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Record W4407323949 · doi:10.1097/tp.0000000000005349

Organ Transplantation in India: INDEED, for the Common Good!

2025· article· en· W4407323949 on OpenAlexaboutno aff
Ashwin Rammohan, Vivek Kute, ManishR Balwani, Arpita Ray Chaudhury

Bibliographic record

VenueTransplantation · 2025
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsnot available
Fundersnot available
KeywordsTransplantationOrgan transplantationMedicineInternal medicine

Abstract

fetched live from OpenAlex

We were deeply concerned by the article “Organ Transplantation in India: NOT for the Common Good” by Domínguez-Gil et al,1 which we felt provided an unfairly critical view of the current state of organ transplantation in India. We aim to provide a point-by-point rebuttal based on actual figures and ground-reality rather than tabloid-press articles as cited by the authors. It is true that in the past 5 y, there has been an extraordinary growth in the number of transplantations in India (more than those achieved over several decades by European countries).1 While it is natural to be wary of this astronomical increase in transplant numbers, the authors’ assumption that this growth is likely nefarious reflects an outdated western mindset, rather than a true understanding of over 2 decades of massively coordinated effort by the Government of India, transplant professionals and all other stakeholders in the country.2 The use of words such as “seemingly” and “apparently” highlight this lack of clarity and evidence and seem to be patronizing in its praise. Another example is the authors’ viewpoint regarding living donor transplantation (LDT). The development of LDT has been presented with a negative connotation. This shows a scant understanding of the geo-socio-political idiosyncrasies prevalent in the Asian region, and unlike the west, its conventional dependence on LDT.3 Interestingly, no such aspersions have been cast against countries like Korea and Japan, which are even more dependent on LDT than India. The authors have further confused LDT and deceased donor transplantation with regards to foreigners having access to organs in India. The authors’ accusation of deceased donor organs being preferentially allocated to foreigner is presumptuous at best. The current organ allocation system under the aegis of the Government of India and state-wise organ transplant governing bodies is a very transparent process—and is reserved for Indian nationals.4 In the event, there are no suitable recipients; the organ gets allocated to a foreign national. In the state of Tamil Nadu, where the highest number of deceased donations in the country occur, hearts and lungs were allocated to foreign nationals in the early part of the program. With increased waitlisting of Indian patients, there has been a steady decline year on year to negligible levels.5 In 2023, 2 of 65 hearts and 1 of 50 lungs were allocated to foreigners (Table 1).5 With increasing demand, this trend is likely to continue and will become like liver and kidney donations, which have not been allocated to any foreign national in the past 5 y (Table 1).5 In contrast, in the United States in 2019, 5.9% of all adults added to the organ waitlist were non-US citizen/non-US residents and 1.2% added were those who had traveled to the country only for the purpose of transplantation.6 TABLE 1. - Deceased donor transplantation in the state of Tamil Nadu, India over the past 5 years5 Year Kidney Liver Heart Lung Total Indian Intnl. Government Private Total Indian Intnl. Government Private Total Indian Intnl. Government Private Total Indian Intnl. Government Private 2019 212 212 0 33 179 103 103 0 6 97 60 58 2 2 58 48 45 3 0 48 2020 91 91 0 8 83 45 45 0 2 43 27 26 1 1 26 30 26 4 0 30 2021 96 96 0 11 85 54 54 0 0 54 47 47 0 0 47 39 28 1 0 29 2022 270 270 0 66 204 134 134 0 10 124 74 73 1 4 70 39 35 4 0 39 2023 308 308 0 108 200 147 147 0 13 134 65 63 2 3 62 50 49 1 0 50 Intnl., international. Transplantation has conventionally been the so-called “privilege of the rich” and continues to be an expensive proposition world over and not just in India. In fact, it is the exponential growth of transplantation in India that has brought transplantation within the reasonable reach of the working class, especially in the emerging nations. Therefore, organ transplantation in India has indeed been for the common good—providing one of the most economical and financially viable systems in the world. A liver transplant (including LDT) in India costs US dollars (USD)30 000 to USD45 000, while published reports of the total cost of a liver transplant in the United States are nearly 30 times this figure; a mind-boggling USD878 400!7 allowing only the very rich from overseas to gain access to transplantation in the United States; and an individual traveling to the United States for surgery has to pay 3 to 5 times more than what it costs a US resident.8 The authors’ premise of private hospitals’ monetary interests needs close review. Several of these Indian corporate hospitals are actually invested heavily into by western enterprises (Table 2), and it is these “money sharks” and not the transplant physician who actually stands to gain out of the transplantation boom.9 To further make this point, the pay scale of an attending transplant surgeon in India is USD50 000 to USD80 000/annum as compared with over 10 times (USD550 000 to USD1 000 000/annum) in the United States.10 Thus, the authors’ accusations of Indian transplant clinicians making enormous gains remains unfounded. Transplant tourism being equated with organ commerce is erroneous, the authors’ fail to understand that many poor countries find India a more financially viable destination to get a transplant than countries in the west. Even affordable Governments in the middle east are moving to the east for transplantation, where the ministries have a direct tie-up with transplant units. TABLE 2. - Major foreign direct investments into Indian private healthcare9 Private equity investor Country Indian hospital in portfolio Stake holding Valuation in million USD Temasek Holdings (Private) Limited Singapore (sovereign wealth fund) 1. Manipal Hospital 51% 5000 2. AHH 85% 175 3. Medica Synergie 4100 4. Medanta Hospitalsa TPG Inc United States 1. Manipal Hospital 11% 5000 2. AHH Majority 3. Medanta Hospitalsa – 4100 IHH Healthcare Malaysia 1. Fortis Healthcare 31% 4500 Japan (major holder) 2. Global Hospitals 98% 350 KKR United States 1. Baby Memorial Hospital 70% 400 2. Max Hospitalsa 10 000 CVC Capital Partners Luxembourg HCG Hospitals 60% 600 EQT Group Sweden AIG Hospitals 30% 600 Blackstone Inc United States Care Hospitals 74% 2000 OTPP Canada Sahyadri Hospitals 91% 350 Carlyle Group Inc United States Apollo Hospitalsa – 10 500 Medanta Hospitalsa – 4100 British International Investments (UK Government) United Kingdom Narayana Healtha – 3000 Rainbow Children’s Hospitala – 1500 aHoldings before public listing.AHH, Asian Healthcare Holdings; KKR, Kohlberg Kravis Roberts & Co; OTPP, Ontario Teachers’ Pension Plan; USD, US dollars. While it should be conceded that transplantation in India may not be available to all, true social upliftment necessitates broader initiatives beyond just immediate transplant availability: that of addressing poverty. Nonetheless, access to transplants for the underprivileged has greatly improved over the past decade. There are several public sector hospitals in the country that routinely provide transplantation services. In 2023, in the state of Tamil Nadu, 35.1% of all deceased donor renal transplants were performed for free in public sector hospitals (Table 1).5 While traditionally, the private pay-from-pocket healthcare has been only for those with the resources, the central and several state governments (Tamil Nadu, Andhra Pradesh, Gujarat, etc) sponsor an all-inclusive healthcare state insurance for the poor, which includes transplantation at any approved private hospital in the state; which includes LDT.5,11 It is also true that the system is far from perfect, but the authors’ article dilutes the focus from the actual issues that need addressing—those of organ trade and trafficking, unrelated living donations, uniform equity and access to transplantation across the country, etc. By calling organ trade as “validated,” the authors malign the transplant fraternity in India, which has worked very diligently and with great integrity to promote transparency and trust in the system. India has also now endorsed the latest 2024 World Health Assembly resolution on transparency. Several other measures to make the system unequivocally transparent, ethical, and fair, include the introduction of a multilayer validation process to ensure living donations by foreign nationals is appropriately whetted and not just by their embassies, the need for all Indian nationals to prove donor-recipient relationship to a Government appointed committee before LDT, and regulations including the most recent registration of all transplant activity. While the Indian “transplant boom” is likely to raise eyebrows, the article provides a biased and not necessarily evidence-based view of the transplant practices in India. Most references quoted by the authors are anecdotal and sporadic incidents within a large evolving healthcare system.1 We again agree that the system needs improving, and the authors’ comments are well taken, but this article from the senior international transplant fraternity could have been kinder and more constructive—helping us improve rather than be accusatory and label the whole system dysfunctional. Such articles are indeed potentially destructive to the transparency and trust that the common man has been developing over the years in the system, and they can have devastating consequences on the growth of transplantation in this region.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0060.014
Scholarly communication0.0150.014
Open science0.0020.007
Research integrity0.0100.027
Insufficient payload (model declined to judge)0.0090.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.288
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2025
Admission routes1
Has abstractyes

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