Intestinal parasites in hemodialysis patients from developing countries: A systematic review and meta‐analysis
Bibliographic record
Abstract
Intestinal parasitic infection (IPI) is the main cause of gastrointestinal complications in hemodialysis patients due to their impaired immune systems. We conducted a systematic review and meta-analysis to evaluate the prevalence and odds ratio (OR) of IPIs in this population. Relevant eligible studies were identified by searching the PubMed, Science Direct, Scopus, Web of Science, and Google scholar databases up to January 30, 2019. A random-effects meta-analysis model was used to estimate the pooled prevalence, OR, and 95% confidence intervals (CI). Twenty-two studies, from Turkey, Iran, Brazil, Egypt, Saudi Arabia, Pakistan, and Malaysia met eligibility criteria for analysis, and included 11 using a case-control design (980 patients and 893 controls) and 11 studies using a cross-sectional design (a total of 1455 participants). Cross-sectional studies suggested that the pooled prevalence of IPIs in hemodialysis patients was 24% (95% CI, 14-36%; 307/1455). In studies using a case-control design, the pooled prevalence of IPIs in hemodialysis patients (30%, 330/980) was found to be significantly higher than controls (10%, 115/893) (OR, 3.40; 95%CI, 2.37-4.87). With respect to the parasites, Cryptosporidium spp. (OR, 4.49; 95%CI, 2.64-7.64) and Blastocystis sp. (OR, 4.03; 95%CI, 1.20-13.51) were significantly higher in hemodialysis patients compared to the controls. The current study revealed a high prevalence of IPIs in hemodialysis patients from countries in which the baseline prevalence of parasitic infection is high. We recommend that periodic screenings for IPIs in such countries should be incorporated into the routine clinical care of hemodialysis patients.
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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".