Characterizing SCID in Bogota: A Single-Center Experience
Bibliographic record
Abstract
Severe combined immunodeficiency (SCID) is a group of inborn errors of immunity that severely impair the immune system and lead to high susceptibility to infections. We present the cases of nine patients with SCID diagnosed at a pediatric referral center in Bogotá. Of the nine patients, seven (78%) were female and two (22%) were migrants. Consanguinity was reported in two cases, and one involved endogamy. The median age at diagnosis was 4 months and the median age at first infection was 2 months. Bacterial infections were documented in five patients, mostly due to Gram-negative organisms. Seven patients (78%) had BCGitis, three progressed to BCGosis. IgA and IgM levels were decreased in seven patients; total IgE was <15 IU/mL in all. IgG levels were low in all but one patient, reflecting maternal antibodies. Lymphoproliferative responses were severely decreased when tested. Seven cases were classified as “classical” SCID: five due to defects in IL2RG, IL7R, RAG1, RAG2, DCLRE1C, and ADA; two due to compound heterozygosity in RAG2 (one of whom presented with maternal T cell engraftment); and one secondary to a complete 22q11.2 deletion with athymia. There was one patient with leaky SCID secondary to ORAI1 mutations. All patients received immunoglobulin replacement, trimethoprim/sulfamethoxazole, fluconazole, and four-drug therapy for BCG (Bacillus Calmette–Guerin)-related disease. Acyclovir and palivizumab prophylaxis were given to 56% of patients. Two patients died before hematopoietic stem cell transplantation (HSCT) due to severe infections and one patient with 22q11.2 deletion was not a HSCT candidate. Colombia currently lacks a newborn screening program for SCID, leading to delayed diagnoses typically after severe infections during early infancy, frequently with organ involvement that negatively impacts survival. This case series highlights the clinical complexity and diagnostic challenges of SCID in a resource-limited setting, emphasizing the urgent need to guide public health policies for early detection and other strategies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".