Biological cleansing: Toward improving ocular surface surgical outcomes.
Postoperative complications such as dry eye, ocular surface pain, and abnormal wound healing responses, including fibrosis or ectasia, remain a significant concern in corneal, refractive, and cataract surgeries as they occur even in those patients without the classical clinical risk factors. Persistent low-grade or subclinical ocular surface inflammation in these patients may have contributed to these suboptimal outcomes. Inflammatory factors such as IL-1β, IL-6, IL-17A, TNFα, IFNγ, and/or MMP-9 are reported to be higher on the ocular surface of patients with either overt or subclinical inflammation. These inflammatory factors disrupt tissue homeostasis and wound healing response as they (i) sensitize nociceptive (pain) pathways, (ii) destabilize cell-cell adhesion, (iii) increase TGFβ-dependent or independent extracellular matrix (ECM) deposition leading to scarring, and/or (iv) cause ectasia by decreasing ECM deposition and natural collagen cross-linking. These effects of molecular risk factors can be mitigated by preoperative BIOLOGICAL CLEANSING strategies designed to reduce the load of these inflammatory factors on the ocular surface. Depending on the clinical presentation and inflammatory load status, biological cleansing using (i) lubricants; (ii) eyelid hygiene; (iii) ocular surface washes; (iv) topical or oral nutraceuticals; (v) nonpharmacological treatments, such as thermal pulsation therapy and intense light therapy; (vi) topical immunomodulators, such as cyclosporine, tacrolimus, steroids, and Lifitegrast; and (vii) lifestyle modifications, such as diet and probiotics, can be followed. We and others have shown a reduction in these inflammatory factors on the ocular surface using one or more of these strategies. Incorporating biological cleansing protocols into presurgical preparation is a vital step toward modulating ocular surface biology to improve postoperative outcomes for patients.
Authors
Shetty Shetty, Kumar Kumar, Khamar Khamar, Kiran Kiran, Singh Singh, Pawar Pawar, Shetty Shetty, Gokul Gokul, Sethu Sethu, Ghosh Ghosh
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