COVID-19 Renal Pathology Protocols and Pathology Practice in Latin America: Analysis from GlomCon Latin America Working Group (LGlomCon)
Bibliographic record
Abstract
Background: A significant fraction of patients with COVID-19 display renal involvement (60%); however, the histological findings and pathology practice in Latin America (LA) have not been reported. The aim is to know how COVID-19 pandemic has affected the protocols for renal pathology and the main pathology findings in the kidney. Methods: An online survey with 75 questions in 6 sections, directed to pathologists, nephrologists and other specialists from 16 Spanish speaking LA countries treating COVID patients with kidney involvement. We are analyzing the impact of COVID-19 in renal pathology and pathology practice in LA. Results: From 430 responses, 360 (84%) were considered for analysis. Only13 participants from 16 countries were renal pathologists but the rest of responders also contributed with the pathology section. Only 10% is performing renal biopsies (RBx) of COVID-19 patients. Acute kidney injury (AKI) (85%) was the most frequent indication for RBx, hematuria-proteinuria (42%), nephrotic syndrome (28%) and subnephrotic proteinuria (21%). Combination of AKI and other syndrome was seen. Handling fresh tissue for immunofluorescence (IF) is a regular practice in the centers that perform IF (66%). No ultrastructural examination in 90% due to the lack of EM equipment. Postmortem studies only in 3% of the centers. Autopsy and biopsies shiwed thrombotic microangiopathy (TMA), with acute tubular injury (ATI). Pathology redeployment to clinical areas, ICU and inpatient care is seen in 12%. Only 70% of those received guidance or updating clinical courses. Conclusions: The survey has highlighted the deep shortage of renal pathologists and the lack of equipment (EM) compromising the best practice of renal pathology in LA. Protocols for tissue handling for COVID have not been established in any center, adding a burden to the practice. Most frequent indication for renal biopsy is AKI while the presence of TMA and ATI is found in autopsy and renal samples. Collapsing glomerulopathy (CG) has a high prevalence in hispanics and has been described in COVID patients, however CG was not seen. Outbreaks had forzed pathology redeployment to clinical care without proper preparation.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".