Case Studies of Intradialytic Total Parenteral Nutrition in Nocturnal Home Hemodialysis
Bibliographic record
Abstract
Introduction: Malnutrition occurs in 30-50% of dialysis patients. If unable to meet caloric intake requirements, intradialytic parenteral nutrition (IDPN) may be considered. Standard IDPN occurs thrice weekly with intermittent hemodialysis (IHD), but has yielded heterogeneous clinical results. Nocturnal home hemodialysis (NHD) occurs at a median of 5 nights/week with 8 hours/session. Through longer duration and increased frequency, prescribing IDPN with NHD augments IDPN dose. We present a series of four NHD patients who required intradialytic total parenteral nutrition (IDTPN) as their primary source of caloric intake. Case Description: 1. A 25-year old woman with ANCA-vasculitis on Peritoneal Dialysis (PD) developed encapsulating peritoneal sclerosis (EPS) and a small bowel obstruction (SBO). 2. A 60-year old woman with amyloidosis on NHD had weight loss from amyloidosis. 3. A 46-year old man with cryoglobulinemic vasculitis on NHD needed IDTPN twice for GI symptoms and suboptimal intake. 4. A 59-year old man with IgA-nephropathy on PD developed an EPS-related SBO. Outcomes: Our patients received 1200-1590 kCal with each IDTPN session and achieved a significant increase in weight, albumin, and BMI (Table 1) (p<0.05 using a Wilcoxon signed rank test). Metabolic complications resembled those with TPN (cramping, hypertriglycidiemia, transaminitis, and fluid overload), and other complications resembled those of the dialysis population (three hospitalizations and one line infection).Table 1:: Summary of IDTPN outcomesDiscussion: IDTPN significantly improved nutrition without significant side effects. Our cases are the first example of IDPN being used as the primary source of caloric intake (i.e. IDTPN), which was enabled by longer (≤8 hours) and more frequent (≤7/week) sessions. Our study is novel in its focus on NHD, whereas prior IDPN studies have focused on IHD. We highlight this because NHD enables diet liberalization and enhances quality of life, both relevant to malnourished patients. Finally, NHD with IDTPN may be particularly useful for PD patients with EPS, as they need to switch dialysis modality and start parenteral nutrition, but presumably prefer to dialyze at home.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".