Systematic Review software (Veritas Health Innovation, Melbourne, Australia) for data management”.

Comment 13: Line 161: I suggest specifying what are study population measures that will be extracted, like "study population and its characteristics (sex, age, etc)".

Response: Study characteristics to be extracted include study population (described by age and sex), study setting/country, study design and period, funding source, year of data collection, sample size, and study denominator (population-level or health facility). We have now stated this.

Comment 14: Line 164: "time trend reported where available". This is not clear. What is the time trend you are going to extract is it the time since diagnosis of DM, time since LLA, years of data collection?

Response: We intended to measure differences in LLA incidence over years (1990-2022), where possible. Year(s) of data collection data will be helpful to ascertain that, and we have changed to “year(s) of data collection” for clarity.

Comment 15: For the quality assessment tool, since it was adapted, a validation method should be considered before applying it (e.g., face validity, content validity, etc.).

Response: We will now be using the validated Joanna Briggs Institute (JBI) critical appraisal tool for prevalence studies. Studies reporting incidence data will be appraised using validated tools appropriate for the study design. For instance, cohort studies will be critically appraised using the validated Newcastle-Ottawa quality appraisal tool for non-randomised studies [28].

Comment 16: Study outcomes paragraph: A clear definition of the outcomes should be mentioned. Also, it seems that it is written in separate lines, not as one paragraph.

Response: We have now merged the sentences as a paragraph and the definition of outcome is now provided:

“The primary outcome of this review is the incidence and prevalence of DM-related LLA in LMICs. Incidence will be defined as the number of new cases of LLA divided by the total DM population in the study during the specified period. Incidence measures will include incidence rate and cumulative incidence. Reporting of incidence at person level will be one amputation per person (the first or the highest) and both levels of amputation, major and minor will be considered. Prevalence will be defined as the total number of DM-related LLAs in the population for a given period. “

Comment 17: Data analysis and result presentation: No clear or detailed plan for data synthesis and analysis is presented.

Response: We have now improved on our data analysis plan:

“Median and interquartile range of all crude incidence rates will be reported. A Freeman–Tukey double-arcsine transformation will be applied to normalize data given an expected wide variation in extracted crude estimates from studies. Transformed data will be used to calculate summary proportion and 95% CI using a random effects model. A meta-analysis of the estimates of prevalence and incidence will be conducted if studies are sufficiently homogenous. We will assess heterogeneity using the X2 and I2 tests. I2 cut-off values of 0%, 25%, 50% and 75% will represent no, low, moderate and high level of heterogeneity [28]. We will conduct the meta-analysis following DerSimonian and Laird method [29]. Due to potential heterogeneity, DerSimonian-Laird random-effects model is preferred. DerSimonian and Laird method is a widely documented in the literature and is robust in various scenarios including skew-normal and extreme distributions for the effects [30]. However, where meta-analysis is not possible, a narrative synthesis of results will be done, using tables and figures as appropriate for data visualization. Also, in case of heterogeneity, we will carry out sub-group analysis and meta-regression analyses to show the potential sources of heterogeneity. Sub-group analysis will show the distribution across age group, sex and study regions. There should be at least 10 studies for each variable in the model for meta-regression analysis to be performed [31]. A sensitivity analysis will be performed to assess the robustness of the study estimates by assessing the effect of omitting a study at a time on the pooled estimate [31]. Lastly, a funnel plot asymmetry test and Egger’s test will be used to assess publication bias, if there are more than 10 included studies [31].”

Comment 18: Line 178: I suggest removing this sentence as it is already mentioned under "data items and description".

Response: The sentence has been removed.

Comment 19: Lines 181-183: The two sentences should be moved to the "study outcomes paragraph" as they represent a definition of the study's primary outcome (i.e., incidence).

Response: We have now moved the sentences to the study outcome paragraph as shown under comment 16.

Comment 20: Lines 182-183: How you are going to combine two incidence measures in the data synthesis and analysis while they have different denominators (i.e., either DM population at a country level or DM population presenting at healthcare facility). More clarification should be provided.

Response: Analysis will be conducted separately for population and hospital-based studies.

Comment 21: Lines 185-187: I think it would be good to add any potential reasons for not conducting a meta-analysis. A justification for using DerSimonian-Laird random-effects model should be stated. Also, will you consider any method for data transformation?

Response: A justification has been provided:

A meta-analysis of the estimates of prevalence and incidence will be conducted if studies are sufficiently homogenous. We will assess heterogeneity using the X2 and I2 tests. I2 cut-off values of 0%, 25%, 50% and 75% will represent no, low, moderate and high level of heterogeneity [28]. We will conduct the meta-analysis following DerSimonian and Laird method [29]. Due to potential high heterogeneity, DerSimonian-Laird random-effects model is preferred. DerSimonian and Laird method is widely documented in the literature and is robust in various scenarios including skew-normal and extreme distributions for the effects [30]”

Comment 22: Discussion: This section does not reflect the significance and novelty of the current study, as well as the implications of the future findings.

Response: We have revised this section as appropriate. The section now read:

“The burden of DM has been projected to grow exponentially in LMICs in the near future, while the quality of care remains poor [15]. The incidence of LLA among diabetics is considered one of the markers of diabetes care quality, while the prevalence helps us to understand the extent and depth of the disease burden. Also, the worldwide prevalence of LLA is varies. To the best of our knowledge, this proposed study will be the first to provide an estimate of the incidence and prevalence of LLA among persons living with DM in LMICs. An understanding of the LLA burden will inform targeted response. Also, its distribution across various socio-demographic groups, as defined by age or gender, for instance, may help in identifying populations at risk and designing appropriate interventions targeting those groups. Likewise, variance across countries may inform future research studies which might look at the DM care in settings with a lower incidence of LLA and identify lessons that may be translated to other resource-limited settings. This review will follow a systematic approach using a predefined protocol and following standard recommendations for data extraction [32]. Potential limitations that may be encountered include heterogeneity in the individual studies related to the quality of the study designs, definitions used, or methods of assessing outcomes. We will, however, provide a detailed narrative report highlighting these discrepancies and provide suggestions for improving future studies.”

Comment 23: Line 66: HbA1c was abbreviated without prior definition.

Response: We have now defined HbA1c

Comment 24: Line 59: Better to write it as "access to healthcare services"

Response: We have revised this section.

Comment 25: Lines 130-133: Be consistent in the letter case of keywords.

Response: Thank you for your observation. We have adjusted these.

“A comprehensive systematic search of the literature will be conducted on five databases: MEDLINE, Embase, Scopus, CINAHL, and African Journals Online (AJOL) using a combination of MeSH terms and keywords such as “diabetes”, “amputation”, “lower limb amputation”, “lower extremity amputation”, “amputee”, “incidence “ and “population study”

Decision Letter 1

Daoud Al-Badriyeh

30 Mar 2022

Lower limb amputations among individuals living with diabetes mellitus in low- and middle-income countries: a systematic review protocol

PONE-D-21-29205R1

Dear Dr. Ajayi,

Thank you for providing enough revision and details to satisfy the reviewers/editor comments. We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Daoud Al-Badriyeh

Academic Editor

PLOS ONE

Acceptance letter

Daoud Al-Badriyeh

5 Apr 2022

PONE-D-21-29205R1

Lower limb amputations among individuals living with diabetes mellitus in low- and middle-income countries: a systematic review protocol

Dear Dr. Ajayi:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Daoud Al-Badriyeh

Academic Editor

PLOS ONE

Articles from PLoS ONE are provided here courtesy of PLOS

RESOURCES