ReviewPharmaceuticals (Basel, Switzerland)2023
Pathophysiology and Therapeutic Management of Bone Loss in Patients with Critical Illness.
Review in Pharmaceuticals (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 6 citations in OpenAlex.
- Application of lower limb exoskeleton robots in elderly patients with ICU-acquired weakness: a prospective clinical study.BMC geriatrics · 2026Trial
- Beyond Tumor Control in Sporadic Neuroendocrine Tumor: Metabolic and Bone Health During Treatment with Somatostatin Analogs.Journal of clinical medicine · 2026Article
- Calcium Disorders in Rheumatic Diseases: An Overlooked Problem With Major Clinical Implications.Cureus · 2026Review
- Bone Turnover Markers as Biomarkers of Cough Dysfunction and Respiratory Risk in Subacute Ischemic Stroke.Diagnostics (Basel, Switzerland) · 2026Article
- Sepsis in multimorbidity: a domain-based framework for systemic vulnerability and precision care.Frontiers in medicine · 2026Review
- Exploring Cannabidiol's Role in Regenerative Medicine: Focus on Neural and Skeletal Tissues.Biomedicines · 2025Review
- Integrating Network Pharmacology, Quantitative Metabolic Network Analysis,Combinatorial chemistry & high throughput screening · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patients with critical illnesses are at higher risk of comorbidities, which can include bone mineral density loss, bone turnover marker increase, and fragility fractures. Patients admitted to intensive care units (ICUs) have a higher risk of bone fractures. Since hypermetabolism is a characteristic of ICU patients, such patients are often rapidly affected by systemic deterioration, which often results in systemic wasting disease. Major risk factors for ICU-related bone loss include physical restraint, inflammation, neuroendocrine stress, malnutrition, and medications. A medical history of critical illness should be acknowledged as a risk factor for impaired bone metabolism. Bone loss associated with ICU admission should be recognized as a key component of post-intensive care syndrome, and further research that focuses on treatment protocols and prevention strategies is required. Studies aimed at maintaining gut integrity have emphasized protein administration and nutrition, while research is ongoing to evaluate the therapeutic benefits of anti-resorptive agents and physical therapy. This review examines both current and innovative clinical strategies that are used for identifying risk factors of bone loss. It provides an overview of perioperative outcomes and discusses the emerging novel treatment modalities. Furthermore, the review presents future directions in the treatment of ICU-related bone loss.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.